Today, a datacenter may process different types of flows, including elephant flows and mouse flows. An elephant flow represents a long-lived flow or a continuous traffic flow that is typically associated with high volume connection. Different from an elephant flow, a mouse flow represents a short-lived flow. Mice are often associated with bursty, latency-sensitive applications, whereas elephants tend to be associated with large data transfers in which throughput is far more important than latency.
A problem with elephant flows is that they tend to fill network buffers end-to-end, and this introduces non-trivial queuing delay to anything that shares these buffers. For instance, a forwarding element may be responsible for managing several queues to forward packets, and several packets belonging to a mouse flow may be stuck in the same queue behind a group of other packets belonging to an elephant flow. In a network of elephants and mice, this means that the more latency-sensitive mice are being affected. Another problem is that mice are generally very bursty, so adaptive routing techniques are not effective with them.
Embodiments described herein provide a forwarding element that detects and handles elephant flows. In detecting, the forwarding element of some embodiments monitors statistics or measurements relating to a data flow. As an example, the forwarding element may track the number of bytes sent in the data flow, and specify, based on the number of bytes, whether the data flow should be classified as elephant flow. In some embodiments, the forwarding element performs the monitoring on a per data flow basis by tracking statistics associated with a flow entry (e.g., in a flow table) that is used to process packets.
In some embodiments, the forwarding element is an edge forwarding element. The edge forwarding element is in a unique position to monitor data flows because it represents a last forwarding element before one or more end machine. For instance, the edge forwarding element may be communicatively coupled to a particular machine. The forwarding element can then detect an elephant flow by directly monitoring outbound packets from the particular machine. Alternatively or conjunctively with outbound packets, the forwarding element can detect an elephant flow by directly monitoring inbound packets to the particular machine.
The forwarding element of some embodiments monitors tunneled traffic to detect elephant flows. In some embodiments, the forwarding element is a tunnel endpoint that operates in conjunction with another tunnel endpoint to monitor and detect elephant flows at either ends of the tunnel. As an example, in detecting elephant flows, a first forwarding element at one end of the tunnel may monitor outbound packets from a first network host to a second network host, and a second forwarding element at the other end of the tunnel may monitor outbound packets from the second network host to the first network host.
As mentioned above, the forwarding element of some embodiments tracks the number of bytes sent to detect an elephant flow. In conjunction with byte count or instead of it, the forwarding element of some embodiments factors in time. As an example, the forwarding element might detect an elephant flow solely based on the duration of the data flow. That is, if the duration of the data flow is over a set period of time, the forwarding might determine that the data flow is an elephant flow. Also, instead of byte count, the forwarding element might calculate data transfer rate (e.g., bytes per second) that identifies rate at which the data is transferring over a given time period. The data transfer rate can be used to allow an elephant flow with slow data transfer rate to progress as normal. This is because such an elephant flow may not be contributing or at least significantly contributing in the latency of other data flows, such as mice flows and non-detected elephant flows.
Once an elephant flow is detected, the forwarding element of some embodiments treats the flow differently than a mouse flow. In some embodiments, a first forwarding element marks each packet associated with a detected elephant flow in some manner to differentiate it from other packets. The packet is then sent over the network and received at a second forwarding element at the next hop or some other subsequent hop. The second forwarding element then uses the marking to process the packet different from other packets associated with other data flows in order to reduce any delays caused by the detected elephant flow in processing the other packets associated with the other data flows. The second element may perform a quality of service (QOS) operation on the packet. For instance, the second forwarding element may place the packet in a particular queue different from one or more other queues used to process other packets (e.g., packets associated with mice flows and non-detected elephant flows). In this manner, one set of packets belonging to a mouse flow is not held in the same queue behind another set of packets belonging to an elephant flow for a prolonged period of time.
In some embodiments, the forwarding sets at least one bit in the packet's header to indicate that the packet belongs to the detected elephant flow. As an example, the forwarding element of some embodiments sets a (Differentiated Services Code Point) DSCP bit in the packet's header and allows the fabric (e.g., another forwarding element in the network) to handle the packet through standard queuing mechanisms. The DSCP bit or some other bit may be set in the packet's tunnel header. The DSCP field provides different levels of service to be assigned to network traffics, such as IP packets. However, if there is no encapsulation, the actual packet can be marked with a marking.
In some embodiments, the forwarding element facilitates in breaking an elephant flow into a number of mouse flows. The basic idea here is to split an elephant follow up into a bunch of mouse flows (e.g., by using more than one ephemeral source port for the flow). This approach has the nice property that the fabric remains simple and uses a single queuing and routing mechanism for all traffic. One way to implement this in an overlay network is to modify the ephemeral port of the outer header to create the necessary entropy needed by the multipathing hardware. In some embodiments, the forwarding element performs a traceroute to identify a network map and chooses different paths based on the network map.
In addition, several embodiments that detect elephant flows based on the size of a packet are described in U.S. patent application Ser. No. 14/231,652, entitled “Detecting an Elephant Flow Based on the Size of a Packet”, filed concurrently with this application, and now issued as U.S. Pat. No. 9,548,924. Some embodiments that report elephant flows to a network controller are described in U.S. patent application Ser. No. 14/231,654, entitled “Reporting Elephant Flows to a Network Controller”, filed concurrently with this application, and now published as U.S. Publication 2015/0163145. These U.S. Patent Applications are incorporated herein by reference. In addition, some embodiments provide a system that detects an elephant flow by examining the operations of a machine. In some embodiments, the machine is a physical machine or a virtual machine (VM). In detecting, the system identifies an initiation of a new data flow associated with the machine. The new data flow can be an outbound data flow or an inbound data flow. The system then determines, based on the amount of data being sent or received, if the data flow is an elephant flow.
The preceding Summary is intended to serve as a brief introduction to some embodiments as described herein. It is not meant to be an introduction or overview of all 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 and the Drawings is needed. Moreover, the claimed subject matters are not to be limited by the illustrative details in the Summary, Detailed Description and the Drawings, but rather are to be defined by the appended claims, because the claimed subject matters can be embodied in other specific forms without departing from the spirit of the subject matters.
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.
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.
Embodiments described herein provide a forwarding element that detects and handles elephant flows. In detecting, the forwarding element of some embodiments monitors statistics or measurements relating to a data flow. As an example, the forwarding element may track the number of bytes sent in the data flow, and specify, based on the number of bytes, whether the data flow should be classified as elephant flow. In some embodiments, the forwarding element performs the monitoring on a per data flow basis by tracking statistics associated with a flow entry (e.g., in a flow table) that is used to process packets.
Once an elephant flow is detected, the forwarding element of some embodiments treats it differently than a mouse flow. In some embodiments, the forwarding element marks each packet associated with a detected elephant flow in some manner to differentiate it from a packet associated with a mouse flow. The packet is then sent over the network and received at a next hop or some other subsequent hop that recognizes the mark. Thereafter, the packet is placed in a particular queue different from one or more other queues used to process other packets (e.g., packets associated with mice flows and non-detected elephant flows). In this manner, one set of packets belonging to a mouse flow is not held in the same queue behind another set of packets belonging to an elephant flow for a prolonged period of time.
