Detecting and resolving multicast traffic performance issues

Information

  • Patent Grant
  • 11102065
  • Patent Number
    11,102,065
  • Date Filed
    Thursday, December 12, 2019
    4 years ago
  • Date Issued
    Tuesday, August 24, 2021
    2 years ago
Abstract
The subject disclosure relates to systems and methods for improving multicast traffic flows in a computer network. In some aspects, a method of the technology includes steps for receiving multicast traffic statistics from each of a plurality of switches in a computer network, aggregating the multicast traffic statistics into a time-series database, and identifying a low-performing multicast flow based on the time-series database. In some aspects, the method can include steps for automatically reconfiguring the computer network to improve the low-performing multicast flow. Systems and machine readable media are also provided.
Description
BACKGROUND
1. Technical Field

The subject technology relates systems and methods for identifying and correcting performance problems in multicast traffic flows. In particular, aspects of the technology provide solutions for moving (e.g., re-rooting) multicast trees to improve multicast performance.


2. Introduction

In some network configurations, several end user terminals, or hosts, may wish to receive the same data at the same time. This data can include anything from video or audio content, or software updates, to information about the network itself. While it would be possible to send this information simultaneously and individually to each host in the network, this would involve the transmission of replicated data throughout the network. Methods of multicasting data have therefore been developed in which data is transmitted through the network only to those destinations or hosts that have indicated a desire to receive the data, for example, by joining a corresponding multicast group. Generally, multicast data is replicated in the network only where the route to two destination hosts splits. Therefore, only one copy of the data is sent through the network until routes to the destination hosts diverge. Data is therefore sent through the network in a multicast tree, from which branches are formed as destination routes diverge.





BRIEF DESCRIPTION OF THE DRAWINGS

Certain features of the disclosed technology are set forth in the appended claims. However, the accompanying drawings, which are included to provide further understanding, illustrate certain aspects and together with the description explain the principles of the subject technology. In the drawings:



FIG. 1 illustrates an example network environment in which some aspects of the technology can be implemented.



FIG. 2A illustrates an example of a multicast flow (FTAG) and port matrix for a network switch, according to some aspects of the technology.



FIG. 2B illustrates a portion of a network fabric, including network devices such as leaf and spine switches, on which some aspects of the technology can be implemented.



FIG. 3 illustrates a flow chart of an exemplary algorithm that can be used to automatically resolve multicast traffic performance issues, according to some aspects of the technology.



FIG. 4 illustrates an example a network device configured to implement various aspects of the subject technology.





DETAILED DESCRIPTION

The detailed description set forth below is intended as a description of various configurations of the subject technology and is not intended to represent the only configurations in which the technology can be practiced. The appended drawings are incorporated herein and constitute a part of the detailed description. The detailed description includes specific details for the purpose of providing a more thorough understanding of the subject technology. However, it will be clear and apparent that the subject technology is not limited to the specific details set forth herein and may be practiced without these details. In some instances, structures and components are shown in block diagram form in order to avoid obscuring certain concepts of the technology.


Overview:


A method performed for implementing aspects of the technology can include steps for receiving multicast traffic statistics from each of a plurality of switches in a computer network, aggregating the multicast traffic statistics into a time-series database, and using the time-series database, automatically identifying a low-performing multicast flow. In some approaches, the method can further include steps for reconfiguring the network to improve the low-performing multicast flow, e.g., to reduce packet drop events, and improve traffic throughput. As discussed in further detail below, network reconfigurations can be performed automatically, e.g., by a network controller, or another suitable network process. Some reconfigurations can include the suppression of selected communication links (e.g., “links”) between network devices, such as link “pruning.” In some instances, network reconfiguration can involve the pruning of a given Forwarding Tag (“FTAG”), e.g., by removing a selected FTAG from a list of available FTAGs. Additionally, some network reconfigurations can involve the migration or re-rooting of an entire multicast tree, e.g., from a source switch to a new (destination) switch in the network.


Description:


An increasing amount of network traffic is the result of streaming media applications, such as Live TV. With the proliferation of media traffic, Internet Protocol (IP) multicast performance is rapidly becoming a focal point for cloud providers. When a media stream (such as a live video stream) experiences packet drops, the result is skipped frames, resulting in a degraded end-user experience. To ensure a high quality user experience, datacenters and other providers of media traffic need to proactively monitor their networks to mitigate packet drops.


It is often difficult for network administrators to fix multicast flow problems because conventional network deployments lack tools for identifying multicast issues. For example, in conventional configurations, network administrators must manually trace multicast traffic through the network and identify where drops are happening. This is typically performed by manually reading counters from each switch associated with a low performing multicast flow. Drop events must then be manually traced to pinpoint traffic bottlenecks. It is almost impossible to manually determine what path a multicast tree takes, what flows take those trees, and what trees are experiencing drops in a short enough time to make necessary network changes. Additionally, manually troubleshooting problems associated with multicast flows is not scalable, and therefore must be repeated every time the network experiences performance issues.


Aspects of the disclosed technology address the foregoing problems by providing systems and methods for identifying multicast drop events, and automatically pushing new network configurations to improve traffic flow quality. The technology can be implemented by a network controller, or other system enabled to configure/reconfigure network nodes and links necessary to re-rout multicast trees. In some aspects, the network controller is configured to automatically prune individual links associated with a multicast flow, automatically prune multicast trees associated with a multicast flow, and/or to re-root an entire multicast tree by transferring the root to a new destination switch, such as a new network spine that is determined to be suitable for the associated flow.


In some implementations, a network controller is configured to periodically receive traffic statistics from various switches e.g., spine switches, or other routing devices in the network fabric. Traffic statistics can be transmitted by each reporting switch, using a corresponding hardware offload engine, and can include various types of information about the switch's load and performance. By way of non-limiting example, traffic statistics can include information identifying one or more of: a corresponding switch/spine, port, multicast flow, flow bandwidth, port bandwidth, a number of transmitted or received FTAG packets per port, a total number of packets sent or received and/or packet drop counts.


It is understood that the various traffic statistics can be collected for unicast traffic (e.g., unicast statistics) and/or multicast traffic (e.g., multicast statistics), and transmitted by an offload engine. The traffic statistics are then aggregated by a monitoring device, such as a network controller, or other monitoring process, and stored into a time-indexed database.


