Method and system of application-aware routing with crowdsourcing

Information

  • Patent Grant
  • 11444872
  • Patent Number
    11,444,872
  • Date Filed
    Sunday, December 1, 2019
    5 years ago
  • Date Issued
    Tuesday, September 13, 2022
    2 years ago
Abstract
In one aspect, a computerized method of an application routing service includes the step of using a deep-packet inspection (DPI) technique on a first network flow to identify an application. The method includes the step of storing an Internet-protocol (IP) address and a port number used by the application and an identity of the application in a database. The method includes the step of detecting a second network flow. The method includes the step of identifying the IP address and the port number of the application in the second network flow. The method includes the step of looking up the IP address and the port number in the database. The method includes the step of identifying the application based on the IP address and the port number.
Description
FIELD OF THE INVENTION

This application relates generally to computer networking, and more specifically to a system, article of manufacture and method of establishing a cloud-based multipath routing protocol.


DESCRIPTION OF THE RELATED ART

Deep-packet inspection (DPI) can be used to identify an application is inside a data flow. For example, a voice-call service (e.g. Skype®, etc.) application can be executed. Various routing decisions can be implemented based on the identity of the application. However, a DPI engine may not be able to identify the voice-call service application from the first packet. For example, this can be a TCP send to set up a connection. If a networking system wishes to make a routing decision (e.g. use a specific wide-area network (WAN) link for a Skype® call, etc.), it may not be able to do so on the first packet. The decision must wait until after the until the voice-call service protocol starts passing back and forth and the DPI engine identifies the voice-call service application signature. Accordingly, improvements to application-aware routing are desired.


BRIEF SUMMARY OF THE INVENTION

In one aspect, a computerized method of an application routing service includes the step of using a deep-packet inspection (DPI) technique on a first network flow to identify an application. The method includes the step of storing an Internet-protocol (IP) address and a port number used by the application and an identity of the application in a database. The method includes the step of detecting a second network flow. The method includes the step of identifying the IP address and the port number of the application in the second network flow. The method includes the step of looking up the IP address and the port number in the database. The method includes the step of identifying the application based on the IP address and the port number.


In another aspect, A computerized method useful for implementing an application routing service includes the step of extracting from a data packet of a network flow a layer three (3) information and a layer four (4) information. The method includes the step of querying a local application routing cache to obtain an application name based on the layer three (3) information and the layer four (4) information. The method includes the step of providing a routing decision based on the application name.


In yet another aspect, a computerized method useful for implementing an application routing service includes, with an edge device, using deep-packet inspection (DPI) to identify a network flow, wherein the network flow is identified with an internet protocol (IP) identity and a port number of the network flow. The edge device stores the IP identity and the port number of the network flow in a local application routing database. The edge device reports the IP identity and the port number to a specified Orchestrator. Another edge device requests the IP identity and the port number from the specified Orchestrator. The other edge device receives the IP identity and the port number from the specified Orchestrator. The other edge device identifies an application in another network flow using the IP identity and the port number.





BRIEF DESCRIPTION OF THE DRAWINGS


FIG. 1 illustrates an example self-healing network with redundant gateways, according to some embodiments.



FIG. 2 illustrates an example system that includes autonomous gateways, according to some embodiments



FIG. 3 illustrates an example of a system of an instant VPN, according to some embodiments.



FIG. 4 illustrates another example of a system of an instant VPN, according to some embodiments.



FIGS. 5 A-B illustrates an example of a system of a cloud multipath to an Internet endpoint, according to some embodiments.



FIG. 6 illustrates an example process of an application-aware routing, according to some embodiments.



FIG. 7 illustrates another example process of an application-aware routing, according to some embodiments.



FIG. 8 illustrates application-aware routing with crowdsourcing, according to some embodiments.



FIG. 9 depicts an exemplary computing system that can be configured to perform any one of the processes provided herein.





The Figures described above are a representative set, and are not exhaustive with respect to embodying the invention.


DESCRIPTION

Disclosed are a system, method, and article of manufacture for application-aware routing with crowdsourcing. The following description is presented to enable a person of ordinary skill in the art to make and use the various embodiments. Descriptions of specific devices, techniques, and applications are provided only as examples. Various modifications to the examples described herein can be readily apparent to those of ordinary skill in the art, and the general principles defined herein may be applied to other examples and applications without departing from the spirit and scope of the various embodiments.


Reference throughout this specification to “one embodiment,” “an embodiment,” ‘one example,’ or similar language means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the present invention. Thus, appearances of the phrases “in one embodiment,” “in an embodiment,” and similar language throughout this specification may, but do not necessarily, all refer to the same embodiment.


Furthermore, the described features, structures, or characteristics of the invention may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided, such as examples of programming, software modules, user selections, network transactions, database queries, database structures, hardware modules, hardware circuits, hardware chips, etc., to provide a thorough understanding of embodiments of the invention. One skilled in the relevant art can recognize, however, that the invention may be practiced without one or more of the specific details, or with other methods, components, materials, and so forth. In other instances, well-known structures, materials, or operations are not shown or described in detail to avoid obscuring aspects of the invention.


The schematic flow chart diagrams included herein are generally set forth as logical flow chart diagrams. As such, the depicted order and labeled steps are indicative of one embodiment of the presented method. Other steps and methods may be conceived that are equivalent in function, logic, or effect to one or more steps, or portions thereof, of the illustrated method. Additionally, the format and symbols employed are provided to explain the logical steps of the method and are understood not to limit the scope of the method. Although various arrow types and line types may be employed in the flow chart diagrams, and they are understood not to limit the scope of the corresponding method. Indeed, some arrows or other connectors may be used to indicate only the logical flow of the method. For instance, an arrow may indicate a waiting or monitoring period of unspecified duration between enumerated steps of the depicted method. Additionally, the order in which a particular method occurs may or may not strictly adhere to the order of the corresponding steps shown.


Definitions

Example definitions for some embodiments are now provided.


Cloud computing can involve deploying groups of remote servers and/or software networks that allow centralized data storage and online access to computer services or resources. These groups of remote servers and/or software networks can be a collection of remote computing services.


Cloud Edge (CE) can include a cloud multipath to an Internet endpoint.


Customer-premises equipment (CPE) can be any terminal and associated equipment located at a subscriber's premises and connected with a carrier's telecommunication channel at the demarcation point.


Edge device can be a device that provides an entry point into enterprise or service provider core networks. An edge device can be software running in a virtual machine (VM) located in a branch office and/or customer premises.


Flow can be a grouping of packets that match a five (5) tuple which is a combination of Source IP Address (SIP), Destination IP Address (DIP), L4 Source Port (SPORT) and L4 Destination Port (DPORT) and the L4 protocol (PROTO).


Forward error correction (FEC) (e.g. channel coding) can be a technique used for controlling errors in data transmission over unreliable or noisy communication channels.


Deep learning can be a type of machine learning based on a set of algorithms that attempt to model high-level abstractions in data by using model architectures, with complex structures or otherwise, composed of multiple non-linear transformations


Deep Packet Inspection (DPI) can be the ability to analyze the different layers of a packet on the network.


Gateway can be a node (e.g. a router) on a computer network that serves as an access point to another network.


Internet Protocol Security (IPsec) can be a protocol suite for securing Internet Protocol (IP) communications by authenticating and encrypting each IP packet of a communication session.


Multipath routing can be a routing technique of using multiple alternative paths through a network.


Multilink bundle can be a collection of simultaneously opened bandwidth channels that are coherently and logically controlled by preset commands.


Multiprotocol Label Switching (MPLS) can be a mechanism in telecommunications networks that directs data from one network node to the next based on short path labels rather than long network addresses, thus avoiding complex lookups in a routing table.


Orchestrator can include a software component that provides multi-tenant and role based centralized configuration management and visibility.


Quality of Service (QoS) can include the ability to define a guaranteed set of actions such as routing, resource constraints (e.g. bandwidth, latency etc.).


Session can be a semi-permanent interactive information interchange between two or more communicating devices.


Software as a service (SaaS) can be a software licensing and delivery model in which software is licensed on a subscription basis and is centrally hosted.


Tunneling protocol can allow a network user to access or provide a network service that the underlying network does not support or provide directly.


Virtual Desktop Infrastructure (VDI) is a desktop-oriented service that hosts user desktop environments on remote servers and/or blade PCs. Users access the desktops over a network using a remote display protocol.


Virtual private network (VPN) can extend a private network across a public network, such as the Internet. It can enable users to send and receive data across shared or public networks as if their computing devices were directly connected to the private network, and thus benefit from the functionality, security and management policies of the private network.


Voice over IP (VoIP) can a methodology and group of technologies for the delivery of voice communications and multimedia sessions over Internet Protocol (IP) networks, such as the Internet.


Additional example definitions are provided herein.


Scalable, Self-Healing Network Cloud Service for Branch Networking



FIG. 1 illustrates an example self-healing network 100 with redundant gateways, according to some embodiments. In network 100, data traffic can be routed to different gateways for different purposes. Multiple gateways can serve the same destination utilizing dynamic routing protocol. As services (e.g. SaaS 102) in the Internet (e.g. computer networks 104) may not centrally located. The combination of the Internet's wide distribution of services and/or changes in the transport quality across can lead to the use of different egress points to access different destinations. This is accomplished by deploying multiple gateways (e.g. gateways A-B 106-108) in stand-alone or redundant configurations.


An Orchestrator can inform each edge device (e.g. VCE 110) of a list of gateways it has been assigned. Additionally, routes and/or services can be assigned a subset of the gateway list that can be used for communication with a specific destination. The edge device can then perform a static determination by metrics assigned to each gateway. For example, each gateway can be assigned a metric based on geographic distance from the edge and/or a dynamic determination based on empirically measured loss, latency and/or jitter to the gateway across the Internet.


In the redundant configuration of FIG. 1, gateways A-B 106-108 can support dynamic routing protocols on the non-edge device side. This can ensure that the gateway chosen for traffic destined from the edge to the gateway is also advertised from the gateway upstream as the route with the lowest cost for return traffic. Various attributes of gateways are now discussed.