In some embodiments, the forwarding element facilitates in breaking an elephant flow into a number of mouse flows. The basic idea here is to split an elephant up into a bunch of mice (e.g., by using more than one ephemeral source port for the flow). This approach has the nice property that the fabric remains simple and uses a single queuing and routing mechanism for all traffic. One way to implement this in an overlay network is to modify the ephemeral port of the outer header to create the necessary entropy needed by the multipathing hardware.
Several example detection and handling mechanisms will be described in detail below. In particular, Section I describes several example techniques for detecting elephant flows based on a threshold value. This is followed by Section II that describes several example handling a detected elephant flow by marking packets associated with elephant flow with a marking. Section III then several examples of handling a detected elephant flow by breaking the elephant flow into a number of mouse flows. Section IV then describes an electronic system for implementing some embodiments of the invention.
I. Detecting Elephant Flows Based on Statistics
In some embodiments, the forwarding element of some embodiments monitors at least one statistic or measurement relating to a data flow to determine whether the data flow should be classified as an elephant flow. For example, the forwarding element may track the number of bytes sent in a data flow, and specify, based on the number of bytes, whether the data flow should be classified as elephant flow. In some embodiments, the forwarding element performs the monitoring on a per data flow basis by tracking statistics associated with a rule or flow entry (e.g., in a flow table) that is used to process packets.
In monitoring, the forwarding element of some embodiments finds an elephant flow by updating and checking one or more counters (e.g., byte sent, packet sent) associated with a corresponding flow entry. As an example, the forwarding element might check whether the number of bytes sent has reached a certain threshold limit. When the threshold limit has been reached, the forwarding element then specifies that the data flow associated with the flow entry is an elephant flow. The term “packet” is used here as well as throughout this application to 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 “packet” may be used herein to refer to various formatted collections of bits that may be sent across a network, such as Ethernet frames, TCP segments, UDP datagrams, IP packets, etc.
In some embodiments, the forwarding element of some embodiments may also take into account the duration of time that the flow entry has been in memory or cache to handle data transfer. For instance, the forwarding element of some embodiments periodically examines a cache to identify which flows remain in the cache to process packets while others flows timeout or expire. In some embodiments, the forwarding element calculates number of bytes sent over a specified time (e.g., bytes per second (Bps)). Alternatively, if the forwarding element finds a flow that is constantly being used to process packets, the forwarding element may specify the data flow associated with the flow entry as an elephant flow. For instance, the forwarding element may examine the packet count and determine whether a data flow should be categorized as an elephant flow based on the packet count.
In some embodiments, the forwarding element is an edge forwarding element (EFE). Different from a non-edge forwarding element (NEFE), the EFE is in a unique position to identify elephant flows. The EFE has the advantage over a NEFE in that it is the last forwarding element before one or more end machines (e.g., VMs, computing device). Thus, the EFE can more easily monitor traffic coming from and going to an end machine than a NEFE. Such dynamic detection is more difficult with a NEFE. For instance, performing the detection within the network by a NEFE can be difficult because of flow tracking in high-density switching application-specific integrated circuits (ASICs). A number of sampling methods have been proposed, such as sampling the buffers or using sFlow. However, the accuracy of such approaches remains unclear due to the sampling limitations at high speeds.
A. Example Process
Having described a brief overview of detecting elephant flows, an example process will now be described.
The process 100 begins when it identifies (at 105) a data flow. The process 100 then retrieves (at 110) a statistic or measurement relating to the data flow. For example, the process 100 might retrieve a byte count, a packet count, and/or time associated with the flow. The byte count identifies the number of bytes sent using a rule or flow entry (in a flow table or a cache). The packet count identifies the number of packets sent in the data flow with the rule. The time identifies the duration of time that the rule has been in memory (e.g., in a flow table or cache) to process packets. In some embodiments, the process 100 computes bytes over a specified time and/or rate over a specified time to determine if a flow entry is associated with a data transfer session that is transferring large amounts of data.
At 115, the process 100 determines whether the statistical data is greater than a threshold value. If so, the process 100 specifies (at 120) that the data flow is an elephant flow. In specifying, the process 100 of some identifies one or more pieces of information that can be used to identify packets in the elephant data flow. The process 100 may identify tunnel information, such as the tunnel ID, the IP address of the source tunnel endpoint (e.g., the hypervisor), and the IP address of the destination tunnel endpoint. The process 100 of some embodiments identifies the elephant flow packet's ingress port, source transport layer (e.g., UDP or TCP) port, destination transport layer port, Ethernet type, source Ethernet address, destination Ethernet address, source IP address, and/or destination IP address.
If the statistical data is less than the threshold value, the process determines (at 125) whether to examine another flow entry. If there is another flow entry, the process 100 returns to 105, which is described above. Otherwise, the process 100 ends.
Some embodiments perform variations on the process 100. The specific operations of the process 100 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.
B. Example Implementation
An example implementation of a forwarding element that examines statistics will now be described.
In the example of
In some embodiments, the forwarding element is an edge forwarding element. The edge forwarding element is in a unique position to monitor data flows because it represents a last forwarding element before one or more end machine. For instance, the edge forwarding element may be communicatively coupled to a particular machine. The forwarding element can then detect an elephant flow by directly monitoring outbound packets from the particular machine. Alternatively or conjunctively with outbound packets, the forwarding element can detect an elephant flow by directly monitoring inbound packets to the particular machine.
The forwarding element of some embodiments monitors tunneled traffic to detect elephant flows. In some embodiments, the forwarding element is a tunnel endpoint that operates in conjunction with another tunnel endpoint to monitor and detect elephant flows at either ends of the tunnel. As an example, in detecting elephant flows, a first forwarding element at one end of the tunnel may monitor outbound packets from a first network host to a second network host, and a second forwarding element at the other end of the tunnel may monitor outbound packets from the second network host to the first network host.
In some embodiments, the forwarding element 200 (e.g., software or hardware) of some embodiments is a physical forwarding element that implements one or more logical forwarding elements with one or more other physical forwarding elements. For instance, the physical forwarding element may operate in conjunction with at least one other forwarding element to different logical forwarding element for different tenants, users, departments, etc. that use the same shared computing and networking resources. Accordingly, the term “physical forwarding element” is used herein to differentiate it from a logical forwarding element.
In the example of
The kernel module 220 accesses the datapath 225 to find matching flows to process packets. The datapath 225 contains any recently used flows. The flows may be fully specified, or may contain one or more match fields that are wildcarded, in some embodiments. Typically, a flow or rule includes a set of match fields to match against a set of header fields of a packet. The rule also includes a set of actions (e.g., one or more actions) to perform on the packet if the set of header fields matches the set of match fields. When the kernel module 220 receives the packet's header values or hashes of a hash of the header values, it tries to find a matching flow entry or rule installed in the datapath 225. If it does not find one, then the control is shifted to the userspace daemon 205.
To handle such cases, the userspace daemon 205 includes a flow installer 210. In some embodiments, the flow installer 210 is referred to in some embodiments as open flow protocol datapath interface (ofproto-dif). When there is a miss in the datapath 225, the flow installer 210 is called to install a rule (i.e., a flow entry) in the datapath cache based on one or more flows in a set of one or more flow tables. In this manner, the forwarding element 200 can quickly process each subsequent packet with the same set of header values using the rule in the datapath cache 225. The datapath cache 225 provides a fast path to process incoming packets because it does not involve any translation at the userspace by the userspace daemon 205.
