Method and apparatus for providing a service with a plurality of service nodes

Information

  • Patent Grant
  • 11722367
  • Patent Number
    11,722,367
  • Date Filed
    Friday, December 12, 2014
    9 years ago
  • Date Issued
    Tuesday, August 8, 2023
    10 months ago
Abstract
Some embodiments provide an elastic architecture for providing a service in a computing system. To perform a service on the data messages, the service architecture uses a service node (SN) group that includes one primary service node (PSN) and zero or more secondary service nodes (SSNs). The service can be performed on a data message by either the PSN or one of the SSN. However, in addition to performing the service, the PSN also performs a load balancing operation that assesses the load on each service node (i.e., on the PSN or each SSN), and based on this assessment, has the data messages distributed to the service node(s) in its SN group. Based on the assessed load, the PSN in some embodiments also has one or more SSNs added to or removed from its SN group. To add or remove an SSN to or from the service node group, the PSN in some embodiments directs a set of controllers to add (e.g., instantiate or allocate) or remove the SSN to or from the SN group. Also, to assess the load on the service nodes, the PSN in some embodiments receives message load data from the controller set, which collects such data from each service node. In other embodiments, the PSN receives such load data directly from the SSNs.
Description
BACKGROUND

Load balancers are commonly used in datacenters to spread the traffic load to a number of available computing resources that can handle a particular type of traffic. For instance, load balancers are topologically deployed at the edge of the network and between different types of VMs (e.g., between webservers and application servers, and between application servers and the database servers). The load balancers are in some deployments standalone machines (e.g., F5 machines) that perform load balancing functions. Also, in some deployments, the load balancers are service virtual machines (VMs) that execute on the same host computing devices that execute the different layers of servers that have their traffic balanced by the load balancers.


In many load balancer deployments, the load balancers serve as chokepoint locations in the network topology because they become network traffic bottlenecks as the traffic load increases. Also, these deployments do not seamlessly grow and shrink the number of the computing devices that receive the load balanced traffic, as the data traffic increases and decreases.


BRIEF SUMMARY

Some embodiments provide an elastic architecture for providing a service in a computing system. To perform a service on the data messages, the service architecture uses a service node (SN) group that includes one primary service node (PSN) and zero or more secondary service nodes (SSNs). The service can be performed on a data message by either the PSN or one of the SSN. However, in addition to performing the service, the PSN also performs a load balancing operation that assesses the load on each service node (i.e., on the PSN or each SSN), and based on this assessment, has the data messages distributed to the service node(s) in its SN group.


Based on the assessed load, the PSN in some embodiments also has one or more SSNs added to or removed from its SN group. In some embodiments, the PSN in some embodiments directs a set of controllers to add (e.g., instantiate or allocate) or remove an SSN to or from the SN group. Also, to assess the load on the service nodes, the PSN in some embodiments receives message load data from the controller set, which collects such data from each service node. In other embodiments, the PSN receives such load data directly from the SSNs.


As mentioned above, the PSN has the data messages distributed among the service nodes in its SN group based on its assessment of the message traffic load on the service nodes of the SN group. The PSN uses different techniques in different embodiments to distribute the data messages to the service node(s) in its group. In some embodiments, the PSN receives each data message for which the service has to be performed. In these embodiments, the PSN either performs the service on the data message, or re-directs the data message to an SSN to perform the service on the data message. To redirect the data messages, the PSN in different embodiments uses different techniques, such as MAC redirect (for L2 forwarding), IP destination network address translation (for L3 forwarding), port address translation (for L4 forwarding), L2/L3 tunneling, etc. In some embodiments, the PSN has a connection data store that maintains the identity of the service node that it previously identified for each data message flow, in order to ensure that data messages that are part of the same flow are directed to the same service node (i.e., to the PSN or the same SSN).


In other embodiments, the PSN configures a set of one or more front-end load balancers (FLBs) that receives the data messages before the PSN, so that the FLB set can direct the data messages to the PSN or the SSN. To configure the FLB set, the PSN in some embodiments receives the first data message of a new data message flow that is received by the FLB set so that the PSN can figure out how the new flow should be distributed. When such a data message has to be forwarded to a particular SSN, the PSN in some embodiments directs the data message to the SSN, and configures the FLB set to direct the data message's flow to the SSN. Before the configuration of the FLB set is completed, the PSN in some embodiments may have to receive data messages that are part of this flow (i.e., the flow that is directed to the particular SSN). In such situation, the PSN of some embodiments direct the data messages to the particular SSN, until the load balancer set can directly forward subsequent data messages of this flow to the particular SSN.


In other embodiments, the PSN configures the FLB set differently. For instance, in some embodiments, the PSN configures the FLB set by simply providing the identity (e.g., the MAC and/or IP address) of each service node in the SN group, and the FLB set uses its own load balancing scheme (e.g., a standard equal cost multipath, ECMP, scheme) to distribute the data message flows to the service nodes in the SN group in a stateful or stateless manner. In other embodiments, the PSN configures the FLB set by providing to the FLB set a load balancing parameter set that provides a particular scheme for the FLB set to use to distribute the data message flows to the service nodes in the SN group.


For example, in some embodiments, the PSN provides to the FLB set a hash table that defines multiple hash value ranges and a service node for each hash value range. In some such embodiments, a load balancer in the FLB set generates a hash value from a header parameter set of a data message flow, identifies the hash range (in the hash table) that contains the hash value, and selects for the data message flow the service node that is associated with the identified hash range. To make its flow distribution stateful, the load balancer in some embodiments stores the identity of the identified service node for the data message flow in a flow connection-state storage, which the load balancer can subsequently access to select the identified service node for subsequent data messages of the flow.


In some embodiments, the service nodes (PSN and SSNs), as well as some or all of the source compute nodes (SCNs) and destination compute nodes (DCNs) that send and receive messages to and from the service nodes, are machines (e.g., virtual machines (VMs) or containers) that execute on host computing devices. A host computing device in some embodiments can execute an arbitrary combination of SCNs, DCNs and service nodes. In some embodiments, the host also executes one or more software forwarding elements (e.g., software switches and/or software routers) to interconnect the machines that execute on the host and to interconnect these machines (through the network interface of the host and intervening forwarding elements outside of the host) with other SCNs, DCNs, and/or service nodes that operate outside of the host. In some embodiments, one or more SCNs, DCNs, and service nodes (PSN and SSNs) are standalone devices (i.e., are not machines that execute on a host computing device with other machines).


The elastic service architecture of some embodiments can be used to provide different services in a computer network. In some embodiments, the services can be any one of the traditional middlebox services, such as load balancing, firewall, intrusion detection, intrusion protection, network address translation (NAT), WAN (wide area network) optimizer, etc. When the service that is performed by the service node group is not load balancing, the PSN of the service node group (that includes the PSN and one or more SSNs) in some embodiments performs a load balancing service in addition to the service performed by all the service nodes in the group. As mentioned above, the PSN in some embodiments performs this load balancing service in order to ensure that the SN group's service is distributed among the service nodes of the group (i.e., in order to distribute the data message load among these service nodes). As described above, the PSN performs different load balancing operations in different embodiments. These operations range from re-directing data message flows directly to the SSNs in some embodiments, to configuring a FLB set to direct the data message flows to the service nodes in other embodiments.


In some cases, the SN group's service is load balancing. In these cases, the PSN performs two types of load balancing. The first type of load balancing is the same load balancing that is performed by all of the service nodes in the group, while the second type of load balancing is a load balancing operation that the PSN performs to ensure that the first type of load balancing is distributed among the group's service nodes (including the PSN). For instance, in some embodiments, the first type load balancing operation is based on L3, L4 and/or L7 parameters of the data messages, and each SN of the group performs this load balancing operation. In addition to performing this load balancing operation, the PSN in some embodiments also performs a second load balancing operation, which is an L2 load balancing operation (e.g., a load balancing operation that relies on the data message L2 parameters and on MAC redirect) that distribute the data messages (on which it does not perform the first type load balancing) to one or more other service nodes of the SN group.


In other embodiments, the first type load balancing operation is based on L4 and/or L7 parameters of the data messages. Each SN of the group performs this L4 and/or L7 load balancing operation. In addition, the PSN of some embodiments also performs an L2 and/or L3 load balancing operation (e.g., a load balancing operation that relies on the data message L3 parameters and IP address DNAT) to distribute the data messages (on which it does not perform the first type load balancing) to one or more other service nodes of the SN group.


In cases where the SN group's service is load balancing, the PSN second type of load balancing operation in some embodiments might not require the PSN to directly re-direct the data message flows to the SSN. For instance, in some embodiments, the PSN's second type load balancing might simply configure an FLB set to direct the data message flows to the service nodes. As mentioned above, the PSN can configure the FLB set differently in different embodiments, e.g., by providing to the FLB set only the SN group membership data, or providing to the FLB set a hash table that for each of several header-parameter, specifies hash-value ranges identifies a service node.


In some embodiments, the SSNs of a SN group also re-direct the data message flows that they receive. For example, in some embodiments, the PSN supplies to an FLB set a SN group update each time a service node is added to or removed from the group. In some such embodiments, each FLB in the FLB set distributes the data message flows in a stateless manner. Before such an FLB in the FLB set updates its distribution scheme based on the updated group membership, the FLB might send a new data message flow to a first service node based on the FLB's old distribution scheme. After this FLB updates its distribution scheme based on the updated group membership, the FLB might send the data message flow to the a second service node based on the FLB's new distribution scheme.


For such a case, the first service node needs to re-direct the data messages for the new flow to the second service node that needs to process these data messages based on the new distribution scheme. When the FLB set distributes data message flows based on its own load balancing distribution scheme, each service node needs to perform this load balancing distribution scheme so that they can predict the service node that should receive the new data message flow based on an updated SN group membership. When the FLB set distributes data message flows based on load balancing parameter (LBP) set provided by the PSN (e.g., based on the hash table provided by the PSN), each SSN in some embodiments either (1) obtains the LBP set form the PSN, or (2) performs the same load balancing operations as the PSN in order to independently derive the LBP set that the PSN will provide to the FLB set. In these embodiments, each SSN uses the LBP set in order to re-direct a new message flow to the correct service node when the FLB set forwards the message flow incorrectly to the SSN.


When the FLB set distributes data message flows in a stateless manner, a first service node (e.g., a PSN or an SSN) might also need to re-direct to a second service node an old data message flow that it receives from the FLB set, because the second service node has previously been processing the data message flow and the FLB set statelessly has begun forwarding the data message flow to the first service node based on an update that it has received from the PSN. To perform this re-direction, the service nodes in some embodiments synchronize in real-time flow connection-state data that identifies the flows that each of them is handling at any time. In some embodiments, the flow connection-state data is synchronized through control channel communication between the service nodes.


The preceding Summary is intended to serve as a brief introduction to some embodiments of the invention. It is not meant to be an introduction or overview of all inventive subject matter disclosed in this document. The Detailed Description that follows and the Drawings that are referred to in the Detailed Description will further describe the embodiments described in the Summary as well as other embodiments. Accordingly, to understand all the embodiments described by this document, a full review of the Summary, Detailed Description, the Drawings and the Claims is needed. Moreover, the claimed subject matters are not to be limited by the illustrative details in the Summary, Detailed Description and the Drawing.





BRIEF DESCRIPTION OF THE DRAWINGS

The novel features of the invention are set forth in the appended claims. However, for purposes of explanation, several embodiments of the invention are set forth in the following figures.



FIG. 1 illustrates an example service architecture of some embodiments of the invention.



FIG. 2 illustrates a multi-host computer system of some embodiments of the invention.



FIG. 3 conceptually illustrates a process that a primary service node (PSN) performs whenever the PSN receives a data message in some embodiments.



FIG. 4 illustrates an example of how service nodes are added to a service node (SN) group and how the group's PSN distributes the data traffic among the service node of the SN group.



FIG. 5 illustrates an example of the secondary service nodes (SSNs) of one SN group are PSNs or SSNs of another SN group.



FIG. 6 illustrates an example of two different service node groups performing two different services for data messages that are sent to the same set of destination compute nodes after they are processed by the service nodes of groups.



FIG. 7 illustrates a process that the PSN of a load balancing SN group performs in some embodiments.



FIG. 8 illustrates an example of how load balancers are added to a load-balancing service group, and how the group's PSN distributes the data traffic among the load balancers of the group.



FIG. 9 illustrates a process of a PSN of some embodiments that configures a set of one or more front end load balancers (FLBs) to distribute data message flows that the PSN identifies as flows that should be processed by other service nodes of the PSN's SN group.



FIG. 10 illustrates an example of a PSN working with an FLB as service nodes are added to a SN group.



FIG. 11 illustrates an example of each service node having a load balancer that performs the secondary load balancing operation to direct messages to other service nodes.



FIG. 12 illustrates a process that a load balancer of a PSN or an SSN performs in some embodiments that have the PSN configure a stateless FLB set with periodic LBP set updates.



FIG. 13 presents an example that is similar to the example illustrated in FIG. 11, except that the service operation of the SN group is a load balancing operation.



FIG. 14 illustrates an architecture of a host that executes one or more SVMs and one or more load balancers of some embodiments of the invention.



FIGS. 15 and 16 presents examples of load balancing rules that are stored in the LB rule storage.



FIG. 17 illustrates a process that the LB agent performs in some embodiments each time that it receives updated group memberships and/or global statistics from a controller set.



FIG. 18 illustrates a process that the LB agent of the PSN SVM performs in some embodiments to elastically adjust the membership of the PSN's SN group.



FIG. 19 illustrates a process that one or more controllers in the controller set perform in some embodiments.



FIG. 20 illustrates an elastic SN group of some embodiments being used to elastically provide services at an edge of a network.



FIG. 21 conceptually illustrates a computer system with which some embodiments of the invention are implemented.





DETAILED DESCRIPTION

In the following detailed description of the invention, numerous details, examples, and embodiments of the invention are set forth and described. However, it will be clear and apparent to one skilled in the art that the invention is not limited to the embodiments set forth and that the invention may be practiced without some of the specific details and examples discussed.


Some embodiments provide an elastic architecture for providing a service in a computing system. As used in this document, data messages refer to a collection of bits in a particular format sent across a network. One of ordinary skill in the art will recognize that the term data message may be used herein to refer to various formatted collections of bits that may be sent across a network, such as Ethernet frames, IP packets, TCP segments, UDP datagrams, etc.


To perform a service on the data messages, the service architecture uses a service node (SN) group that includes one primary service node (PSN) and zero or more secondary service nodes (SSNs). The service can be performed on a data message by either the PSN or one of the SSN. In addition to performing its group's service, the PSN also performs a load balancing operation that assesses the load on each service node (i.e., on the PSN or each SSN), and based on this assessment, has the data messages distributed to the service node(s) in its SN group.


Based on the assessed load, the PSN in some embodiments also has one or more SSNs added to or removed from its SN group. To add or remove an SSN to or from the service node group, the PSN in some embodiments directs a set of controllers to add (e.g., instantiate or allocate) or remove the SSN to or from the SN group. Also, to assess the load on the service nodes, the PSN in some embodiments receives message load data from the controller set, which collects such data from each service node. In other embodiments, the PSN receives such load data directly from the SSNs.


The elastic service architecture of some embodiments can be used to provide different services in a computer network. In some embodiments, the services can be any one of the traditional middlebox services, such as load balancing, firewall, intrusion detection, intrusion protection, network address translation (NAT), WAN optimizer, etc. When the service that is performed by the service node group is not load balancing, the PSN of the service node group (that includes the PSN and one or more SSNs) in some embodiments performs a load balancing service in addition to the service performed by all the service nodes in the group. As mentioned above, the PSN performs this load balancing service in order to ensure that the SN group's service is distributed among the service nodes of the group. This load balancing service of the PSN is different in different embodiments. This service ranges from re-directing data message flows directly to the SSNs in some embodiments, to configuring a front-end load balancer (FLB) set to direct the data message flows to the service nodes in other embodiments, as further described below.


On the other hand, when the SN group's service is load balancing, the PSN performs two types of load balancing. The first type of load balancing is the same load balancing that is performed by all of the service nodes in the group, while the second type of load balancing is a load balancing operation that the PSN performs to ensure that the first type of load balancing is distributed among the group's service nodes (including the PSN).


For instance, in some embodiments, the first type load balancing operation is an L3, L4 and/or L7 load balancing operation, while the second type of load balancing operation is an L2 load balancing operation. In other embodiments, the first type load balancing operation is an L4 and/or L7 load balancing operation, while the second type of load balancing operation is an L2 and/or L3 load balancing operation. As used in this document, references to L2, L3, L4, and L7 layers are references respectively to the second data link layer, the third network layer, the fourth transport layer, and the seventh application layer of the OSI (Open System Interconnection) layer model.


In different embodiments, the PSN uses different techniques to distribute the data messages to one or more SSNs. In some embodiments, the PSN receives each data messages for which the service has to be performed, and either performs the service on the data message, or re-directs the data message to an SSN to perform the service on the data message. In other embodiments, the PSN configures an FLB set that receives the data messages before the PSN, so that the FLB set can direct the data messages to the PSN or the SSN. As further described below, the PSN can configure the FLB set differently in different embodiments, e.g., by providing to the FLB set only the SN group membership data, by configuring the FLB set for each flow, or by providing to the FLB set a hash table that identifies a service node for each of several header-parameter, hash-value ranges.



FIGS. 3-8 illustrate several examples of a PSN that does not use an FLB set to distribute the data messages to SSNs in its SN group, while FIGS. 9-13 illustrate several examples of a PSN that uses an FLB set to do this task. Before explaining these examples, a multi-host system of some embodiments will be first described by reference to FIGS. 1 and 2. In this system, the service nodes (PSN and SSNs), as well as some or all of the source compute nodes (SCNs) and destination compute nodes (DCNs) that send and receives messages from the service nodes, are machines (e.g., virtual machines (VMs) or containers) that execute on host computing devices. Notwithstanding these examples, one of ordinary skill will realize that the elastic service architecture in some embodiments is used in computer networks that have one or more SCNs, DCNs, and service nodes (PSN and SSNs) operate as standalone devices (i.e., as machines that do not execute on a host computing device with other machines).



FIG. 1 illustrates an example service architecture 100 of some embodiments of the invention. In this deployment, two different sets of elastically adjustable service node groups 150 and 155 are deployed between three groups 160, 165, and 170 of compute nodes. As shown, the compute nodes in each CN group and the service nodes in each SN groups are virtual machines that execute on six host computing devices 105-130 in a datacenter. In FIG. 1, the service nodes in SN group 150 are designated with the acronym SNG1, while the service nodes in SN group 155 are designated with the acronym SNG2. In the discussion below, the compute nodes are referred to as guest VMs (GVMs) while the service nodes are referred to as service VMs (SVMs).


The service node group 150 has three service nodes, while the service node group 155 has two service nodes. In each of these groups, one service node is a primary service node, with each other node being a secondary service node. The two SN groups 150 and 155 can perform the same service operation (e.g., load balancing operation) or can perform two different service operations (e.g., a firewall operation for SN group 150 and a load balancing operation for SN group 155). However, even when the two SN groups perform the same service operation, the service operation of one SN group is distinct and independent from the service operation of the other SN group (e.g., the SN groups perform two different firewall operations).