FIG. 2 illustrates an example system 200 that includes autonomous gateways, according to some embodiments. Gateway High Availability (HA) and horizontal scalability can be inherent as configuration is edge-driven and not configured on gateway 204. Edge tunnel initialization can configure, gateway 204. Edge devices 208 A-B can communicate QoS information to gateway 204 so they have information on how to treat network traffic. Implementing versioning in the flow header can ensures that gateway 204 have the correct QoS information. This is accomplished by creating flows with a version number of one (1) on the edge and incrementing this version every time a policy change is enacted on the edge. If the gateway receives a message with a higher than expected version number in the header, it will request the edge to send the updated policy information.


It is noted that each individual gateway is a self-contained autonomous entity. This is accomplished by driving configuration of gateway 204 through the edge devices 208 A-B rather than gateway 204 being directly configured by the Orchestrator. In the initial negotiation, edge devices 208 A-B can send an MP_INIT message (e.g. an initial MP tunnel establishment handshake message exchange between the edge device and the gateway device) which contains all the information needed to identify the edge device and serve as a secure and unsecure gateway for edge device traffic. This can include a logical identifier for the enterprise which is used for virtual routing and/or forwarding. The logical Identifier can also be used for subnets that are routable behind edge devices 208 A-B.


If edge devices 208 A-B is the first edge device belonging to the enterprise to connect to gateway 204, a new virtual routing and forwarding (VRF) table can be created for the enterprise. Edge devices 208 A-B's subnets can be inserted into the enterprise VRF. If edge devices 208 A-B are not the first from an enterprise to connect, the enterprise logical identifier can be used to index into the existing VRF and edge devices 208 A-B's subnets can be added to the existing table.


In another example, when a new flow is created on an edge device, the parameters used to perform QoS and/or routing on the flow can be transmitted along with the first packet to any of the gateway 204 that are handling the flow. In this manner gateway 204 can be inherently highly available. If the gateway service is removed and replaced with a new gateway service instance, edge devices 208 A-B can send a new MP_INIT which can recreate the VRF and then continue sending data traffic uninterrupted through the gateway.


By this same token, gateway 204 can be highly available because the edge can switch between gateways without interrupting customer traffic. For example, when an Orchestrator inserts an additional gateway in a gateway list that can be assigned an edge device. The edge device can then connect and begin using the gateway seamlessly without any requirement for Orchestrator to gateway communication. This removes the need for the Orchestrator to synchronize configuration changes on the edge device and the gateway as the edge device is used as the intermediary.


In another example, a gateway need not be a single gateway instance but the Internet Protocol (IP) address may be the external facing IP address of a gateway load balancer. The gateway load balancer can start and stop individual gateway instances. If the gateway load balancers detect that an instance is near its CPU and/or throughput capacity, it can shift traffic to an alternate gateway transparently and/or create a new gateway and begin steering connections to it. When gateway reboots, upgrades or maintenance are required, the gateway load balancer can steer traffic away from those instances that require maintenance to make these operations transparent to the end user.



FIG. 3 illustrates an example of a system 300 of an instant VPN, according to some embodiments. The edge device (e.g. edge devices 306-310) and gateway 304 can automatically negotiate IPsec tunnels alongside their unsecure Velocloud Multipath Protocol (VCMP) tunnels in preparation for the transmission of secure traffic. This can be performed irrespective of whether or not a VPN has been enabled on the device. In this manner, the network can be prepared to transmit secure traffic at any time. Leveraging this, an “Instant VPN” can be delivered by toggling VPN on or off on Orchestrator 302. Each edge device has a list of local subnets that are sent to gateway 304 during MP_INIT. Each subnet is can include an indication of whether or not it is reachable over VPN. When VPN is enabled on Orchestrator 302, each edge device can be informed that its subnets are reachable over VPN and each edge device can update its gateways with this information. When VPN is disabled on Orchestrator 302, each edge device can be informed that its subnets are not reachable over VPN. The edge device can update gateway 304 accordingly.


Between each edge device and its associated gateways can be a routing protocol. The routing protocol can relay state information to peers that are one hop away. For example, edge device A 306 can have a subnet A. Edge device B 308 can have subnet B. When the user enables VPN on Orchestrator 302, edge device A 306 and edge device B 308 can inform the gateways that their local subnets A and B are reachable over VPN. The gateway(s) can then inform peers in the enterprise VRF. In this way, a message can be sent to edge device B 308 instructing it that subnet A is now reachable through it. A message can also be sent to edge device A 306 instructing it that subnet B is now reachable through it. When an edge device loses connectivity to a gateway, gateway 304 can relay to peers in the VRF that the subnet is no longer reachable and the edge device updates the routing/forwarding table to mark all routes via that unreachable gateway. In this way, gateways can be added or removed, and/or routes added and removed, without restarts and/or loss of connectivity assuming at least one gateway is connected at all times.


In some examples, “Always on” IPsec tunnels can be provided. Enable/disable VPN operations can include the insertion and/or removal of routes for the appropriate VPN zone. VRF can include enterprise logical identifier on gateway ensuring multi-tenancy.



FIG. 4 illustrates another example of a system 400 of an instant VPN, according to some embodiments. A special edge device called a Datacenter Edge (DCE) 404 can be deployed as customer premise equipment. DCE 404 can be deployed in an enterprise data center, along with Orchestrator 402. DCE 404 can subsume some of the functionality of the gateway, including this route protocol management. A typical use case for this deployment can be in a pure MPLS network 406 in which there are no public Internet links and thus no public Internet gateways. In one example, route propagation can occur the same as described supra except that the VRF and routing protocol messages are managed by DCE 404. MPLS network 406 can connect with edge devices 408-412.



FIGS. 5 A-B illustrate an example of system 500 of a cloud-based multipath routing technique to an Internet endpoint (e.g. a cloud edge 516), according to some embodiments. Edge device 506 and gateway 518 can implement a multipath solution to deliver a reliable connection across the public Internet for outbound connections (e.g. between server 508 and client 502) initiated from the edge (e.g. edge device 506) through gateway 518, as well as for their return traffic. This can include multilink bundle(s). An alternate use case can include when the network traffic is initiated from an outside source. For example, the network traffic can be initiated from the Internet to server 508 in a branch office behind edge device 506.


In an example deployment, this can be Implemented by enabling a set of inbound firewall rules that allow network traffic in one or more of the wide area network (WAN) links attached to the edge device. Such an inbound connection can use a single link. For example, a session established on link A 510 may fail if link A 510 fails, and similarly for link B 512. Therefore, there is a desire to be able to support inbound connections reliably without compromising the security of the deployment.


This can be achieved by cloud edge (CE) device 516. CE 516 can be implemented in a cloud-computing environment. CE 516 can join the same VRF as that of edge device 506.


Edge device 506 can be used to accesses various resources (e.g. server 508) to be reliably accessed. In one example, edge device 506 can be set to deny inbound traffic by default. Edge device 506 can allow an administrator to specify various sources and destinations of traffic that are permitted (e.g. client 502).


For example, a rule could be created that enable the public IP address of a client 502 to reach server 508 via a public IP address 514. Public IP address 514 can be assigned to the “LAN” side of CE 516. The administrator can then connect to public IP address 514 in the cloud rather than the IP address of one of the links at the site directly. Client 502 can then securely connect over a VPN to server 508 inside the network. CE 516 can be located anywhere in the (e.g. public) Internet 504. In one example, CE 516 can be located in any of a public Cloud Service Providers (CSPs). For example, CE 516 can be implemented in a proprietary cloud-computing platform such as, inter alia, Amazon EC2® and the like. It is noted that resources from Server 508 may arrive via Link A 510 and/or Link B 512. Accordingly, this traffic can continue even if one of the links completely fails. In this way, system 500 can provide resiliency for the network as Link A 510 and/or Link B 512 can be used simultaneously and service can continue even if one of the links falls.


An intelligent edge device (e.g. edge device 506 of FIG. 5) can provide intelligent QoS. For example, applications may respond differently to key network parameters like latency, jitter, bandwidth, packet loss and processing capabilities such as available CPU cycles. For example, a VoIP application may use low bandwidth and may be sensitive to jitter, packet loss. The VoIP application may also consume a large number of CPU cycles despite the low throughput (e.g. because of smaller packet sizes). In contrast, VDI may use high bandwidth and low latency but may not very sensitive to jitter. Accordingly, a network stack can implement a suite of link optimization and remediation technologies to achieve the dual goal of optimal network resource utilization and remediating adverse network events, such as, inter alia: FEC to compensate for packet loss; jitter buffering to counter jitter; and per-packet load balancing to aggregate bandwidth usage and ensure the lowest latency path.


Smart QoS can map application flow into a traffic class and priority queue. A combination of the traffic class and priority queue can then decide the optimal routing, load balancing and remediation to be used for that flow given the prevailing network conditions at that point of time. The network stack can use the following innovations to adapt to dynamic network conditions:


In an intelligent default, the distributed management plane (e.g. an Orchestrator) sets up the edge device with a set of default QoS settings for each application. Each application can then be tagged with an SLA. The SLA can indicate a hint to the edge device for the prioritization and/or sensitivity for that particular application.


In an intelligent pre-emption, a multi-tenant, geo-diverse, network transport agnostic overlay network can be implemented. This can create a situation where the network can pre-empt adverse and/or localized network events by statistical and heuristics based analysis of the network monitoring data that is collected at the Orchestrator. This can remediate certain network conditions that are not addressed by adaptive QoS (e.g. tail drops which result in large number of packets dropped indiscriminately in the core of a service provider network) due to time taken to adapt and the fact that such a loss cannot be really compensated. In a geo-localized region, in the event of constant tail drops for a network service provider, the service can proactively turn on aggressive FEC (e.g. ‘always-on FEC’) for sensitive applications in both the specific geo-location. In one example, a slightly larger geography for sites that are using the same provider can be used in lieu of the specific geo-location. The ‘always-on FEC’ can also be configured at the Orchestrator in order to pre-empt network errors and react faster to network errors.


Adaptive QoS can be implemented by monitoring and/or instrumenting network paths. For example, adaptive QoS can be implemented to remediate a network condition that may not conform to the configured SLA for that application. To offset the overheads as a result of the continuous monitoring, the QoE (e.g. user responsiveness) can be periodically or constantly computed to reduce/augment the network monitoring.


Smart QoS can utilize deep learning methods. In addition to responding to dynamic network conditions, the smart QoS can work in tandem with application performance monitoring (APM) to adjust traffic priority based on L7 data. When the DPI engine fails to identify the application, the network stack can utilize statistical parameters (e.g. packet arrival rate, throughput) and heuristics (e.g. User Datagram Protocol (UDP) can be used by real-time applications) to identify the right set of technologies to provide the best performance.