In some embodiments, the forwarding element 200 includes a detection module 215 is responsible for detecting elephant flows. Conceptually, the detection module 210 module retrieves data relating to a flow entry in the datapath 225. The detection module 210 then compares the data against a threshold value to determine if the flow entry is associated with an elephant flow.
Different embodiments use different mechanisms to examine statistics or measurements relating to various flows. In some embodiments, the physical forwarding element 200 iterates through each flow (e.g., in the datapath cache or in a flow table) periodically and/or when triggered. For instance, the forwarding element may be configured with a rule or programmed to validate each flow in the datapath cache every set period of time (e.g., every one second at minimum). Alternatively, or conjunctively, the physical forwarding element can be triggered to perform dynamic detection each time a flow entry or rule (e.g., in the datapath cache or in a flow table) is used to process a packet.
Having described several components of the forwarding element 200, an example operation of the forwarding element will now be described by reference to three time periods (T1-T3) that are shown in
At T1, the forwarding element 200 has three flow entries 230-240 in the datapath 225 to process incoming packets. Each flow entry is associated with statistical data, such as byte sent and packet sent. The flow installer 210 might have installed each of these flow entries to quickly process incoming packets. In the example of T1, the first flow entry 230 has been used to process one packet, the second flow entry 235 has been used to process a hundred packets, and third flow entry 240 has been used to process four packets. At this time (T1), the detection module might be examining data relating the flow entries 230-240 in order to find an elephant.
T2 represents sometime after T1. At T1, the forwarding element 200 now only has two flow entries 230 and 235 in the datapath 225 to process incoming packets. Particularly, the flow entry 240 has been removed from the datapath 225. In this example, the flow entry 240 was removed from the database cache 225 because it was no longer being used to process any incoming packets. In some embodiments, the userspace daemon 205 performs a flow eviction process to remove each flow that is no longer being used from the datapath 225. The flow eviction process determines if a flow entry in the datapath has expired and, if so, removes the flow entry from the datapath. For instance, if the flow entry has not been used for a set period of time, the userspace daemon 205 deletes the flow entry from the datapath 225. This feature prevents the datapath 225 from being filled with potentially many flow entries that has not been used for some time, which in turns speeds up the classifier lookup.
T2 shows that the flow entries 230 and 235 were used to process additional packets. Namely, the flow entry 230 has been used to process 50 packets, and the flow entry 235 has been used to process 500 packets. Again, at T2, the detection module 215 might be examining data relating each of the flow entries 230 and 235 in order to determine if the corresponding flow entry belongs to an elephant flow.
T3 represents sometime after T2. At T3, the forwarding element 200 now only has one flow entry 235 left in the datapath 225 to process packets. Specifically, the flow entry 230 has been removed from the datapath 225. The flow entry 230 was removed from the database cache because it was no longer being used to process packets. T3 also shows that the flow entry 235 has been used to process additional packets. In particular, the flow entry 235 has now been used to process 1000 packets.
At T3, the detection module 215 has retrieved data relating the flow entry 235. The detection module 215 has also compared the data against one or more threshold values. Based on the comparison, the detection module 215 has detected that the flow entry 235 as being associated with an elephant flow.
C. Flows with Wildcard Match Fields
The forwarding element of some embodiments supports match rules with wildcard match fields. Each rule may include one or more wildcard fields and/or one or more fields that are at least partially wildcarded. For instance, a first portion of an IP destination address match field may be fully specified, while the remaining portion of the IP address match field is wildcarded. The forwarding element uses such non-exact match rules to reduce the overhead in making packet forwarding decisions (e.g., at the userspace with the userspace daemon). In some embodiments, a rule with a wild card match field (or a portion of the match field wildcarded) is also referred to as a megaflow. The term “megaflow” is used to distinguish the flow from an exact match rule, also referred to herein as a “microflow”. A small number of megaflows installed into the kernel can process a diverse collection of packets, eliminating much overhead by sending fewer packets from the kernel to userspace.
The problem with such a megaflow is that it may be used to process multiple different data flows. The megaflow may be used process packets in an elephant flow, as well as a mouse flow. This is because at least one match field (or a portion thereof) is wildcarded or sub-masked. For instance, several different packets, which are associated with different data flows, can be processed by one wildcard flow as long as each packet has a set of header values that match a set of non-wildcard fields. Therefore, the statistical data associated with the megaflow may be unreliable data source to make a determination of whether a data flow should be classified as an elephant flow.
A first example solution to the megaflow problem is for the forwarding element to disable the megaflow feature when elephant detection feature is enabled. A second example solution would be to perform dynamically disable the megaflow feature. For instance, the forwarding element can periodically disable or shoot the megaflow feature and see which packets are sent up to userspace. The idea here is to periodically remove one or more megaflows from the datapath and check what gets reported. The forwarding element may then decide, based on the report, that a megaflow may be associated with an elephant flow. A third example solution to the megaflow problem is to sample what microflows are in the datapath. For instance, the forwarding element would sample the datapath periodically for different microflows. If a forwarding element encounters a same microflow multiple times, the forwarding element can check the flow's statistical data to determine if the microflow is associated with an elephant data flow.
In some embodiments, the forwarding element caches megaflows but also caches one or more microflows associated with each megaflow. That is, for each wildcard flow, the forwarding element can still keep track of each non-wildcard flow relating to the wildcard flow. For instance, the forwarding element can push down a wildcard flow into the datapath; however, on a per CPU basis, the forwarding element can have non-wildcard flows. Each of these non-wildcard flows can then be exposed or queried to retrieve the corresponding statistical data.
In the example of
Another alternate approach to the solving the megaflow problem is to perform recirculation. The recirculation can be performed at the kernel space with the kernel module 345, in some embodiments. Recirculation entails finding a matching flow in one table and performing a resubmit action to another table. For example, in the example of
II. Marking Packets Associated with an Elephant Flow
Once an elephant flow is detected, the forwarding element of some embodiments treats the flow differently than a mouse flow. In some embodiments, a first forwarding element marks each packet associated with a detected elephant flow in some manner to differentiate it from other packets. The packet is then sent over the network and received at a second forwarding element at the next hop or some other subsequent hop. The second forwarding element then uses the marking to process the packet different from other packets associated with other data flows in order to reduce any delays caused by the detected elephant flow in processing the other packets associated with the other data flows. The second element may perform a quality of service (QOS) operation on the packet. For instance, the second forwarding element may place the packet in a particular queue different from one or more other queues used to process other packets (e.g., packets associated with mice flows and non-detected elephant flows). In this manner, one set of packets belonging to a mouse flow is not held in the same queue behind another set of packets belonging to an elephant flow for a prolonged period of time.
In some embodiments, the forwarding sets at least one bit in the packet's header to indicate that the packet belongs to the detected elephant flow. As an example, the forwarding element of some embodiments sets a (Differentiated Services Code Point) DSCP bit in the packet's header and allows the fabric (e.g., another forwarding element in the network) to handle the packet through standard queuing mechanisms. The DSCP bit or some other bit may be set in the packet's tunnel header. However, if there is no encapsulation, the actual packet can be marked with a marking.
B. Example Process
Having described a brief overview of marking packets, an example process will now be described.