Each CN group can include an arbitrary collection of compute nodes, or it can be a collection of a particular type of compute nodes. For instance, the CN groups 160, 165, and 170 in some deployments are a collection of web servers 160, application servers 165, and database server 170, while in other embodiments one CN group (e.g., group 165) includes a collection of different types of servers.


A host computing device (also referred to as a host) in some embodiments can execute an arbitrary combination of SCN, DCN and SN virtual machines. FIG. 1 illustrates that in addition to the GVMs and SVMs that execute on the hosts, each host also executes a software forwarding element (SFE) 135 in some embodiments. The SFE 135 on a host communicatively couples the VMs of the host to each other, and to other devices outside of the host (e.g., VMs on other hosts) through a network interface card (NIC) of the host and the intervening network fabric (such as switches and routers) outside of the host. Examples of SFEs include software switches, software routers, etc.


In some embodiments, the VMs execute on top of a hypervisor, which is a software layer that enables the virtualization of the shared hardware resources of the host. In some of these embodiments, the hypervisor provides the SFE functionality on a host computing device, while in other embodiments, the forwarding element functionality is provided by another software module or hardware component (e.g., the network interface card) of the host computing device.


In some embodiments, each service node in an SN group maintains statistics regarding the message traffic load that it processes. Each service node in some embodiments forwards the collected statistics to a set of controllers, which aggregates these statistics and distributes aggregated load data to the PSN in the SN group. Alternatively, in some embodiments, the SSNs directly forward their collected statistics to the PSN.


In some embodiments, the PSN of a SN group uses the aggregated load data to control how the data message flows are directed to different service nodes in its group. In some embodiments, the aggregated load data are also used to determine when new service nodes should be added to or removed from a SN group. In some embodiments, each SSN also receives the load data from the controller set or from other service nodes, in order to compute the load balancing parameters that the PSN will compute.



FIG. 2 illustrates a multi-host system 200 of some embodiments that includes a controller set that gathers statistics from the service nodes and distributes aggregated statistics to the PSNs. As shown, this system includes multiple hosts 205-215, a set of one or more controllers 225, and a network 275. The network 275 communicatively couples the hosts with each other and with the controller set. In some embodiments, the network is a local area network (LAN), a wide area network (WAN), and/or a network of networks (e.g., Internet).


In some embodiments, the hosts 205-215 are similar to the hosts 105-130 of FIG. 1. In FIG. 2, the communicative couplings between each SFE on a host and the GVMs and SVMs on the host are conceptually illustrated. As mentioned above, the SFE on the host communicatively couples the GVMs and SVMs of the host to each other, and to other devices outside of the host (e.g., VMs on other hosts) through the host's NIC and the intervening network 275.



FIG. 2 also shows each host 205, 210, or 215 having an SVM agent 260 for communicating with the controller set 225. Through this communication, the SVM agent can receive configuration data for configuring the operation of the SVMs that operate on the agent's host. Also, in some embodiments, the SVM agent forwards message load statistics from the SVMs on the agent's host to the controller set 225. In some embodiments, the SVM agent aggregates and/or analyzes some of the statistics before relaying processed statistics to the controller set, while in other embodiments the SVM agent relays collected raw statistics to the controller set.


When a PSN executes on the agent's host, the SVM agent of some embodiments receives global load statistics or load balancing parameters from the controller set 225 to supply to any PSN that executes on its host. In some embodiments, the SVM agent receives aggregated statistics from the controller set, analyzes the aggregated statistics, and generates and/or to adjusts the load balancing parameters of the PSN that executes on the agent's hosts.


In some embodiments, the SVM agents are not used at all, or are used for only some of the above-described operations. For instance, in some embodiments, the PSN and SSN SVMs directly send their load statistic data to the controller set 235, and/or the PSN SVMs directly receive the global statistic data from the controller set 235. Also, in some embodiments, the SVM agents are not used to compute or adjust the load balancing parameters of the PSNs, as the PSN SVMs compute or adjust these values. In some embodiments, the SVM agents are not used to configure the SVMs. For instance, in some embodiments, the controller set 225 communicates directly with the SVMs to configure their operations.


As mentioned above, the controller set 225 in some embodiments receives load statistic data from the SVMs of each SN group, generates global load statistic data from the received data, and distributes the global load statistic data to the PSN of the SN group. In other embodiments, the SSNs send their load statistics data directly to the PSN of their group. In different embodiments, the SVMs provide the load statistic data (e.g., to the controller set or to the PSN) in terms of different metrics. Examples of such metrics include number of data message flows currently being processed, number of data messages processed within a particular time period, number of payload bytes in the processed messages, etc.


The controller set distributes the global load statistic data in different forms in different embodiments. In some embodiments, global load data is in the same format as the format that the controller set receives the load data from the service nodes, except that the global load data is an aggregation of the received statistic data from the different service nodes. In other embodiments, the controller set processes the load statistic data from the SVMs to produce processed global statistic data that is in a different format or is expressed in terms of different metrics than the load statistic data that it receives from the service nodes.


Based on the distributed global load statistic data, the PSN of a SN group in some embodiments generates load balancing parameter (LBP) set for distributing the data message flows (e.g., new data message flows) to the service nodes of the group. In some embodiments, the PSN then uses the LBP set to distribute the data message flows to the service nodes of its SN group, while in other embodiments, the PSN uses the LBP set to configure an FLB set to distribute the data message flows.


As mentioned above, even in the embodiments that the PSN configures the FLB set, the PSN in some embodiments uses the LBP set to distribute the data message flows (e.g., because the FLB set statelessly distributes the load or has not yet reconfigured for a new LBP set that is provided by the PSN). In some embodiments, an SSN might also have to distribute the data message flows during this interim time period for similar reasons. To do this, each SSN of a SN group would have to receive the global load statistic data from the controller set, or the global load statistic data or LBP set from the PSN (directly from the PSN or indirectly through the controller set).


Instead of distributing global load statistic data, the controller set 225 of some embodiments generates LBP set from the statistic data that it receives from the service nodes of an SN group, and distributes the load balancing parameter set to the PSN of the SN group. In some embodiments, the PSN then uses this load balancing parameter set to distribute the data message flows to the service nodes of its SN group, while in other embodiments, the PSN uses the load balancing parameter set to configure an FLB set to distribute the data message flows. Again, in some cases (e.g., because the FLB set statelessly distributes the load or has not yet reconfigured for a new LBP set that is provided by the PSN), the PSN in some embodiments might have to use the load balancing parameter set to distribute the data message flows. In some embodiments, an SSN might also have to distribute the data message flows for the same reasons, and for this, the SSN would have to receive LBP set from the controller set.


In addition to distributing global load statistic data and/or load balancing parameters, the controller set 225 in some embodiments also adds service nodes to an SN group, or removes service nodes from the SN group, based on the monitored load on the service nodes in the SN group. In some embodiments, the controller set 225 adds or removes a service node based on its own determination, while in other embodiments the controller set adds or removes a service node in response to a request from the PSN of the SN group. In some embodiments, the controller set 225 adds a service node by instantiating a new SVM and adding this SVM to the SN group. In other embodiments, the controller set 225 adds the service node by allocating a previously instantiated SVM to the SN group.


In some embodiments, the controller set 225 provide control and management functionality for defining (e.g., allocating or instantiating) and managing one or more VMs on the host computing devices 205-215. The controller set 225 also provide control and management functionality for defining and managing multiple logical networks that are defined on the common software forwarding elements of the hosts. In some embodiments, the controller set 225 includes multiple different sets of one or more controllers for performing different sets of the above-described controller operations.



FIGS. 3-8 illustrate several examples of a PSN that directly distributes the data messages to the SSN of its SN group without the use of an FLB set. FIG. 3 conceptually illustrates a process 300 that such a PSN performs whenever the PSN receives a data message in some embodiments. The process 300 identifies one service node in the PSN's SN group that should process the received data message, and then directs the identified service node to perform the SN group's service for the received data message. The identified service node can be the PSN itself, or it can be an SSN in the SN group.


As shown in FIG. 3, the process 300 starts (at 305) when the PSN receives a data message. In some embodiments, the received data message is addressed to the SN group. For instance, in some embodiments, the received data message is a data packet that contains the virtual IP (VIP) address of the SN group as its destination address. In some of these embodiments, the group address is not only defined by the VIP address, but also by the port number of the service. In some embodiments, the SN group address is the address of the PSN of the group.


After receiving the data message, the process determines (at 310) whether the received message is part of a particular data message flow for which the PSN has previously processed at least one data message. To make this determination, the process examines (at 310) a flow connection-state data storage that stores (1) the identity of each of several data message flows that the PSN previously processed, and (2) the identity of the service node that the PSN previously identified as the service node for processing the data messages of each identified flow. In some embodiments, the process identifies each flow in the connection-state data storage in terms of one or more flow attributes, e.g., the flow's five tuple header values, which are the source IP address, destination IP address, source port, destination port, and protocol. Also, in some embodiments, the connection-state data storage is hash indexed based on the hash of the flow attributes (e.g., of the flow's five tuple header values). For such a storage, the PSN generates a hash value from the header parameter set of a data message, and then uses this hash value to identify one or more locations in the storage to examine for a matching header parameter set (i.e., for a matching data message flow attribute set).


When the process identifies (at 310) an entry in the flow connection-state data storage that matches the received data message flow's attributes (i.e., when the process determines that it previously processed another data message that is part of the same flow as the received data message), the process directs (at 315) the received data message to the service node (in the SN group) that is identified in the matching entry of the connection-state data storage (i.e., to the service node that the PSN previously identified for processing the data messages of the particular data message flow). This service node then performs the service on the data message, and augments the statistics that it maintains (e.g., the data message count, the byte count, etc.) regarding the data messages that it processes. This service node can be the PSN itself, or it can be an SSN in the SN group. After 315, the process ends.


On the other hand, when the process determines (at 310) that the connection-state data storage does not store an entry for the received data message (i.e., determines that it previously did not process another data message that is part of the same flow as the received data message), the process transitions to 320. In some embodiments, the connection-state data storage periodically removes old entries that have not matched any received data messages in a given duration of time. Accordingly, in some embodiments, when the process determines (at 310) that the connection-state data storage does not store an entry for the received data message, the process may have previously identified a service node for the data message's flow, but the matching entry might have been removed from the connection-state data storage.


At 320, the process determines whether the received data message should be processed locally by the PSN, or remotely by another service node of the SN group. To make this determination, the PSN in some embodiments performs a load balancing operation that identifies the service node for the received data message flow based, based on the load balancing parameter set that the PSN maintains for the SN group at the time that the data message is received. As mentioned before, the load balancing parameter set is adjusted in some embodiments (1) based on updated statistic data regarding the traffic load on each service node in the SN group, and (2) based on service nodes that are added to or removed from the SN group.


The process 300 performs different load balancing operations (at 320) in different embodiments. In some embodiments, the load balancing operation relies on L2 parameters of the data message flows (e.g., generates hash values form the L2 parameters, such as source MAC addresses, to identify hash ranges that specify service nodes for the generated hash values) to distribute the data messages to service nodes, while in other embodiments, the load balancing operations relies on L3/L4 parameters of the flows (e.g., generates hash values form the L3/L4 parameters, such as five tuple header values, to identify hash ranges that specify service nodes for the generated hash values) to distribute the data messages to service nodes. In yet other embodiments, the load balancing operations (at 320) use different techniques (e.g., round robin techniques) to distribute the load amongst the service nodes.


When the process determines (at 320) that the PSN should process the received data message, the process directs (at 325) a service module of the PSN to perform the SN group's service on the received data message. Based on this operation, the PSN's service module also augments (at 325) the statistics that it maintains (e.g., the data message count, the byte count, etc.) regarding the data messages that the PSN processes. At 325, the process 300 also creates an entry in the flow connection-state data storage to identify the PSN as the service node for processing data messages that are part of the same flow as the received data message. In some embodiments, this entry identifies the PSN and identifies the received data message header values (e.g., five tuple values) that specify the message's flow. After 325, the process ends.


When the process determines (at 320) that based on its load balancing parameter set, the PSN should not process the received data message, the process identifies (at 320) another service node in the PSN's SN group to perform the service on the data message. Thus, in this situation, the process directs (at 330) the message to another service node in the PSN's SN group. To redirect the data messages, the PSN in different embodiments uses different techniques, such as MAC redirect (for L2 forwarding), IP destination network address translation (for L3 forwarding), port address translation (for L4 forwarding), L2/L3 tunneling, etc.


To perform MAC redirect, the process 300 in some embodiments changes the MAC address to a MAC address of the service node that it identifies at 320. For instance, in some embodiments, the process changes the MAC address to a MAC address of another SFE port in a port group that contains the SFE port connected with the PSN. More specifically, in some embodiments, the service nodes (e.g., SVMs) of a SN group are assigned ports of one port group that can be specified on the same host or different hosts. In some such embodiments, when the PSN wants to redirect the data message to another service node, it replaces the MAC address of the PSN's port in the data message with the MAC address of the port of the other service node, and then provides this data message to the SFE so that the SFE can forward it directly or indirectly (through other intervening forwarding elements) to the port of the other service node.


Similarly, to redirect the data message to the other service node through IP destination network address translation (DNAT), the PSN replaces the destination IP address in the data message to the destination IP address of the other service node, and then provides this data message to the SFE so that the SFE can forward it directly or indirectly (through other intervening forwarding elements) to the other service node. In some embodiments, the initial destination IP address in the data message that gets replaced is the VIP of the SN group. This VIP in some embodiments is the IP address of the PSN.


To redirect the data message to the other service node through port address translation, the PSN replaces the destination port address in the data message to the destination port address of the other service node, and then uses this new port address to direct the data message to the other service node. In some embodiments, the PSN's network address translation may include changes to two or more of the MAC address, IP address, and port address.


After directing (at 330) the data message to the other service node, the process creates (at 335) an entry in the connection-state data storage to identify the other service node as the service node for processing data messages that are part of the same flow as the received data message. In some embodiments, this entry identifies (1) the other service node and (2) the received data message header values (e.g., five tuple values) that specify the message's flow. After 335, the process ends.



FIG. 4 illustrates an example of how service nodes are added to a SN group 400, and how the group's PSN distributes the data traffic among the service node of the SN group. This example is illustrated in three stages 405-415 that illustrate the operation of the SN group at three different instances in time. The first stage 405 illustrates that at a time T1, the SN group just includes the PSN 420. As shown, the PSN 420 has a load balancer (LB) and a service virtual machine (SVM1). In the first stage 405, the PSN receives all data messages on which the SN group has to perform its service, performs this service on these messages, and then directs these messages to their destination compute nodes 425.


In some embodiments, the destination node for a data message after a service node performs a service on the data message is the source compute node that sent the data message directly or indirectly to the service node group. In other embodiments, the service node is deployed at the edge of a network, and the destination node for a data message that a service node processes, is the compute node or forwarding element inside or outside of the network to which the service node is configured to send its processed messages. In still other embodiments, the service node identifies the destination node for a data message that it processes based on the data message's header parameters and based on the service node's configured rules that control its operation.


The second stage 410 illustrates that a time T2, the SN group has been expanded to include another service node, SSN1, which is implemented by a second service virtual machine, SVM2. In some embodiments, the service node SSN1 is added to the group because the data message load on the group has exceeded a first threshold value. The controller set 225 in some embodiments adds SSN1 when it detects that the data message load has exceeded the first threshold value, or when the PSN detects this condition and directs the controller set to add SSN1. To assess whether the data message load exceeds a threshold value, the controller set or PSN in different embodiments quantify the data message load based on different metrics. In some embodiments, these metrics include one or more of the following parameters: (1) number of flows being processed by the SN group or by individual service nodes in the group, (2) number of packets being processed by the SN group or by individual service nodes in the group, (3) amount of packet data being processed by the SN group or by individual service nodes in the group.


The second stage 410 also illustrates that time T2 the PSN performs the SN group's service on some of the data message flows, while directing other data message flows to SSN1 so that this service node can perform this service on these other flows. As shown, once either the PSN or SSN1 performs the service on a data message, the PSN or SSN1 directs the data message to one of the destination compute nodes that should receive the data message after the SN group processes them. As shown in FIG. 4, the PSN performs a load balancing (LB) operation before performing its own SN group service. The LB operation is the operation that determines which service node in the SN group should perform the group's service on each data message that the PSN receives. In some embodiments, the LB operation is also the operation that determines when service nodes should be added to or removed from the SN group.


The third stage 415 illustrates that a time T3, the SN group has been expanded to include yet another service node, SSN2, which is a third service virtual machine, SVM3. In some embodiments, the service node SSN2 is added to the group because the data message load on the group, or on SVM1 and/or SVM2, has exceeded a second threshold value, which is the same as the first threshold value in some embodiments or is different than the first threshold value in other embodiments. As before, the controller set 225 in some embodiments adds SSN2 when it or the PSN detects that the data message load has exceeded the second threshold value. The third stage 415 also illustrates that time T3, the PSN performs the SN group's service on some of the data message flows, while directing other data message flows to SSN1 or SSN2, so that these service nodes can perform this service on these other flows. As shown, once any of the service nodes, PSN, SSN1, or SSN2, performs the service on a data message, the service node directs the data message to one of the destination compute nodes that should receive the data message after the SN group processes them.


In some embodiments, the SSNs of one SN group are PSNs or SSNs of another SN group. FIG. 5 illustrates an example of this by showing two operational stages 510 and 515 of two different SN groups 500 and 505. The two operational stages 510 and 515 show the operation of each SN group at two different instances in time. The first stage 510 illustrates that at a time T1, the SN group 500 just includes PSN1, while SN group 505 just includes PSN2. The service operations of PSN1 are performed by SVM1, while the service operations of PSN2 are performed by SVM2. As shown, each PSN has a load balancer to perform its load balancing operation to distribute the load among the service nodes in its SN group.


In the first stage 510, PSN1 receives all data messages on which the SN group 500 has to perform its service, performs this service on these messages, and then directs these messages to a first set of destination compute nodes 525. Similarly, in this stage, PSN2 receives all data messages on which the SN group 505 has to perform its service, performs this service on these messages, and then directs these messages to a second set of destination compute nodes 530, which is different than the first set of compute nodes 525.


The second stage 515 illustrates that a time T2, the SN group 500 has been expanded to include SVM2 as a service node SSN1. Accordingly, at this stage, SVM2 performs the service operations of PSN1 of SN group 505, and the service operations of SSN1 of SN group 500. In some embodiments, the controller set or PSN1 decides to add SVM2 as service node SSN1 to SN group 500 because the data message load on this group (i.e., on PSN1) has exceeded a first threshold value (as detected by the controller set or the PSN1) and SVM2 has excess capacity to handle service operations for SN group 500.


The second stage 515 also illustrates that time T2 the PSN1 performs the service of SN group 500 on some of the data message flows, while directing other data message flows to SVM2 so that SVM2 can perform the service of group 500 on these other flows. At this stage, the SVM2 not only performs the service of group 500 on the flows passed by the PSN1, but also performs the service of group 505 on the message flows that it receives for group 505. Once either the SVM1 or SVM2 performs the service of group 500 on a data message, the SVM directs the data message to one of the first set of destination compute nodes 525. Also, once SVM2 performs the service of group 505 on a data message, this SVM directs the data message to one of the second set of destination compute nodes 530.