A slow learning with crowdsourcing example is now discussed. Slow learning (e.g. to implement application-aware routing) with crowdsourcing methods can include generating a prepopulated list of well-known applications augmented by mid-flow detected data from a DPI engine. This can enable determination of an application with a first-received packet. Prepopulated data is automatically validated by a DPI engine. Any changes can be fed back locally as well as communicated to the Orchestrator. Some or all data can be shared to other edges/enterprises via the Orchestrator. In one example, L3, L4 network information can be used to create a composite application-routing database. As used herein, L3 network information can include network layer (layer 3) information. As used herein, L4 network information can include transport layer (layer 4) information. The application-routing database (e.g. a local application routing cache, etc.) can be populated by three different types of learning/sources. The first source of information built into the database can include a pre-populated map of DIP/DPORT (Destination Internet Protocol Address/Destination Port Number) to application types (e.g. termed fast learning). A second source of information can include a map of DIP/DPORT to applications that is learned from ‘mid-flow’ application detection by the DPI engine (e.g. slow learning). The third source of information can also include a map of DIP/DPORT to application names. This can include crowd-sourced (e.g. DIP/DPORT to application name mapping) information that is anonymized and aggregated at the Orchestrator. This mapping can then be shared across different enterprises (e.g. crowd-sourced learning).


Various methods of populating, updating and recovering the application-routing database are now provided. The application-routing database can be pre-populated with the set of known applications that can be identified by the DIP/DPORT and/or packaged as a part of the CPE. Alternatively, it can be downloaded from the Orchestrator. Additionally, an IT Administrator may enter customized DIP/DPORT to application mappings which can be added to the application routing database in the edge device via the Orchestrator. This method can be a component of fast learning.


The application-routing database can also be updated by ‘mid-flow’ DPI detection data as a result of slow learning methods on the edge device. In addition to this, the fast learning data and slow learning updates from different enterprises can be anonymized and/or aggregated at the Orchestrator. It can be sent down to all the edge device(s) under the management of the Orchestrator. These updates can be part of the crowd-sourced learning methods.


An example application-routing database recovery method is now provided. When an edge device first communicates with the Orchestrator, it can receive the data for pre-population of the application-routing database. This information can include any updates. Updates from slow learning and/or crowd-sourced learning can be synchronized to shared memory areas in the edge device. The updates can be recovered from service outages.



FIG. 6 illustrates an example process 600 of an application-aware routing, according to some embodiments. In step 602, the layer 3 (L3) and/or layer 4 (L4) information is extracted and matched against the application routing database (e.g. database in FIG. 6). In step 604, if this flow does not find a match in the database, then process 600 moves to step 608. If ‘yes’, then process 600 moves to step 606. In step 606, the matched application is used to look-up and apply the application specific routing policies. In step 608, on failure to find a match in the database, the flow is passed over to the DPI engine. The classification from the DPI engine is used to populate the database for future flows. The current flow may obtain some default routing policies as well. In this way, when the same application flow is encountered again, it can find a successful match in database. The application specific routing policy can then be applied for that application flow. A worst-case guarantee of application routing from the second flow can be provided in some examples. It is noted that in the seven-layer OSI model of computer networking, the network layer is L3 and the transport layer is L4.



FIG. 7 illustrates another example process 700 of an application-aware routing, according to some embodiments. For example, in an alternative step 608, the L3, L4 information can be communicated to an application routing lookup service (e.g. can be a local service synchronized with an aggregated crowd source updated remote service running in the Orchestrator like DNS). In one embodiment, an application-routing database can reside in the Orchestrator. At set intervals (e.g. every thirty (30) seconds, etc.) the edge-device can request the current state of the application-routing database from the Orchestrator and update the local application routing database. Optionally, the cached entries can be expired using a TT (Time-to-Live) value.


In step 702, at a specified period, process 700 can request the current state of the application-routing database from the orchestrator and update the local application routing database. In step 704, L3, L4 information is extracted from a packet and a query is made to the local application routing database to identify application name. In step 706, it can be determined whether step 704 successful? If ‘no’, then process 700 use a default routing policy in step 708. If ‘yes’, then the application name that was matched is used to make a routing decision in step 710. In step 712, process 700 can continue to test the flow with the DPI engine for the veracity of the application type. In case of a mismatch send a message to the orchestrator informing the mismatch. the orchestrator then decides whether to change the corresponding entry based similar updates from other crowd-sourced participants. In step 714, the flow is passed over to the dpi engine and the classification from the dpi engine is used to populate the local application routing cache and send a message to the orchestrator to add an entry.



FIG. 8 illustrates application-aware routing with crowdsourcing according to some embodiments. In step 802, process 800 can use DPI to identify a network flow. In step 804, process 800 store internet protocol (IP) identity and port number of the network flow. In step 806, process 800 report learned IP identity and port number to an applicable Orchestrator. In step 808, process 800 another edge requests the updated IP identity and port number and receives it. In step 810, process 800 the IP identity and port number is received on the other edge and matches the application routing database now even though it has never seen that packet locally or implemented DPI.


Additional Exemplary Computer Architecture and Systems



FIG. 9 depicts an exemplary computing system 900 that can be configured to perform any one of the processes provided herein. In this context, computing system 900 may include, for example, a processor, memory, storage, and I/O devices (e.g., monitor, keyboard, disk drive, Internet connection, etc.). However, computing system 900 may include circuitry or other specialized hardware for carrying out some or all aspects of the processes. In some operational settings, computing system 900 may be configured as a system that includes one or more units, each of which is configured to carry out some aspects of the processes either in software, hardware, or some combination thereof.



FIG. 9 depicts computing system 900 with a number of components that may be used to perform any of the processes described herein. The main system 902 includes a motherboard 904 having an I/O section 906, one or more central processing units (CPU) 908, and a memory section 910, which may have a flash memory card 912 related to it. The I/O section 906 can be connected to a display 914, a keyboard and/or other user input (not shown), a disk storage unit 916, and a media drive unit 918. The media drive unit 918 can read/write a computer-readable medium 920, which can contain programs 922 and/or data. Computing system 900 can include a web browser. Moreover, it is noted that computing system 900 can be configured to include additional systems in order to fulfill various functionalities. Computing system 900 can communicate with other computing devices based on various computer communication protocols such a Wi-Fi, Bluetooth® (and/or other standards for exchanging data over short distances includes those using short-wavelength radio transmissions), USB, Ethernet, cellular, an ultrasonic local area communication protocol, etc.


CONCLUSION

Although the present embodiments have been described with reference to specific example embodiments, various modifications and changes can be made to these embodiments without departing from the broader spirit and scope of the various embodiments. For example, the various devices, modules, etc. described herein can be enabled and operated using hardware circuitry, firmware, software or any combination of hardware, firmware, and software (e.g., embodied in a machine-readable medium).


In addition, it can be appreciated that the various operations, processes, and methods disclosed herein can be embodied in a machine-readable medium and/or a machine accessible medium compatible with a data processing system (e.g., a computer system), and can be performed in any order (e.g., including using means for achieving the various operations). Accordingly, the specification and drawings are to be regarded in an illustrative rather than a restrictive sense. In some embodiments, the machine-readable medium can be a non-transitory form of machine-readable medium.

Claims
  • 1. A method for implementing a virtual private network (VPN) for an enterprise, the method comprising: deploying a gateway in at least one public cloud to connect a plurality of premises of an enterprise;at each of at least two premises of the enterprise, deploying an edge device that automatically connects to the gateway to establish the VPN for the enterprise;from each deployed edge device, providing to the gateway a set of local subnets of the edge device that is reachable over the VPN; andfrom the gateway, distributing to each particular deployed edge device each set of local subnets provided by each other deployed edge device for the particular deployed edge device to use to forward packets to each other deployed edge device.
  • 2. The method of claim 1 further comprising before the VPN is established between the gateway and each deployed edge device, negotiating a secure connection link between the gateway and each deployed edge device in preparation for transmission of secure traffic between the gateway and edge device once the VPN is established.
  • 3. The method of claim 2 further comprising establishing a VPN between the gateway and a particular edge device after the particular edge device receives a message from an orchestrator that the VPN should be established.
  • 4. The method of claim 2 further comprising at each edge device, establishing an unsecure tunnel with the gateway before negotiating the secure connection link between the edge device and the gateway,said establishing comprising sending, as part of a handshake message exchange, information needed to identify the edge device and a logical identifier for the enterprise.
  • 5. The method of claim 4, wherein as part of the handshake message exchange between the gateway and the edge device, the edge device provides to the gateway the set of local subnets of the edge device.
  • 6. The method of claim 4, wherein the edge device automatically contacts the gateway and provides data as part of the handshake message exchange because each individual gateway is a self-contained autonomous entity that can be configured through the edge devices rather than being configured by an external orchestrator.
  • 7. The method of claim 4 further comprising creating, at the gateway, a new virtual routing and forwarding (VRF) table for the enterprise after being contacted by an initial edge device of the entity.
  • 8. The method of claim 7 further comprising inserting, at the gateway, each edge devices set of reachable local subnets in the VRF table of the edge device's enterprise.
  • 9. The method of claim 1, wherein providing the set of local subnets comprises: receiving, at each deployed particular edge device, a message from an orchestrator that the VPN has been enabled;after receiving the message, sending the gateway a message to indicate that the set of local subnets of the particular edge device are reachable over the VPN.
  • 10. The method of claim 2, wherein providing the set of local subnets further comprises in preparation for establishing the VPN, providing the set of local subnets before receiving the message from the orchestrator that the VPN has been enabled.
  • 11. The method of claim 1 further comprising implementing a routing protocol between each edge device and the gateway.
  • 12. The method of claim 11, wherein the routing protocol relays state information of each particular edge device that connects to the gateway to each other edge device that connects to the gateway and thus is one hop away.
  • 13. The method of claim 12 further comprising: defining a virtual routing and forwarding (VRF) table for the enterprise; andidentifying in the VRF table each edge device that is one hop away from a particular edge device.
  • 14. The method of claim 12, wherein the state information includes the local subnets reachable over the VPN.
  • 15. A non-transitory machine readable medium storing a program implementing a virtual private network (VPN) for an enterprise, the program for execution by at least one processing unit, the program comprising sets of instructions for: configuring a gateway in at least one public cloud to connect a plurality of premises of an enterprise;configuring, at each of at least two premises of the enterprise, an edge device that automatically connects to the gateway to establish the VPN for the enterprise;configuring each deployed edge device to provide to the gateway a set of local subnets of the edge device that is reachable over the VPN; andconfiguring the gateway to distribute to each particular deployed edge device each set of local subnets provided by each other deployed edge device for the particular deployed edge device to use to forward packets to each other deployed edge device.
  • 16. The non-transitory machine readable medium of claim 15, wherein the program further comprises a set of instructions for configuring each deployed edge device to negotiate a secure connection link with the gateway before the VPN is established between the gateway and the edge device, in order to establish transmission of secure traffic between the gateway and edge device.
  • 17. The non-transitory machine readable medium of claim 16, wherein the program further comprising sets of instructions for configuring each edge device to establish an unsecure tunnel with the gateway before negotiating the secure connection link between the edge device and the gateway, by sending, as part of a handshake message exchange, information needed to identify the edge device and a logical identifier for the enterprise.
  • 18. The non-transitory machine readable medium of claim 17, wherein as part of the handshake message exchange between the gateway and the edge device, the edge device provides to the gateway the set of local subnets of the edge device.
  • 19. The non-transitory machine readable medium of claim 17, wherein the edge device automatically contacts the gateway and provides data as part of the handshake message exchange because each individual gateway is a self-contained autonomous entity that can be configured through the edge devices rather than being configured by an external orchestrator.
  • 20. The non-transitory machine readable medium of claim 17, wherein the program further comprises a set of instructions for creating, at the gateway, a new virtual routing and forwarding (VRF) table for the enterprise after being contacted by an initial edge device of the entity.
  • 21. The non-transitory machine readable medium of claim 20, wherein the program further comprises a set of instructions for configuring the gateway to insert each edge devices set of reachable local subnets in the VRF table of the edge device's enterprise.
  • 22. The non-transitory machine readable medium of claim 15, wherein each deployed particular edge device receives a message from an orchestrator that the VPN has been enabled, and after receiving the message, sends the gateway a message to indicate that the set of local subnets of the particular edge device are reachable over the VPN.
CROSS REFERENCE TO RELATED CLAIM OF BENEFIT TO PRIOR APPLICATIONS