In some embodiments, the process 400 detects an elephant flow based on one or more statistics associated with a data flow. The process of some embodiments the size of each of several packets in a data flow to determine whether the data flow is an elephant flow. The process inspects the size because, in order for the packet to be of a certain size, the data flow had to already have gone through a slow start in which smaller packets are transferred and by definition be an elephant flow. As an example, the Transmission Control Protocol (TCP) uses a slow start algorithm in order to avoid congesting the network with an inappropriately large burst of data. The TCP also uses the algorithm to slowly probe the network to determine the available capacity. The process of some embodiments takes advantage of such a slow start algorithm by using it to detect elephant flows.
The process 400 of some embodiments detects an elephant flow by examining the operations of a machine. The elephant flow represents a long-lived data flow or a continuous traffic flow that is associated with large data transfer. In some embodiments, the machine is a physical machine or a virtual machine (VM). In detecting, the process 400 identifies an initiation of a new data flow associated with the machine. The new data flow can be an outbound data flow or an inbound data flow. The process 400 then determines, based on the amount of data being sent or received, if the data flow is an elephant flow.
As shown in
The process 400 then determines (at 425) whether there is another packet that is associated with the elephant flow. If so, the process 400 returns to 410, which is described above. Otherwise, the process 400 ends. Here, the process identifies an elephant flow and marks, based on the identification, packet headers (e.g., with DSCP (QOS) marking) before sending encapsulated packet to the physical fabric. The physical fabric uses this bit to assign packets to different internal queues. This prevents elephant connections ballooning or increasing the latency of mice connections, which are more likely to be about low-latency application operations.
Some embodiments perform variations on the process 400. The specific operations of the process 400 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.
B. Example Implementations
In the first stage 505, the edge forwarding element 505 detects an elephant flow. The second stage 510 shows the edge forwarding element 505 marking a packet that belongs to the elephant flow. This is followed by the third stage 515, which shows the edge forwarding element 505 forwarding the packet 545 to the non-edge forwarding element 525.
In the fourth stage 520, the non-edge forwarding element 505 has received the packet from the edge forwarding element 525. Specifically, the packet 545 has been received by a Quality of Service (QOS) engine 530 that executes on the non-edge forwarding element 525. In this example, the non-edge forwarding element includes a number of queues (e.g., 535, 540, etc.). Typically, a forwarding element (e.g., top-of-rack switch) has several different queues (e.g., eight queues), and the forwarding element can be configured to specify how packets are placed into the different queues and how the queues are drained. Here, the QOS engine reads the marking, select the queue 540 based on the marking, and place the packet 545 in that selected queues. In this example, since the elephants and mice are all sharing the same infrastructure. The marking is used so that one or more packets belonging to a mouse flow is not stuck in a queue behind a group of packets belong to an elephant flow.
III. Breaking Elephants into Mice
In some embodiments, the forwarding element facilitates in breaking an elephant flow into a number of mouse flows. The basic idea here is to split an elephant follow up into a bunch of mouse flows (e.g., by using more than one ephemeral source port for the flow). This approach has the nice property that the fabric remains simple and uses a single queuing and routing mechanism for all traffic. One way to implement this in an overlay network is to modify the ephemeral port of the outer header to create the necessary entropy needed by the multipathing hardware.
A. Example Process
At 615, the process 600 assigns one of several different source ports to the packet. After marking the header, the process 600 then forwards (at 620) the packet to another forwarding element. The process 600 then determines (at 625) whether there is another packet that is associated with the elephant flow. If so, the process 600 returns to 610, which is described above. Otherwise, the process 600 ends.
Some embodiments perform variations on the process 600. The specific operations of the process 600 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.
B. Example Implementations
Four operational stages 715-730 of a network 700 are shown in
The second stage 815 shows the EFE 701 forwarding the next packet to the NEFE 702. The third stage 815 shows that the NEFE 702 has received the next packet. Here, the NEFE 702 breaks the elephant flow into a mouse flow by choosing another ECMP leg to route the next packet based on the different source port. Specifically, instead of NEFE 703 or NEFE 705, the NEFE 702 has chosen to forward the packet to NEFE 704. Accordingly, in the third stage 815, the NEFE 702 sends the packet to NEFE 704.
In the example described above, the core static ECMP is extended by edge sourced dynamic-load based entropy. That is, the overlays allow the system to repurpose the classic 5-tuple used for ECMP within the fabric. The 5-tuple comprising the source IP address, destination IP address, protocol type, TCP/UDP source port, and TCP/UDP destination port. A single logical connection does not need to translate into one outer (Stateless Transport Tunneling (STT), Virtual Extensible LAN (VXLAN)) 5-tuple for its lifetime but instead the system can use several outer 5-tuples over the lifetime of the connection. A practical way to achieve this is to reassign the outer source port after a set of packets has been sent over the logical connection. This will result in more uniform traffic distribution across the physical fabric links and hence more bandwidth available for the endpoints.
Also, in the example described above, a first forwarding assigns different header values (e.g., hashes) for different packets in a same data flow. The packets are then processed by a second forwarding to break the elephant data flow into one or more smaller mouse data flows. One of ordinary skill in the art would understand that these operations could be performed on one forwarding element rather than multiple forwarding element. For instance, a forwarding element of some embodiments can monitor a data flow associated with a network host to detect an elephant flow, and perform load balancing by sending traffic belonging to a detected elephant flow along different paths. The forwarding element may also generate different hashes to send traffic along the different paths.
C. Reordering Problem
One downside of using the STT protocol may be one of its prominent features: efficiently sending large contiguous blocks of data. Ideally, many small packets would be sent through different paths. However, the TCP segmentation offload (TSO) engine takes a large (up to 64 KB) TCP segment and breaks it into MTU-sized fragments with the same TCP header (and thus, source port). For instance, the forwarding element may calculate a hash of the inner packet headers, and place the hash in the outer source (e.g., UDP, TCP) port where it feeds into a link aggregation control protocol (LACP)/ECMP hash calculation. This means each segment will take the same path instead of multiple routes. On the other hand, when packets take multiple routes, they can introduce reordering due to different numbers of hops or queuing delays.
To prevent reordering, the system of some embodiments introduces additional state into a particular protocol, such as STT, VXLAN, etc.
When an elephant flow is detected, the sender's protocol stack (e.g., STT stack) can choose multiple source ports for the elephant flow. The sender can also use the same elephant flow ID and increment a sequence number counter for each successive packet. This is illustrated in the four stages 905-920 of
In the second stage 910, the NEFE 2702 has received the first packet from the EFE 701. The NEFE 702 then forwards the first packet to a particular path based on the hash value. The second stage 910 also illustrates the EFE 701 sending second packet. The second packet is assigned the same elephant flow ID; however, the second packet's sequence number counter has been incremented by one, and a different hash value has been assigned to the source port of the second packet's outer header.