Some embodiments do not allow one SN group to add an underutilized SVM of another SN group (i.e., to use the excess capacity of another service node group's underutilized SVM). However, some of these embodiments allow one SN group to add a service node by instantiating or utilizing a new SVM on a host that executes the PSN or SSN of another SN group. In this manner, these embodiments allow one SN group to capture the underutilized computational capacity of another group's host.


In the example illustrated in FIG. 5, the two SN groups 500 and 505 direct data messages to different sets of compute nodes 525 and 530. However, in some embodiments, the destination compute nodes of the two groups partially or fully overlap. FIG. 6 illustrates an example of two different service node groups 600 and 605 performing two different services for data messages that are sent to the same set of destination compute nodes 625 after they are processed by the service nodes of groups 600 and 605. The only difference between the examples of FIGS. 5 and 6 is that in FIG. 5, the SN groups 500 and 505 direct the processed data messages to two different sets of compute nodes 525 and 530, while in FIG. 6, the SN groups 600 and 605 direct the processed data messages to the same set of compute nodes 625.


In some embodiments, the service of a SN group is load balancing traffic that a set of SCNs sends to a set of two or more DCNs. In such cases, the SN group's PSN performs two types of load balancing. The first type of load balancing is the same load balancing that is performed by all of the service nodes in the group, while the second type of load balancing is a load balancing operation that the PSN performs to ensure that the first type of load balancing is distributed among the group's service nodes (including the PSN).


For instance, in some embodiments, the first type load balancing operation is an L3, L4 and/or L7 load balancing operation, while the second type of load balancing operation is an L2 load balancing operation. In other embodiments, the first type load balancing operation is an L4 and/or L7 load balancing operation, while the second type of load balancing operation is an L2 and/or L3 load balancing operation. An LN load balancing operation distributes the load amongst the DCNs based on LN header parameters of the data messages, where N is an integer that can be 2, 3, 4, or 7. When a load balancing that is based on different layer parameters, the load balancing operation distributes the load amongst the DCNs based on different layer header parameters. For example, when the load balancing is based on L2 and L3 header values, the load balancer in some embodiments generates a hash of the L2 and L3 header values of the data message flow and identifies a DCN for the data message flow based on the L2 and L3 header values. Alternatively, for such an example, the load balancer in some embodiments uses the flow's L2 and L3 header values to identify a load balancing rule that provides load balancing criteria for selecting a DCN for the data message flow (e.g., by using the criteria to pick the DCN in a round robin manner).



FIG. 7 illustrates a process 700 that the PSN of a load balancing SN group performs in some embodiments. This process is similar to the process 300 of FIG. 3, except that the service that is performed by the SN group is a load balancing operation that distributes data messages among the compute nodes of a DCN group. The PSN process 700 (1) performs a load balancing operation (referred to above and below as the second type of load balancing), to identify one load balancer in the SN group that should process the received data message, and then (2) directs the data message to the identified load balancer to perform another type of load balancing operation (referred to above and below as the first type of load balancing) on the data message. The identified load balancer can be the PSN itself, or it can be an SSN in the SN group.


As shown in FIG. 7, the process 700 starts (at 705) when the PSN receives a data message. In some embodiments, the received data message is addressed to the SN group. For instance, in some embodiments, the received data message is a data packet that contains the virtual IP (VIP) address of the SN group as its destination address. In some embodiments, the SN group address is the IP address of the PSN of the group.


After receiving the data message, the process determines (at 710) whether the received message is part of a particular data message flow for which the PSN has previously processed at least one data message. To make this determination, the process examines (at 710) a flow connection-state data storage that stores (1) the identity of each of several data message flows that the PSN previously processed, and (2) the identity of the load balancer that the PSN previously identified as the load balancer for processing the data messages of each identified flow. In some embodiments, the process 700 identifies each flow in the connection-state data storage in terms of one or more flow attributes, e.g., the flow's five tuple header values. Also, in some embodiments, the connection-state data storage is hash indexed based on the hash of the flow attributes (e.g., of the flow's five tuple header values).


When the process identifies (at 710) an entry in the connection-state data storage that matches the received data message flow's attributes (i.e., when the process determines that it previously processed another data message that is part of the same flow as the received data message), the process directs (at 715) the received data message to the load balancer (in the SN group) that is identified in the matching entry of the connection-state data storage (i.e., to the load balancer that the PSN previously identified for processing the data messages of the particular data message flow). This load balancer then performs the first type of load balancing operation on the data message to direct the received data message to one compute node in the DCN set. This load balancer also augments the statistics that it maintains (e.g., the data message count, the byte count, etc.) regarding the data messages that it processes. This load balancer can be the PSN itself, or it can be an SSN in the SN group. After 715, the process ends.


On the other hand, when the process determines (at 710) that the connection-state data storage does not store an entry for the received data message (i.e., determines that it previously did not process another data message that is part of the same flow as the received data message), the process determines (at 720) whether the received data message should be processed locally by the PSN, or remotely by another load balancer of the SN group. To make this determination, the PSN in some embodiments performs the second type of load balancing operation that relies on a second set of load balancing parameters that the PSN maintains for the SN group at the time that the data message is received.


The second type of load balancing operation is based on different load balancing parameter sets in different embodiments. For instance, in some embodiments, the second type of load balancing operation is an L2 load balancing operation that relies on load balancing parameter set that are defined in terms of L2 parameters. In other embodiments, the second type of load balancing operation is an L2 and/or L3 load balancing operation that relies on load balancing parameter set that are defined in terms of L2 and/or L3 parameters. As mentioned before, the load balancing parameter set is adjusted in some embodiments (1) based on updated statistic data regarding the traffic load on each load balancer in the SN group, and (2) based on load balancers that are added to or removed from the SN group.


When the process determines (at 720) that the PSN should process the received data message, the process directs (at 725) a load balancer module of the PSN to perform the first type of load balancing operation on the received data message. The first type of load balancing operation relies on a first set of load balancing parameter that the PSN maintains for the DCN group at the time that the data message is received.


The first type of load balancing operation is based on different load balancing parameter sets in different embodiments. For instance, in some embodiments, the first type load balancing operation is an L3, L4 and/or L7 load balancing operation and the load balancing parameter set is defined in terms of L3, L4 and/or L7 parameters. In other embodiments, the first type load balancing operation is an L4 and/or L7 load balancing operation and the load balancing parameter set is defined in terms of L4 and/or L7 parameters.


Also, in some embodiments, an LB parameter set includes load balancing criteria that the load balancer uses to select a destination for the message (e.g., to select a destination in a weighted round robin fashion). In other embodiments, an LB parameter set includes a hash table that specifies several hash value ranges and a destination for each hash value range. The load balancer generates a hash value from a set of header values (e.g., the L3, L4 and/or L7 parameter) of a data message, and then selects for the message the destination that is associated with the hash-value range that contains the generated hash value. Some embodiments uses the same load balancing approaches (e.g., hashing approaches) for the first and second load balancing operations of the PSN, while other embodiments uses different load balancing approaches (e.g., a hashing approach and a round robin approach) sets for these load balancing operations of the PSN.


At 725, the PSN also augments the statistics that it maintains (e.g., the data message count, the byte count, etc.) regarding the data messages that it distributes to the DCN identified at 725. At 725, the process 700 also creates an entry in the connection-state data storage to identify the PSN as the load balancer for performing the first type of load balancing operation on the data messages that are part of the same flow as the received data message. In some embodiments, this entry identifies the PSN and identifies the received data message header values (e.g., five tuple values) that specify the message's flow. After 725, the process ends.


When the process determines (at 720) that based on its second set of load balancing parameters, the PSN should not distribute the received data message to one of the DCNs, the process identifies (at 720) another load balancer in the PSN's SN group to distribute the data message to a DCN. Thus, in this situation, the process directs (at 730) the message to another load balancer in the PSN's SN group. To redirect the data messages, the PSN in different embodiments uses different techniques, such as MAC redirect (for L2 forwarding), IP destination network address translation (for L3 forwarding), port address translation (for L4 forwarding), L2/L3 tunneling, etc. These techniques were described above by reference to operation 330 of the process 300 of FIG. 3.


After directing (at 730) the data message to the other load balancer, the process creates (at 735) an entry in the connection-state data storage to identify the other load balancer as the service node for load balancing the data messages that are part of the same flow as the received data message. In some embodiments, this entry identifies (1) the other service node and (2) the received data message header values (e.g., five tuple values) that specify the message's flow. After 735, the process ends.


As mentioned above, the PSN's distribution of the data messages to other load balancers in its load balancing service group is based on the second set of load balancing parameters that is adjusted based on message load data aggregated and distributed by the controller set in some embodiments. In some embodiments, the data aggregated and distributed by the controller set also updates the first set of load balancing parameters that the load balancers in the PSN's load balancer group use to distribute the data messages amongst the DCNs in the DCN group. Examples of modifying such load balancing operations based on dynamically gathered and updated message load data is described in U.S. patent application Ser. No. 14/557,287 now issued as U.S. Pat. No. 10,320,679.



FIG. 8 illustrates an example of how load balancers are added to a load-balancing service group 800, and how the group's PSN distributes the data traffic among the load balancers of the group. This example is similar to the example illustrated in FIG. 4, except that the service nodes are load balancers. FIG. 8 illustrated three operational stages 805-815 of the service group 800 at three different instances in time. The first stage 805 illustrates that at a time T1, the service group 800 just includes the PSN 820. As shown, the PSN receives all the data messages that have to be load balanced, and based on a first set of load balancing parameters, distributes these messages among the compute nodes of a DCN group 825.


In FIG. 8, the PSN 820 is shown to include two load balancers, which are LB1_1 and LB2. LB 1_1 is a first type load balancer that distributes the data messages between the compute nodes of the DCN group, while LB2 is a second type load balancer that distributes the data messages between the first type load balancers of the service group 800 so that one of these load balancers can distribute the data messages between the compute nodes of the DCN group 825. In the first stage, the PSN 820 is the only first type load balancer of the service group 800, so the PSN's second type load balancer at this stage simply forwards all the data messages to the PSN's LB1_1.


The second stage 810 illustrates that a time T2, the service group 800 has been expanded to include a service node SSN1, which in this example is a load balancer LB 1_2. In some embodiments, the LB 1_2 is added to the group because the data message load on the group has exceeded a first threshold value. The controller set 225 in some embodiments adds LB 1_2 when it detects that the data message load has exceeded the first threshold value, or when the PSN detects this condition and directs the controller set to add this secondary service node. To assess whether the data message load exceeds a threshold value, the controller set or PSN in different embodiments quantify the data message load based on different metrics, such as the metrics described above (e.g., by reference to FIG. 4).


The second stage 810 also illustrates that at time T2, the LB 1_1 performs the group's load balancing on some of the data message flows, while directing other data message flows to LB 1_2 so that this load balancer can perform this service on these other flows. As shown, the first type load balancing operation that either the LB 1_1 or LB 1_2 performs on a data message, directs the data message to one of the compute nodes in the DCN group 825. As shown in FIG. 8, the PSN's LB2 performs the second load balancing operation before performing the first load balancing operation. The second load-balancing operation is the operation that determines which first type load balancer in the service group 800 should distribute each data message among the DCNs.


The third stage 815 illustrates that a time T3, the SN group has been expanded to include yet another service node SSN2, which in this example is a load balancer LB 1_3. In some embodiments, the load balancer LB 1_3 is added to the group because the data message load on the group or on the PSN or SSN1 has exceeded a second threshold value. As before, the controller set 225 in some embodiments adds LB 1_3 when it or the PSN detects that the data message load has exceeded the second threshold value. The third stage 815 also illustrates that at time T3, the PSN distributes some of the data message flows among the DCNs, while directing other data message flows to LB 1_2 and LB 1_3 so that these load balancers can distribute these other flows among the DCNs.


Instead of relying on the SN group's PSN to distribute directly the data messages among the service nodes of the SN group, some embodiments use one or more front-end load balancers to do this task. For general purpose service nodes, FIG. 9 illustrates a process 900 of a PSN of some embodiments that configures a set of one or more FLBs to distribute data message flows that the PSN identifies as flows that should be processed by other service nodes of the PSN's SN group. This process is identical to the process 300 of FIG. 3, except that the process 900 includes an operation 945 that sends configuration data to the FLB set to configure this set to forward data messages that are part of a message flow that should be processed by another service node (based on the determination at 320), to the other service node.


After sending (at 945) the configuration data to the FLB set, the PSN might continue to receive data messages for a data message flow that should be directed to another service node because the FLB set has not yet been reconfigured based on the sent configuration data, and therefore continues to send data messages of the redirected flow to the PSN. In a subsequent iteration for a data message of a flow that should be directed to another service node, the process forwards the data message to the other service node at 315.



FIG. 10 illustrates an example of a PSN working with a front-end load balancer 1050 as service nodes are added to a SN group 1000. This example is similar to the example illustrated in FIG. 4 except that in FIG. 10, there is now the front-end load balancer 1050 that directs the data message flows to the service nodes in the SN group 1000. In some embodiments, the front-end load balancer 1050 is a hardware appliance (e.g., an F5 load balancer), standard switch, or high-end software switch, while the service nodes in the SN group 1000 are SVMs executing on host computing devices. Also, while only one front-end load balancer is illustrated in FIG. 10, two or more front-end load balancers are used in some embodiments of the invention to distribute the load among the service nodes of one or more SN groups.



FIG. 10 illustrates three operational stages 1005-1015 of the SN group 1000 at three different instances in time. The first stage 1005 illustrates that at a time T1, the SN group just includes the PSN 1020. As shown, the PSN is formed by (1) a service virtual machine SVM1, which performs the service of the SN group, and (2) a load balancer LB, which performs a load balancing operation that identifies the service node in the SN group that should perform the group's service on each data message that the PSN receives. In the first stage 1005, the load balancer directs all the data messages to its SVM1, which performs the SN group's service on these messages and then directs these messages to their destination compute nodes 1025.


The second stage 1010 illustrates that at a time T2, the SN group 1000 has been expanded to include another service node, SSN1, which is the service virtual machine SVM2. In some embodiments, the service node SSN1 is added to the group because the data message load on the group has exceeded a first threshold value, as quantified by a set of metrics (such as those described above by reference to FIG. 4). The controller set 225 in some embodiments adds SSN1 when it detects that the data message load has exceeded the first threshold value, or when the PSN detects this condition and directs the controller set to add SSN1.


The second stage 1010 also illustrates that at time T2, the PSN configures the load balancer to direct some of the flows to the PSN while directing other flows to SSN1. Because of this configuration, the PSN performs the SN group's service on some of the data message flows, while SSN1 performs this service on other data message flows. The second stage 1010 also shows that the load balancer LB of the PSN 1020 directs some of the data message flows to SSN1 for this service node to process. These directed messages are those that the SSN1 has to process, but the PSN receives because the front-end load balancer 1050 has not yet been configured to forward these data messages to SSN1. As shown, once either the PSN or SSN1 performs the service on a data message, the PSN or SSN1 directs the data message to one of the destination compute nodes 1025 that should receive the data message after the SN group processes them.


The third stage 1015 illustrates that at time T3, the SN group 1000 has been expanded to include yet another service node, SSN2, which is the service virtual machine SVM2. In some embodiments, the service node SSN2 is added to the group because the data message load on the group, or on PSN and/or SSN1, has exceeded a second threshold value, as quantified by a set of metrics like those described above. As before, the controller set 225 in some embodiments adds SSN2 when it or the PSN detects that the data message load has exceeded the second threshold value.


The third stage 1015 also illustrates that at time T3, the PSN configures the load balancer 1050 to distribute the flows amongst all the SN group members, i.e., amongst PSN, SSN1, and SSN2. Because of this configuration, the PSN performs the SN group's service on some of the data message flows, SSN1 performs this service on other data message flows, and SSN2 performs this service on yet other data message flows. As shown, once the PSN, SSN1 or SSN2 performs the service on a data message, the PSN, SSN1 or SSN2 directs the data message to one of the destination compute nodes that should receive the data message after the SN group processes them.


The third stage 1015 also shows that the load balancer LB of the PSN 1020 directs some of the data message flows to SSN1 and SSN2 for these service nodes to process. These directed messages are those that SSN1 or SSN2 has to process, but the PSN receives because the front-end load balancer 1050 has not yet been configured to forward to these data messages to SSN1 or SSN2. In other embodiments, the PSN's load balancer does not direct the data message flows to SSNs during the second and third stages 1010 and 1015. For instance, in some embodiments, the FLB set queues a new data message flow until it receives instructions from the PSN as to which service node should process the new data message flow. In other embodiments, the PSN's load balancer does not direct the data messages to other SSNs because the FLB set statefully distributes the data message flows to the service nodes, as further explained below.


In the example illustrated in FIGS. 9 and 10, the FLB 1050 sends each new flow to the PSN 1020, so that the PSN's LB 1080 can program (configure) the FLB 1050 to direct the flow to a SSN if an SSN needs to process this new flow. Absent receiving such instructions, the FLB 1050 will send all the data messages for the flow to the PSN. In other embodiments, the PSN does not configure the FLB for each new flow (i.e., on a flow-by-flow basis), but rather configures the FLB with a load balancing parameter (LBP) set that the FLB set analyzes to determine how to distribute data message flows to the service nodes of the SN group.


The PSNs of different embodiments provide different LBP sets to their FLB sets. For instance, in some embodiments, the distributed LBP set includes the SN group membership (e.g., the network address (L2 and/or L3 address) of each service node in the SN group). In these embodiments, the FLB uses its own load balancing scheme (e.g., its own equal cost multipath, ECMP, process) to distribute the data message flows amongst the service nodes of the SN group. For instance, in some embodiments, the FLB set's ECMP process generates hash ranges based on the SN group membership that the PSN provides, and then uses the generated hash ranges to distribute the data message flows amongst the service nodes.


In other embodiments, the PSN's distributes LBP set includes the SN group membership and a distribution scheme for the FLB to use to distribute flows across the service nodes of the SN group. For instance, in some embodiments, the PSN provides to the FLB a hash table that identifies each service node of a SN group and specifies a hash range for each service node of the group. In some embodiment, the hash table (e.g., a hash table the PSN generates for itself or for an FLB) can specify the same destination node (e.g., the same service node) for two or more contiguous or non-contiguous hash ranges specified by the hash table.


The FLB generates a hash value for each flow (e.g., from the flow's five tuple), and then uses the PSN-provided hash value to identify the service node for the flow (i.e., identifies the hash range in the supplied table that contains the generated hash value, and then identifies the service node associated with the identified hash range). In some embodiments, each time that the SN group membership changes, the PSN distributes to the FLB set a new LBP set, which may include (i) an updated group membership to the FLB set and/or (ii) an updated distribution scheme (e.g., an updated hash table). Also, in some embodiments, each time that the PSN determines that the load distribution has to be modified amongst the existing service nodes of the SN group, the PSN distributes an updated LBP set to the FLB set to modify the FLB set's distribution of the data message flows amongst the service nodes of the SN group. In some embodiments, an updated LBP set includes an updated hash table, which may have more hash ranges or new service nodes for previously specified hash ranges.