The database can then be monitored to identify candidate multicast flows for which network reconfiguration may improve performance, i.e., for which link pruning, multicast (FTAG) pruning, or multicast root-transfer (re-rooting) could reduce drop events.


Selection of a given multicast flow can be performed based on a consideration for the overall impact that would be incurred by the network with the new network configuration. In some approaches, new configurations resulting in a smaller network impact are preferred over reconfigurations that would require major network changes and/or cause significant disruptions to other flows. For example, multicast flows with a greater percentage of packet drops and/or lower overall traffic bandwidth can be prioritized for reconfiguration. Conversely, multicast flows of greater size (bandwidth) may be of a lower priority, due to the potential for causing greater network disruptions. The various parameters used to identify/select network flows for improvement can vary depending on the desired implementation, and in some instances, can be configurable parameters, for example, that are set by a network administrator.


As used herein, link pruning refers to any reconfiguration that re-routes traffic away from an existing link between two network entities. Link pruning can be used to remove a link from the allowable FTAG link-set, so long as reachability is not affected. Multicast tree pruning refers to the elimination of one or more multicast trees from a source switch. Multicast tree pruning is typically performed in where multiple FTAG trees are available for broadcast, and a target multicast tree (FTAG) can be pruned without affecting reachability. In turn, multicast root-transfer (re-rooting), involves the movement of a multicast tree's root from a source switch (e.g., a source spine switch), to a destination switch, such as a new destination spine switch.


Due to a greater potential for traffic disruptions, multicast tree re-rooting may only be performed when link pruning and/or multicast tree pruning are insufficient to resolve performance issues. In some implementations, multicast re-rooting is not performed automatically, but rather, is presented as an option (e.g., to a user or network administrator), together with other information detailing the expected impact of the proposed reconfiguration. This information can include details about the new configuration to be pushed, identification of one or more other links, or potentially affected traffic flows, and/or an identification of one or more network devices to be effected.



FIG. 1 illustrates a diagram of an example network environment 100 in which multicast monitoring can be performed. Fabric 112 can represent the underlay (i.e., the physical network) of environment 100. Fabric 112 includes spine switches 1-N (102A N) (collectively “102”) and leaf switches 1-N (104A-N) (collectively “104”). Leaf switches 104 can reside at the edge of fabric 112, and can represent the physical network edges. Leaf switches 104 can be, for example, top-of-rack (“ToR”) switches, aggregation switches, gateways, ingress and/or egress switches, provider edge devices, and/or any other type of routing or switching device.


Leaf switches 104 can be responsible for routing and/or bridging tenant or endpoint packets and applying network policies. Spine 102 can perform switching and routing within fabric 112. Thus, network connectivity in fabric 112 can flow from spine switches 102 to leaf switches 104, and vice versa.


Leaf switches 104 can provide servers 1-4 (106A-D) (collectively “106”), hypervisors 1-4 (108A-108D) (collectively “108”), virtual machines (VMs) 1-4 (110A-110D) (collectively “110”). For example, leaf switches 104 can encapsulate and decapsulate packets to and from servers 106 in order to enable communications throughout environment 100. Leaf switches 104 can also connect other network-capable device(s) or network(s), such as a firewall, a database, a server, etc., to the fabric 112. Leaf switches 104 can also provide any other servers, resources, endpoints, external networks, VMs, services, tenants, or workloads with access to fabric 112.


As discussed in further detail with respect to FIG. 2B below, leaf switches 104 and spine switches 102 can be used to carry multicast flows, for example, to/from one or more hosts in the network (not illustrated).



FIG. 2A illustrates an example of a multicast flow (FTAG) and port matrix 200, that represents FTAG/port associations for a given network switch. Port matrix 200 can be used to facilitate link pruning decisions. The FTAG/port matrix can be compiled and stored at the associated switch and/or a centralized network controller that is coupled to the switch. Port matrix 200 can be used by the network controller to identify candidate links that can be pruned to improve at least one multicast flow. As discussed in detail below, in some instances, link pruning decisions should be based on determinations of host reachability and bandwidth reallocation, i.e., the availability of one or more other links to absorb bandwidth for a pruned link. That is, candidate links can be ranked higher for pruning where host reachability is not impacted, and/or where smaller amounts of traffic are to be redirected in the network.


In some aspects, reachability link pruning decisions can also be pre-conditioned on network reachability. That is, candidate links can only be pruned if it is first determined that reachability for network traffic flowing over those links will not be impacted, i.e., reduced.


Link utilization statistics for each FTAG/port pair can be compared to determine packet drop percentages and bandwidth statistics for each link. In some implementations, bandwidth statistics can include combined measures for multicast traffic and/or unicast traffic; however, in some preferred implementations, only multicast traffic may be considered. The FTAG, port pair with the highest drop percentage, and/or lowest total bandwidth on that FTAG can be selected for link pruning. By way of example, matrix 200 illustrates a configuration in which each port has FTAGs A, B, or C. If FTAG B sends 1 million packets, and experiences 500 packet drops, whereas FTAG A sends 100 thousand packets and experiences 500 packet drops, then FTAG A, having the higher drop percentage, may be prioritized for pruning over FTAG B.


Once a link associated with a specific FTAG is selected for pruning, it is determined if any hosts connected to the FTAG will no longer be reachable if the link is pruned, i.e., to determine if the selected link provides a redundant path. Further to the example illustrated in FIG. 2A, FTAG A includes both ports 0 and 1 as fanout links. If any destination (host) subscribed to FTAG A is reachable through both ports 0 and 1, then port 0 can be pruned from FTAG A, as the traffic can be routed through port 1, without compromising reachability.


In some aspects, link pruning can be skipped if an alternative link is unavailable, or unable to absorb the traffic bandwidth from the pruned link. That is, link pruning decisions can also take into consideration whether the required increase in bandwidth for one or more alternative links exceeds an allowed bandwidth for those links. Further to the above example, pruning FTAG A at port 0 would cause the traffic to be routed through port 1, increasing the bandwidth throughput on port 1. As such, the increased traffic load on port 1 should not result in packet drops.