The third stage 915 is similar to the second stage 910. In particular, the NEFE 2702 has received the second packet from the EFE 701. The NEFE 702 then forwards the second packet to another path based on the hash value. The third stage 910 also illustrates the EFE 701 sending a third packet with the same elephant flow ID, an incremented sequence number, and another different hash value. The fourth stage 920 shows the NEFE 702 forwarding the third packet to another different path based on the third packet's associated hash value. Although not shown in
The receiver opportunistically tries to forward segments (i.e., packets) to the recipient in sequential order according the sequence number counter. The receiver of some embodiments maintains a buffer that holds segments that are greater than the counter ID the receiver expects. In some embodiments, the receiver immediately gives the recipient any contiguous block that it can that begins with the counter ID that the receiver expects. If after a relatively small delay, the receiver does not have the counter ID it expects, but has later ones, the receiver forwards what each packet the receiver has to the recipient. The receiver of some embodiments always sets the expected counter ID to the last counter it forwarded. If a segment for an elephant flow comes in with a lower ID than expected, the receiver of some embodiments always immediately forwarded to the recipient. Alternatively, the receiver can just drop the future segments (i.e., out of order segments) if it is concerned about introducing reordering.
Four stages 1005-1020 are shown in
The first stage 1005 shows the EFE 711 receiving the first packet from the NEFE 710. The first packet is received in order. Accordingly, in the second stage 1010, the EFE 711 forwards the first packet to the machine 1025. The third stage 1015 shows the EFE 711 receiving the third packet from the NEFE 710. The third packet is received out of sequence. Accordingly, in the fourth stage 1020, the EFE 711 stores the packet is the buffer 1025.
Three stages 1105-1115 are shown in
In the example described above, the system introduces additional state into a particular protocol, such as STT, VXLAN, etc. An alternate approach to handling the reordering is to overload the TCP timestamp option, which the network interface controller or card (NIC) dutifully duplicates on transmit and receive for each fragment or each maximum transmission unit (MTU) sized packet. In the timestamp option, the system would encode a similar elephant flow ID and counter. The positive in this is that that the receiver can immediately flush its cache for that elephant flow if it knows that any earlier fragment is missing. One downside of this approach is some additional complexity and copying the elephant flow identifier (ID) and counter into each fragment.
D. Choosing Legs
In some embodiments, the forwarding element performs a traceroute to identify a network map and chooses different paths for packets associated with an elephant flow. For instance, the forwarding element of some embodiment determines one tunnel source port for each possible Layer 3 (L3) path, e.g. using a variant of the Paris traceroute algorithm. Once determined, the forwarding element (e.g., the forwarding element daemon) performs a precise mapping from flow to tunnel source port (e.g., in userspace). The forwarding element then would not have to perform the hashing of each flow to the whole set of source ports. Instead, the forwarding element specifies several distinct subsets of tunnel source ports, which would take distinct sets of L3 paths in the fabric. As an example, the forwarding element can specify for each flow the specific subset of source ports it could be hashed to. In this manner, the forwarding element ensures that elephant flows take different paths by hashing them to different sets of tunnel source ports.
Two stages 1214 and 1216 are shown in
As shown in the first stage 1214, the EFE 1202 sends a second packet with the TTL field value incremented by one second to two seconds. The NEFE 1204 receives the second packet, decrements the second packet's TTL value by one second, and instead of returning an error message, forwards the second packet to the NEFE 1206. The NEFE 1206 receives the second packet and decrements the second packet's TTL and returns a message. The EFE 1202 then increments the time again and sends a third packet to identify the NEFE 1210. Lastly, the EFE 1204 sends the fourth packet with the TTL time incremented to identify the EFE 1212.
The second stage 1216 shows the EFE 1202 performing a traceroute to identify a second path in the network 1200. Here, the EFE 1202 performs similar probes as the first stage 1214. However, the NEFE 1204 sends each packet that it receives along the second path to the NEFE 1208. Here, the EFE 1202 might have randomize the source port value to a different value than the first stage 1214. In this way, the traceroute can map out the second available paths. In some embodiments, the EFE 1202 uses a same flow identifier for each path and maps one path at a time, as illustrated in
In some embodiments, Paris traceroute controls the probe header fields to allow all probes towards a destination to follow the same path in the presence of per-flow load balancing. Paris traceroute does this by varying header fields that are within the first 28 octets, but are not used for load balancing. For instance in TCP probes, Paris traceroute varies the sequence number. In UDP probes, it is the checksum field. This may require the manipulation of the payload to yield the desired checksum. In addition, for (Internet Control Message Protocol) ICMP probes, the algorithm may use a combination of the ICMP identifier and the sequence number. Paris traceroute sets the value of the ICMP identifier and sequence number to keep constant the header checksum of all probes to a destination.
IV. Electronic System
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 computational or 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, random access memory (RAM) chips, hard drives, erasable programmable read-only memories (EPROMs), electrically erasable programmable read-only memories (EEPROMs), 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.
The bus 1305 collectively represents all system, peripheral, and chipset buses that communicatively connect the numerous internal devices of the electronic system 1300. For instance, the bus 1305 communicatively connects the processing unit(s) 1310 with the read-only memory 1330, the system memory 1325, and the permanent storage device 1335.
From these various memory units, the processing unit(s) 1310 retrieves 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) 1330 stores static data and instructions that are needed by the processing unit(s) 1310 and other modules of the electronic system. The permanent storage device 1335, 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 electronic system 1300 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 1335.
Other embodiments use a removable storage device (such as a floppy disk, flash memory device, etc., and its corresponding drive) as the permanent storage device. Like the permanent storage device 1335, the system memory 1325 is a read-and-write memory device. However, unlike storage device 1335, the system memory 1325 is a volatile read-and-write memory, such a random access memory. The system memory 1325 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 1325, the permanent storage device 1335, and/or the read-only memory 1330. From these various memory units, the processing unit(s) 1310 retrieves instructions to execute and data to process in order to execute the processes of some embodiments.
The bus 1305 also connects to the input and output devices 1340 and 1345. The input devices 1340 enable the user to communicate information and select commands to the electronic system. The input devices 1340 include alphanumeric keyboards and pointing devices (also called “cursor control devices”), cameras (e.g., webcams), microphones or similar devices for receiving voice commands, etc. The output devices 1345 display images generated by the electronic system or otherwise output data. The output devices 1345 include printers and display devices, such as cathode ray tubes (CRT) or liquid crystal displays (LCD), as well as speakers or similar audio output devices. Some embodiments include devices such as a touchscreen that function as both input and output devices.
Finally, as shown in
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. In addition, some embodiments execute software stored in programmable logic devices (PLDs), ROM, or RAM devices.
As used in this specification and any claims of this application, 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 and any claims of this application, 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 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. In addition, a number of the figures (including
This application claims the benefit of U.S. Provisional Patent Application 61/913,899, entitled “Detecting and Handling Elephant Flows”, filed on Dec. 9, 2013. U.S. Provisional Patent Application 61/913,899 is incorporated herein by reference.