In some embodiments, a front-end load balancer and a PSN use stateful load balancing processes that ensure that flows that were previously processed with a service node, remain with that node even after a new service node is added to the SN group. This is because without the stateful nature of these load balancing processes, a flow that was processed by one service node might get directed to a new service node because the addition of a new node might affect a load balancing scheme or a load balancing computation (e.g., a hash computation) that the load balancers use to distribute the data message flows amongst the service nodes of the group. One way that an FLB or PSN ensures stateful load balancing in some embodiments is to use a flow connection-state storage that stores the identity of the service node for a previously processed flow.


In other embodiments, the FLB set uses a stateless load balancing scheme. For instance, in some embodiments, the FLB is a simple forwarding element (e.g., hardware or software switch) that receives the SN group membership, defines several hash value ranges and their associated service nodes based on the number of service nodes, and then performs a stateless ECMP process that distributes the data messages as it receives by generating hashes of the message header values and determining the hash ranges that contain the generated hashes. In other embodiments, the FLB is a forwarding element (e.g., software or hardware switch) that (1) receives from the PSN a hash table containing several hash value ranges and their associated service nodes, and (2) performs a stateless ECMP process that distributes the data messages as it receives them by generating hashes of the message header values and determining the hash ranges that contain the generated hashes.


The FLB in either of these approaches does not maintain the flow connection states. Whenever the PSN provides a new LBP set (e.g., new SN group membership and/or distribution scheme) in either of these stateless approaches, the FLB may forward a flow that was previously processed by one service node to another service node. To avoid different service nodes from processing the same flow, the service nodes of the SN group of some embodiments synchronize their flow connection states (e.g., through control channel communications) so that when an FLB forwards an old flow that was handled by a first service node to a second service node, the second service node can detect that the first service node was processing this flow and re-direct the flow to the second service node. In some embodiments, a service node may also re-direct a new flow to another service node when the flow was not previously processed by the other service node. For example, in some cases, the service node detects that although the flow is new and has not been processed by any other service node, it should be handled by another service node once the FLB set reconfigures based on an updated LBP set that the PSN distributes.


To determine when flows need to be re-directed, each service node (i.e., the PSN and each SSN) in a SN group in some embodiments includes a load balancer that performs the secondary load balancing operation to direct messages to other service nodes. FIG. 11 illustrates an example of one such approach. This example is similar to the example illustrated in FIG. 10 in that a SN group 1100 is shown to be growing from one service node (PSN 1020) to three service nodes (PSN, SSN1 and SSN2) in three operational stages 1105-1115. Also, like the example of FIG. 10, the service nodes provide their processed data messages to the compute nodes 1125.


However, in the example illustrated in FIG. 11, the PSN does not configure the FLB on a flow-by-flow basis, but rather provides the FLB 1150 with an updated LBP set each time that it modifies the SN group. The updated LBP set includes just the SN group membership updated in some embodiments, while it also includes a distribution scheme (e.g., a hash table) in other embodiments.


In the example of FIG. 11, the FLB 1150 distributes the data message flows in a stateless manner. Accordingly, in this example, each service node includes a load balancer, which, as shown in the second and third stages 1110 and 1115, allows each service node to forward to the other service nodes the data message flows that the FLB 1150 forwards to it that should really be processed by the other service nodes.


One example of a data message flow that a first service node re-directs to a second service node includes a flow that was previously processed by the second service node but that after the LBP set updated, gets forwarded to the first service node by the FLB's stateless load balancing. To identify such a flow, the service nodes of some embodiments synchronize their flow connection states (e.g., through control channel communications). Another example for re-directing a data message flow is when the FLB has not yet reconfigured its operations based on a new LBP set from the PSN and forwards a new flow to a service node that determines based on the new LBP set another service node should process this new flow. To identify the need for such a re-direction, the SSNs in some embodiments obtain the LBP set updates from the PSN, or derive the LBP set updates independently of the PSN by using similar update processes. To derive the LBP set updates independently, the SSNs receive the same global statistics (from the controller set or from the other service nodes) as the PSN in some embodiments.



FIG. 12 illustrates a process 1200 that a load balancer of a PSN or an SSN (e.g., SSN1 of FIG. 11) performs in some embodiments that have the PSN configure a stateless FLB set with periodic LBP set updates. This process ensures that the PSN or SSN processes data message flows that it should process, while directing other data message flows that other service nodes have to perform to other service nodes in the group.


As shown in FIG. 12, the process 1200 starts (at 1205) when the service node (PSN or SSN) receives a data message (e.g., from the PSN or the FLB set). After receiving the data message, the process determines (at 1210) whether the received message is part of a data message flow that one of the service nodes has previously processed. To make this determination, the process examines (at 1210) a flow connection-state data storage that stores (1) the identity of the data message flows that the service nodes previously processed, and (2) the identity of the service node that previously processed the identified flow.


The flow connection-state storage includes the flows that are being currently processed by all the service nodes. To maintain this storage, the service nodes synchronize the records in the connection-state storage on a real-time basis in some embodiments. This synchronization is through control channel communications in some embodiments. Also, in some embodiments, the process identifies each flow in the connection-state data storage in terms of one or more flow attributes, e.g., the flow's five tuple header values. As mentioned above, the connection-state data storages in some embodiments are hash indexed storages.


When the process identifies (at 1210) an entry in the connection-state data storage that matches the received data message flow's attributes (i.e., when it determines that the data message flow has been previously processed by one of the service nodes), the process then determines (at 1212) the identity of the service node that should process the data message from the matching connection-state data storage entry. When this matching entry specifies that another service node should process the received message, the process then directs (at 1214) the received data message to this other service node and then ends. The process 1200 re-directs the data messages to the other service node using one of the approaches mentioned above (e.g., MAC redirect, destination network address translation, etc.).


When the process determines (at 1212) that the matching entry identifies the process' associated SVM (e.g., SVM1 of PSN or SVM2 of SSN1 in FIG. 11) as the service node for the received data message, the process then directs (at 1215) its own SVM to perform this service. This SVM then performs the service on the data message, and augments the statistics that it maintains (e.g., the data message count, the byte count, etc.) regarding the data messages that it processes. After 1215, the process ends.


When the process determines (at 1210) that the connection-state data storage does not store an entry for the received data message (i.e., determines that the received data message flow is not a flow currently being processed by any service node), the process determines (at 1220) whether the received data message should be processed locally by its SVM, or remotely by another service node of the SN group. In some embodiments, another service node should process the received data message's flow when the LBP set (e.g., SN group membership) has changed but the FLB set has yet to complete its reconfiguration for a new distribution scheme that accounts for LBP set update (e.g., an addition or removal of a service node to the SN group).


To make the determination at 1220, the process needs to know of the LBP set update. When the process is performed by an SSN, the SSN would have to receive the LBP set update from the PSN, or would have to independently derive the LBP set update by using similar processes and similar input data as the PSN. In some embodiments, the LBP set update identifies the service node that should process a new data message flow. In other embodiments, the FLB set uses the LBP set to derive its load distribution scheme (e.g., to derive the hash values for its ECMP distribution scheme). For these embodiments, a service node would need to generate a load distribution scheme (e.g., to generate a hash table) from the LBP set update in the same manner as the FLB set, and then use this generated distribution scheme to identify the service node that should receive a new data message load (e.g., to identify the service node associated with a hash table range that contains a hash that is derived from the data message's header values).


When the process determines (at 1220) that its associated SVM should process the received data message, the process directs (at 1225) its SVM to perform the SN group's service on the received data message. Based on this operation, the SVM also augments (at 1225) the statistics that it maintains (e.g., the data message count, the byte count, etc.) regarding the data messages that it processes. At 1225, the process 1200 also creates an entry in the connection-state data storage to identify its SVM as the service node for processing data messages that are part of the same flow as the received data message. In some embodiments, this entry identifies the SVM and identifies the received data message header values (e.g., five tuple values) that specify the message's flow. After 1225, the process ends.


When the process determines (at 1220) that another service node should process the data message, the process directs (at 1230) the message to another service node in the SN group. To redirect the data messages, the process 1200 in different embodiments uses different techniques, such as MAC redirect (for L2 forwarding), IP destination network address translation (for L3 forwarding), port address translation (for L4 forwarding), L2/L3 tunneling, etc. These operations were described above by reference to FIG. 3.


After directing (at 1230) the data message to the other service node, the process creates (at 1235) an entry in the connection-state data storage to identify the other service node as the service node for processing data messages that are part of the same flow as the received data message. In some embodiments, this entry identifies (1) the other service node and (2) the received data message header values (e.g., five tuple values) that specify the message's flow. After 1235, the process ends


In the example illustrated in FIGS. 10 and 11, the service nodes of SN group 1000 or 1100 can be any type of service nodes, e.g., firewalls, intrusion detection systems, intrusion prevention systems, WAN optimizers, etc. However, in some cases, the service that is provided by the SN group is a load balancing service. To illustrate this, FIG. 13 presents an example that is identical to the example illustrated in FIG. 11, except that the service operation of the SN group is a load balancing operation. Accordingly, in the example illustrated in FIG. 13, each service node performs two types of load balancing operations. One operation is to distribute the data message flows to other the service nodes that need to process the flows, while the other operation is to distribute the processed data message load to the DCNs of a DCN group.


As mentioned above, the distribution of the data message load to the DCNs is referred to as the first type load balancing while the distribution of the data message load to the group's service nodes (so that each can perform the first type load balancing) is referred to as the second type load balancing. In some embodiments, the PSN's second type load balancing in the system of FIG. 13 differs slightly from the SSN's second type load balancing in that this operation of the PSN also entails (1) directing the controller set to modify the SN group membership, and (2) informing the FLB of the change to the SN group (e.g., after receiving confirmation of this change from the controller set).


In some embodiments, one SVM performs both the load balancing operation and the service operation (which may be a non-load balancing service or a load balancing service) of a PSN or an SSN. However, in other embodiments, the two operations of such a service node (e.g., of a PSN, or of an SSN in the cases where the SSN performs a load balancing operation and another service) are performed by two different modules of the service node's associated host.


In some of these embodiments, the service node's service operation is performed by an SVM, while the service node's load balancing operation is performed by a load balancer that intercepts data messages from the datapath to the SVM. One such approach is illustrated in FIG. 14. Specifically, this figure illustrates an architecture of a host 1400 that executes one or more SVMs 1405 and one or more load balancers 1415 of some embodiments of the invention. In this architecture, each SVM 1405 in some embodiments pairs with a load balancer 1415 to form one service node of a SN group, as further described below. In other embodiments, only the PSN is implemented by an associated pair of an SVM 1405 and a load balancer 1415; the SSNs in these embodiments are implemented by an SVM 1405.


In addition to the SVMs 1405 and load balancers 1415, the host 1400 executes one or more GVMs 1402, a software forwarding element 1410, an LB agent 1420, and a publisher 1422. The host also has LB rule storage 1440 and the STATs data storage 1445, as well as group membership data storage 1484, policy data storage 1482, aggregated statistics data storage 1486, and connection state storage 1490.


The software forwarding element (SFE) 1410 executes on the host to communicatively couple the VMs of the host to each other and to other devices outside of the host (e.g., other VMs on other hosts) through the host's physical NIC (PNIC) and one or more forwarding elements (e.g., switches and/or routers) that operate outside of the host. As shown, the SFE 1410 includes a port 1430 to connect to a PNIC (not shown) of the host. For each VM, the SFE also includes a port 1435 to connect to the VM's VNIC 1425. In some embodiments, the VNICs are software abstractions of the PNIC that are implemented by the virtualization software (e.g., by a hypervisor). Each VNIC is responsible for exchanging packets between its VM and the SFE 1410 through its corresponding SFE port. As shown, a VM's egress datapath for its data messages includes (1) the VM's VNIC 1425, (2) the SFE port 1435 that connects to this VNIC, (3) the SFE 1410, and (4) the SFE port 1430 that connects to the host's PNIC. The VM's ingress datapath is the same except in the revere order (i.e., first the port 1430, then the SFE 1410, then the port 1435, and finally the VNIC 1425.


In some embodiments, the SFE 1410 is a software switch, while in other embodiments it is a software router or a combined software switch/router. The SFE 1410 in some embodiments implements one or more logical forwarding elements (e.g., logical switches or logical routers) with SFEs executing on other hosts in a multi-host environment. A logical forwarding element in some embodiments can span multiple hosts to connect VMs that execute on different hosts but belong to one logical network. In other words, different logical forwarding elements can be defined to specify different logical networks for different users, and each logical forwarding element can be defined by multiple SFEs on multiple hosts. Each logical forwarding element isolates the traffic of the VMs of one logical network from the VMs of another logical network that is serviced by another logical forwarding element. A logical forwarding element can connect VMs executing on the same host and/or different hosts.


Through its port 1430 and a NIC driver (not shown), the SFE 1410 connects to the host's PNIC to send outgoing packets and to receive incoming packets. The SFE 1410 performs message-processing operations to forward messages that it receives on one of its ports to another one of its ports. For example, in some embodiments, the SFE tries to use header values in the VM data message to match the message to flow based rules, and upon finding a match, to perform the action specified by the matching rule (e.g., to hand the packet to one of its ports 1430 or 1435, which directs the packet to be supplied to a destination VM or to the PNIC). In some embodiments, the SFE extracts from a data message a virtual network identifier and a MAC address. The SFE in these embodiments uses the extracted VNI to identify a logical port group, and then uses the MAC address to identify a port within the port group.


The SFE ports 1435 in some embodiments include one or more function calls to one or more modules that implement special input/output (I/O) operations on incoming and outgoing packets that are received at the ports. One of these function calls for a port is to a load balancer in the load balancer set 1415. In some embodiments, the load balancer performs the load balancing operations on incoming data messages that are addressed to load balancer's associated VM (e.g., the load balancer's SVM that has to perform a service on the data message). For the embodiments illustrated by FIG. 14, each port 1435 has its own load balancer 1415. In other embodiments, some or all of the ports 1435 share the same load balancer 1415 (e.g., all the ports share one load balancer, or all ports that are part of the same logical network share one load balancer).


Examples of other I/O operations that are implemented by the ports 1435 include ARP proxy operations, message encapsulation operations (e.g., encapsulation operations needed for sending messages along tunnels to implement overlay logical network operations), etc. By implementing a stack of such function calls, the ports can implement a chain of I/O operations on incoming and/or outgoing messages in some embodiments. Instead of calling the I/O operators (including the load balancer set 1415) from the ports 1435, other embodiments call these operators from the VM's VNIC or from the port 1430 of the SFE.


In some embodiments, a PSN of a SN group is formed by an SVM 1405 and the SVM's associated in-line load balancer 1415. Also, for the embodiments that have an SSN perform a load balancing operation in addition to its service operation, the SSN is formed by an SVM and the SVM's associated in-line load balancer 1415. When an SSN does not perform a load balancing operation to distribute message flows to other service nodes, each SSN is implemented by only an SVM in some embodiments, while other embodiments implement each SSN with an SVM and an load balancer 1415 so that this load balancer can maintain statistics regarding the data message load on the SSN's SVM.


In some embodiments, an SVM's load balancer performs the load balancing operation needed to distribute data messages to its own SVM or to other SVMs in its SN group. When the SVM and the load balancer form a PSN, the PSN's load balancer in some embodiments may one or more of the following operations: (1) directing the controller set to modify SN group membership, (2) supplying statistics to the controller set, (3) receiving global statistics from the controller set, (4) receiving statistics from the SSNs, and (5) providing LBP data (including group membership data) to the SSNs.


When a PSN works with an FLB set, the PSN's load balancer in some embodiments configures (e.g., provides LBP set to) the FLB set, so that the FLB set can perform its load balancing operation to distribute the load amongst the service nodes of the SN group 1300. The PSN's load balancer configures the FLB differently in different embodiments. For instance, in some embodiments, the PSN simply provides the FLB with a list of service nodes in the SN group. In other embodiments, the PSN also provides the FLB with a specific distribution scheme (e.g., a hash lookup table, etc.). In still other embodiments, for each new flow that the FLB sends the PSN, the PSN configures the FLB with the identity of the service node for processing this new flow.


In other embodiments, the PSN's load balancer does not communicate with the controller set, does not send LBP data to its group's SSNs, and/or does not configure the FLB, because some or all of these operations are performed by the LB agent 1420 of the PSN's host. For instance, in some of embodiments, the LB agent 1420 of the host communicates with the controller set (1) to provide statistics regarding its hosts service nodes, and (2) to receive global statistics, group membership updates, and/or membership update confirmations for the SN group of any PSN that executes on its host. Also, in some embodiments, the LB agent 1420 provides the SSNs with LBP data and/or configures the FLB, as further described below.


In some embodiments, each SN group is associated with a VIP address and this address is associated with the SN group's PSN. In some of these embodiments, the load balancer 1415 of the SN group's PSN handles ARP messages that are directed to the group's VIP. In this manner, the initial data messages of new data message flows to the group's VIP will be forwarded to the load balancer of the group's PSN. In other embodiments, the PSN's load balancer does not handle the ARP messages to the group's VIP but another module that executes on the PSN's host handles the ARP messages and this module's response ensures that the initial data messages of new data message flows to the group's VIP are forwarded to the PSN's load balancer. For example, in some embodiments, an ARP proxy module is inserted in the datapath of the PSN's SVM in the same manner as the PSN's load balancer (i.e., the ARP proxy is called by the SVM's VNIC or SFE port). This ARP proxy then responds to the ARP messages for the SN group's VIP address. It should be noted that the ARP message response is disabled on all SSN of the SN group. Also, in some embodiments, the PSN's ARP module (e.g., its load balancer or ARP proxy module) sends out gratuitous ARP replies at the beginning when the service is started on the primary host.


A service node's load balancer 1415 performs its load balancing operations based on the LB rules that are specified in the LB rule storage 1440. For a virtual address (e.g., VIP) of a load balanced group, the LB rule storage 1440 stores a load balancing rule that specifies two or more physical addresses (e.g., MAC addresses) of service nodes of the group to which a data message can be directed. As mentioned above, a PSN's associated load balancer may direct a data message to its SVM or to one or more SVMs that execute on the same host or different hosts. In some embodiments, this load balancing rule also includes load balancing metrics for specifying how the load balancer should bias the spreading of traffic across the service nodes of the group associated with a virtual address.


One example of such load balancing metrics is illustrated in FIG. 15, which presents examples of load balancing rules that are stored in the LB rule storage 1440. As shown, this data storage includes multiple LB rules 1500, with each LB rule associated with one load balanced SN group. In this example, each load balance rule includes (1) a set of data-message identifying tuples 1505, (2) several MAC addresses 1510 of several SNs of the load balanced SN group, and (3) a weight value 1515 for each IP address.


Each rule's tuple set 1505 includes the VIP address of the rule's associated SN group. In some embodiments, the tuple set 1505 also includes other data message identifiers, such as source IP address, source port, destination port, and protocol. In some embodiments, a load balancer examines a LB data storage by comparing one or more message identifier values (e.g., message five-tuple header values) to the rule tuple sets 1505 to identify a rule that has a tuple set that matches the message identifier values. Also, in some embodiments, the load balancer identifies the location in the data storage 1440 that may contain a potentially matching tuple set for a received data message by generating a hash of the received data message identifier values (e.g., the message five-tuple header values) and using this hash as an index that identifies one or more locations that may store a matching entry. The load balancer then examines the tuple set 1505 at an identified location to determine whether the tuple set 1505 stored at this location matches the received message's identifier values.