In some aspects, if it is determined that a bandwidth threshold for a new target port/link would be exceeded, alternative links can be considered for pruning. Alternatively, if no candidate FTAG links can be pruned, then determinations can be made regarding multicast tree pruning, as discussed in further detail with respect to network environment 201, below.



FIG. 2B illustrates an example of a partial network environment 201, including network devices on which some aspects of the technology can be implemented. Environment 201 includes spine switches (Spine 0 and Spine 1), each connected to leaf switches (Leaf 0, and Leaf 1). It is understood that environment 201 only represents a portion of a network fabric, for example, as described with respect to network 100 in FIG. 1, above. In the illustrated example, spine and leaf switches are configured for carrying multicast flows originating from at least one host device connected to Leaf 0 and/or Leaf 1 (not illustrated), and for providing the multicast traffic to recipient hosts (not illustrated).


In implementations wherein the source switch (e.g., Spine 0 or Spine 1) can be configured to choose multiple FTAG trees for broadcast, selected FTAG trees can be pruned to reduce the load corresponding with that FTAG. In the example of FIG. 2B, if Spine 0 experiences FTAG A drops on a particular downlink port, bandwidth contributions for each link into Spine 0 (e.g., A0, and A1) can be computed to determine which provides the smallest bandwidth contribution. If link A0 is determined to have the smallest contribution that can also account for the packet drops on the downlink, link A0 may be more highly ranked for potential pruning than link A1. Subsequently, each ranked link can be examined to determine if the associated FTAG tree is part of an equal-cost multi-path (ECMP) set. In the illustrated example, Leaf 0 to Spine 0 has an ECMP set of FTAGs, i.e., FTAG A and FTAG B. If both FTAG A and FTAG B provide the same subscriber reachability, then either can be considered valid options for sending traffic, and thus FTAG A on Leaf 0 could be a candidate for pruning.


In order to complete FTAG pruning, it is first determined if alternate links have the capacity to absorb the additional traffic. Further to the above example, to prune FTAG A from Leaf 0, the link from Leaf 0 to Spine 1 (link B0) would need the capacity to absorb the traffic from link A0. If pruning the selected FTAG would result in packet drop mitigation, then FTAG A can be pruned, e.g., from the source ECMP list on Leaf 0. If flow performance would not be improved by pruning FTAG A, additional analysis/ranking of links can be performed, e.g., by re-analyzing reachability for the various FTAGs.


In some implementations, it may be determined that there are no suitable solutions for FTAG pruning. In such instances, multicast FTAG re-rooting can be considered. However, before FTAG movement is performed, suitability of FTAG re-rooting is considered, for example, by the controller (or other network monitoring process), on a spine-by-spine basis to determine if re-rooting in a new spine would improve flow performance. For example, if FTAG A is rooted in Spine 0 and needs to be moved, candidate spines could include Spine 1, as well as one or more other spines (e.g., Spine 2, not illustrated). If Spine 1 provides similar subscriber reachability as Spine 0, but Spine 2 does not, then only Spine 1 may be considered as a destination candidate for FTAG A.


Other parameters can also be considered. For example, before multicast re-rooting is performed, various ingress and egress ports of the candidate spine switch can be analyzed to determine if the added multicast bandwidth can be accommodated. By way of example, ingress and egress ports of Spine 1 can be analyzed to see if each can accommodate additional bandwidth resulting from traffic on links A0 and A1, should FTAG A be re-rooted in Spine 1. If the candidate destination spine is capable of absorbing the added traffic from FTAG A, re-rooting can be performed. Alternatively, no re-rooting is attempted, and a message or indication may be delivered to the network administrator, e.g., via the network controller, to indicate that multicast flow performance issues could not be resolved through network reconfiguration.


Although re-rooting can be performed automatically, because multicast re-rooting requires significant network configuration changes, in some aspects, re-rooting may be provided as an option, for example, to the network administrator before any network changes are implemented. In such instances, the administrator can be provided an alert indicating the new configuration to be pushed to move the multicast tree.



FIG. 3 illustrates a flow chart of an example process 300 used to resolve multicast traffic performance issues, according to some aspects of the technology. Process 300 begins with step 302 in which multicast statistics are received from multiple switches in a computer network. The multicast statistics can be received by a network controller, or other monitoring hardware and/or software. Statistics can be provided by an offload engine for a respective switch/router, and can include various types of metrics relating to current or historic device performance. For example, multicast statistics can indicate the frequency of packet drop events, or bandwidth statistics for particular flows, e.g., on a port-by-port basis.


In step 304, the multicast statistics are aggregated (e.g., by the network controller), into a time-series database. The time-series database can provide a snapshot of current and historic flow performance, e.g., for various FTAGs, across different leaf/spine switches in the network fabric. Subsequently, at step 306, low performing multicast flows are identified through analysis of the time-series database. As discussed above with respect to FIG. 2A, flows experiencing performance degradation can be identified for each switch/router on a port-by-port basis. Flow statistics for each FTAG/port pair can be aggregated for multiple switches/routers to determine overall performance for the multicast flow. Additionally, several different types of flow statistics can be considered when prioritizing multicast flows. For example, a flow can be selected/prioritized for further inspection based on a ratio of packet drop events to flow size (bandwidth). That is, flows with greater proportions of packet drops can be prioritized. Additionally, smaller multicast flows may be given precedence since redirection of smaller traffic volumes can be less disruptive to overall network performance.


Once a flow has been identified, different network reconfiguration options can be considered to improve flow performance. As discussed above, link pruning may be considered first, as link pruning can require the least impactful network configuration changes. If link pruning is determined to likely improve flow performance, without affecting host reachability, a new network configuration can be automatically pushed to redirect traffic around the pruned link/s. In some aspects, the new network configuration may first be provided to a network administrator or other user, for example, to give the administrator an opportunity to approve the new configuration before it is pushed. Alternatively, if link pruning is not possible, or determined to not improve flow performance, multicast pruning (e.g., FTAG pruning) can be considered.