Number | Name | Date | Kind |
---|---|---|---|
5224100 | Lee et al. | Jun 1993 | A |
5245609 | Ofek et al. | Sep 1993 | A |
5265092 | Soloway et al. | Nov 1993 | A |
5504921 | Dev et al. | Apr 1996 | A |
5550816 | Hardwick et al. | Aug 1996 | A |
5668810 | Cannella, Jr. | Sep 1997 | A |
5729685 | Chatwani et al. | Mar 1998 | A |
5751967 | Raab et al. | May 1998 | A |
5781534 | Perlman et al. | Jul 1998 | A |
6104699 | Holender et al. | Aug 2000 | A |
6104700 | Haddock et al. | Aug 2000 | A |
6141738 | Munter et al. | Oct 2000 | A |
6219699 | McCloghrie et al. | Apr 2001 | B1 |
6430160 | Smith et al. | Aug 2002 | B1 |
6456624 | Eccles et al. | Sep 2002 | B1 |
6512745 | Abe et al. | Jan 2003 | B1 |
6539432 | Taguchi et al. | Mar 2003 | B1 |
6658002 | Ross et al. | Dec 2003 | B1 |
6680934 | Cain | Jan 2004 | B1 |
6721334 | Ketcham | Apr 2004 | B1 |
6785843 | McRae et al. | Aug 2004 | B1 |
6941487 | Balakrishnan et al. | Sep 2005 | B1 |
6963585 | Le Pennec et al. | Nov 2005 | B1 |
6999454 | Crump | Feb 2006 | B1 |
7012919 | So et al. | Mar 2006 | B1 |
7079544 | Wakayama et al. | Jul 2006 | B2 |
7149817 | Pettey | Dec 2006 | B2 |
7149819 | Pettey | Dec 2006 | B2 |
7197572 | Matters et al. | Mar 2007 | B2 |
7200144 | Terrell et al. | Apr 2007 | B2 |
7209439 | Rawlins et al. | Apr 2007 | B2 |
7283473 | Arndt et al. | Oct 2007 | B2 |
7342916 | Das et al. | Mar 2008 | B2 |
7362752 | Kastenholz | Apr 2008 | B1 |
7370120 | Kirsch et al. | May 2008 | B2 |
7391771 | Orava et al. | Jun 2008 | B2 |
7450598 | Chen et al. | Nov 2008 | B2 |
7463579 | Lapuh et al. | Dec 2008 | B2 |
7478173 | Delco | Jan 2009 | B1 |
7483370 | Dayal et al. | Jan 2009 | B1 |
7533176 | Freimuth et al. | May 2009 | B2 |
7555002 | Arndt et al. | Jun 2009 | B2 |
7606260 | Oguchi et al. | Oct 2009 | B2 |
7627692 | Pessi | Dec 2009 | B2 |
7633955 | Saraiya et al. | Dec 2009 | B1 |
7634622 | Musoll et al. | Dec 2009 | B1 |
7640353 | Shen et al. | Dec 2009 | B2 |
7643488 | Khanna et al. | Jan 2010 | B2 |
7649851 | Takashige et al. | Jan 2010 | B2 |
7706266 | Plamondon | Apr 2010 | B2 |
7710874 | Balakrishnan et al. | May 2010 | B2 |
7760735 | Chen et al. | Jul 2010 | B1 |
7764599 | Doi et al. | Jul 2010 | B2 |
7792987 | Vohra et al. | Sep 2010 | B1 |
7802000 | Huang et al. | Sep 2010 | B1 |
7808919 | Nadeau et al. | Oct 2010 | B2 |
7808929 | Wong et al. | Oct 2010 | B2 |
7818452 | Matthews et al. | Oct 2010 | B2 |
7826482 | Minei et al. | Nov 2010 | B1 |
7839847 | Nadeau et al. | Nov 2010 | B2 |
7885276 | Lin | Feb 2011 | B1 |
7936770 | Frattura et al. | May 2011 | B1 |
7937438 | Miller et al. | May 2011 | B1 |
7937492 | Kompella et al. | May 2011 | B1 |
7940763 | Kastenholz | May 2011 | B1 |
7948986 | Ghosh et al. | May 2011 | B1 |
7953865 | Miller et al. | May 2011 | B1 |
7991859 | Miller et al. | Aug 2011 | B1 |
7995483 | Bayar et al. | Aug 2011 | B1 |
8004900 | Dutta | Aug 2011 | B2 |
8027354 | Portolani et al. | Sep 2011 | B1 |
8031606 | Memon et al. | Oct 2011 | B2 |
8031633 | Bueno et al. | Oct 2011 | B2 |
8046456 | Miller et al. | Oct 2011 | B1 |
8054832 | Shukla et al. | Nov 2011 | B1 |
8055789 | Richardson et al. | Nov 2011 | B2 |
8060875 | Lambeth | Nov 2011 | B1 |
8131852 | Miller et al. | Mar 2012 | B1 |
8149737 | Metke et al. | Apr 2012 | B2 |
8155028 | Abu-Hamdeh et al. | Apr 2012 | B2 |
8161270 | Parker et al. | Apr 2012 | B1 |
8166201 | Richardson et al. | Apr 2012 | B2 |
8199750 | Schultz et al. | Jun 2012 | B1 |
8223668 | Allan et al. | Jul 2012 | B2 |
8224931 | Brandwine et al. | Jul 2012 | B1 |
8224971 | Miller et al. | Jul 2012 | B1 |
8265075 | Pandey | Sep 2012 | B2 |
8281067 | Stolowitz | Oct 2012 | B2 |
8312129 | Miller et al. | Nov 2012 | B1 |
8339959 | Moisand et al. | Dec 2012 | B1 |
8339994 | Gnanasekaran et al. | Dec 2012 | B2 |
8345558 | Nicholson et al. | Jan 2013 | B2 |
8351418 | Zhao et al. | Jan 2013 | B2 |
8355328 | Matthews | Jan 2013 | B2 |
8456984 | Ranganathan et al. | Jun 2013 | B2 |
8504718 | Wang et al. | Aug 2013 | B2 |
8571031 | Davies et al. | Oct 2013 | B2 |
8611351 | Gooch et al. | Dec 2013 | B2 |
8612627 | Brandwine | Dec 2013 | B1 |
8619731 | Montemurro et al. | Dec 2013 | B2 |
8625594 | Safrai et al. | Jan 2014 | B2 |
8625603 | Ramakrishnan et al. | Jan 2014 | B1 |
8625616 | Vobbilisetty et al. | Jan 2014 | B2 |
8644188 | Brandwine et al. | Feb 2014 | B1 |
8762501 | Kempf et al. | Jun 2014 | B2 |
8819259 | Zuckerman et al. | Aug 2014 | B2 |
8838743 | Lewites et al. | Sep 2014 | B2 |
8976814 | Dipasquale | Mar 2015 | B2 |
9032095 | Traina et al. | May 2015 | B1 |
9762507 | Gandham et al. | Sep 2017 | B1 |
20010043614 | Viswanadham et al. | Nov 2001 | A1 |
20020062422 | Butterworth et al. | May 2002 | A1 |
20020093952 | Gonda | Jul 2002 | A1 |
20020194369 | Rawlins et al. | Dec 2002 | A1 |
20030041170 | Suzuki | Feb 2003 | A1 |
20030058850 | Rangarajan et al. | Mar 2003 | A1 |
20030063556 | Hernandez | Apr 2003 | A1 |
20030093341 | Millard et al. | May 2003 | A1 |
20030191841 | DeFerranti et al. | Oct 2003 | A1 |
20040073659 | Rajsic et al. | Apr 2004 | A1 |
20040098505 | Clemmensen | May 2004 | A1 |
20040186914 | Shimada | Sep 2004 | A1 |
20040264472 | Oliver et al. | Dec 2004 | A1 |
20040267866 | Carollo et al. | Dec 2004 | A1 |
20040267897 | Hill et al. | Dec 2004 | A1 |
20050018669 | Arndt et al. | Jan 2005 | A1 |