In some embodiments, the MAC addresses 1510 of an LB rule are the MAC addresses of the SVMs of the SN group that has the VIP address specified in the rule's tuple set 1505. The weight values 1515 for the MAC addresses of each LB rule provide the criteria for a load balancer to spread the traffic to the SVMs that are identified by the MAC addresses. For instance, in some embodiments, the PSN's load balancer use a weighted round robin scheme to spread the traffic to the SVMs of the load balanced SN group. As one example, assume that the SN group has five SNs (i.e., five SVMs) and the weight values for the MAC addresses of these SNs are 1, 3, 1, 3, and 2. Based on these values, a load balancer would distribute data messages that are part of ten new flows as follows: 1 to the first MAC address, 3 to the second MAC address, 1 to the third MAC address, 3 to the fourth MAC address, and 2 to the fifth MAC address.


When the load balancer 1415 identifies an LB rule for a received data message and then based on the rule's LB criteria identifies an SVM for the data message, the load balancer then replaces the message's original destination MAC address with the identified SVM's MAC address when the message's original destination MAC address is not the identified SVM's MAC address (i.e., is not the MAC address of the load balancer's SVM). The load balancer then sends the data message along its datapath. In some embodiments, this operation entails returning a communication to the SFE port 1435 (that called the load balancer) to let the port know that the load balancer is done with its processing of the data message. The SFE port 1435 can then handoff the data message to the SFE 1410 or can call another I/O chain operator to perform another operation on the data message. Instead of using MAC redirect, the load balancers 1415 of some embodiments perform destination network address translation (DNAT) operations on the received data messages in order to direct the data messages to the correct SVMs. DNAT operations entail replacing the VIP address in the data message with the IP address of the identified SVM.


In some embodiments, the load balancers maintain statistics in the STAT data storage 1445 about the data messages that they direct to their associated SVM. To maintain such statistics for data message load on the SSNs, some embodiments have a load balancer 1415 for each SSN even when the SSNs do not have to distribute message flows to other service nodes. In such cases, other embodiments do not employ a load balancer 1415 for an SSN, but rather have the SSN's SVM maintain such statistics and have the LB agent of the SVM's host obtain these statistics from the SVM.


In some embodiments, the LB agent 1420 periodically supplies to the controller set the statistics that are gathered (e.g., by the load balancers 1415 or the SVMs 1405 of the service nodes) for a SN group and stored in the STAT data storage 1445. In some embodiments, LB agent 1420 generates and updates the LBP set (e.g., load balancing weight values or load balancing hash table) for a SN group with PSNs and/or SSNs on the agent's host. When multiple different SN groups have SVMs and load balancers executing on a host, the host's LB agent 1420 in some embodiments performs some or all of its operations for all of the SN groups that execute on its host. Other embodiments, however, use different LB agents for different SN groups that have SVMs and load balancers executing on the same host.


To gracefully switch between different LBP sets, the LB rules in some embodiments specify time periods for different LBP sets that are valid for different periods of time. FIG. 16 illustrates examples of load balancing rules 1600 that are stored in the LB rule storage 1440 in some embodiments. Each load balancing rule 1600 has one message identifying tuple 1605, one or more MAC address sets 1610, and one weight value set 1615 for each MAC address set. Each MAC address set 1610 has two or more MAC addresses, and each weight value set has one weight value for each MAC address in its associated MAC address set.


In the example illustrated in FIG. 16, each pair of associated MAC address set and weight value set has a time period during which the MAC address set 1610 and its associated weight value set 1615 are valid. For instance, in a LB rule, the time value for one MAC address set might specify “before 1 pm on 9/1/2014,” while the time value for another MAC address set might specify “after 12:59 pm on 9/1/2014.” These two time periods allow the load balancers to seamlessly switch from using one MAC address set and its associated weight value set to another MAC address set and its associated weight value set at 1 pm on 9/1/2014. These two MAC address sets might be identical and they might only differ in their associated weight value sets, or the two MAC address sets might be different. Two MAC address sets might differ but have overlapping MAC addresses (e.g., one set might have five MAC addresses, while another set might have four of these five MAC addresses when one SN is removed from a SN group). Alternatively, two MAC address sets might differ by having no MAC addresses in common.


In FIG. 16, the time period values and the weight values are used in the LB rules. One of ordinary skill will realize that in other embodiments, the LB rules do include the weight values, but include the time values to allow the load balancer to gracefully switch between different LBP sets, e.g., switch between two different hash lookup tables.


As shown in FIG. 14, the host includes a connection state storage 1490 in which each load balancer 1415 stores data records that allow the load balancer to maintain connection state for data messages that are part of the same flow, and thereby to distribute statefully data messages that are part of the same flow to the same SVM.


More specifically, whenever a load balancer identifies an SVM for a data message based on the message's group destination address (e.g., the destination VIP), the load balancer not only may replace the destination MAC address, but also stores a record in the connection state storage 1490 to identify the SVM for subsequent data messages that are part of the same flow. This record stores the MAC address of the identified SVM along with the data message's header values (e.g., source IP address, source port, destination port, destination VIP, protocol). The connection data storage 1490 is hash indexed based on the hash of the data message header values.


Accordingly, to identify an SVM for a received data message, the load balancer first checks the connection state storage 1490 to determine whether it has previously identified an SVM for receiving data messages that are in the same flow or flow hash range as the received message. If so, the load balancer uses the SVM that is identified in the connection state storage. Only when the load balancer does not find a connection record in the connection state storage 1490, the load balancer in some embodiments examines the LB rule storage to try to identify an SVM for the data message.


In FIG. 14, only one connection state storage 1490 is illustrated for all the load balancers 1415. In other embodiments, each load balancer has its own connection state storage 1490. In yet other embodiments, the host has several connection state storage 1490, but two or more load balancers can share a connection state storage (e.g., two load balancers that are balancing the load for two VMs that are part of the same logical network). As mentioned above, the connection data storages for the service nodes of a SN group (e.g., the connection data storages on different hosts) are synchronized in some embodiments, so that a PSN or an SSN can forward to another service node a data message flow that is sent by an FLB set, when the data message flow has to be processed by the other service node.


As mentioned above, the LB agent 1420 of some embodiments gathers (e.g., periodically collects) the statistics that the load balancers store in the STATs data storage(s) 1445, and relays these statistics to the controller set. Based on statistics that the controller set gathers from various LB agents of various hosts, the LB controller set in some embodiments (1) distributes the aggregated statistics to each host's LB agent so that each LB agent can define and/or adjust its load balancing parameter set, and/or (2) analyzes the aggregated statistics to specify and distribute some or all of the load balancing parameter set for the load balancers to enforce. In some embodiments where the LB agent receives new load balancing parameter set from the LB controller set, the LB agent stores the parameter set in the host-level LB rule storage 1488 for propagation to the LB rule storage(s) 1440.


In the embodiment where the LB agent receives aggregated statistics from the LB controller set, the LB agent stores the aggregated statistics in the global statistics data storage 1486. In some embodiments, the LB agent 1420 analyzes the aggregated statistics in this storage 1486 to define and/or adjust the LBP set (e.g., weight values or hash lookup tables), which it then stores in the LB rule storage 1488 for propagation to the LB rule storage(s) 1440. The publisher 1422 retrieves each LB rule that the LB agent 1420 stores in the LB rule storage 1488, and stores the retrieved rule in the LB rule storage 1440 of the load balancer 1415 that needs to enforce this rule.


The LB agent 1420 not only propagates LB rule updates based on newly received aggregated statistics, but it also propagates LB rules or updates LB rules based on updates to SN groups. In some embodiments, the controller set updates the SN group. In other embodiments, the SN group's PSN modifies the SN group. In still other embodiments, the controller set updates the SN group at the direction of the group's PSN (e.g., at the direction of the LB agent 1420 or the load balancer 1415 of the PSN SVM of the SN group).


The LB agent 1420 stores each SN group's members in the group data storage 1484. When a SN is added to or removed from a SN group, the LB agent 1420 of some embodiments stores this update in the group storage 1484, and then formulates updates to the LB rules to add or remove the destination address of this SN from the LB rules that should include or already include this address. Again, the LB agent 1420 stores such updated rules in the rule data storage 1488, from where the publisher propagates them to the LB rule storage(s) 1440 of the load balancers that need to enforce these rules.


In some embodiments, the LB agent 1420 stores in the policy storage 1482, LB policies that direct the operation of the LB agent in response to newly provisioned SVMs and their associated load balancers, and/or in response to updated global statistics and/or adjusted SN group membership. The policies in the policy storage 1482 in some embodiments are supplied by the controller set.



FIG. 17 illustrates a process 1700 that the LB agent 1420 performs in some embodiments each time that it receives updated group memberships and/or global statistics from the controller set 225. As shown, the process 1700 starts (at 1705) when it receives from the controller set 225 updated statistics for at least one SN group and/or updated membership to at least one SN group.


At 1710, the process 1700 determines whether the received update includes an update to the membership of at least one SN group for which the LB agents generates and/or maintains the LB rules. In some embodiments, the PSN's load balancer 1415 or the LB agent 1420 direct the controller set to instantiate a new SVM for the SN group or to allocate a previously instantiated SVM to the SN group, when the load balancer 1415 or the LB agent 1420 determine that a new service node should be added to the SN group. Similarly, when the load balancer 1415 or the LB agent 1420 determine that the SN group should shrink, the load balancer 1415 or the LB agent 1420 direct the controller set to remove one or more SVMs from the SN group. Thus, in these embodiments, the received group update is in response to a group adjustment request from the load balancer 1415 or the LB agent 1420.


When the process determines (at 1710) that the received update does not include a membership update, the process transitions to 1720. Otherwise, the process creates and/or updates (at 1715) one or more records in the group membership storage 1484 to store the updated group membership that the process received at 1705. From 1715, the process transitions to 1720.


At 1720, the process 1700 determines whether the received update includes updated statistics for at least one SN group for which the LB agents generates and/or maintains the LB rules. If not, the process transitions to 1730. Otherwise, the process creates and/or updates (at 1725) one or more records in the global statistics storage 1486 to store the updated global statistics that the process received at 1705. From 1725, the process transitions to 1730.


At 1730, the process initiates a process to analyze the updated records in the group membership storage 1484 and/or the global statistics storage 1486 to update the group memberships (e.g., the IP addresses) and/or the load balancing parameter set (e.g., the weight values or hash lookup table) of one or more LB rules in the host-level LB rule data storage 1488. In some embodiments, the policies that are stored in the policy storage 1482 control how the LB agent 1420 updates the LB rules based on the updated group membership record(s) and/or the updated global statistics. In some embodiments, the LB agent performs an identical or similar process (1) when the LB agent powers up (e.g., when its host powers up) to configure the LB rules of the load balancers on the host, and (2) when a new SVM 1405 is instantiated on the host and the LB agent needs to configure the LB rules of the instantiated SVM's associated load balancer 1415.


In different embodiments, the process 1700 updates (at 1730) the load balancing parameter set differently. For instance, in some embodiments, the process updates weight values and/or time values for load balancing criteria, and/or updates the service nodes for one or more weight values. In other embodiments, the process updates hash tables by modifying hash ranges, adding new hash ranges, and/or specifying new service nodes for new or previous hash ranges. As mentioned before, multiple contiguous or non-contiguous hash ranges in some embodiments can map to the same service node. In some embodiments, updates to the hash table re-assign a hash range from one service node to another service node.


From the host-level LB rule data storage 1488, the publisher 1422 propagates each new or updated LB rule to the LB rule data storages 1440 of the individual load balancers 1415 (on the same host) that need to process the new or updated LB rule. In publishing each new or updated LB rule, the publisher 1422 does not publish the LB rule to the rule data storage 1440 of a load balancer (on the same host) that does not need to process the rule.


In some embodiments, the updated LB rules also have to be supplied the load balancers of the SSNs. In some of these embodiments, the updated LB rules are distributed by the LB agent 1420 or publisher 1422 of the PSN's host to the host-level data storage 1488 of other hosts that execute SSNs of the PSN's SN group. In other embodiments, however, the LB agent 1420 on these other hosts follows the same LB policies to generate the same LB rule updates on these other hosts, and the publisher on these hosts pushes these updated LB rules to the LB rule data storages 1440 of the SSNs' load balancers 1415. Accordingly, in these embodiments, the updated rules do not need to be distributed from the PSN's host to the hosts that execute SSNs of the PSN's SN group.


After 1730, the process 1700 ends.



FIG. 18 illustrates a process 1800 that the LB agent 1420 of the PSN SVM performs in some embodiments to elastically adjust the membership of the PSN's SN group. The LB agent periodically performs this process to analyze global statistics regarding the message load on the SN group's service nodes and when necessary to adjust the SN group membership to alleviate load on the service nodes or eliminate unused excess capacity on the service nodes.


As shown, the process 1800 initially analyzes (at 1805) the data message load on the service nodes of the SN group. Next, at 1810, the process determines whether the SN group membership should be updated in view of analyzed message load data. In some embodiments, when the message load on the SN group as a whole exceeds a first threshold, the process determines (at 1810) that a service node should be added to the SN group. In other embodiments, the process decides (at 1810) to add a service node to the SN group when the message load on one or more service nodes in the SN group exceeds the first threshold.


Conversely, the process determines (at 1810) to remove a service node from the SN group when it determines that the message load on the SN group as a whole, or on one or more service nodes individually, is below a second threshold value. The second threshold value is different than the first threshold value in some embodiments, while it is the same as the first threshold value in other embodiments. Several examples for quantifying message load (for comparison to threshold values) were described above. These examples include metrics such as number of data message flows currently being processed, number of data messages processed within a particular time period, number of payload bytes in the processed messages, etc. For these examples, the threshold values can similarly be quantified in terms of these metrics.


When the process determines (at 1810) that it does not need to adjust the group membership, the process ends. Otherwise, the process transitions to 1815, where it performs the set of operations for adding one or more service nodes to, or removing one or more service nodes from, the SN group. In some embodiments, the sequence of operations for adding a service node is the same as the sequence of operations for removing a service node.


In other embodiments, these two sequences are not similar. For instance, in some embodiments, to add a service node, the process 1800 initially directs the controller set to add the service node, and then after receiving notification from the controller set regarding the addition of the service node, the process updates the load balancing rules of the PSN, and when applicable, the SSNs and FLBs. On the other hand, the process 1800 of some embodiments removes a service node by (1) initially directing the PSN (and when applicable, the SSNs and FLBs) to stop sending new flows to the service node, and then (2) after a transient delay or a sufficient reduction in the usage of the service node, directing the controller set to remove the service node from the SN group.


In still other embodiments, the process 1800 can follow other sequences of operations to add a service node to, or remove a service node from, the SN group. Also, in other embodiments, the PSN's LB agent does not perform the elastic adjustment process 1800. For instance, in some embodiments, the PSN's load balancer performs this process. In other embodiments, the controller set performs this process.



FIG. 19 illustrates a process 1900 that one or more controllers in the controller set perform in some embodiments. The controller set performs this process to distribute global statistics and/or group membership updates for a SN group. As shown, the process 1900 starts (at 1905) when it (1) receives statistics from one or more LB agents 1420 or load balancers 1415, and/or (2) receives membership updates for a SN group.


The process 1900 in some embodiments receives the group membership updates from another process of the controller set. For instance, in some embodiments, a virtualization manager informs the process 1900 that a new SVM has been added to an SN group when a new SVM has been created for the SN group, or has been removed from the SN group when the SVM has been terminated or has failed in the SN group. In some embodiments, the virtualization manager instantiates a new SVM or allocates a previously instantiated SVM to the SN group at the behest of the process 1900, as further described below.


At 1910, the process updates (1) the global statistics that the controller set maintains for the SN group based on the statistics received at 1905, and/or (2) the SN group's membership that the controller set maintains based on the group updates received at 1905. Next, at 1915, the process determines based on the updated statistics whether it should have one or more SVM specified or removed for the group. For instance, when the updated statistics causes the aggregated statistics for the SN group to exceed a threshold load value for one or more SNs in the group, the process 1900 determines that one or more new SVMs have to be specified (e.g., allotted or instantiated) for the SN group to reduce the load on SVMs previously specified for the group. Conversely, when the updated statistics shows that a SVM in a SN group is being underutilized or is no longer being used to handle any flows, the process 1900 determines (at 1915) that the SVM has to be removed for the SN group. In some embodiments, process 1900 also determines that SN group membership should be modified when it receives such a request from the PSN (e.g., through the PSN's LB agent or load balancer).


When the process 1900 determines (at 1915) that it should have one or more SVMs added to or removed for the group, the process requests (at 1920) one or more virtualization manager to add or remove the SVM(s), and then transitions to 1925. In some embodiments, a virtualization manager is a process that one or more controllers in the controller set execute, while in other embodiments, the virtualization manager is a process that is executed by one or more servers that are outside of the controller set that handles the LB data collection and data distribution.


The process 1900 also transitions to 1925 when it determines (at 1915) that no SVM needs to be added to or removed from the SN group. At 1925, the process determines whether the time has reached for it to distribute membership update and/or global statistics to one or more LB agents executing on one or more hosts. In some embodiments, the process 1900 distributes membership updates and/or global statistics on a periodic basis. In other embodiments, however, the process 1900 distributes membership update and/or global statistics for the SN group whenever this data is modified. Also, in some embodiments, the process 1900 distributes updated statistics and/or group membership to only the LB agent of the SN group's PSN, while in other embodiments, the process distributes the updated statistics and/or group membership to the LB agent of each host that executes the SVM of the PSN and/or an SSN of the group. In the embodiments where the process distributes statistic and membership updates to only the LB agent of the group's PSN, one or more modules on the PSN's host distribute the updated LB rules and/or group membership to the SSNs if the SSNs need such data.


When the process determines (at 1925) that it does not need to distribute new data, it transitions to 1930 to determine whether it has received any more statistic and/or membership updates for which it needs to update its records. If so, the process transitions back to 1910 to process the newly received statistic and/or membership updates. If not, the process transitions back to 1925 to determine again whether it should distribute new data to one or more LB agents.


When the process determines (at 1925) that should distribute membership update(s) and/or global statistics, it distributes (at 1935) this data to one or more LB agents that need to process this data to specify and/or update the load balancing rules that they maintain for their load balancers on their hosts. After 1935, the process determines (at 1940) whether it has received any more statistic and/or membership updates for which it needs to update its records. If not, the process remains at 1940 until it receives statistics and/or membership updates, at which time it transitions back to 1910 to process the newly received statistic and/or membership updates.


In the embodiments described above by reference to FIG. 19, the controller set distributes global statistics to the LB agents, which analyze this data to specify and/or adjust the LB rules that they maintain. In other embodiments, however, the controller set analyzes the global statistics that it gathers, and based on this analysis specifies and/or adjusts LBP sets or LB rules, which it then distributes to the LB agents 1420 or load balancers 1415.