In instances where multicast pruning is determined to improve flow performance, a new network configuration can be automatically pushed, e.g., to prune one or more identified FTAGs necessary to improve flow performance. In some approaches, multicast pruning may be presented as an option to a network administrator, e.g., via a network controller, so that the network administrator can approve the new network configuration before changes are pushed.


In aspects wherein multicast pruning is determined to not be a viable option, multicast re-rooting is considered. Determinations regarding whether multicast re-rooting can be performed can depend on the availability and performance metrics of a viable candidate switch (e.g., spine switch) in which the multicast flow can be re-rooted. As discussed above, subscriber reachability by the candidate destination is determined. Candidate destination switches offering full, or substantially complete, subscriber reachability can be preferred over switches with limited or less complete reachability. Because multicast re-rooting can involve substantial network reconfiguration, re-rooting may be presented as an option to the network administrator, including various details of the overall network impact, before configuration changes get pushed to the network.



FIG. 4 illustrates an example network device 410 that can be used to implement a spine and/or leaf router, as discussed above. Network device 410 includes a master central processing unit (CPU) 462, interfaces 468, and a bus 415 (e.g., a PCI bus). When acting under the control of appropriate software or firmware, the CPU 462 is responsible for executing packet management, error detection, and/or routing functions. The CPU 462 preferably accomplishes all these functions under the control of software including an operating system and any appropriate applications software. CPU 462 may include one or more processors 463 such as processors from the Intel, ARM, MIPS or Motorola family of microprocessors. In an alternative embodiment, processor 463 is specially designed hardware for controlling the operations of router 410. In a specific embodiment, a memory 461 (such as non-volatile RAM and/or ROM) also forms part of CPU 462. However, there are many different ways in which memory could be coupled to the system.


Interfaces 468 can be provided as interface cards (sometimes referred to as “line cards”). Generally, they control the sending and receiving of data packets over the network and sometimes support other peripherals used with the router 410. Among the interfaces that may be provided are Ethernet interfaces, frame relay interfaces, cable interfaces, DSL interfaces, token ring interfaces, and the like. In addition, various very high-speed interfaces may be provided such as fast token ring interfaces, wireless interfaces, Ethernet interfaces, Gigabit Ethernet interfaces, ATM interfaces, HSSI interfaces, POS interfaces, FDDI interfaces and the like. Generally, these interfaces may include ports appropriate for communication with the appropriate media. In some cases, they may also include an independent processor and, in some instances, volatile RAM. The independent processors may control such communications intensive tasks as packet switching, media control and management. By providing separate processors for the communications intensive tasks, these interfaces allow the master microprocessor 462 to efficiently perform routing computations, network diagnostics, security functions, etc.


Although the system shown in FIG. 4 is one specific network device of the present invention, it is by no means the only network device architecture on which the present invention can be implemented. For example, an architecture having a single processor that handles communications as well as routing computations, etc. is often used. Further, other types of interfaces and media could also be used with the router.


Regardless of the network device's configuration, it may employ one or more non-transitory memories or memory modules (including memory 461) configured to store program instructions for general-purpose network operations and mechanisms necessary to implement the network reconfiguration methods discussed above. For example, memory 461 can include a non-transitory computer-readable medium that includes instructions for causing CPU 462 to execute operations for receiving traffic statistics from each of a plurality of switches in a computer network, aggregating the statistics into a time-series database, and automatically identifying a low-performing multicast flow, based on the time-series database. In some implementations, memory 461 can further include instructions for reconfiguring the computer network to improve the low-performing multicast flow.


It is understood that any specific order or hierarchy of steps in the processes disclosed is an illustration of exemplary approaches. Based upon design preferences, it is understood that the specific order or hierarchy of steps in the processes may be rearranged, or that only a portion of the illustrated steps be performed. Some of the steps may be performed simultaneously. For example, in certain circumstances, multitasking and parallel processing may be advantageous. Moreover, the separation of various system components in the embodiments described above should not be understood as requiring such separation in all embodiments, and it should be understood that the described program components and systems can generally be integrated together in a single software product or packaged into multiple software products.


The previous description is provided to enable any person skilled in the art to practice the various aspects described herein. Various modifications to these aspects will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other aspects. Thus, the claims are not intended to be limited to the aspects shown herein, but are to be accorded the full scope consistent with the language claims, wherein reference to an element in the singular is not intended to mean “one and only one” unless specifically so stated, but rather “one or more.”


A phrase such as an “aspect” does not imply that such aspect is essential to the subject technology or that such aspect applies to all configurations of the subject technology. A disclosure relating to an aspect may apply to all configurations, or one or more configurations. A phrase such as an aspect may refer to one or more aspects and vice versa. A phrase such as a “configuration” does not imply that such configuration is essential to the subject technology or that such configuration applies to all configurations of the subject technology. A disclosure relating to a configuration may apply to all configurations, or one or more configurations. A phrase such as a configuration may refer to one or more configurations and vice versa.


The word “exemplary” is used herein to mean “serving as an example or illustration.” Any aspect or design described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other aspects or designs.