This application is a continuation of U.S. patent application Ser. No. 15/407,767, filed Jan. 17, 2017, now published as U.S. Patent Publication 2017/0126564. U.S. patent application Ser. No. 15/407,767 claims priority and is a continuation-in-part of U.S. patent application Ser. No. 15/097,282, filed on Apr. 12, 2016, now issued as U.S. Pat. No. 10,135,789. U.S. patent application Ser. No. 15/097,282 claims priority from U.S. Provisional Patent Application No. 62/146,786, filed Apr. 13, 2015. U.S. patent application Ser. No. 15/407,767 is hereby incorporated by reference in its entirety.

US Referenced Citations (755)
Number Name Date Kind
5652751 Sharony Jul 1997 A
5909553 Campbell et al. Jun 1999 A
6154465 Pickett Nov 2000 A
6157648 Voit et al. Dec 2000 A
6201810 Masuda et al. Mar 2001 B1
6363378 Conklin et al. Mar 2002 B1
6445682 Weitz Sep 2002 B1
6744775 Beshai et al. Jun 2004 B1
6976087 Westfall et al. Dec 2005 B1
7003481 Banka et al. Feb 2006 B2
7280476 Anderson Oct 2007 B2
7313629 Nucci et al. Dec 2007 B1
7320017 Kurapati et al. Jan 2008 B1
7373660 Guichard May 2008 B1
7581022 Griffin et al. Aug 2009 B1
7680925 Sathyanarayana et al. Mar 2010 B2
7681236 Tamura et al. Mar 2010 B2
7962458 Holenstein et al. Jun 2011 B2
8094575 Vadlakonda et al. Jan 2012 B1
8094659 Arad Jan 2012 B1
8111692 Ray Feb 2012 B2
8141156 Mao et al. Mar 2012 B1
8224971 Miller et al. Jul 2012 B1
8228928 Parandekar et al. Jul 2012 B2
8243589 Trost et al. Aug 2012 B1
8259566 Chen et al. Sep 2012 B2
8274891 Averi et al. Sep 2012 B2
8301749 Finklestein et al. Oct 2012 B1
8385227 Downey Feb 2013 B1
8566452 Goodwin et al. Oct 2013 B1
8630291 Shaffer et al. Jan 2014 B2
8661295 Khanna et al. Feb 2014 B1
8724456 Hong et al. May 2014 B1
8724503 Johnsson et al. May 2014 B2
8745177 Kazerani et al. Jun 2014 B1
8799504 Capone et al. Aug 2014 B2
8804745 Sinn Aug 2014 B1
8806482 Nagargadde et al. Aug 2014 B1
8855071 Sankaran et al. Oct 2014 B1
8856339 Mestery et al. Oct 2014 B2
8964548 Keralapura et al. Feb 2015 B1
8989199 Sella et al. Mar 2015 B1
9009217 Nagargadde et al. Apr 2015 B1
9055000 Ghosh et al. Jun 2015 B1
9060025 Xu Jun 2015 B2
9071607 Twitchell, Jr. Jun 2015 B2
9075771 Gawali et al. Jul 2015 B1
9135037 Petrescu-Prahova et al. Sep 2015 B1
9137334 Zhou Sep 2015 B2
9154327 Marino et al. Oct 2015 B1
9203764 Shirazipour et al. Dec 2015 B2
9306949 Richard et al. Apr 2016 B1
9323561 Ayala et al. Apr 2016 B2
9336040 Dong et al. May 2016 B2
9354983 Yenamandra et al. May 2016 B1
9356943 Lopilato et al. May 2016 B1
9379981 Zhou et al. Jun 2016 B1
9413724 Xu Aug 2016 B2
9419878 Hsiao et al. Aug 2016 B2
9432245 Sorenson et al. Aug 2016 B1
9438566 Zhang et al. Sep 2016 B2
9450817 Bahadur et al. Sep 2016 B1
9450852 Chen et al. Sep 2016 B1
9462010 Stevenson Oct 2016 B1
9467478 Khan et al. Oct 2016 B1
9485163 Fries et al. Nov 2016 B1
9521067 Michael et al. Dec 2016 B2
9525564 Lee Dec 2016 B2
9559951 Sajassi Jan 2017 B1
9563423 Pittman Feb 2017 B1
9602389 Maveli et al. Mar 2017 B1
9608917 Anderson et al. Mar 2017 B1
9608962 Chang Mar 2017 B1
9621460 Mehta et al. Apr 2017 B2
9641551 Kariyanahalli May 2017 B1
9648547 Hart et al. May 2017 B1
9665432 Kruse et al. May 2017 B2
9686127 Ramachandran et al. Jun 2017 B2
9715401 Devine et al. Jul 2017 B2
9717021 Hughes et al. Jul 2017 B2
9722815 Mukundan et al. Aug 2017 B2
9747249 Cherian et al. Aug 2017 B2
9755965 Yadav et al. Sep 2017 B1
9787559 Schroeder Oct 2017 B1
9807004 Koley et al. Oct 2017 B2
9819540 Bahadur et al. Nov 2017 B1
9819565 Djukic et al. Nov 2017 B2
9825822 Holland Nov 2017 B1
9825911 Brandwine Nov 2017 B1
9825992 Xu Nov 2017 B2
9832128 Ashner et al. Nov 2017 B1
9832205 Santhi et al. Nov 2017 B2
9875355 Williams Jan 2018 B1
9906401 Rao Feb 2018 B1
9930011 Clemons, Jr. et al. Mar 2018 B1
9935829 Miller et al. Apr 2018 B1
9942787 Tillotson Apr 2018 B1
10038601 Becker et al. Jul 2018 B1
10057183 Salle et al. Aug 2018 B2
10057294 Xu Aug 2018 B2
10135789 Mayya et al. Nov 2018 B2
10142226 Wu et al. Nov 2018 B1
10178032 Freitas Jan 2019 B1
10187289 Chen et al. Jan 2019 B1
10200264 Menon et al. Feb 2019 B2
10229017 Zou et al. Mar 2019 B1
10237123 Dubey et al. Mar 2019 B2
10250498 Bales et al. Apr 2019 B1
10263832 Ghosh Apr 2019 B1
10320664 Nainar et al. Jun 2019 B2
10320691 Matthews et al. Jun 2019 B1
10326830 Singh Jun 2019 B1
10348767 Lee et al. Jul 2019 B1
10355989 Panchai et al. Jul 2019 B1
10425382 Mayya et al. Sep 2019 B2
10454708 Mibu Oct 2019 B2
10454714 Mayya et al. Oct 2019 B2
10461993 Turabi et al. Oct 2019 B2
10498652 Mayya et al. Dec 2019 B2
10511546 Singarayan et al. Dec 2019 B2
10523539 Mayya et al. Dec 2019 B2
10550093 Ojima et al. Feb 2020 B2
10554538 Spohn et al. Feb 2020 B2
10560431 Chen et al. Feb 2020 B1
10565464 Han et al. Feb 2020 B2
10567519 Mukhopadhyaya et al. Feb 2020 B1
10574528 Mayya et al. Feb 2020 B2
10594516 Cidon et al. Mar 2020 B2
10594659 El-Moussa et al. Mar 2020 B2
10608844 Cidon et al. Mar 2020 B2
10637889 Ermagan et al. Apr 2020 B2
10666460 Cidon et al. May 2020 B2
10686625 Cidon et al. Jun 2020 B2
10693739 Naseri et al. Jun 2020 B1
10749711 Mukundan et al. Aug 2020 B2
10778466 Cidon et al. Sep 2020 B2
10778528 Mayya et al. Sep 2020 B2
10805114 Cidon et al. Oct 2020 B2
10805272 Mayya et al. Oct 2020 B2
10819564 Turabi et al. Oct 2020 B2
10826775 Moreno et al. Nov 2020 B1
10841131 Cidon et al. Nov 2020 B2
10911374 Kumar et al. Feb 2021 B1
10938693 Mayya et al. Mar 2021 B2
10951529 Duan et al. Mar 2021 B2
10958479 Cidon et al. Mar 2021 B2
10959098 Cidon et al. Mar 2021 B2
10992558 Silva et al. Apr 2021 B1
10992568 Michael et al. Apr 2021 B2
10999100 Cidon et al. May 2021 B2
10999137 Cidon et al. May 2021 B2
10999165 Cidon et al. May 2021 B2
11005684 Cidon May 2021 B2
11018995 Cidon et al. May 2021 B2
11044190 Ramaswamy et al. Jun 2021 B2
11050588 Mayya et al. Jun 2021 B2
11050644 Hegde et al. Jun 2021 B2
11071005 Shen et al. Jul 2021 B2
11089111 Markuze et al. Aug 2021 B2
11095612 Oswal et al. Aug 2021 B1
11102032 Cidon et al. Aug 2021 B2
11108851 Kurmala et al. Aug 2021 B1
11115347 Gupta et al. Sep 2021 B2
11115426 Pazhyannur et al. Sep 2021 B1
11115480 Markuze et al. Sep 2021 B2
11121962 Michael et al. Sep 2021 B2
11121985 Gidon et al. Sep 2021 B2
11128492 Sethi et al. Sep 2021 B2
11153230 Cidon et al. Oct 2021 B2
11171885 Cidon et al. Nov 2021 B2
11212140 Mukundan et al. Dec 2021 B2
11212238 Cidon et al. Dec 2021 B2
11223514 Mayya et al. Jan 2022 B2
11245641 Ramaswamy et al. Feb 2022 B2
11252079 Michael et al. Feb 2022 B2
11252105 Cidon et al. Feb 2022 B2
11252106 Cidon et al. Feb 2022 B2
11258728 Cidon et al. Feb 2022 B2
20020085488 Kobayashi Jul 2002 A1
20020087716 Mustafa Jul 2002 A1
20020198840 Banka et al. Dec 2002 A1
20030061269 Hathaway et al. Mar 2003 A1
20030088697 Matsuhira May 2003 A1
20030112766 Riedel et al. Jun 2003 A1
20030112808 Solomon Jun 2003 A1
20030126468 Markham Jul 2003 A1
20030161313 Jinmei et al. Aug 2003 A1
20030189919 Gupta et al. Oct 2003 A1
20030202506 Perkins et al. Oct 2003 A1
20030219030 Gubbi Nov 2003 A1
20040059831 Chu et al. Mar 2004 A1