The elastic SN groups of some embodiments are used to elastically provide services (e.g., load balancing, firewall, etc.) at the edge of a network. FIG. 20 illustrates one such example. In this example, three layers of load balancers are topologically positioned before three layers of compute nodes of a compute cluster 2000. The three layers of compute nodes are a web server layer 2005, an application server layer 2010, and a data storage layer 2015.


In this example, the first load balancing layer 2020 is implemented by using an elastic load balancing group of some embodiments of the invention. This elastic group is identical to the group that was described above by reference to FIG. 13. The elastic LB group 2020 is deployed at the edge the network of the compute cluster 2000. The cluster's network interconnects the compute nodes of the cluster with each other and with other devices outside of the cluster's network. In some embodiments, the compute cluster 2000 is a shared-cloud datacenter or an entity's datacenter, while in other embodiments, the cluster is a portion of a datacenter.


Also, in this example, the second and third layers 2025 and 2030 of load balancers are implemented by the inline load balancers of the web server and application server VMs of some embodiments. In some embodiments, these inline load balancers are implemented like the load balancers 1415 of FIG. 14, except that they intercept the data messages on the egress path of their associated sever VMs in order to spread these messages to the VMs of the next stage of servers. This distributed in-line load balancing is further described in U.S. patent application Ser. No. 14/557,287, now issued as U.S. Pat. No. 10,320,679.


Many of the above-described features and applications are implemented as software processes that are specified as a set of instructions recorded on a computer readable storage medium (also referred to as computer readable medium). When these instructions are executed by one or more processing unit(s) (e.g., one or more processors, cores of processors, or other processing units), they cause the processing unit(s) to perform the actions indicated in the instructions. Examples of computer readable media include, but are not limited to, CD-ROMs, flash drives, RAM chips, hard drives, EPROMs, etc. The computer readable media does not include carrier waves and electronic signals passing wirelessly or over wired connections.


In this specification, the term “software” is meant to include firmware residing in read-only memory or applications stored in magnetic storage, which can be read into memory for processing by a processor. Also, in some embodiments, multiple software inventions can be implemented as sub-parts of a larger program while remaining distinct software inventions. In some embodiments, multiple software inventions can also be implemented as separate programs. Finally, any combination of separate programs that together implement a software invention described here is within the scope of the invention. In some embodiments, the software programs, when installed to operate on one or more electronic systems, define one or more specific machine implementations that execute and perform the operations of the software programs.



FIG. 21 conceptually illustrates a computer system 2100 with which some embodiments of the invention are implemented. The computer system 2100 can be used to implement any of the above-described hosts, controllers, and managers. As such, it can be used to execute any of the above described processes. This computer system includes various types of non-transitory machine readable media and interfaces for various other types of machine readable media. Computer system 2100 includes a bus 2105, processing unit(s) 2110, a system memory 2125, a read-only memory 2130, a permanent storage device 2135, input devices 2140, and output devices 2145.


The bus 2105 collectively represents all system, peripheral, and chipset buses that communicatively connect the numerous internal devices of the computer system 2100. For instance, the bus 2105 communicatively connects the processing unit(s) 2110 with the read-only memory 2130, the system memory 2125, and the permanent storage device 2135.


From these various memory units, the processing unit(s) 2110 retrieve instructions to execute and data to process in order to execute the processes of the invention. The processing unit(s) may be a single processor or a multi-core processor in different embodiments. The read-only-memory (ROM) 2130 stores static data and instructions that are needed by the processing unit(s) 2110 and other modules of the computer system. The permanent storage device 2135, on the other hand, is a read-and-write memory device. This device is a non-volatile memory unit that stores instructions and data even when the computer system 2100 is off. Some embodiments of the invention use a mass-storage device (such as a magnetic or optical disk and its corresponding disk drive) as the permanent storage device 2135.


Other embodiments use a removable storage device (such as a floppy disk, flash drive, etc.) as the permanent storage device. Like the permanent storage device 2135, the system memory 2125 is a read-and-write memory device. However, unlike storage device 2135, the system memory is a volatile read-and-write memory, such a random access memory. The system memory stores some of the instructions and data that the processor needs at runtime. In some embodiments, the invention's processes are stored in the system memory 2125, the permanent storage device 2135, and/or the read-only memory 2130. From these various memory units, the processing unit(s) 2110 retrieve instructions to execute and data to process in order to execute the processes of some embodiments.


The bus 2105 also connects to the input and output devices 2140 and 2145. The input devices enable the user to communicate information and select commands to the computer system. The input devices 2140 include alphanumeric keyboards and pointing devices (also called “cursor control devices”). The output devices 2145 display images generated by the computer system. The output devices include printers and display devices, such as cathode ray tubes (CRT) or liquid crystal displays (LCD). Some embodiments include devices such as a touchscreen that function as both input and output devices.


Finally, as shown in FIG. 21, bus 2105 also couples computer system 2100 to a network 2165 through a network adapter (not shown). In this manner, the computer can be a part of a network of computers (such as a local area network (“LAN”), a wide area network (“WAN”), or an Intranet, or a network of networks, such as the Internet. Any or all components of computer system 2100 may be used in conjunction with the invention.


Some embodiments include electronic components, such as microprocessors, storage and memory that store computer program instructions in a machine-readable or computer-readable medium (alternatively referred to as computer-readable storage media, machine-readable media, or machine-readable storage media). Some examples of such computer-readable media include RAM, ROM, read-only compact discs (CD-ROM), recordable compact discs (CD-R), rewritable compact discs (CD-RW), read-only digital versatile discs (e.g., DVD-ROM, dual-layer DVD-ROM), a variety of recordable/rewritable DVDs (e.g., DVD-RAM, DVD-RW, DVD+RW, etc.), flash memory (e.g., SD cards, mini-SD cards, micro-SD cards, etc.), magnetic and/or solid state hard drives, read-only and recordable Blu-Ray® discs, ultra density optical discs, any other optical or magnetic media, and floppy disks. The computer-readable media may store a computer program that is executable by at least one processing unit and includes sets of instructions for performing various operations. Examples of computer programs or computer code include machine code, such as is produced by a compiler, and files including higher-level code that are executed by a computer, an electronic component, or a microprocessor using an interpreter.


While the above discussion primarily refers to microprocessor or multi-core processors that execute software, some embodiments are performed by one or more integrated circuits, such as application specific integrated circuits (ASICs) or field programmable gate arrays (FPGAs). In some embodiments, such integrated circuits execute instructions that are stored on the circuit itself.


As used in this specification, the terms “computer”, “server”, “processor”, and “memory” all refer to electronic or other technological devices. These terms exclude people or groups of people. For the purposes of the specification, the terms display or displaying means displaying on an electronic device. As used in this specification, the terms “computer readable medium,” “computer readable media,” and “machine readable medium” are entirely restricted to tangible, physical objects that store information in a form that is readable by a computer. These terms exclude any wireless signals, wired download signals, and any other ephemeral or transitory signals.


While the invention has been described with reference to numerous specific details, one of ordinary skill in the art will recognize that the invention can be embodied in other specific forms without departing from the spirit of the invention. For instance, this specification refers throughout to computational and network environments that include virtual machines (VMs). However, virtual machines are merely one example of data compute nodes (DCNs) or data compute end nodes, also referred to as addressable nodes. DCNs may include non-virtualized physical hosts, virtual machines, containers that run on top of a host operating system without the need for a hypervisor or separate operating system, and hypervisor kernel network interface modules.


VMs, in some embodiments, operate with their own guest operating systems on a host using resources of the host virtualized by virtualization software (e.g., a hypervisor, virtual machine monitor, etc.). The tenant (i.e., the owner of the VM) can choose which applications to operate on top of the guest operating system. Some containers, on the other hand, are constructs that run on top of a host operating system without the need for a hypervisor or separate guest operating system. In some embodiments, the host operating system uses name spaces to isolate the containers from each other and therefore provides operating-system level segregation of the different groups of applications that operate within different containers. This segregation is akin to the VM segregation that is offered in hypervisor-virtualized environments that virtualize system hardware, and thus can be viewed as a form of virtualization that isolates different groups of applications that operate in different containers. Such containers are more lightweight than VMs.


Hypervisor kernel network interface module, in some embodiments, is a non-VM DCN that includes a network stack with a hypervisor kernel network interface and receive/transmit threads. One example of a hypervisor kernel network interface module is the vmknic module that is part of the ESXi™ hypervisor of VMware, Inc.


One of ordinary skill in the art will recognize that while the specification refers to VMs, the examples given could be any type of DCNs, including physical hosts, VMs, non-VM containers, and hypervisor kernel network interface modules. In fact, the example networks could include combinations of different types of DCNs in some embodiments.


A number of the figures (e.g., FIGS. 3, 7, 9, 12, and 17-19) conceptually illustrate processes. The specific operations of these processes may not be performed in the exact order shown and described. The specific operations may not be performed in one continuous series of operations, and different specific operations may be performed in different embodiments. Furthermore, the process could be implemented using several sub-processes, or as part of a larger macro process. In view of the foregoing, one of ordinary skill in the art would understand that the invention is not to be limited by the foregoing illustrative details, but rather is to be defined by the appended claims.