Claims
  • 1. A computer-implemented method comprising: receiving, at a network controller, multicast traffic statistics from each of a plurality of switches in a computer network;aggregating, by the network controller, the multicast traffic statistics into a time-series database;automatically identifying, by the network controller, a low-performing multicast flow, based on the time-series database, wherein the low-performing multicast flow is associated with a source switch; andreconfiguring the computer network to improve the low-performing multicast flow;wherein identifying the low-performing multicast flow further comprises computing a total packet throughput for one or more forwarding tag (FTAG) and port pairs.
  • 2. The computer-implemented method of claim 1, wherein reconfiguring the computer network further comprises: determining, by the network controller, if a multicast root corresponding with the low-performing multicast flow can be transferred to a destination switch in the computer network; andreconfiguring the source switch and the destination switch to transfer the multicast root to the destination switch.
  • 3. The computer-implemented method of claim 2, wherein reconfiguring the source switch and the destination switch further comprises: providing an alert to a network administrator, via the network controller, the alert indicating a recommended network configuration to improve the low-performing multicast flow; andreceiving a response from the network administrator, the response indicating either an approval or rejection of the recommended network configuration.
  • 4. The computer-implemented method of claim 1, wherein reconfiguring the computer network further comprises: automatically pruning one or more links associated with the low-performing multicast flow.
  • 5. The computer-implemented method of claim 1, wherein reconfiguring the computer network further comprises: automatically pruning a multicast tree associated with the low-performing multicast flow.
  • 6. A network controller for improving multicast traffic flows, comprising: one or more processors; anda non-transitory computer-readable medium comprising instructions stored therein, which when executed by the processors, cause the processors to perform operations comprising: receiving multicast traffic statistics from each of a plurality of switches in a computer network;aggregating the multicast traffic statistics into a time-series database;automatically identifying a low-performing multicast flow, based on the time-series database, wherein the low-performing multicast flow is associated with a source switch; andreconfiguring the computer network to improve the low-performing multicast flow;wherein identifying the low-performing multicast flow comprises computing a total packet throughput for one or more forwarding tag (FTAG) and port pairs.
  • 7. The network controller of claim 6, wherein reconfiguring the computer network further comprises: determining if a multicast root corresponding with the low-performing multicast flow can be transferred to a destination switch in the computer network; andreconfiguring the source switch and the destination switch to transfer the multicast root to the destination switch.
  • 8. The network controller of claim 7, wherein reconfiguring the source switch and the destination switch further comprises: providing an alert to a network administrator the alert indicating a recommended network configuration to improve the low-performing multicast flow; andreceiving a response from the network administrator, the response indicating either an approval or rejection of the recommended network configuration.
  • 9. The network controller of claim 6, wherein reconfiguring the computer network further comprises: automatically pruning one or more links associated with the low-performing multicast flow.
  • 10. The network controller of claim 6, wherein reconfiguring the computer network further comprises: automatically pruning a multicast tree associated with the low-performing multicast flow.
  • 11. A non-transitory computer-readable storage medium comprising instructions stored therein, which when executed by one or more processors, cause the processors to perform operations comprising: receiving multicast traffic statistics from each of a plurality of switches in a computer network;aggregating the multicast traffic statistics into a time-series database;automatically identifying a low-performing multicast flow, based on the time-series database, wherein the low-performing multicast flow is associated with a source switch; andreconfiguring the computer network to improve the low-performing multicast flow;wherein identifying the low-performing multicast flow further comprises computing a total packet throughput for one or more forwarding tag (FTAG) and port pairs.
  • 12. The non-transitory computer-readable storage medium of claim 11, wherein reconfiguring the computer network further comprises: determining if a multicast root corresponding with the low-performing multicast flow can be transferred to a destination switch in the computer network; andreconfiguring the source switch and the destination switch to transfer the multicast root to the destination switch.
  • 13. The non-transitory computer-readable storage medium of claim 12, wherein reconfiguring the source switch and the destination switch further comprises: providing an alert to a network administrator, the alert indicating a recommended network configuration to improve the low-performing multicast flow; andreceiving a response from the network administrator, the response indicating either an approval or rejection of the recommended network configuration.
  • 14. The non-transitory computer-readable storage medium of claim 11, wherein reconfiguring the computer network further comprises: automatically pruning one or more links associated with the low-performing multicast flow.
  • 15. The non-transitory computer-readable storage medium of claim 11, wherein reconfiguring the computer network further comprises: automatically pruning a multicast tree associated with the low-performing multicast flow.
CROSS-REFERENCE TO RELATED APPLICATION

The instant application is a Continuation of, and claims priority to, U.S. patent application Ser. No. 15/658,945 entitled DETECTING AND RESOLVING MULTICAST TRAFFIC PERFORMANCE ISSUES filed Jul. 25, 2017, the contents of which are herein incorporated by reference in its entirety.