20040068668 Lor et al. Apr 2004 A1
20040165601 Liu et al. Aug 2004 A1
20040224771 Chen et al. Nov 2004 A1
20050078690 DeLangis Apr 2005 A1
20050154790 Nagata et al. Jul 2005 A1
20050172161 Cruz et al. Aug 2005 A1
20050195754 Nosella Sep 2005 A1
20050265255 Kodialam et al. Dec 2005 A1
20060002291 Alicherry et al. Jan 2006 A1
20060114838 Mandavilli et al. Jun 2006 A1
20060171365 Borella Aug 2006 A1
20060182034 Klinker et al. Aug 2006 A1
20060182035 Vasseur Aug 2006 A1
20060193247 Naseh et al. Aug 2006 A1
20060193252 Naseh et al. Aug 2006 A1
20070064604 Chen et al. Mar 2007 A1
20070064702 Bates et al. Mar 2007 A1
20070083727 Johnston et al. Apr 2007 A1
20070091794 Filsfils et al. Apr 2007 A1
20070103548 Carter May 2007 A1
20070115812 Hughes May 2007 A1
20070121486 Guichard et al. May 2007 A1
20070130325 Lesser Jun 2007 A1
20070162639 Chu et al. Jul 2007 A1
20070177511 Das et al. Aug 2007 A1
20070237081 Kodialam et al. Oct 2007 A1
20070260746 Mirtorabi et al. Nov 2007 A1
20070268882 Breslau et al. Nov 2007 A1
20080002670 Bugenhagen et al. Jan 2008 A1
20080049621 McGuire et al. Feb 2008 A1
20080055241 Goldenberg et al. Mar 2008 A1
20080080509 Khanna et al. Apr 2008 A1
20080095187 Jung et al. Apr 2008 A1
20080117930 Chakareski et al. May 2008 A1
20080144532 Chamarajanagar et al. Jun 2008 A1
20080181116 Kavanaugh et al. Jul 2008 A1
20080219276 Shah Sep 2008 A1
20080240121 Xiong et al. Oct 2008 A1
20090013210 McIntosh et al. Jan 2009 A1
20090125617 Klessig et al. May 2009 A1
20090141642 Sun Jun 2009 A1
20090154463 Hines et al. Jun 2009 A1
20090247204 Sennett et al. Oct 2009 A1
20090274045 Meier et al. Nov 2009 A1
20090276657 Wetmore et al. Nov 2009 A1
20090303880 Maltz et al. Dec 2009 A1
20100008361 Guichard et al. Jan 2010 A1
20100017802 Lojewski Jan 2010 A1
20100046532 Okita Feb 2010 A1
20100061379 Parandekar et al. Mar 2010 A1
20100080129 Strahan et al. Apr 2010 A1
20100088440 Banks et al. Apr 2010 A1
20100091823 Retana et al. Apr 2010 A1
20100107162 Edwards et al. Apr 2010 A1
20100118727 Draves et al. May 2010 A1
20100118886 Saavedra May 2010 A1
20100165985 Sharma et al. Jul 2010 A1
20100191884 Holenstein et al. Jul 2010 A1
20100223621 Joshi et al. Sep 2010 A1
20100226246 Proulx Sep 2010 A1
20100290422 Haigh et al. Nov 2010 A1
20100309841 Conte Dec 2010 A1
20100309912 Mehta et al. Dec 2010 A1
20100322255 Hao et al. Dec 2010 A1
20100332657 Elyashev et al. Dec 2010 A1
20110007752 Silva et al. Jan 2011 A1
20110032939 Nozaki et al. Feb 2011 A1
20110040814 Higgins Feb 2011 A1
20110075674 Li et al. Mar 2011 A1
20110107139 Middlecamp et al. May 2011 A1
20110110370 Moreno et al. May 2011 A1
20110141877 Xu et al. Jun 2011 A1
20110142041 Imai Jun 2011 A1
20110153909 Dong Jun 2011 A1
20110235509 Szymanski Sep 2011 A1
20110255397 Kadakia et al. Oct 2011 A1
20120008630 Ould-Brahim Jan 2012 A1
20120027013 Napierala Feb 2012 A1
20120136697 Peles et al. May 2012 A1
20120157068 Eichen et al. Jun 2012 A1
20120173694 Yan et al. Jul 2012 A1
20120173919 Patel et al. Jul 2012 A1
20120182940 Taleb et al. Jul 2012 A1
20120221955 Raleigh et al. Aug 2012 A1
20120227093 Shalzkamer et al. Sep 2012 A1
20120250682 Vincent et al. Oct 2012 A1
20120250686 Vincent et al. Oct 2012 A1
20120281706 Agarwal et al. Nov 2012 A1
20120287818 Corti et al. Nov 2012 A1
20120300615 Kempf et al. Nov 2012 A1
20120307659 Yamada Dec 2012 A1
20120317270 Vrbaski et al. Dec 2012 A1
20120317291 Wolfe Dec 2012 A1
20130019005 Hui et al. Jan 2013 A1
20130021968 Reznik et al. Jan 2013 A1
20130044764 Casado et al. Feb 2013 A1
20130051237 Ong Feb 2013 A1
20130051399 Zhang et al. Feb 2013 A1
20130054763 Merwe et al. Feb 2013 A1
20130086267 Gelenbe et al. Apr 2013 A1
20130103834 Dzerve et al. Apr 2013 A1
20130124718 Griffith et al. May 2013 A1
20130124911 Griffith et al. May 2013 A1
20130124912 Griffith et al. May 2013 A1
20130128889 Mathur et al. May 2013 A1
20130142201 Kim et al. Jun 2013 A1
20130170354 Takashima et al. Jul 2013 A1
20130173788 Song Jul 2013 A1
20130182712 Aguayo et al. Jul 2013 A1
20130191688 Agarwal et al. Jul 2013 A1
20130238782 Zhao et al. Sep 2013 A1
20130242718 Zhang Sep 2013 A1
20130254599 Katkar et al. Sep 2013 A1
20130258839 Wang et al. Oct 2013 A1
20130258847 Zhang et al. Oct 2013 A1
20130266015 Qu et al. Oct 2013 A1
20130266019 Qu et al. Oct 2013 A1
20130283364 Chang et al. Oct 2013 A1
20130286846 Atlas et al. Oct 2013 A1
20130297611 Moritz et al. Nov 2013 A1
20130297770 Zhang Nov 2013 A1
20130301469 Suga Nov 2013 A1
20130301642 Radhakrishnan et al. Nov 2013 A1
20130308444 Sem-Jacobsen et al. Nov 2013 A1
20130315242 Wang et al. Nov 2013 A1
20130315243 Huang et al. Nov 2013 A1
20130329548 Nakil et al. Dec 2013 A1
20130329601 Yin et al. Dec 2013 A1
20130329734 Chesla et al. Dec 2013 A1
20130346470 Obstfeld et al. Dec 2013 A1
20140019604 Twitchell, Jr. Jan 2014 A1
20140019750 Dodgson et al. Jan 2014 A1
20140040975 Raleigh et al. Feb 2014 A1
20140064283 Balus et al. Mar 2014 A1
20140071832 Johnsson et al. Mar 2014 A1
20140092907 Sridhar et al. Apr 2014 A1
20140108665 Arora et al. Apr 2014 A1
20140112171 Pasdar Apr 2014 A1
20140115584 Mudigonda et al. Apr 2014 A1
20140123135 Huang et al. May 2014 A1
20140126418 Brendel et al. May 2014 A1
20140156818 Hunt Jun 2014 A1
20140156823 Liu et al. Jun 2014 A1
20140164560 Ko et al. Jun 2014 A1
20140164617 Jalan et al. Jun 2014 A1
20140173113 Vemuri et al. Jun 2014 A1
20140173331 Martin et al. Jun 2014 A1
20140181824 Saund et al. Jun 2014 A1
20140208317 Nakagawa Jul 2014 A1
20140219135 Li et al. Aug 2014 A1
20140223507 Xu Aug 2014 A1
20140229210 Sharifian et al. Aug 2014 A1
20140244851 Lee Aug 2014 A1
20140258535 Zhang Sep 2014 A1
20140269690 Tu Sep 2014 A1
20140279862 Dietz et al. Sep 2014 A1
20140280499 Basavaiah et al. Sep 2014 A1
20140317440 Biermayr et al. Oct 2014 A1
20140321277 Lynn, Jr. et al. Oct 2014 A1
20140337500 Lee Nov 2014 A1
20140341109 Cartmell et al. Nov 2014 A1
20140372582 Ghanwani et al. Dec 2014 A1
20150003240 Drwiega et al. Jan 2015 A1
20150016249 Mukundan et al. Jan 2015 A1
20150029864 Raileanu et al. Jan 2015 A1
20150039744 Niazi et al. Feb 2015 A1
20150046572 Cheng et al. Feb 2015 A1
20150052247 Threefoot et al. Feb 2015 A1
20150052517 Raghu et al. Feb 2015 A1
20150056960 Egner et al. Feb 2015 A1
20150058917 Xu Feb 2015 A1
20150088942 Shah Mar 2015 A1
20150089628 Lang Mar 2015 A1
20150092603 Aguayo et al. Apr 2015 A1
20150096011 Watt Apr 2015 A1
20150124603 Ketheesan et al. May 2015 A1
20150134777 Onoue May 2015 A1
20150139238 Pourzandi et al. May 2015 A1
20150146539 Mehta et al. May 2015 A1
20150163152 Li Jun 2015 A1
20150169340 Haddad et al. Jun 2015 A1
20150172121 Farkas et al. Jun 2015 A1
20150172169 DeCusatis et al. Jun 2015 A1
20150188823 Williams et al. Jul 2015 A1
20150189009 Bemmel Jul 2015 A1
20150195178 Bhattacharya et al. Jul 2015 A1
20150201036 Nishiki et al. Jul 2015 A1
20150222543 Song Aug 2015 A1
20150222638 Morley Aug 2015 A1
20150236945 Michael et al. Aug 2015 A1
20150236962 Veres et al. Aug 2015 A1
20150244617 Nakil et al. Aug 2015 A1
20150249644 Xu Sep 2015 A1
20150257081 Ramanujan et al. Sep 2015 A1