Claims
  • 1. A non-transitory machine readable medium of a primary service node (PSN), the medium storing a program for performing a particular service on data messages, the program comprising sets of instructions for: at the PSN: receiving a data message that requires the particular service;identifying a service node (SN) in a SN group to perform the particular service on data messages that are in a same flow as the received data message, said SN group comprising the PSN;when the PSN identifies the PSN as the identified SN for the received data message's flow, performing at the PSN the particular service on the received data message and on the data messages in the same flow as the received data message; andwhen the PSN identifies another SN as the identified SN for the received data message's flow, directing the received data message to the other identified SN for the other identified SN to perform the particular service on the received data message.
  • 2. The non-transitory machine readable medium of claim 1, wherein the set of instructions for directing the received data message to the other identified SN comprises a set of instructions for directing the data messages that are in the same flow as the received data message to the other identified SN for the other identified SN to perform the particular service on the data messages in the same flow.
  • 3. The non-transitory machine readable medium of claim 1: wherein the particular service is a non-load balancing service, the other identified SN is a secondary service node (SSN), and the SN group comprises a plurality of SSNs in addition to the PSN; andwherein the set of instructions for identifying a service node comprises a set of instructions for performing load balancing operations to distribute data message flows among the service nodes of the SN group.
  • 4. The non-transitory machine readable medium of claim 3, wherein the load balancing operations are based on load balancing criteria that are defined to ensure even distribution of data message traffic load to the service nodes.
  • 5. The non-transitory machine readable medium of claim 3, wherein the non-load balancing service is one of a firewall service, an intrusion detection service, and a WAN optimizer service.
  • 6. The non-transitory machine readable medium of claim 3, wherein the set of instructions for performing the load balancing operations comprises a set of instructions for identifying at least one load balancing rule that identifies load balancing criteria for distributing the data message flows to the service nodes.
  • 7. The non-transitory machine readable medium of claim 6, wherein the set of instructions for identifying the load balancing rule comprises a set of instructions for identifying the load balancing rule by using a set of data message header parameters associated with the SN group.
  • 8. The non-transitory machine readable medium of claim 7, wherein the set of data message header parameters includes a virtual Internet Protocol (VIP) address associated with the SN group.
  • 9. The non-transitory machine readable medium of claim 8, wherein the VIP address is an Internet Protocol (IP) address of the PSN.
  • 10. The non-transitory machine readable medium of claim 1, wherein the set of instructions for directing the received data message to the other identified SN comprises a set of instructions for changing a destination media access control (MAC) address of the data message to a MAC address of the other identified SN.
  • 11. The non-transitory machine readable medium of claim 1, wherein the set of instructions for directing the received data message to the other identified SN comprises a set of instructions for changing a destination Internet Protocol (IP) address of the data message to an IP address of the other identified SN.
  • 12. The non-transitory machine readable medium of claim 1, wherein the set of instructions for directing the received data message to the other identified SN comprises a set of instructions for configuring a front end load balancer to send the received data message and the data messages that are part of the same flow as the received data message to the other identified SN.
  • 13. The non-transitory machine readable medium of claim 1, wherein each service node includes a service virtual machine (SVM) that executes on a host computing device in a system with a plurality of host computing devices;wherein the PSN further includes a load balancer that executes on the host computing device along with the PSN's SVM; andwherein the load balancer is an inline load balancer that intercepts data messages from the datapath of the PSN's SVM and identifies a service node in the SN group that should perform the particular service on the data message.
  • 14. A method for performing a particular service on data messages, for a primary service node (PSN) of a service node (SN) group that comprises the PSN and at least one secondary service node (SSN), the method comprising: at the PSN, receiving a first data message and identifying the PSN as the service node to perform the particular service on data messages that are in a same flow as the first data message;performing, at the PSN, the particular service on the first data message and on data messages in the same flow as the first data message;at the PSN, receiving a second data message and identifying the SSN as the service node to perform the particular service on data messages that are in a same flow as the second data message; anddirecting the second data message and the data messages in the same flow as the second data message to the SSN to perform the particular service on the second data message and the data messages in the same flow as the second data message.
  • 15. The method of claim 14, wherein the service is a non-load balancing service and the SN group comprises a plurality of SSNs, the method further comprising performing load balancing operations to distribute data message flows among the service nodes of the SN group.
  • 16. The method of claim 15, wherein the load balancing operations are based on load balancing criteria that are defined to ensure even distribution of data message traffic load to the service nodes.
  • 17. The method of claim 14, wherein directing the second data message to the SSN comprises changing destination media access control (MAC) addresses of the second data message and the data messages in the same flow as the second data message to a MAC address of the SSN.
  • 18. The method of claim 14, wherein directing the second data message to the SSN comprises changing destination Internet Protocol (IP) addresses of the second data message and the data messages in the same flow as the second data message to an IP address of the SSN.
  • 19. The method of claim 14, wherein directing the second data message to the SSN comprises configuring a front end load balancer to send the second data message and the data messages that are part of the same flow as the second data message to the SSN.
US Referenced Citations (726)
Number Name Date Kind
6006264 Colby et al. Dec 1999 A
6104700 Haddock et al. Aug 2000 A
6154448 Petersen et al. Nov 2000 A
6772211 Lu et al. Aug 2004 B2
6779030 Dugan et al. Aug 2004 B1
6826694 Dutta et al. Nov 2004 B1
6880089 Bommareddy et al. Apr 2005 B1
6985956 Luke et al. Jan 2006 B2
7013389 Srivastava et al. Mar 2006 B1
7209977 Acharya et al. Apr 2007 B2
7239639 Cox et al. Jul 2007 B2
7379465 Aysan et al. May 2008 B2
7406540 Acharya et al. Jul 2008 B2
7447775 Zhu et al. Nov 2008 B1
7480737 Chauffour et al. Jan 2009 B2
7487250 Siegel Feb 2009 B2
7499463 Droux et al. Mar 2009 B1
7649890 Mizutani et al. Jan 2010 B2
7698458 Liu et al. Apr 2010 B1
7818452 Matthews et al. Oct 2010 B2
7898959 Arad Mar 2011 B1
7921174 Denise Apr 2011 B1
7948986 Ghosh et al. May 2011 B1
8078903 Parthasarathy et al. Dec 2011 B1
8094575 Vadlakonda et al. Jan 2012 B1
8175863 Ostermeyer et al. May 2012 B1
8190767 Maufer et al. May 2012 B1
8201219 Jones Jun 2012 B2
8223634 Tanaka et al. Jul 2012 B2
8224885 Doucette et al. Jul 2012 B1
8230493 Davidson et al. Jul 2012 B2
8266261 Akagi Sep 2012 B2
8339959 Moisand et al. Dec 2012 B1
8451735 Li May 2013 B2
8484348 Subramanian et al. Jul 2013 B2
8488577 Macpherson Jul 2013 B1
8521879 Pena et al. Aug 2013 B1
8615009 Ramamoorthi et al. Dec 2013 B1
8707383 Bade et al. Apr 2014 B2
8738702 Belanger et al. May 2014 B1
8743885 Khan et al. Jun 2014 B2
8804720 Rainovic et al. Aug 2014 B1
8804746 Wu et al. Aug 2014 B2
8811412 Shippy Aug 2014 B2
8830834 Sharma et al. Sep 2014 B2
8832683 Heim Sep 2014 B2
8849746 Candea et al. Sep 2014 B2
8856518 Sridharan et al. Oct 2014 B2
8862883 Cherukur et al. Oct 2014 B2
8868711 Skjolsvold et al. Oct 2014 B2
8873399 Bothos et al. Oct 2014 B2
8874789 Zhu Oct 2014 B1
8892706 Dalal Nov 2014 B1
8914406 Haugsnes et al. Dec 2014 B1
8971345 McCanne et al. Mar 2015 B1
8989192 Foo et al. Mar 2015 B2
8996610 Sureshchandra et al. Mar 2015 B1
9009289 Jacob Apr 2015 B1
9094464 Scharber et al. Jul 2015 B1
9104497 Mortazavi Aug 2015 B2
9148367 Kandaswamy et al. Sep 2015 B2
9178709 Higashida et al. Nov 2015 B2
9191293 Iovene et al. Nov 2015 B2
9203748 Jiang et al. Dec 2015 B2
9225638 Jain et al. Dec 2015 B2
9225659 McCanne et al. Dec 2015 B2
9232342 Seed et al. Jan 2016 B2
9237098 Patel et al. Jan 2016 B2
9256467 Singh et al. Feb 2016 B1
9258742 Pianigiani et al. Feb 2016 B1
9264313 Manuguri et al. Feb 2016 B1
9277412 Freda et al. Mar 2016 B2
9397946 Yadav Jul 2016 B1
9407540 Kumar et al. Aug 2016 B2
9407599 Koponen et al. Aug 2016 B2
9442752 Roth et al. Sep 2016 B1
9479358 Klosowski et al. Oct 2016 B2
9503530 Niedzielski Nov 2016 B1
9531590 Jain et al. Dec 2016 B2
9577845 Thakkar et al. Feb 2017 B2
9602380 Strassner Mar 2017 B2
9686192 Sengupta et al. Jun 2017 B2
9686200 Pettit et al. Jun 2017 B2
9705702 Foo et al. Jul 2017 B2
9705775 Zhang et al. Jul 2017 B2
9755898 Jain et al. Sep 2017 B2
9755971 Wang et al. Sep 2017 B2
9774537 Jain et al. Sep 2017 B2
9787559 Schroeder Oct 2017 B1
9787605 Zhang et al. Oct 2017 B2
9804797 Ng et al. Oct 2017 B1
9825810 Jain et al. Nov 2017 B2
9860079 Cohn et al. Jan 2018 B2
9900410 Dalal Feb 2018 B2
9935827 Jain et al. Apr 2018 B2
9979641 Jain et al. May 2018 B2
9985896 Koponen et al. May 2018 B2
9996380 Singh et al. Jun 2018 B2
10013276 Fahs et al. Jul 2018 B2
10042722 Chigurupati et al. Aug 2018 B1
10075470 Vaidya et al. Sep 2018 B2
10079779 Zhang et al. Sep 2018 B2
10084703 Kumar et al. Sep 2018 B2
10091276 Bloomquist et al. Oct 2018 B2
10104169 Moniz et al. Oct 2018 B1
10129077 Jain et al. Nov 2018 B2
10129180 Zhang et al. Nov 2018 B2
10135636 Jiang et al. Nov 2018 B2
10135737 Jain et al. Nov 2018 B2
10158573 Lee et al. Dec 2018 B1
10187306 Nainar et al. Jan 2019 B2
10200493 Bendapudi et al. Feb 2019 B2
10212071 Kancherla et al. Feb 2019 B2
10225137 Jain et al. Mar 2019 B2
10237379 Kumar et al. Mar 2019 B2
10250501 Ni Apr 2019 B2
10257095 Jain et al. Apr 2019 B2
10284390 Kumar et al. May 2019 B2
10305822 Tao et al. May 2019 B2
10320679 Jain et al. Jun 2019 B2
10333822 Jeuk et al. Jun 2019 B1
10341233 Jain et al. Jul 2019 B2
10341427 Jalan et al. Jul 2019 B2
10375155 Cai et al. Aug 2019 B1
10397275 Jain et al. Aug 2019 B2
10445509 Thota et al. Oct 2019 B2
10484334 Lee et al. Nov 2019 B1
10516568 Jain et al. Dec 2019 B2
10547508 Kanakarajan Jan 2020 B1
10554484 Chanda et al. Feb 2020 B2
10594743 Hong et al. Mar 2020 B2
10609091 Hong et al. Mar 2020 B2
10609122 Argenti et al. Mar 2020 B1
10623309 Gampel et al. Apr 2020 B1
10637750 Bollineni et al. Apr 2020 B1
10645060 Ao et al. May 2020 B2
10645201 Mishra et al. May 2020 B2
10659252 Boutros et al. May 2020 B2
10693782 Jain et al. Jun 2020 B2
10708229 Sevinc et al. Jul 2020 B2
10728174 Boutros et al. Jul 2020 B2
10757077 Rajahalme et al. Aug 2020 B2
10812378 Nainar et al. Oct 2020 B2
10834004 Yigit et al. Nov 2020 B2
10853111 Gupta et al. Dec 2020 B1
10938668 Zulak et al. Mar 2021 B1
10938716 Chin et al. Mar 2021 B1
10997177 Howes et al. May 2021 B1
11026047 Greenberger et al. Jun 2021 B2
11055273 Meduri et al. Jul 2021 B1
11075839 Zhuang et al. Jul 2021 B2
11153190 Mahajan et al. Oct 2021 B1
11157304 Watt, Jr. et al. Oct 2021 B2
11184397 Annadata et al. Nov 2021 B2
11316900 Schottland et al. Apr 2022 B1
11398983 Wijnands et al. Jul 2022 B2
11528213 Venkatasubbaiah et al. Dec 2022 B2
20020010783 Primak et al. Jan 2002 A1
20020078370 Tahan Jun 2002 A1
20020097724 Halme et al. Jul 2002 A1
20020194350 Lu et al. Dec 2002 A1
20030065711 Acharya et al. Apr 2003 A1
20030093481 Mitchell et al. May 2003 A1
20030097429 Wu et al. May 2003 A1
20030105812 Flowers et al. Jun 2003 A1
20030188026 Denton et al. Oct 2003 A1
20030236813 Abjanic Dec 2003 A1
20040066769 Ahmavaara et al. Apr 2004 A1
20040210670 Anerousis et al. Oct 2004 A1
20040215703 Song et al. Oct 2004 A1
20040249776 Horvitz et al. Dec 2004 A1
20050021713 Dugan et al. Jan 2005 A1
20050089327 Ovadia et al. Apr 2005 A1
20050091396 Nilakantan et al. Apr 2005 A1
20050114429 Caccavale May 2005 A1
20050114648 Akundi et al. May 2005 A1
20050132030 Hopen et al. Jun 2005 A1
20050198200 Subramanian et al. Sep 2005 A1
20050249199 Albert et al. Nov 2005 A1
20060069776 Shim et al. Mar 2006 A1
20060112297 Davidson May 2006 A1
20060130133 Andreev Jun 2006 A1
20060155862 Kathi et al. Jul 2006 A1
20060195896 Fulp et al. Aug 2006 A1
20060233155 Srivastava Oct 2006 A1
20070061492 Riel Mar 2007 A1
20070121615 Weill et al. May 2007 A1
20070153782 Fletcher et al. Jul 2007 A1
20070214282 Sen Sep 2007 A1
20070248091 Khalid et al. Oct 2007 A1
20070260750 Feied et al. Nov 2007 A1
20070288615 Keohane et al. Dec 2007 A1
20070291773 Khan et al. Dec 2007 A1
20080005293 Bhargava et al. Jan 2008 A1
20080031263 Ervin et al. Feb 2008 A1
20080046400 Shi Feb 2008 A1
20080049614 Briscoe et al. Feb 2008 A1
20080049619 Twiss Feb 2008 A1
20080049786 Ram et al. Feb 2008 A1
20080072305 Casado et al. Mar 2008 A1
20080084819 Parizhsky et al. Apr 2008 A1
20080095153 Fukunaga et al. Apr 2008 A1
20080104608 Hyser et al. May 2008 A1
20080195755 Lu et al. Aug 2008 A1
20080225714 Denis Sep 2008 A1
20080239991 Applegate et al. Oct 2008 A1
20080247396 Hazard Oct 2008 A1
20080276085 Davidson et al. Nov 2008 A1
20080279196 Friskney et al. Nov 2008 A1
20090003349 Havemann et al. Jan 2009 A1
20090003364 Fendick et al. Jan 2009 A1
20090003375 Havemann et al. Jan 2009 A1
20090019135 Eswaran et al. Jan 2009 A1
20090037713 Khalid et al. Feb 2009 A1
20090063706 Goldman Mar 2009 A1
20090129271 Ramankutty et al. May 2009 A1
20090172666 Yahalom et al. Jul 2009 A1
20090190506 Belling et al. Jul 2009 A1
20090199268 Ahmavaara et al. Aug 2009 A1
20090235325 Dimitrakos et al. Sep 2009 A1
20090238084 Nadeau et al. Sep 2009 A1
20090249472 Litvin et al. Oct 2009 A1
20090265467 Peles Oct 2009 A1
20090271586 Shaath Oct 2009 A1
20090299791 Blake et al. Dec 2009 A1
20090300210 Ferris Dec 2009 A1
20090303880 Maltz et al. Dec 2009 A1
20090307334 Maltz et al. Dec 2009 A1
20090327464 Archer et al. Dec 2009 A1
20100031360 Seshadri et al. Feb 2010 A1
20100036903 Ahmad et al. Feb 2010 A1
20100100616 Bryson et al. Apr 2010 A1
20100131638 Kondamuru May 2010 A1
20100165985 Sharma et al. Jul 2010 A1
20100223364 Wei Sep 2010 A1
20100223621 Joshi et al. Sep 2010 A1
20100235915 Memon et al. Sep 2010 A1
20100254385 Sharma et al. Oct 2010 A1
20100257278 Gunturu Oct 2010 A1
20100265824 Chao et al. Oct 2010 A1
20100281482 Pike et al. Nov 2010 A1
20100332595 Fullagar et al. Dec 2010 A1
20110010578 Dominguez et al. Jan 2011 A1
20110016348 Pace et al. Jan 2011 A1
20110022695 Dalal et al. Jan 2011 A1
20110022812 Van Der Linden et al. Jan 2011 A1
20110035494 Pandey et al. Feb 2011 A1
20110040893 Karaoguz et al. Feb 2011 A1
20110055845 Nandagopal Mar 2011 A1
20110058563 Saraph et al. Mar 2011 A1
20110090912 Shippy Apr 2011 A1
20110164504 Bothos et al. Jul 2011 A1
20110194563 Shen et al. Aug 2011 A1
20110211463 Matityahu et al. Sep 2011 A1
20110225293 Rathod Sep 2011 A1
20110235508 Goel et al. Sep 2011 A1
20110261811 Battestilli Oct 2011 A1
20110268118 Schlansker et al. Nov 2011 A1
20110271007 Wang et al. Nov 2011 A1
20110276695 Maldaner Nov 2011 A1
20110283013 Grosser et al. Nov 2011 A1
20110295991 Aida Dec 2011 A1
20110317708 Clark Dec 2011 A1
20120005265 Ushioda et al. Jan 2012 A1
20120011281 Hamada et al. Jan 2012 A1
20120014386 Xiong et al. Jan 2012 A1
20120023231 Ueno Jan 2012 A1
20120054266 Kazerani et al. Mar 2012 A1
20120089664 Igelka Apr 2012 A1
20120137004 Smith May 2012 A1
20120140719 Hui et al. Jun 2012 A1
20120144014 Natham et al. Jun 2012 A1
20120147894 Mulligan et al. Jun 2012 A1
20120155266 Patel et al. Jun 2012 A1
20120176932 Wu et al. Jul 2012 A1
20120185588 Error Jul 2012 A1
20120195196 Ghai et al. Aug 2012 A1
20120207174 Shieh Aug 2012 A1
20120213074 Goldfarb et al. Aug 2012 A1
20120230187 Tremblay et al. Sep 2012 A1
20120239804 Liu et al. Sep 2012 A1
20120246637 Kreeger et al. Sep 2012 A1
20120266252 Spiers et al. Oct 2012 A1
20120281540 Khan et al. Nov 2012 A1
20120287789 Aybay et al. Nov 2012 A1
20120303784 Zisapel et al. Nov 2012 A1
20120303809 Patel et al. Nov 2012 A1
20120311568 Jansen Dec 2012 A1
20120317260 Husain et al. Dec 2012 A1
20120317570 Dalcher et al. Dec 2012 A1
20120331188 Riordan et al. Dec 2012 A1
20130003735 Chao et al. Jan 2013 A1
20130021942 Bacthu et al. Jan 2013 A1
20130031544 Sridharan et al. Jan 2013 A1
20130039218 Narasimhan et al. Feb 2013 A1
20130044636 Koponen et al. Feb 2013 A1
20130058346 Sridharan et al. Mar 2013 A1
20130073743 Ramasamy et al. Mar 2013 A1
20130100851 Bacthu et al. Apr 2013 A1
20130125120 Zhang et al. May 2013 A1
20130136126 Wang et al. May 2013 A1
20130142048 Gross, IV et al. Jun 2013 A1
20130148505 Koponen et al. Jun 2013 A1
20130151661 Koponen et al. Jun 2013 A1
20130159487 Patel et al. Jun 2013 A1
20130160024 Shtilman et al. Jun 2013 A1
20130163594 Sharma et al. Jun 2013 A1
20130166703 Hammer et al. Jun 2013 A1
20130170501 Egi et al. Jul 2013 A1
20130201989 Hu Aug 2013 A1
20130227097 Yasuda et al. Aug 2013 A1
20130227550 Weinstein et al. Aug 2013 A1
20130287026 Davie Oct 2013 A1
20130287036 Banavalikar et al. Oct 2013 A1
20130291088 Shieh et al. Oct 2013 A1
20130297798 Arisoylu et al. Nov 2013 A1
20130301472 Allan Nov 2013 A1
20130311637 Kamath et al. Nov 2013 A1
20130318219 Kancherla Nov 2013 A1
20130322446 Biswas et al. Dec 2013 A1
20130332983 Koorevaar et al. Dec 2013 A1
20130336319 Liu et al. Dec 2013 A1
20130343174 Guichard et al. Dec 2013 A1
20130343378 Veteikis et al. Dec 2013 A1
20140003232 Guichard et al. Jan 2014 A1
20140003422 Mogul et al. Jan 2014 A1
20140010085 Kavunder et al. Jan 2014 A1
20140029447 Schrum, Jr. Jan 2014 A1
20140046997 Dain et al. Feb 2014 A1
20140046998 Dain et al. Feb 2014 A1
20140052844 Nayak et al. Feb 2014 A1
20140059204 Nguyen et al. Feb 2014 A1
20140059544 Koganty et al. Feb 2014 A1
20140068602 Gember et al. Mar 2014 A1
20140092738 Grandhi et al. Apr 2014 A1
20140092914 Kondapalli Apr 2014 A1
20140096183 Jain et al. Apr 2014 A1
20140101226 Khandekar et al. Apr 2014 A1
20140101656 Zhu et al. Apr 2014 A1