US Referenced Citations (422)
Number Name Date Kind
5812773 Norin Sep 1998 A
5889896 Meshinsky et al. Mar 1999 A
6108782 Fletcher et al. Aug 2000 A
6178453 Mattaway et al. Jan 2001 B1
6298153 Oishi Oct 2001 B1
6343290 Cossins et al. Jan 2002 B1
6643260 Kloth et al. Nov 2003 B1
6683873 Kwok et al. Jan 2004 B1
6721804 Rubin et al. Apr 2004 B1
6733449 Krishnamurthy et al. May 2004 B1
6735631 Oehrke et al. May 2004 B1
6996615 McGuire Feb 2006 B1
7054930 Cheriton May 2006 B1
7058706 Lyer et al. Jun 2006 B1
7062571 Dale et al. Jun 2006 B1
7111177 Chauvel et al. Sep 2006 B1
7212490 Kao et al. May 2007 B1
7277948 Igarashi et al. Oct 2007 B2
7313667 Pullela et al. Dec 2007 B1
7379846 Williams et al. May 2008 B1
7480672 Hahn et al. Jan 2009 B2
7496043 Leong et al. Feb 2009 B1
7536476 Alleyne May 2009 B1
7567504 Darling et al. Jul 2009 B2
7583665 Duncan et al. Sep 2009 B1
7606147 Luft et al. Oct 2009 B2
7644437 Volpano Jan 2010 B2
7647594 Togawa Jan 2010 B2
7773510 Back et al. Aug 2010 B2
7808897 Mehta et al. Oct 2010 B1
7881957 Cohen et al. Feb 2011 B1
7917647 Cooper et al. Mar 2011 B2
8010598 Tanimoto Aug 2011 B2
8028071 Mahalingam et al. Sep 2011 B1
8041714 Aymeloglu et al. Oct 2011 B2
8121117 Amdahl et al. Feb 2012 B1
8171415 Appleyard et al. May 2012 B2
8234377 Cohn Jul 2012 B2
8244559 Horvitz et al. Aug 2012 B2
8250215 Stienhans et al. Aug 2012 B2
8280880 Aymeloglu et al. Oct 2012 B1
8284664 Aybay et al. Oct 2012 B1
8301746 Head et al. Oct 2012 B2
8345692 Smith Jan 2013 B2
8406141 Couturier et al. Mar 2013 B1
8407413 Yucel et al. Mar 2013 B1
8448171 Donnellan et al. May 2013 B2
8477610 Zuo et al. Jul 2013 B2
8495356 Ashok et al. Jul 2013 B2
8495725 Ahn Jul 2013 B2
8510469 Portolani Aug 2013 B2
8514868 Hill Aug 2013 B2
8532108 Li et al. Sep 2013 B2
8533687 Greifeneder et al. Sep 2013 B1
8547974 Guruswamy et al. Oct 2013 B1
8560639 Murphy et al. Oct 2013 B2
8560663 Baucke et al. Oct 2013 B2
8589543 Dutta et al. Nov 2013 B2
8590050 Nagpal et al. Nov 2013 B2
8611356 Yu et al. Dec 2013 B2
8612625 Andreis et al. Dec 2013 B2
8630291 Shaffer et al. Jan 2014 B2
8639787 Lagergren et al. Jan 2014 B2
8656024 Krishnan et al. Feb 2014 B2
8660129 Brendel et al. Feb 2014 B1
8719804 Jain May 2014 B2
8775576 Hebert et al. Jul 2014 B2
8797867 Chen et al. Aug 2014 B1
8805951 Faibish et al. Aug 2014 B1
8850002 Dickinson et al. Sep 2014 B1
8850182 Fritz et al. Sep 2014 B1
8856339 Mestery et al. Oct 2014 B2
8909928 Ahmad et al. Dec 2014 B2
8918510 Gmach et al. Dec 2014 B2
8924720 Raghuram et al. Dec 2014 B2
8930747 Levijarvi et al. Jan 2015 B2
8938775 Roth et al. Jan 2015 B1
8959526 Kansal et al. Feb 2015 B2
8977754 Curry, Jr. et al. Mar 2015 B2
9009697 Breiter et al. Apr 2015 B2
9015324 Jackson Apr 2015 B2
9043439 Bicket et al. May 2015 B2
9049115 Rajendran et al. Jun 2015 B2
9063789 Beaty et al. Jun 2015 B2
9065727 Liu et al. Jun 2015 B1
9075649 Bushman et al. Jul 2015 B1
9130846 Szabo et al. Sep 2015 B1
9164795 Vincent Oct 2015 B1
9167050 Durazzo et al. Oct 2015 B2
9201701 Boldyrev et al. Dec 2015 B2
9201704 Chang et al. Dec 2015 B2
9203784 Chang et al. Dec 2015 B2
9223634 Chang et al. Dec 2015 B2
9244776 Koza et al. Jan 2016 B2
9251114 Ancin et al. Feb 2016 B1
9264478 Hon et al. Feb 2016 B2
9294408 Dickinson et al. Mar 2016 B1
9313048 Chang et al. Apr 2016 B2
9361192 Smith et al. Jun 2016 B2
9379982 Krishna et al. Jun 2016 B1
9380075 He et al. Jun 2016 B2
9432245 Sorenson, III et al. Aug 2016 B1
9432294 Sharma et al. Aug 2016 B1
9444744 Sharma et al. Sep 2016 B1
9473365 Melander et al. Oct 2016 B2
9503530 Niedzielski Nov 2016 B1
9558078 Farlee et al. Jan 2017 B2
9571570 Mutnuru Feb 2017 B1
9613078 Vermeulen et al. Apr 2017 B2
9628471 Sundaram et al. Apr 2017 B1
9658876 Chang et al. May 2017 B2
9692802 Bicket et al. Jun 2017 B2
9755858 Bagepalli et al. Sep 2017 B2
10541866 Sharpless Jan 2020 B2
20010055303 Horton et al. Dec 2001 A1
20020073337 Ioele et al. Jun 2002 A1
20020143928 Maltz et al. Oct 2002 A1
20020166117 Abrams et al. Nov 2002 A1
20020174216 Shorey et al. Nov 2002 A1
20030018591 Komisky Jan 2003 A1
20030056001 Mate et al. Mar 2003 A1
20030228585 Inoko et al. Dec 2003 A1
20040004941 Malan et al. Jan 2004 A1
20040034702 He Feb 2004 A1
20040088542 Daude et al. May 2004 A1
20040095237 Chen et al. May 2004 A1
20040131059 Ayyakad et al. Jul 2004 A1
20040197079 Latvala et al. Oct 2004 A1
20040264481 Darling et al. Dec 2004 A1
20050060418 Sorokopud Mar 2005 A1
20050125424 Herriott et al. Jun 2005 A1
20060062187 Rune Mar 2006 A1
20060104286 Cheriton May 2006 A1
20060126665 Ward et al. Jun 2006 A1
20060146825 Hofstaedter et al. Jul 2006 A1
20060155875 Cheriton Jul 2006 A1
20060168338 Bruegl et al. Jul 2006 A1
20060233106 Achlioptas et al. Oct 2006 A1
20070174663 Crawford et al. Jul 2007 A1