20150271056 Chunduri et al. Sep 2015 A1
20150271104 Chikkamath et al. Sep 2015 A1
20150271303 Neginhal et al. Sep 2015 A1
20150281004 Kakadia et al. Oct 2015 A1
20150312142 Barabash et al. Oct 2015 A1
20150312760 O'Toole Oct 2015 A1
20150317169 Sinha et al. Nov 2015 A1
20150334025 Rader Nov 2015 A1
20150334696 Gu et al. Nov 2015 A1
20150341271 Gomez Nov 2015 A1
20150349978 Wu et al. Dec 2015 A1
20150350907 Timariu et al. Dec 2015 A1
20150358236 Roach et al. Dec 2015 A1
20150363221 Terayama et al. Dec 2015 A1
20150363733 Brown Dec 2015 A1
20150365323 Duminuco et al. Dec 2015 A1
20150372943 Hasan et al. Dec 2015 A1
20150372982 Herle Dec 2015 A1
20150381407 Wang et al. Dec 2015 A1
20150381493 Bansal et al. Dec 2015 A1
20160020844 Hart et al. Jan 2016 A1
20160021597 Hart et al. Jan 2016 A1
20160035183 Buchholz et al. Feb 2016 A1
20160036924 Koppolu et al. Feb 2016 A1
20160036938 Aviles et al. Feb 2016 A1
20160037434 Gopal et al. Feb 2016 A1
20160072669 Saavedra Mar 2016 A1
20160072684 Manuguri et al. Mar 2016 A1
20160080502 Yadav et al. Mar 2016 A1
20160105353 Cociglio Apr 2016 A1
20160105392 Thakkar et al. Apr 2016 A1
20160105471 Nunes et al. Apr 2016 A1
20160105488 Thakkar et al. Apr 2016 A1
20160117185 Fang et al. Apr 2016 A1
20160134461 Sampath et al. May 2016 A1
20160134528 Lin et al. May 2016 A1
20160134591 Liao et al. May 2016 A1
20160142373 Ossipov May 2016 A1
20160150055 Choi May 2016 A1
20160164832 Bellagamba et al. Jun 2016 A1
20160164914 Madhav et al. Jun 2016 A1
20160173338 Wolting Jun 2016 A1
20160191363 Haraszti et al. Jun 2016 A1
20160191374 Singh et al. Jun 2016 A1
20160192403 Gupta et al. Jun 2016 A1
20160197834 Luft Jul 2016 A1
20160197835 Luft Jul 2016 A1
20160198003 Luft Jul 2016 A1
20160210209 Verkaik et al. Jul 2016 A1
20160212773 Kanderholm et al. Jul 2016 A1
20160218947 Hughes et al. Jul 2016 A1
20160218951 Vasseur et al. Jul 2016 A1
20160255169 Kovvuri et al. Sep 2016 A1
20160261493 Li Sep 2016 A1
20160261495 Xia et al. Sep 2016 A1
20160261506 Hegde et al. Sep 2016 A1
20160261639 Xu Sep 2016 A1
20160269298 Li et al. Sep 2016 A1
20160269926 Sundaram Sep 2016 A1
20160285736 Gu Sep 2016 A1
20160308762 Teng et al. Oct 2016 A1
20160315912 Mayya et al. Oct 2016 A1
20160323377 Einkauf et al. Nov 2016 A1
20160328159 Coddington et al. Nov 2016 A1
20160330111 Manghirmalani et al. Nov 2016 A1
20160352588 Subbarayan et al. Dec 2016 A1
20160353268 Senarath et al. Dec 2016 A1
20160359738 Sullenberger et al. Dec 2016 A1
20160366187 Kamble Dec 2016 A1
20160371153 Dornemann Dec 2016 A1
20160380886 Blair et al. Dec 2016 A1
20160380906 Hodique et al. Dec 2016 A1
20170005986 Bansal et al. Jan 2017 A1
20170006499 Hampel et al. Jan 2017 A1
20170012870 Blair et al. Jan 2017 A1
20170019428 Cohn Jan 2017 A1
20170026283 Williams et al. Jan 2017 A1
20170026355 Mathaiyan et al. Jan 2017 A1
20170034046 Cai et al. Feb 2017 A1
20170034052 Chanda et al. Feb 2017 A1
20170034129 Sawant et al. Feb 2017 A1
20170048296 Ramalho et al. Feb 2017 A1
20170053258 Carney et al. Feb 2017 A1
20170055131 Kong et al. Feb 2017 A1
20170063674 Maskalik et al. Mar 2017 A1
20170063782 Jain et al. Mar 2017 A1
20170063794 Jain et al. Mar 2017 A1
20170064005 Lee Mar 2017 A1
20170093625 Pera et al. Mar 2017 A1
20170097841 Chang et al. Apr 2017 A1
20170104653 Badea et al. Apr 2017 A1
20170104755 Arregoces et al. Apr 2017 A1
20170109212 Gaurav et al. Apr 2017 A1
20170118173 Arramreddy et al. Apr 2017 A1
20170123939 Maheshwari et al. May 2017 A1
20170126516 Tiagi et al. May 2017 A1
20170126564 Mayya et al. May 2017 A1
20170134186 Mukundan et al. May 2017 A1
20170134520 Abbasi et al. May 2017 A1
20170139789 Fries et al. May 2017 A1
20170142000 Cai et al. May 2017 A1
20170149637 Banikazemi et al. May 2017 A1
20170155557 Desai et al. Jun 2017 A1
20170163473 Sadana et al. Jun 2017 A1
20170171310 Gardner Jun 2017 A1
20170181210 Nadella et al. Jun 2017 A1
20170195161 Ruel et al. Jul 2017 A1
20170195169 Mills et al. Jul 2017 A1
20170201585 Doraiswamy et al. Jul 2017 A1
20170207976 Rovner et al. Jul 2017 A1
20170214545 Cheng et al. Jul 2017 A1
20170214701 Hasan Jul 2017 A1
20170223117 Messerli et al. Aug 2017 A1
20170237710 Mayya et al. Aug 2017 A1
20170257260 Govindan et al. Sep 2017 A1
20170257309 Appanna Sep 2017 A1
20170264496 Ao et al. Sep 2017 A1
20170279717 Bethers et al. Sep 2017 A1
20170279803 Desai et al. Sep 2017 A1
20170280474 Vesterinen et al. Sep 2017 A1
20170288987 Pasupathy et al. Oct 2017 A1
20170289002 Ganguli et al. Oct 2017 A1
20170289027 Ratnasingham Oct 2017 A1
20170295264 Touitou et al. Oct 2017 A1
20170302565 Ghobadi et al. Oct 2017 A1
20170310641 Jiang et al. Oct 2017 A1
20170310691 Vasseur et al. Oct 2017 A1
20170317954 Masurekar et al. Nov 2017 A1
20170317969 Masurekar et al. Nov 2017 A1
20170317974 Masurekar et al. Nov 2017 A1
20170337086 Zhu et al. Nov 2017 A1
20170339054 Yadav et al. Nov 2017 A1
20170339070 Chang et al. Nov 2017 A1
20170364419 Lo Dec 2017 A1
20170366445 Nemirovsky et al. Dec 2017 A1
20170366467 Martin et al. Dec 2017 A1
20170373950 Szilagyi et al. Dec 2017 A1
20170374174 Evens et al. Dec 2017 A1
20180006995 Bickhart et al. Jan 2018 A1
20180007005 Chanda et al. Jan 2018 A1
20180007123 Cheng et al. Jan 2018 A1
20180013636 Seetharamaiah et al. Jan 2018 A1
20180014051 Phillips et al. Jan 2018 A1
20180020035 Boggia et al. Jan 2018 A1
20180034668 Mayya et al. Feb 2018 A1
20180041425 Zhang Feb 2018 A1
20180062875 Tumuluru Mar 2018 A1
20180062914 Boutros et al. Mar 2018 A1
20180062917 Chandrashekhar et al. Mar 2018 A1
20180063036 Chandrashekhar et al. Mar 2018 A1
20180063193 Chandrashekhar et al. Mar 2018 A1
20180063233 Park Mar 2018 A1
20180063743 Tumuluru et al. Mar 2018 A1
20180069924 Tumuluru et al. Mar 2018 A1
20180074909 Bishop et al. Mar 2018 A1
20180077081 Lauer et al. Mar 2018 A1
20180077202 Xu Mar 2018 A1
20180084081 Kuchibhotla et al. Mar 2018 A1
20180097725 Wood et al. Apr 2018 A1
20180114569 Strachan et al. Apr 2018 A1
20180123910 Fitzgibbon May 2018 A1
20180131608 Jiang et al. May 2018 A1
20180131615 Zhang May 2018 A1
20180131720 Hobson et al. May 2018 A1
20180145899 Rao May 2018 A1
20180159796 Wang et al. Jun 2018 A1
20180159856 Gujarathi Jun 2018 A1
20180167378 Kostyukov et al. Jun 2018 A1
20180176073 Dubey et al. Jun 2018 A1
20180176082 Katz et al. Jun 2018 A1
20180176130 Banerjee et al. Jun 2018 A1
20180213472 Ishii et al. Jul 2018 A1
20180219765 Michael et al. Aug 2018 A1
20180219766 Michael et al. Aug 2018 A1
20180234300 Mayya et al. Aug 2018 A1
20180260125 Botes et al. Sep 2018 A1
20180262468 Kumar et al. Sep 2018 A1
20180270104 Zheng et al. Sep 2018 A1
20180278541 Wu et al. Sep 2018 A1
20180287907 Kulshreshtha et al. Oct 2018 A1
20180295101 Gehrmann Oct 2018 A1
20180295529 Jen et al. Oct 2018 A1
20180302286 Mayya et al. Oct 2018 A1
20180302321 Manthiramoorthy et al. Oct 2018 A1
20180307851 Lewis Oct 2018 A1
20180316606 Sung et al. Nov 2018 A1
20180351855 Sood et al. Dec 2018 A1
20180351862 Jeganathan et al. Dec 2018 A1
20180351863 Vairavakkalai et al. Dec 2018 A1
20180351882 Jeganathan et al. Dec 2018 A1