20140108665 Arora et al. Apr 2014 A1
20140115578 Cooper et al. Apr 2014 A1
20140129715 Mortazavi May 2014 A1
20140149696 Frenkel et al. May 2014 A1
20140164477 Springer et al. Jun 2014 A1
20140169168 Jalan et al. Jun 2014 A1
20140169375 Khan et al. Jun 2014 A1
20140195666 Dumitriu et al. Jul 2014 A1
20140207968 Kumar et al. Jul 2014 A1
20140254374 Janakiraman et al. Sep 2014 A1
20140254591 Mahadevan et al. Sep 2014 A1
20140269487 Kalkunte Sep 2014 A1
20140269717 Thubert et al. Sep 2014 A1
20140269724 Mehler et al. Sep 2014 A1
20140280896 Papakostas et al. Sep 2014 A1
20140281029 Danforth Sep 2014 A1
20140282526 Basavaiah et al. Sep 2014 A1
20140301388 Jagadish et al. Oct 2014 A1
20140304231 Kamath et al. Oct 2014 A1
20140307744 Dunbar et al. Oct 2014 A1
20140310391 Sorenson et al. Oct 2014 A1
20140310418 Sorenson, III et al. Oct 2014 A1
20140317677 Vaidya et al. Oct 2014 A1
20140321459 Kumar et al. Oct 2014 A1
20140330983 Zisapel Nov 2014 A1
20140334485 Jain et al. Nov 2014 A1
20140334488 Guichard et al. Nov 2014 A1
20140341029 Allan et al. Nov 2014 A1
20140351452 Bosch et al. Nov 2014 A1
20140362682 Guichard et al. Dec 2014 A1
20140362705 Pan Dec 2014 A1
20140369204 Anand et al. Dec 2014 A1
20140372567 Ganesh et al. Dec 2014 A1
20140372616 Arisoylu et al. Dec 2014 A1
20140372702 Subramanyam et al. Dec 2014 A1
20150003453 Sengupta et al. Jan 2015 A1
20150003455 Haddad et al. Jan 2015 A1
20150009995 Gross, IV et al. Jan 2015 A1
20150016279 Zhang et al. Jan 2015 A1
20150023354 Li et al. Jan 2015 A1
20150026345 Ravinoothala et al. Jan 2015 A1
20150026362 Guichard et al. Jan 2015 A1
20150030024 Venkataswami et al. Jan 2015 A1
20150052262 Chanda et al. Feb 2015 A1
20150052522 Chanda et al. Feb 2015 A1
20150063102 Mestery et al. Mar 2015 A1
20150063364 Thakkar et al. Mar 2015 A1
20150071301 Dalal Mar 2015 A1
20150073967 Katsuyama et al. Mar 2015 A1
20150078384 Jackson et al. Mar 2015 A1
20150092551 Moisand et al. Apr 2015 A1
20150092564 Aldrin Apr 2015 A1
20150103645 Shen et al. Apr 2015 A1
20150103679 Tessmer et al. Apr 2015 A1
20150103827 Quinn et al. Apr 2015 A1
20150109901 Fan et al. Apr 2015 A1
20150124608 Agarwal et al. May 2015 A1
20150124622 Kovvali et al. May 2015 A1
20150124840 Bergeron May 2015 A1
20150138973 Kumar et al. May 2015 A1
20150139041 Bosch et al. May 2015 A1
20150146539 Mehta et al. May 2015 A1
20150156035 Foo et al. Jun 2015 A1
20150188770 Naiksatam et al. Jul 2015 A1
20150195197 Yong et al. Jul 2015 A1
20150213087 Sikri Jul 2015 A1
20150215819 Bosch et al. Jul 2015 A1
20150222640 Kumar et al. Aug 2015 A1
20150236948 Dunbar et al. Aug 2015 A1
20150237013 Bansal et al. Aug 2015 A1
20150242197 Alfonso et al. Aug 2015 A1
20150244617 Nakil et al. Aug 2015 A1
20150263901 Kumar et al. Sep 2015 A1
20150263946 Tubaltsev et al. Sep 2015 A1
20150271102 Antich Sep 2015 A1
20150280959 Vincent Oct 2015 A1
20150281089 Marchetti Oct 2015 A1
20150281098 Pettit et al. Oct 2015 A1
20150281125 Koponen et al. Oct 2015 A1
20150281179 Raman et al. Oct 2015 A1
20150281180 Raman et al. Oct 2015 A1
20150288671 Chan et al. Oct 2015 A1
20150288679 Ben-Nun et al. Oct 2015 A1
20150295831 Kumar et al. Oct 2015 A1
20150319078 Lee et al. Nov 2015 A1
20150319096 Yip et al. Nov 2015 A1
20150358235 Zhang et al. Dec 2015 A1
20150358294 Kancharla et al. Dec 2015 A1
20150365322 Shalzkamer et al. Dec 2015 A1
20150370586 Cooper et al. Dec 2015 A1
20150370596 Fahs et al. Dec 2015 A1
20150372840 Benny et al. Dec 2015 A1
20150372911 Yabusaki et al. Dec 2015 A1
20150379277 Thota et al. Dec 2015 A1
20150381493 Bansal et al. Dec 2015 A1
20150381494 Cherian et al. Dec 2015 A1
20150381495 Cherian et al. Dec 2015 A1
20160006654 Fernando et al. Jan 2016 A1
20160028640 Zhang et al. Jan 2016 A1
20160043901 Sankar et al. Feb 2016 A1
20160043952 Zhang et al. Feb 2016 A1
20160057050 Ostrom et al. Feb 2016 A1
20160057687 Horn et al. Feb 2016 A1
20160065503 Yohe et al. Mar 2016 A1
20160080253 Wang et al. Mar 2016 A1
20160087888 Jain et al. Mar 2016 A1
20160094384 Jain et al. Mar 2016 A1
20160094389 Jain et al. Mar 2016 A1
20160094451 Jain et al. Mar 2016 A1
20160094452 Jain et al. Mar 2016 A1
20160094453 Jain et al. Mar 2016 A1
20160094455 Jain et al. Mar 2016 A1
20160094456 Jain et al. Mar 2016 A1
20160094457 Jain et al. Mar 2016 A1
20160094631 Jain et al. Mar 2016 A1
20160094632 Jain et al. Mar 2016 A1
20160094633 Jain et al. Mar 2016 A1
20160094642 Jain et al. Mar 2016 A1
20160094643 Jain et al. Mar 2016 A1
20160094661 Jain et al. Mar 2016 A1
20160099948 Ott et al. Apr 2016 A1
20160105333 Lenglet et al. Apr 2016 A1
20160119226 Guichard et al. Apr 2016 A1
20160127306 Wang et al. May 2016 A1
20160127564 Sharma et al. May 2016 A1
20160134528 Lin et al. May 2016 A1
20160149784 Zhang et al. May 2016 A1
20160149816 Wu et al. May 2016 A1
20160149828 Vijayan et al. May 2016 A1
20160162320 Singh et al. Jun 2016 A1
20160164776 Biancaniello Jun 2016 A1
20160164787 Roach et al. Jun 2016 A1
20160164826 Riedel et al. Jun 2016 A1
20160173373 Guichard et al. Jun 2016 A1
20160182684 Connor et al. Jun 2016 A1
20160197831 Foy et al. Jul 2016 A1
20160197839 Li et al. Jul 2016 A1
20160203817 Formhals et al. Jul 2016 A1
20160205015 Halligan et al. Jul 2016 A1
20160212048 Kaempfer et al. Jul 2016 A1
20160212237 Nishijima Jul 2016 A1
20160218918 Chu et al. Jul 2016 A1
20160226700 Zhang et al. Aug 2016 A1
20160226754 Zhang et al. Aug 2016 A1
20160226762 Zhang et al. Aug 2016 A1
20160232019 Shah et al. Aug 2016 A1
20160248685 Pignataro et al. Aug 2016 A1
20160277210 Lin et al. Sep 2016 A1
20160277294 Akiyoshi Sep 2016 A1
20160294612 Ravinoothala et al. Oct 2016 A1
20160294933 Hong et al. Oct 2016 A1
20160294935 Hong et al. Oct 2016 A1
20160308758 Li et al. Oct 2016 A1
20160308961 Rao Oct 2016 A1
20160337189 Liebhart et al. Nov 2016 A1
20160337249 Zhang et al. Nov 2016 A1
20160337317 Hwang et al. Nov 2016 A1
20160344565 Batz et al. Nov 2016 A1
20160344621 Roeland et al. Nov 2016 A1
20160352866 Gupta et al. Dec 2016 A1
20160366046 Anantharam et al. Dec 2016 A1
20160373364 Yokota Dec 2016 A1
20160378537 Zou Dec 2016 A1
20170005882 Tao et al. Jan 2017 A1
20170005920 Previdi et al. Jan 2017 A1
20170005923 Babakian Jan 2017 A1
20170005988 Bansal et al. Jan 2017 A1
20170019303 Swamy et al. Jan 2017 A1
20170019329 Kozat et al. Jan 2017 A1
20170019331 Yong Jan 2017 A1
20170019341 Huang et al. Jan 2017 A1
20170026417 Ermagan et al. Jan 2017 A1
20170033939 Bragg et al. Feb 2017 A1
20170063683 Li et al. Mar 2017 A1
20170063928 Jain et al. Mar 2017 A1
20170064048 Pettit et al. Mar 2017 A1
20170064749 Jain et al. Mar 2017 A1
20170078176 Lakshmikantha et al. Mar 2017 A1
20170078961 Rabii et al. Mar 2017 A1
20170093698 Farmanbar Mar 2017 A1
20170093758 Chanda Mar 2017 A1
20170099194 Wei Apr 2017 A1
20170126497 Dubey et al. May 2017 A1
20170126522 McCann et al. May 2017 A1
20170126726 Han May 2017 A1
20170134538 Mahkonen et al. May 2017 A1
20170142012 Thakkar et al. May 2017 A1
20170147399 Cropper et al. May 2017 A1
20170149582 Cohn et al. May 2017 A1
20170149675 Yang May 2017 A1
20170163531 Kumar et al. Jun 2017 A1
20170163724 Puri et al. Jun 2017 A1
20170171159 Kumar et al. Jun 2017 A1
20170180240 Kem et al. Jun 2017 A1
20170195255 Pham et al. Jul 2017 A1
20170208000 Bosch et al. Jul 2017 A1
20170208011 Bosch et al. Jul 2017 A1
20170208532 Zhou Jul 2017 A1
20170214627 Zhang et al. Jul 2017 A1
20170220306 Price et al. Aug 2017 A1
20170230333 Glazemakers et al. Aug 2017 A1
20170230467 Salgueiro et al. Aug 2017 A1
20170237656 Gage Aug 2017 A1
20170250869 Voellmy Aug 2017 A1
20170250902 Rasanen et al. Aug 2017 A1
20170250917 Ruckstuhl et al. Aug 2017 A1
20170251065 Furr et al. Aug 2017 A1
20170257432 Fu et al. Sep 2017 A1
20170264677 Li Sep 2017 A1
20170273099 Zhang et al. Sep 2017 A1
20170279938 You et al. Sep 2017 A1
20170295021 Gutiérrez et al. Oct 2017 A1
20170295100 Hira et al. Oct 2017 A1
20170310588 Zuo Oct 2017 A1
20170310611 Kumar et al. Oct 2017 A1
20170317887 Dwaraki et al. Nov 2017 A1
20170317926 Penno et al. Nov 2017 A1
20170317936 Swaminathan et al. Nov 2017 A1
20170317954 Masurekar et al. Nov 2017 A1
20170317969 Masurekar et al. Nov 2017 A1
20170318097 Drew et al. Nov 2017 A1
20170324651 Penno et al. Nov 2017 A1
20170331672 Fedyk et al. Nov 2017 A1
20170339110 Ni Nov 2017 A1
20170339600 Roeland et al. Nov 2017 A1
20170346764 Tan et al. Nov 2017 A1
20170353387 Kwak et al. Dec 2017 A1
20170364794 Mahkonen et al. Dec 2017 A1
20170366605 Chang et al. Dec 2017 A1
20170373990 Jeuk et al. Dec 2017 A1
20180004954 Liguori et al. Jan 2018 A1
20180006935 Mutnuru et al. Jan 2018 A1
20180026911 Anholt et al. Jan 2018 A1
20180041425 Zhang Feb 2018 A1
20180041470 Schultz et al. Feb 2018 A1
20180041524 Reddy et al. Feb 2018 A1
20180063018 Bosch et al. Mar 2018 A1
20180063087 Hira et al. Mar 2018 A1
20180091420 Drake et al. Mar 2018 A1
20180102919 Hao et al. Apr 2018 A1
20180102965 Hari et al. Apr 2018 A1
20180115471 Curcio et al. Apr 2018 A1
20180123950 Garg et al. May 2018 A1
20180124061 Raman et al. May 2018 A1
20180139098 Sunavala et al. May 2018 A1
20180145899 Rao May 2018 A1
20180159733 Poon et al. Jun 2018 A1
20180159801 Rajan et al. Jun 2018 A1
20180159943 Poon et al. Jun 2018 A1
20180176177 Bichot et al. Jun 2018 A1
20180176294 Vacaro et al. Jun 2018 A1
20180183764 Gunda Jun 2018 A1
20180184281 Tamagawa et al. Jun 2018 A1
20180191600 Hecker et al. Jul 2018 A1
20180198692 Ansari et al. Jul 2018 A1
20180198705 Wang et al. Jul 2018 A1
20180198791 Desai et al. Jul 2018 A1
20180203736 Vyas et al. Jul 2018 A1
20180205637 Li Jul 2018 A1
20180213040 Pak et al. Jul 2018 A1
20180219762 Wang et al. Aug 2018 A1
20180227216 Hughes Aug 2018 A1
20180234360 Narayana et al. Aug 2018 A1
20180247082 Durham et al. Aug 2018 A1
20180248713 Zanier et al. Aug 2018 A1
20180248755 Hecker et al. Aug 2018 A1
20180248790 Tan et al. Aug 2018 A1
20180248986 Dalal Aug 2018 A1
20180262427 Jain et al. Sep 2018 A1
20180262434 Koponen et al. Sep 2018 A1
20180278530 Connor et al. Sep 2018 A1
20180288129 Joshi et al. Oct 2018 A1
20180295036 Krishnamurthy et al. Oct 2018 A1
20180295053 Leung et al. Oct 2018 A1
20180302242 Hao et al. Oct 2018 A1
20180309632 Kompella et al. Oct 2018 A1
20180337849 Sharma et al. Nov 2018 A1
20180349212 Liu et al. Dec 2018 A1
20180351874 Abhigyan et al. Dec 2018 A1
20190007382 Nirwal et al. Jan 2019 A1
20190020580 Boutros et al. Jan 2019 A1
20190020600 Zhang et al. Jan 2019 A1
20190020684 Qian et al. Jan 2019 A1
20190028347 Johnston et al. Jan 2019 A1
20190028384 Penno et al. Jan 2019 A1
20190028577 D?Souza et al. Jan 2019 A1
20190036819 Kancherla et al. Jan 2019 A1
20190068500 Hira Feb 2019 A1
20190089679 Kahalon et al. Mar 2019 A1
20190097838 Sahoo et al. Mar 2019 A1
20190102280 Caldato et al. Apr 2019 A1
20190108049 Singh et al. Apr 2019 A1
20190116063 Bottorff et al. Apr 2019 A1
20190121961 Coleman et al. Apr 2019 A1
20190124096 Ahuja et al. Apr 2019 A1
20190132220 Boutros et al. May 2019 A1
20190132221 Boutros et al. May 2019 A1
20190140863 Nainar et al. May 2019 A1
20190140947 Zhuang et al. May 2019 A1
20190140950 Zhuang et al. May 2019 A1
20190149512 Sevinc et al. May 2019 A1
20190149516 Rajahalme et al. May 2019 A1
20190149518 Sevinc et al. May 2019 A1
20190166045 Peng et al. May 2019 A1
20190173778 Faseela et al. Jun 2019 A1
20190173850 Jain et al. Jun 2019 A1
20190173851 Jain et al. Jun 2019 A1
20190222538 Yang et al. Jul 2019 A1
20190229937 Nagarajan et al. Jul 2019 A1
20190230126 Kumar et al. Jul 2019 A1
20190238363 Boutros et al. Aug 2019 A1
20190238364 Boutros et al. Aug 2019 A1
20190268384 Hu et al. Aug 2019 A1
20190286475 Mani Sep 2019 A1
20190288915 Denyer et al. Sep 2019 A1
20190288947 Jain et al. Sep 2019 A1
20190306036 Boutros et al. Oct 2019 A1
20190306086 Boutros et al. Oct 2019 A1
20190342175 Wan et al. Nov 2019 A1
20190377604 Cybulski Dec 2019 A1
20190379578 Mishra et al. Dec 2019 A1
20190379579 Mishra et al. Dec 2019 A1
20200007388 Johnston et al. Jan 2020 A1
20200036629 Roeland et al. Jan 2020 A1
20200059761 Li et al. Feb 2020 A1
20200067828 Liu et al. Feb 2020 A1
20200073739 Rungta et al. Mar 2020 A1
20200076684 Naveen et al. Mar 2020 A1
20200076734 Naveen et al. Mar 2020 A1
20200084141 Bengough et al. Mar 2020 A1
20200084147 Gandhi et al. Mar 2020 A1
20200136960 Jeuk et al. Apr 2020 A1
20200145331 Bhandari et al. May 2020 A1
20200162318 Patil et al. May 2020 A1
20200162352 Jorgenson et al. May 2020 A1
20200183724 Shevade et al. Jun 2020 A1
20200195711 Abhigyan et al. Jun 2020 A1
20200204492 Sarva et al. Jun 2020 A1
20200213366 Hong et al. Jul 2020 A1
20200220805 Dhanabalan Jul 2020 A1
20200272493 Lecuyer et al. Aug 2020 A1
20200272494 Gokhale et al. Aug 2020 A1
20200272495 Rolando et al. Aug 2020 A1
20200272496 Mundaragi et al. Aug 2020 A1
20200272497 Kavathia et al. Aug 2020 A1
20200272498 Mishra et al. Aug 2020 A1
20200272499 Feng et al. Aug 2020 A1
20200272500 Feng et al. Aug 2020 A1
20200272501 Chalvadi et al. Aug 2020 A1
20200274757 Rolando et al. Aug 2020 A1
20200274769 Naveen et al. Aug 2020 A1
20200274778 Lecuyer et al. Aug 2020 A1
20200274779 Rolando et al. Aug 2020 A1
20200274795 Rolando et al. Aug 2020 A1
20200274801 Feng et al. Aug 2020 A1
20200274808 Mundaragi et al. Aug 2020 A1
20200274809 Rolando et al. Aug 2020 A1
20200274810 Gokhale et al. Aug 2020 A1
20200274826 Mishra et al. Aug 2020 A1
20200274944 Naveen et al. Aug 2020 A1
20200274945 Rolando et al. Aug 2020 A1
20200287962 Mishra et al. Sep 2020 A1
20200344088 Selvaraj et al. Oct 2020 A1
20200358696 Hu et al. Nov 2020 A1
20200364074 Gunda et al. Nov 2020 A1
20200382412 Chandrappa et al. Dec 2020 A1
20200382420 Suryanarayana et al. Dec 2020 A1
20200389401 Enguehard et al. Dec 2020 A1
20210004245 Kamath et al. Jan 2021 A1
20210011812 Mitkar et al. Jan 2021 A1
20210011816 Mitkar et al. Jan 2021 A1
20210029088 Mayya et al. Jan 2021 A1
20210067439 Kommula et al. Mar 2021 A1
20210073736 Alawi et al. Mar 2021 A1
20210117217 Croteau et al. Apr 2021 A1
20210136147 Giassa et al. May 2021 A1
20210240734 Shah et al. Aug 2021 A1
20210266295 Stroz Aug 2021 A1
20210271565 Bhavanarushi et al. Sep 2021 A1
20210311758 Cao et al. Oct 2021 A1
20210314310 Cao et al. Oct 2021 A1
20210328913 Nainar et al. Oct 2021 A1
20210349767 Asayag et al. Nov 2021 A1
20210377160 Faseela Dec 2021 A1
20220019698 Durham et al. Jan 2022 A1
20220038310 Boutros et al. Feb 2022 A1
20220060467 Montgomery et al. Feb 2022 A1
Foreign Referenced Citations (28)
Number Date Country
3034809 Mar 2018 CA
1689369 Oct 2005 CN
101594358 Dec 2009 CN
101729412 Jun 2010 CN
103516807 Jan 2014 CN
103795805 May 2014 CN
104471899 Mar 2015 CN
107204941 Sep 2017 CN
109213573 Jan 2019 CN
110521169 Nov 2019 CN
107105061 Sep 2020 CN
112181632 Jan 2021 CN
2426956 Mar 2012 EP
2005311863 Nov 2005 JP
2015519822 Jul 2015 JP
9918534 Apr 1999 WO
2008095010 Aug 2008 WO
2014182529 Nov 2014 WO
2016053373 Apr 2016 WO
2016054272 Apr 2016 WO
2019084066 May 2019 WO
2019147316 Aug 2019 WO
2019157955 Aug 2019 WO
2019168532 Sep 2019 WO
2019226327 Nov 2019 WO
2020046686 Mar 2020 WO
2020171937 Aug 2020 WO
2021041440 Mar 2021 WO
Non-Patent Literature Citations (26)
Entry
Portions of prosecution history of U.S. Appl. No. 14/569,249, Apr. 4, 2016, Jain, Jayant, et al.
Portions of prosecution history of U.S. Appl. No. 14/569,452, Jun. 14, 2016, Jain, Jayant, et al.
Author Unknown, “Datagram,” Jun. 22, 2012, 2 pages, retrieved from https://web.archive.org/web/20120622031055/https://en.wikipedia.org/wiki/datagram.
Author Unknown, “AppLogic Features,” Jul. 2007, 2 pages. 3TERA, Inc.
Author Unknown, “Enabling Service Chaining on Cisco Nexus 1000V Series,” Month Unknown, 2012, 25 pages, Cisco.
Dixon, Colin, et al., “An End to the Middle,” Proceedings of the 12th Conference on Hot Topics in Operating Systems, May 2009, 5 pages, USENIX Association, Berkeley, CA, USA.
Dumitriu, Dan Mihai, et al., (U.S. Appl. No. 61/514,990), filed Aug. 4, 2011, 31 pages.
Greenberg, Albert, et al., “VL2: A Scalable and Flexible Data Center Network,” SIGCOMM '09, Aug. 17-21, 2009, 12 pages, ACM, Barcelona, Spain.
Guichard, J., et al., “Network Service Chaining Problem Statement,” Network Working Group, Jun. 13, 2013, 14 pages, Cisco Systems, Inc.
Halpern, J., et al., “Service Function Chaining (SFC) Architecture,” draft-ietf-sfc-architecture-02, Sep. 20, 2014, 26 pages, IETF.
Joseph, Dilip Anthony, et al., “A Policy-aware Switching Layer for Data Centers,” Jun. 24, 2008, 26 pages, Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USA.
Kumar, S., et al., “Service Function Chaining Use Cases in Data Centers,” draft-ietf-sfc-dc-use-cases-01, Jul. 21, 2014, 23 pages, IETF.
Liu, W., et al., “Service Function Chaining (SFC) Use Cases,” draft-liu-sfc-use-cases-02, Feb. 13, 2014, 17 pages, IETF.
Salsano, Stefano, et al., “Generalized Virtual Networking: An Enabler for Service Centric Networking and Network Function Virtualization,” 2014 16th International Telecommunications Network Strategy and Planning Symposium, Sep. 17-19, 2014, 7 pages, IEEE, Funchal, Portugal.
Sekar, Vyas, et al., “Design and Implementation of a Consolidated Middlebox Architecture,” 9th USENIX Symposium on Networked Systems Design and Implementation, Apr. 25-27, 2012, 14 pages, USENIX, San Jose, CA, USA.
Sherry, Justine, et al., “Making Middleboxes Someone Else's Problem: Network Processing as a Cloud Service,” In Proc. of SIGCOMM '12, Aug. 13-17, 2012, 12 pages, Helsinki, Finland.
Casado, Martin, et al., “Virtualizing the Network Forwarding Plane,” Dec. 2010, 6 pages.
Karakus, Murat, et al., “Quality of Service (QoS) in Software Defined Networking (SDN): A Survey,” Journal of Network and Computer Applications, Dec. 9, 2016, 19 pages, vol. 80, Elsevier, Ltd.
Non-Published Commonly Owned U.S. Appl. No. 16/905,909, filed Jun. 18, 2020, 36 pages, Nicira, Inc.
Lin, Po-Ching, et al., “Balanced Service Chaining in Software-Defined Networks with Network Function Virtualization,” Computer: Research Feature, Nov. 2016, 9 pages, vol. 49, No. 11, IEEE.
Xiong, Gang, et al., “A Mechanism for Configurable Network Service Chaining and Its Implementation,” KSII Transactions on Internet and Information Systems, Aug. 2016, 27 pages, vol. 10, No. 8, KSII.
Siasi, N., et al., “Container-Based Service Function Chain Mapping,” 2019 SoutheastCon, Apr. 11-14, 2019, 6 pages, IEEE, Huntsville, AL, USA.
Author Unknown, “Research on Multi-tenancy Network Technology for Datacenter Network,” May 2015, 64 pages, Beijing Jiaotong University.
Author Unknown, “MPLS,” Mar. 3, 2008, 47 pages.
Cianfrani, Antonio, et al., “Translating Traffic Engineering Outcome into Segment Routing Paths: the Encoding Problem,” 2016 IEEE Conference on Computer Communications Workshops (Infocom Wkshps): GI 2016: 9th IEEE Global Internet Symposium, Apr. 10-14, 2016, 6 pages, IEEE, San Francisco, CA, USA.
Li, Qing-Gu, “Network Virtualization of Data Center Security,” Information Security and Technology, Oct. 2012, 3 pages.
Related Publications (1)
Number Date Country
20160094454 A1 Mar 2016 US
Provisional Applications (3)
Number Date Country
62086136 Dec 2014 US
62083453 Nov 2014 US
62058044 Sep 2014 US