20070223487 Kajekar et al. Sep 2007 A1
20070242830 Conrado et al. Oct 2007 A1
20080005293 Bhargava et al. Jan 2008 A1
20080080524 Tsushima et al. Apr 2008 A1
20080084880 Dharwadkar Apr 2008 A1
20080165778 Ertemalp Jul 2008 A1
20080198752 Fan et al. Aug 2008 A1
20080198858 Townsley et al. Aug 2008 A1
20080201711 Amir Husain Aug 2008 A1
20080235755 Blaisdell et al. Sep 2008 A1
20090006527 Gingell, Jr. et al. Jan 2009 A1
20090019367 Cavagnari et al. Jan 2009 A1
20090031312 Mausolf et al. Jan 2009 A1
20090083183 Rao et al. Mar 2009 A1
20090138763 Arnold May 2009 A1
20090177775 Radia et al. Jul 2009 A1
20090178058 Stillwell, III et al. Jul 2009 A1
20090182874 Morford et al. Jul 2009 A1
20090265468 Annambhotla et al. Oct 2009 A1
20090265753 Anderson et al. Oct 2009 A1
20090293056 Ferris Nov 2009 A1
20090300608 Ferris et al. Dec 2009 A1
20090313562 Appleyard et al. Dec 2009 A1
20090323706 Germain et al. Dec 2009 A1
20090328031 Pouyadou et al. Dec 2009 A1
20100036903 Ahmad et al. Feb 2010 A1
20100042720 Stienhans et al. Feb 2010 A1
20100061250 Nugent Mar 2010 A1
20100115341 Baker et al. May 2010 A1
20100131765 Bromley et al. May 2010 A1
20100149966 Achlioptas et al. Jun 2010 A1
20100191783 Mason et al. Jul 2010 A1
20100192157 Jackson et al. Jul 2010 A1
20100205601 Abbas et al. Aug 2010 A1
20100211782 Auradkar et al. Aug 2010 A1
20100293270 Augenstein et al. Nov 2010 A1
20100318609 Lahiri et al. Dec 2010 A1
20100325199 Park et al. Dec 2010 A1
20100325441 Laurie et al. Dec 2010 A1
20100333116 Prahlad et al. Dec 2010 A1
20110016214 Jackson Jan 2011 A1
20110035754 Srinivasan Feb 2011 A1
20110055396 Dehaan Mar 2011 A1
20110055398 Dehaan et al. Mar 2011 A1
20110055470 Portolani Mar 2011 A1
20110072489 Parann-Nissany Mar 2011 A1
20110075667 Li et al. Mar 2011 A1
20110110382 Jabr et al. May 2011 A1
20110116443 Yu et al. May 2011 A1
20110126099 Anderson et al. May 2011 A1
20110138055 Daly et al. Jun 2011 A1
20110145413 Dawson et al. Jun 2011 A1
20110145657 Bishop et al. Jun 2011 A1
20110173303 Rider Jul 2011 A1
20110185063 Head et al. Jul 2011 A1
20110185065 Stanisic et al. Jul 2011 A1
20110206052 Tan et al. Aug 2011 A1
20110213966 Fu et al. Sep 2011 A1
20110219434 Betz et al. Sep 2011 A1
20110231715 Kunii et al. Sep 2011 A1
20110231899 Pulier et al. Sep 2011 A1
20110239039 Dieffenbach et al. Sep 2011 A1
20110252327 Awasthi et al. Oct 2011 A1
20110261811 Battestilli et al. Oct 2011 A1
20110261828 Smith Oct 2011 A1
20110276675 Singh et al. Nov 2011 A1
20110276951 Jain Nov 2011 A1
20110283013 Grosser et al. Nov 2011 A1
20110295998 Ferris et al. Dec 2011 A1
20110305149 Scott et al. Dec 2011 A1
20110307531 Gaponenko et al. Dec 2011 A1
20110320870 Kenigsberg et al. Dec 2011 A1
20120005724 Lee Jan 2012 A1
20120036234 Staats et al. Feb 2012 A1
20120054367 Ramakrishnan et al. Mar 2012 A1
20120072318 Akiyama et al. Mar 2012 A1
20120072578 Alam Mar 2012 A1
20120072581 Tung et al. Mar 2012 A1
20120072985 Davne et al. Mar 2012 A1
20120072992 Arasaratnam et al. Mar 2012 A1
20120084445 Brock et al. Apr 2012 A1
20120084782 Chou et al. Apr 2012 A1
20120096134 Suit Apr 2012 A1
20120102193 Rathore et al. Apr 2012 A1
20120102199 Hopmann et al. Apr 2012 A1
20120131174 Ferris et al. May 2012 A1
20120137215 Kawara May 2012 A1
20120158967 Sedayao et al. Jun 2012 A1
20120159097 Jennas, II et al. Jun 2012 A1
20120167094 Suit Jun 2012 A1
20120173710 Rodriguez Jul 2012 A1
20120179909 Sagi et al. Jul 2012 A1
20120180044 Donnellan et al. Jul 2012 A1
20120182891 Lee et al. Jul 2012 A1
20120185913 Martinez et al. Jul 2012 A1
20120192016 Gotesdyner et al. Jul 2012 A1
20120192075 Ebtekar et al. Jul 2012 A1
20120201135 Ding et al. Aug 2012 A1
20120214506 Skaaksrud et al. Aug 2012 A1
20120222106 Kuehl Aug 2012 A1
20120236716 Anbazhagan et al. Sep 2012 A1
20120240113 Hur Sep 2012 A1
20120265976 Spiers et al. Oct 2012 A1
20120272025 Park et al. Oct 2012 A1
20120281706 Agarwal et al. Nov 2012 A1
20120281708 Chauhan et al. Nov 2012 A1
20120290647 Ellison et al. Nov 2012 A1
20120297238 Watson et al. Nov 2012 A1
20120311106 Morgan Dec 2012 A1
20120311568 Jansen Dec 2012 A1
20120324092 Brown et al. Dec 2012 A1
20120324114 Dutta et al. Dec 2012 A1
20130003567 Gallant et al. Jan 2013 A1
20130013248 Brugler et al. Jan 2013 A1
20130036213 Hasan et al. Feb 2013 A1
20130044636 Koponen et al. Feb 2013 A1
20130066940 Shao Mar 2013 A1
20130080509 Wang Mar 2013 A1
20130080624 Nagai et al. Mar 2013 A1
20130091557 Gurrapu Apr 2013 A1
20130097601 Podvratnik et al. Apr 2013 A1
20130104140 Meng et al. Apr 2013 A1
20130111540 Sabin May 2013 A1
20130117337 Dunham May 2013 A1
20130124712 Parker May 2013 A1
20130125124 Kempf et al. May 2013 A1
20130138816 Kuo et al. May 2013 A1
20130144978 Jain et al. Jun 2013 A1
20130152076 Patel Jun 2013 A1