20180367445 Bajaj Dec 2018 A1
20180373558 Chang et al. Dec 2018 A1
20180375744 Mayya et al. Dec 2018 A1
20180375824 Mayya et al. Dec 2018 A1
20180375967 Pithawala et al. Dec 2018 A1
20190013883 Vargas et al. Jan 2019 A1
20190014038 Ritchie Jan 2019 A1
20190020588 Twitchell, Jr. Jan 2019 A1
20190020627 Yuan Jan 2019 A1
20190028378 Houjyo et al. Jan 2019 A1
20190028552 Johnson et al. Jan 2019 A1
20190036808 Shenoy et al. Jan 2019 A1
20190036810 Michael et al. Jan 2019 A1
20190036813 Shenoy et al. Jan 2019 A1
20190046056 Khachaturian et al. Feb 2019 A1
20190058657 Chunduri et al. Feb 2019 A1
20190058709 Kempf et al. Feb 2019 A1
20190068470 Mirsky Feb 2019 A1
20190068493 Ram et al. Feb 2019 A1
20190068500 Hira Feb 2019 A1
20190075083 Mayya et al. Mar 2019 A1
20190103990 Cidon et al. Apr 2019 A1
20190103991 Cidon et al. Apr 2019 A1
20190103992 Cidon et al. Apr 2019 A1
20190103993 Cidon et al. Apr 2019 A1
20190104035 Cidon et al. Apr 2019 A1
20190104049 Cidon et al. Apr 2019 A1
20190104050 Cidon et al. Apr 2019 A1
20190104051 Cidon et al. Apr 2019 A1
20190104052 Cidon et al. Apr 2019 A1
20190104053 Cidon et al. Apr 2019 A1
20190104063 Cidon et al. Apr 2019 A1
20190104064 Cidon et al. Apr 2019 A1
20190104109 Cidon et al. Apr 2019 A1
20190104111 Cidon et al. Apr 2019 A1
20190104413 Cidon et al. Apr 2019 A1
20190109769 Jain et al. Apr 2019 A1
20190132221 Boutros et al. May 2019 A1
20190140889 Mayya et al. May 2019 A1
20190140890 Mayya et al. May 2019 A1
20190158371 Dillon et al. May 2019 A1
20190158605 Markuze et al. May 2019 A1
20190199539 Deng et al. Jun 2019 A1
20190220703 Prakash et al. Jul 2019 A1
20190238364 Boutros et al. Aug 2019 A1
20190238446 Barzik et al. Aug 2019 A1
20190238449 Michael et al. Aug 2019 A1
20190238450 Michael et al. Aug 2019 A1
20190238483 Marichetty et al. Aug 2019 A1
20190268421 Markuze et al. Aug 2019 A1
20190268973 Bull et al. Aug 2019 A1
20190280962 Michael et al. Sep 2019 A1
20190280963 Michael et al. Sep 2019 A1
20190280964 Michael et al. Sep 2019 A1
20190306197 Degioanni Oct 2019 A1
20190313907 Khachaturian et al. Oct 2019 A1
20190319847 Nahar et al. Oct 2019 A1
20190334813 Raj et al. Oct 2019 A1
20190334820 Zhao Oct 2019 A1
20190342219 Liu et al. Nov 2019 A1
20190356736 Narayanaswamy et al. Nov 2019 A1
20190364099 Thakkar et al. Nov 2019 A1
20190364456 Yu Nov 2019 A1
20190372888 Michael et al. Dec 2019 A1
20190372889 Michael et al. Dec 2019 A1
20190372890 Michael et al. Dec 2019 A1
20200014609 Hockett et al. Jan 2020 A1
20200014615 Michael et al. Jan 2020 A1
20200014616 Michael et al. Jan 2020 A1
20200014661 Mayya et al. Jan 2020 A1
20200014663 Chen et al. Jan 2020 A1
20200021514 Michael et al. Jan 2020 A1
20200021515 Michael et al. Jan 2020 A1
20200036624 Michael et al. Jan 2020 A1
20200044943 Bor-Yaliniz et al. Feb 2020 A1
20200059420 Abraham Feb 2020 A1
20200059459 Abraham et al. Feb 2020 A1
20200092207 Sipra et al. Mar 2020 A1
20200097327 Beyer et al. Mar 2020 A1
20200099659 Cometto et al. Mar 2020 A1
20200106696 Michael et al. Apr 2020 A1
20200119952 Mayya et al. Apr 2020 A1
20200127905 Mayya et al. Apr 2020 A1
20200127911 Gilson et al. Apr 2020 A1
20200153701 Mohan et al. May 2020 A1
20200153736 Liebherr et al. May 2020 A1
20200162407 Tillotson May 2020 A1
20200169473 Rimar et al. May 2020 A1
20200177503 Hooda et al. Jun 2020 A1
20200177550 Valluri et al. Jun 2020 A1
20200177629 Hooda et al. Jun 2020 A1
20200186471 Shen et al. Jun 2020 A1
20200195557 Duan et al. Jun 2020 A1
20200204460 Schneider et al. Jun 2020 A1
20200213212 Dillon et al. Jul 2020 A1
20200213224 Cheng et al. Jul 2020 A1
20200218558 Sreenath et al. Jul 2020 A1
20200235990 Janakiraman et al. Jul 2020 A1
20200235999 Mayya et al. Jul 2020 A1
20200236046 Jain et al. Jul 2020 A1
20200244721 S et al. Jul 2020 A1
20200252234 Ramamoorthi et al. Aug 2020 A1
20200259700 Bhalla et al. Aug 2020 A1
20200267184 Vera-Schockner Aug 2020 A1
20200280587 Janakiraman et al. Sep 2020 A1
20200287819 Theogaraj et al. Sep 2020 A1
20200287976 Theogaraj et al. Sep 2020 A1
20200296011 Jain et al. Sep 2020 A1
20200296026 Michael et al. Sep 2020 A1
20200314006 Mackie et al. Oct 2020 A1
20200314614 Moustafa et al. Oct 2020 A1
20200322230 Natal et al. Oct 2020 A1
20200336336 Sethi et al. Oct 2020 A1
20200344143 Faseela et al. Oct 2020 A1
20200344163 Gupta et al. Oct 2020 A1
20200351188 Arora et al. Nov 2020 A1
20200358878 Bansal et al. Nov 2020 A1
20200366530 Mukundan et al. Nov 2020 A1
20200366562 Mayya et al. Nov 2020 A1
20200382345 Zhao et al. Dec 2020 A1
20200382387 Pasupathy et al. Dec 2020 A1
20200412576 Kondapavuluru et al. Dec 2020 A1
20200413283 Shen et al. Dec 2020 A1
20210006482 Hwang et al. Jan 2021 A1
20210006490 Michael et al. Jan 2021 A1
20210029019 Kottapalli Jan 2021 A1
20210029088 Mayya et al. Jan 2021 A1
20210036888 Makkalla et al. Feb 2021 A1
20210036987 Mishra et al. Feb 2021 A1
20210067372 Cidon et al. Mar 2021 A1
20210067373 Cidon et al. Mar 2021 A1
20210067374 Cidon et al. Mar 2021 A1
20210067375 Cidon et al. Mar 2021 A1
20210067407 Cidon et al. Mar 2021 A1
20210067427 Cidon et al. Mar 2021 A1
20210067442 Sundararajan et al. Mar 2021 A1
20210067461 Cidon et al. Mar 2021 A1
20210067464 Cidon et al. Mar 2021 A1
20210067467 Cidon et al. Mar 2021 A1
20210067468 Cidon et al. Mar 2021 A1
20210105199 H et al. Apr 2021 A1
20210112034 Sundararajan et al. Apr 2021 A1
20210126830 R. et al. Apr 2021 A1
20210126853 Ramaswamy et al. Apr 2021 A1
20210126854 Guo et al. Apr 2021 A1
20210126860 Ramaswamy et al. Apr 2021 A1
20210144091 H et al. May 2021 A1
20210160169 Shen et al. May 2021 A1
20210160813 Gupta et al. May 2021 A1
20210184952 Mayya et al. Jun 2021 A1
20210184966 Ramaswamy et al. Jun 2021 A1
20210184983 Ramaswamy et al. Jun 2021 A1
20210194814 Roux et al. Jun 2021 A1
20210226880 Ramamoorthy et al. Jul 2021 A1
20210234728 Cidon et al. Jul 2021 A1
20210234775 Devadoss et al. Jul 2021 A1
20210234786 Devadoss et al. Jul 2021 A1
20210234804 Devadoss et al. Jul 2021 A1
20210234805 Devadoss et al. Jul 2021 A1
20210235312 Devadoss et al. Jul 2021 A1
20210235313 Devadoss et al. Jul 2021 A1
20210266262 Subramanian et al. Aug 2021 A1
20210279069 Salgaonkar et al. Sep 2021 A1
20210314289 Chandrashekhar et al. Oct 2021 A1
20210328835 Mayya et al. Oct 2021 A1
20210336880 Gupta et al. Oct 2021 A1
20210377109 Shrivastava et al. Dec 2021 A1
20210377156 Michael et al. Dec 2021 A1
20210392060 Silva et al. Dec 2021 A1
20210392070 Tootaghaj et al. Dec 2021 A1
20210399920 Sundararajan et al. Dec 2021 A1
20210399978 Michael et al. Dec 2021 A9
20210400113 Markuze et al. Dec 2021 A1
20220006726 Michael et al. Jan 2022 A1
20220006751 Ramaswamy et al. Jan 2022 A1
20220006756 Ramaswamy et al. Jan 2022 A1
20220035673 Markuze et al. Feb 2022 A1
20220038370 Vasseur et al. Feb 2022 A1
20220038557 Markuze et al. Feb 2022 A1
20220094644 Cidon et al. Mar 2022 A1
Foreign Referenced Citations (30)
Number Date Country
1926809 Mar 2007 CN
102577270 Jul 2012 CN
102811165 Dec 2012 CN
104956329 Sep 2015 CN
106656847 May 2017 CN
110447209 Nov 2019 CN
111198764 May 2020 CN