20050027881 | Figueira et al. | Feb 2005 | A1 |
20050053079 | Havala | Mar 2005 | A1 |
20050083953 | May | Apr 2005 | A1 |
20050111445 | Wybenga et al. | May 2005 | A1 |
20050120160 | Plouffe et al. | Jun 2005 | A1 |
20050132044 | Guingo et al. | Jun 2005 | A1 |
20050182853 | Lewites et al. | Aug 2005 | A1 |
20050220096 | Friskney et al. | Oct 2005 | A1 |
20050232230 | Nagami et al. | Oct 2005 | A1 |
20060002370 | Rabie et al. | Jan 2006 | A1 |
20060026225 | Canali et al. | Feb 2006 | A1 |
20060028999 | Iakobashvili et al. | Feb 2006 | A1 |
20060029056 | Perera et al. | Feb 2006 | A1 |
20060037075 | Frattura et al. | Feb 2006 | A1 |
20060104286 | Cheriton | May 2006 | A1 |
20060140118 | Alicherry et al. | Jun 2006 | A1 |
20060174087 | Hashimoto et al. | Aug 2006 | A1 |
20060187908 | Shimozono et al. | Aug 2006 | A1 |
20060193266 | Siddha et al. | Aug 2006 | A1 |
20060206655 | Chappell et al. | Sep 2006 | A1 |
20060221961 | Basso et al. | Oct 2006 | A1 |
20060246900 | Zheng | Nov 2006 | A1 |
20060262778 | Haumont et al. | Nov 2006 | A1 |
20060282895 | Rentzis et al. | Dec 2006 | A1 |
20060291388 | Amdahl et al. | Dec 2006 | A1 |
20070050763 | Kagan et al. | Mar 2007 | A1 |
20070055789 | Claise et al. | Mar 2007 | A1 |
20070064673 | Bhandaru et al. | Mar 2007 | A1 |
20070156919 | Potti et al. | Jul 2007 | A1 |
20070258382 | Foll et al. | Nov 2007 | A1 |
20070260721 | Bose et al. | Nov 2007 | A1 |
20070283412 | Lie et al. | Dec 2007 | A1 |
20070286185 | Eriksson et al. | Dec 2007 | A1 |
20070297428 | Bose et al. | Dec 2007 | A1 |
20080002579 | Lindholm et al. | Jan 2008 | A1 |
20080002683 | Droux et al. | Jan 2008 | A1 |
20080049614 | Briscoe et al. | Feb 2008 | A1 |
20080049621 | McGuire et al. | Feb 2008 | A1 |
20080049786 | Ram et al. | Feb 2008 | A1 |
20080059556 | Greenspan et al. | Mar 2008 | A1 |
20080071900 | Hecker et al. | Mar 2008 | A1 |
20080086726 | Griffith et al. | Apr 2008 | A1 |
20080159301 | de Heer | Jul 2008 | A1 |
20080240095 | Basturk | Oct 2008 | A1 |
20090006607 | Bu et al. | Jan 2009 | A1 |
20090010254 | Shimada | Jan 2009 | A1 |
20090046581 | Eswaran et al. | Feb 2009 | A1 |
20090150527 | Tripathi et al. | Jun 2009 | A1 |
20090292858 | Lambeth et al. | Nov 2009 | A1 |
20100128623 | Dunn et al. | May 2010 | A1 |
20100131636 | Suri et al. | May 2010 | A1 |
20100214949 | Smith et al. | Aug 2010 | A1 |
20100232435 | Jabr et al. | Sep 2010 | A1 |
20100254385 | Sharma et al. | Oct 2010 | A1 |
20100257263 | Casado et al. | Oct 2010 | A1 |
20100275199 | Smith et al. | Oct 2010 | A1 |
20100306408 | Greenberg et al. | Dec 2010 | A1 |
20110022695 | Dalal et al. | Jan 2011 | A1 |
20110075664 | Lambeth et al. | Mar 2011 | A1 |
20110085461 | Liu et al. | Apr 2011 | A1 |
20110085557 | Gnanasekaran et al. | Apr 2011 | A1 |
20110085559 | Chung et al. | Apr 2011 | A1 |
20110085563 | Kotha et al. | Apr 2011 | A1 |
20110128959 | Bando et al. | Jun 2011 | A1 |
20110164503 | Yong et al. | Jul 2011 | A1 |
20110194567 | Shen | Aug 2011 | A1 |
20110202920 | Takase | Aug 2011 | A1 |
20110249970 | Eddleston et al. | Oct 2011 | A1 |
20110261825 | Ichino | Oct 2011 | A1 |
20110299413 | Chatwani et al. | Dec 2011 | A1 |
20110299534 | Koganti et al. | Dec 2011 | A1 |
20110299537 | Saraiya et al. | Dec 2011 | A1 |
20110305167 | Koide | Dec 2011 | A1 |
20110317559 | Kern et al. | Dec 2011 | A1 |
20110317696 | Aldrin et al. | Dec 2011 | A1 |
20120054367 | Ramakrishnan et al. | Mar 2012 | A1 |
20120079478 | Galles et al. | Mar 2012 | A1 |
20120131222 | Curtis et al. | May 2012 | A1 |
20120159454 | Barham et al. | Jun 2012 | A1 |
20120182992 | Cowart et al. | Jul 2012 | A1 |
20120243539 | Keesara | Sep 2012 | A1 |
20120287791 | Xi | Nov 2012 | A1 |
20130024579 | Zhang et al. | Jan 2013 | A1 |
20130054761 | Kempf et al. | Feb 2013 | A1 |
20130058346 | Sridharan et al. | Mar 2013 | A1 |
20130064088 | Yu et al. | Mar 2013 | A1 |
20130067067 | Miri et al. | Mar 2013 | A1 |
20130163427 | Beliveau et al. | Jun 2013 | A1 |
20130163475 | Beliveau et al. | Jun 2013 | A1 |
20130286846 | Atlas et al. | Oct 2013 | A1 |
20130287026 | Davie | Oct 2013 | A1 |
20130322248 | Guo | Dec 2013 | A1 |
20130332602 | Nakil et al. | Dec 2013 | A1 |
20130339544 | Mithyantha | Dec 2013 | A1 |
20140019639 | Ueno | Jan 2014 | A1 |
20140029451 | Nguyen | Jan 2014 | A1 |
20140108738 | Kim et al. | Apr 2014 | A1 |
20140115578 | Cooper et al. | Apr 2014 | A1 |
20140119203 | Sundaram et al. | May 2014 | A1 |
20140173018 | Westphal et al. | Jun 2014 | A1 |
20140195666 | Dumitriu et al. | Jul 2014 | A1 |
20140233421 | Matthews | Aug 2014 | A1 |
20140281030 | Cui et al. | Sep 2014 | A1 |
20140372616 | Arisoylu et al. | Dec 2014 | A1 |
20150016255 | Bisht et al. | Jan 2015 | A1 |
20150071072 | Ratzin | Mar 2015 | A1 |
20150106804 | Chandrashekhar et al. | Apr 2015 | A1 |
20150120959 | Bennett et al. | Apr 2015 | A1 |
20150124825 | Dharmapurikar et al. | May 2015 | A1 |
20150163117 | Lambeth et al. | Jun 2015 | A1 |
20150163142 | Pettit et al. | Jun 2015 | A1 |
20150163145 | Pettit et al. | Jun 2015 | A1 |
20150163146 | Zhang et al. | Jun 2015 | A1 |
20150172075 | DeCusatis et al. | Jun 2015 | A1 |
20150180769 | Wang et al. | Jun 2015 | A1 |
20150237097 | Devireddy et al. | Aug 2015 | A1 |
Number | Date | Country |
---|---|---|
1154601 | Nov 2001 | EP |
2002-141905 | May 2002 | JP |