1912381 Apr 2008 EP
3041178 Jul 2016 EP
3509256 Jul 2019 EP
2010233126 Oct 2010 JP
2017059991 Mar 2017 JP
2574350 Feb 2016 RU
03073701 Sep 2003 WO
2007016834 Feb 2007 WO
2012167184 Dec 2012 WO
2016061546 Apr 2016 WO
2017083975 May 2017 WO
2019070611 Apr 2019 WO
2019094522 May 2019 WO
2020012491 Jan 2020 WO
2020018704 Jan 2020 WO
2020091777 May 2020 WO
2020101922 May 2020 WO
2020112345 Jun 2020 WO
2021040934 Mar 2021 WO
2021118717 Jun 2021 WO
2021150465 Jul 2021 WO
2021211906 Oct 2021 WO
2022005607 Jan 2022 WO
Non-Patent Literature Citations (32)
Entry
Huang, Cancan, et al., “Modification of Q.SD-WAN,” Rapporteur Group Meeting—Doc, Study Period 2017-2020, Q4/11-DOC1 (190410), Study Group 11, Apr. 10, 2019, 19 pages, International Telecommunication Union, Geneva, Switzerland.
Mudigonda, Jayaram, et al., “NetLord: A Scalable Multi-Tenant Network Architecture for Virtualized Datacenters,” Proceedings of the ACM SIGCOMM 2011 Conference, Aug. 15-19, 2011, 12 pages, ACM, Toronto, Canada.
Non-published Commonly Owned U.S. Appl. No. 16/576,751, filed Sep. 19, 2019, 42 pages, Nicira, Inc.
Non-published Commonly Owned U.S. Appl. No. 16/656,555, filed Oct. 17, 2019, 40 pages, Nicira, Inc.
Petition for Post-Grant Review of U.S. Pat. No. 9,722,815, filed May 1, 2018, 106 pages.
Del Piccolo, Valentin, et al., “A Survey of Network Isolation Solutions for Multi-Tenant Data Centers,” IEEE Communications Society, Apr. 20, 2016, vol. 18, No. 4, 37 pages, IEEE.
Fortz, Bernard, et al., “Internet Traffic Engineering by Optimizing OSPF Weights,” Proceedings IEEE INFOCOM 2000, Conference on Computer Communications, Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies, Mar. 26-30, 2000, 11 pages, IEEE, Tel Aviv, Israel, Israel.
Francois, Frederic, et al., “Optimizing Secure SDN-enabled Inter-Data Centre Overlay Networks through Cognitive Routing,” 2016 IEEE 24th International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems (MASCOTS), Sep. 19-21, 2016, 10 pages, IEEE, London, UK.
Michael, Nithin, et al., “HALO: Hop-by-Hop Adaptive Link-State Optimal Routing,” IEEE/ACM Transactions on Networking, Dec. 2015, 14 pages, vol. 23, No. 6, IEEE.
Mishra, Mayank, et al., “Managing Network Reservation for Tenants in Oversubscribed Clouds,” 2013 IEEE 21st International Symposium on Modelling, Analysis and Simulation of Computer and Telecommunication Systems, Aug. 14-16, 2013, 10 pages, IEEE, San Francisco, CA, USA.
Non-Published Commonly Owned U.S. Appl. No. 16/945,700, filed Jul. 31, 2020, 37 pages, Nicira, Inc.
Non-Published Commonly Owned U.S. Appl. No. 17/068,603, filed Oct. 12, 2020, 37 pages, Nicira, Inc.
Ray, Saikat, et al., “Always Acyclic Distributed Path Computation,” University of Pennsylvania Department of Electrical and Systems Engineering Technical Report, May 2008, 16 pages, University of Pennsylvania ScholarlyCommons.
Webb, Kevin C., et al., “Blender: Upgrading Tenant-Based Data Center Networking,” 2014 ACM/IEEE Symposium on Architectures for Networking and Communications Systems (ANCS), Oct. 20-21, 2014, 11 pages, IEEE, Marina del Rey, CA, USA.
Yap, Kok-Kiong, et al., “Taking the Edge off with Espresso: Scale, Reliability and Programmability for Global Internet Peering,” SIGCOMM '17: Proceedings of the Conference of the ACM Special Interest Group on Data Communication, Aug. 21-25, 2017, 14 pages, Los Angeles, CA.
Sarhan, Soliman Abd Elmonsef, et al., “Data Inspection in SDN Network,” 2018 13th International Conference an Computer Engineering and Systems (ICCES), Dec. 18-19, 2018, 6 pages, IEEE, Cairo, Egypt.
Xie, Junfeng, et al., A Survey of Machine Learning Techniques Applied to Software Defined Networking (SDN) Research Issues and Challenges, IEEE Communications Surveys & Tutorials, Aug. 23, 2018, 38 pages, vol. 21, Issue 1, IEEE.
Alsaeedi, Mohammed, et al., “Toward Adaptive and Scalable OpenFlow-SDN Flow Control: A Survey,” IEEE Access, Aug. 1, 2019, 34 pages, vol. 7, IEEE, retrieved from https://ieeexplore.ieee.org/document/8784036.
Long, Feng, “Research and Application of Cloud Storage Technology in University Information Service,” Chinese Excellent Masters' Theses Full-text Database, Mar. 2013, 72 pages, China Academic Journals Electronic Publishing House, China.
Noormohammadpour, Mohammad, et al., “DCRoute: Speeding up Inter-Datacenter Traffic Allocation while Guaranteeing Deadlines,” 2016 IEEE 23rd International Conference on High Performance Computing (HiPC), Dec. 19-22, 2016, 9 pages, IEEE, Hyderabad, India.
Lasserre, Marc, et al., “Framework for Data Center (DC) Network Virtualization,” RFC 7365, Oct. 2014, 26 pages, IETF.
Lin, Weidong, et al., “Using Path Label Routing in Wide Area Software-Defined Networks with Open Flow,” 2016 International Conference on Networking and Network Applications, Jul. 2016, 6 pages, IEEE.
Alvizu, Rodolfo, et al., “SDN-Based Network Orchestration for New Dynamic Enterprise Networking Services,” 2017 19th International Conference on Transparent Optical Networks, Jul. 2-6, 2017, 4 pages, IEEE, Girona, Spain.
Barozet, Jean-Marc, “Cisco SDWAN,” Deep Dive, Dec. 2017, 185 pages, Cisco, Retreived from https://www.coursehero.com/file/71671376/Cisco-SDWAN-Deep-Divepdf/.
Bertaux, Lionel, et al., “Software Defined Networking and Virtualization for Broadband Satellite Networks,” IEEE Communications Magazine, Mar. 18, 2015, 7 pages, vol. 53, IEEE, retrieved from https://ieeexplore.ieee.org/document/7060482.
Cox, Jacob H., et al., “Advancing Software-Defined Networks: A Survey,” IEEE Access, Oct. 12, 2017, 40 pages, vol. 5, IEEE, retrieved from https://ieeexplore.ieee.org/document/8066287.
Duan, Zhenhai, et al., “Service Overlay Networks: SLAs, QoS, and Bandwidth Provisioning,” IEEE/ACM Transactions on Networking, Dec. 2003, 14 pages, vol. 11, IEEE, New York, NY, USA.
Li, Shengru, et al., “Source Routing with Protocol-oblivious Forwarding (POF) to Enable Efficient e-Health Data Transfers,” 2016 IEEE International Conference on Communications (ICC), May 22-27, 2016, 6 pages, IEEE, Kuala Lumpur, Malaysia.
Ming, Gao, et al., “A Design of SD-WAN-Oriented Wide Area Network Access,” 2020 International Conference on Computer Communication and Network Security (CCNS), Aug. 21-23, 2020, 4 pages, IEEE, Xi'an, China.
Non-Published Commonly Owned U.S. Appl. No. 17/562,890, filed Dec. 27, 2021, 36 pages, Nicira, Inc.
Tootaghaj, Diman Zad, et al., “Homa: An Efficient Topology and Route Management Approach in SD-WAN Overlays,” IEEE INFOCOM 2020—IEEE Conference on Computer Communications, Jul. 6-9, 2020, 10 pages, IFFF, Toronto, ON, Canada.
Guo, Xiangyi, et al., (U.S. Appl. No. 62/925,193), filed Oct. 23, 2019, 26 pages.
Related Publications (1)
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20200106706 A1 Apr 2020 US
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62146786 Apr 2015 US
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Parent 15407767 Jan 2017 US
Child 16699719 US
Continuation in Parts (1)
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Parent 15097282 Apr 2016 US
Child 15407767 US