2003-069609 | Mar 2003 | JP |
2003-124976 | Apr 2003 | JP |
2003-318949 | Nov 2003 | JP |
WO 9506989 | Mar 1995 | WO |
WO 2004047377 | Jun 2004 | WO |
WO 2012126488 | Sep 2012 | WO |
WO 2013184846 | Dec 2013 | WO |
Entry |
---|
Portions of prosecution history of U.S. Appl. No. 14/231,652, Jul. 7, 2016, Pettit, Justin, et al. |
Portions of prosecution history U.S. Appl. No. 14/231,654, Mar. 14, 2016, Pettit, Justin, et al. |
Portions of prosecution history of U.S. Appl. No. 14/502,102, May 16, 2016, Lambeth, W. Andrew, et al. |
Anwer, Muhammad Bilal, et al., “Building a Fast, Virtualized Data Plane with Programmable Hardware,” Aug. 17, 2009, pp. 1-8, VISA'09, ACM Barcelona, Spain. |
Author Unknown, “Open vSwitch, An Open Virtual Switch,” Dec. 30, 2010, 2 pages. |
Author Unknown, “OpenFlow Switch Specification, Version 0.9.0 (Wire Protocol 0x98),” Jul. 20, 2009, pp. 1-36, Open Networking Foundation. |
Author Unknown, “OpenFlow Switch Specification, Version 1.0.0 (Wire Protocol 0x01),” Dec. 31, 2009, pp. 1-42, Open Networking Foundation. |
Author Unknown, “OpenFlow Switch Specification, Version 1.1.0 Implemented (Wire Protoco 0x02),” Feb. 28, 2011, pp. 1-56, Open Networking Foundation. |
Casado, Martin, et al. “Ethane: Taking Control of the Enterprise,” SIGCOMM'07, Aug. 27-31, 2007, pp. 1-12, ACM, Kyoto, Japan. |
Curtis, Andrew R., et al., “DevoFlow: Scaling Flow Management for High-Performance Networks,” Aug. 15, 2011, pp. 254-265, SIGCOMM, ACM. |
Das, Saurav, et al. “Simple Unified Control for Packet and Circuit Networks,” Month Unknown, 2009, pp. 147-148, IEEE. |
Das, Saurav, et al., “Unifying Packet and Circuit Switched Networks with OpenFlow,” Dec. 7, 2009, 10 pages. |
Fernandes, Natalia C., et al., “Virtual networks:isolation, performance, and trends,” Oct. 7, 2010, 17 pages, Institut Telecom and Springer-Verlag. |
Foster, Nate, et al., “Frenetic: A Network Programming Language,” ICFP '11, Sep. 19-21, 2011, 13 pages, Tokyo, Japan. |
Greenhalgh, Adam, et al., “Flow Processing and the Rise of Commodity Network Hardware,” ACM SIGCOMM Computer Communication Review, Apr. 2009, pp. 21-26, vol. 39, No. 2. |
Gude, Natasha, et al., “NOX: Towards an Operating System for Networks,” Jul. 2008, pp. 105-110, vol. 38, No. 3, ACM SIGCOMM Computer communication Review. |
Hinrichs, Timothy L., et al., “Practical Declarative Network Management,” WREN'09, Aug. 21, 2009, pp. 1-10, Barcelona, Spain. |
Koponen, Teemu, et al., “Network Virtualization in Multi-tenant Datacenters,” Aug. 2013, pp. 1-22, VMware, Inc., Palo Alto, California, USA. |
Koponen, Teemu, et al., “Onix: A Distributed Control Platform for Large-scale Production Networks,” In Proc. OSDI, Oct. 2010, pp. 1-14. |
Loo, Boon Thau, et al., “Declarative Routing: Extensible Routing with Declarative Queries,” In Proc. of SIGCOMM, Aug. 21-26, 2005, 12 pages, Philadelphia, PA, USA. |
Loo, Boon Thau, et al., “Implementing Declarative Overlays,” In Proc. of SOSP, Oct. 2005, 16 pages. Brighton, United Kingdom. |
Matsumoto, Nobutaka, et al., “LightFlow: Speeding Up GPU-based Flow Switching and Facilitating Maintenance of Flow Table,” 2012 IEEE 13th International Conference on High Performance Switching and Routing, Jun. 24, 2012, pp. 76-81, IEEE. |
McKeown, Nick, et al., “OpenFlow: Enabling Innovation in Campus Networks,” ACS SIGCOMM Computer communication Review, Apr. 2008, pp. 69-74, vol. 38, No. 2. |
Nygren, Anders, et al., OpenFlow Switch Specification, Version 1.3.4 (Protocol version 0x04), Mar. 27, 2014, pp. 1-84, Open Networking Foundation. (Part 1 of 2). |
Nygren, Anders, et al., OpenFlow Switch Specification, Version 1.3.4 (Protocol version 0x04), Mar. 27, 2014, pp. 85-171, Open Networking Foundation. (Part 2 of 2). |
Pettit, Justin, et al., “Virtual Switching in an Era of Advanced Edges,” Sep., 2010, 7 pages. |
Pfaff, B., et al., “The Open vSwitch Database Management Protocol,” draft-pfaff-ovsdb-proto-00, Aug. 20, 2012, pp. 1-34, Nicira, Inc., Palo Alto, California, USA. |
Pfaff, Ben, et al., “OpenFlow Switch Specification,” Sep. 6, 2012, 128 paegs, The Open Networking Foundation. |
Pfaff, Ben., et al., “Extending Networking into the Virtualization Layer,” Proc. of HotNets, Oct. 2009, pp. 1-6. |
Phaal, Peter, et al., “sFlow Version 5,” Jul. 2004, 46 pages, sFlow.org. |
Phan, Doantam, et al., “Visual Analysis of Network Flow Data with Timelines and Event Plots,” month unknown, 2007, pp. 1-16, VizSEC. |
Popa, Lucian, et al., “Building Extensible Networks with Rule-Based Forwarding,” In USENIX OSDI, Month Unknown, 2010, pp. 1-14. |
Sherwood, Rob, et al., “Carving Research Slices Out of Your Production Networks with OpenFlow,” ACM SIGCOMM Computer Communications Review, Jan. 2010, pp. 129-130, vol. 40, No. 1. |
Sherwood, Rob, et al., “FlowVisor: A Network Virtualization Layer,” Oct. 14, 2009, pp. 1-14, OPENFLOW-TR-2009-1. |
Tavakoli, Arsalan, et al., “Applying NOX to the Datacenter,” month unknown, 2009, 6 pages, Proceedings of HotNets. |
Yu, Minlan, et al., “Scalable Flow-Based Networking with DIFANE,” Aug. 2010, pp. 1-16, In Proceedings of SIGCOMM. |
Number | Date | Country | |
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20150163144 A1 | Jun 2015 | US |
Number | Date | Country | |
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61913899 | Dec 2013 | US |