20130152175 Hromoko et al. Jun 2013 A1
20130159097 Schory et al. Jun 2013 A1
20130159496 Hamilton et al. Jun 2013 A1
20130160008 Cawlfield et al. Jun 2013 A1
20130162753 Hendrickson et al. Jun 2013 A1
20130169666 Pacheco et al. Jul 2013 A1
20130179941 McGloin et al. Jul 2013 A1
20130182712 Aguayo et al. Jul 2013 A1
20130185433 Zhu et al. Jul 2013 A1
20130191106 Kephart et al. Jul 2013 A1
20130198374 Zalmanovitch et al. Aug 2013 A1
20130201989 Hu et al. Aug 2013 A1
20130204849 Chacko Aug 2013 A1
20130232491 Radhakrishnan et al. Sep 2013 A1
20130246588 Borowicz et al. Sep 2013 A1
20130250770 Zou et al. Sep 2013 A1
20130254415 Fullen et al. Sep 2013 A1
20130262347 Dodson Oct 2013 A1
20130283364 Chang et al. Oct 2013 A1
20130297769 Chang et al. Nov 2013 A1
20130318240 Hebert et al. Nov 2013 A1
20130318546 Kothuri et al. Nov 2013 A1
20130339949 Spiers et al. Dec 2013 A1
20140006481 Frey et al. Jan 2014 A1
20140006535 Reddy Jan 2014 A1
20140006585 Dunbar et al. Jan 2014 A1
20140040473 Ho et al. Feb 2014 A1
20140040883 Tompkins Feb 2014 A1
20140052877 Mao Feb 2014 A1
20140056146 Hu et al. Feb 2014 A1
20140059310 Du et al. Feb 2014 A1
20140074850 Noel et al. Mar 2014 A1
20140075048 Yuksel et al. Mar 2014 A1
20140075108 Dong et al. Mar 2014 A1
20140075357 Flores et al. Mar 2014 A1
20140075501 Srinivasan et al. Mar 2014 A1
20140089727 Cherkasova et al. Mar 2014 A1
20140098762 Ghai et al. Apr 2014 A1
20140108985 Scott et al. Apr 2014 A1
20140122560 Ramey et al. May 2014 A1
20140136779 Guha et al. May 2014 A1
20140140211 Chandrasekaran et al. May 2014 A1
20140141720 Princen et al. May 2014 A1
20140156557 Zeng et al. Jun 2014 A1
20140164486 Ravichandran et al. Jun 2014 A1
20140188825 Muthukkaruppan et al. Jul 2014 A1
20140189095 Lindberg et al. Jul 2014 A1
20140189125 Amies et al. Jul 2014 A1
20140215471 Cherkasova Jul 2014 A1
20140222953 Karve et al. Aug 2014 A1
20140244851 Lee Aug 2014 A1
20140245298 Zhou et al. Aug 2014 A1
20140281173 Im et al. Sep 2014 A1
20140282536 Dave et al. Sep 2014 A1
20140282611 Campbell et al. Sep 2014 A1
20140282889 Ishaya et al. Sep 2014 A1
20140289200 Kato Sep 2014 A1
20140295831 Karra et al. Oct 2014 A1
20140297569 Clark et al. Oct 2014 A1
20140297835 Buys Oct 2014 A1
20140310391 Sorensen, III et al. Oct 2014 A1
20140310417 Sorensen, III et al. Oct 2014 A1
20140310418 Sorensen, III et al. Oct 2014 A1
20140314078 Jilani Oct 2014 A1
20140317261 Shatzkamer et al. Oct 2014 A1
20140321278 Cafarelli et al. Oct 2014 A1
20140330976 van Bemmel Nov 2014 A1
20140330977 van Bemmel Nov 2014 A1
20140334488 Guichard et al. Nov 2014 A1
20140362682 Guichard et al. Dec 2014 A1
20140365680 van Bemmel Dec 2014 A1
20140366155 Chang et al. Dec 2014 A1
20140369204 Anand et al. Dec 2014 A1
20140372567 Ganesh et al. Dec 2014 A1
20140379938 Bosch et al. Dec 2014 A1
20150033086 Sasturkar et al. Jan 2015 A1
20150043576 Dixon et al. Feb 2015 A1
20150052247 Threefoot et al. Feb 2015 A1
20150052517 Raghu et al. Feb 2015 A1
20150058382 St. Laurent et al. Feb 2015 A1
20150058459 Amendjian et al. Feb 2015 A1
20150071285 Kumar et al. Mar 2015 A1
20150085870 Narasimha et al. Mar 2015 A1
20150089082 Patwardhan et al. Mar 2015 A1
20150100471 Curry, Jr. et al. Apr 2015 A1
20150103827 Quinn et al. Apr 2015 A1
20150106802 Ivanov et al. Apr 2015 A1
20150106805 Melander et al. Apr 2015 A1
20150117199 Chinnaiah Sankaran et al. Apr 2015 A1
20150117458 Gurkan et al. Apr 2015 A1
20150120914 Wada et al. Apr 2015 A1
20150124622 Kovvali et al. May 2015 A1
20150138973 Kumar et al. May 2015 A1
20150178133 Phelan et al. Jun 2015 A1
20150189009 van Bemmel Jul 2015 A1
20150215819 Bosch et al. Jul 2015 A1
20150227405 Jan et al. Aug 2015 A1
20150242204 Hassine et al. Aug 2015 A1
20150249709 Teng et al. Sep 2015 A1
20150263901 Kumar et al. Sep 2015 A1
20150280980 Bitar Oct 2015 A1
20150281067 Wu Oct 2015 A1
20150281113 Siciliano et al. Oct 2015 A1
20150309908 Pearson et al. Oct 2015 A1
20150319063 Zourzouvillys et al. Nov 2015 A1
20150326524 Tankala et al. Nov 2015 A1
20150339210 Kopp et al. Nov 2015 A1
20150358850 La Roche, Jr. et al. Dec 2015 A1
20150365324 Kumar et al. Dec 2015 A1
20150373108 Fleming et al. Dec 2015 A1
20160011925 Kulkarni et al. Jan 2016 A1
20160013990 Kulkarni et al. Jan 2016 A1
20160026684 Mukherjee et al. Jan 2016 A1
20160062786 Meng et al. Mar 2016 A1
20160094389 Jain et al. Mar 2016 A1
20160094398 Choudhury et al. Mar 2016 A1
20160094453 Jain et al. Mar 2016 A1
20160094454 Jain et al. Mar 2016 A1
20160094455 Jain et al. Mar 2016 A1
20160094456 Jain et al. Mar 2016 A1
20160094480 Kulkarni et al. Mar 2016 A1
20160094643 Jain et al. Mar 2016 A1
20160099847 Melander et al. Apr 2016 A1
20160099853 Nedeltchev et al. Apr 2016 A1
20160099864 Akiya et al. Apr 2016 A1
20160105393 Thakkar et al. Apr 2016 A1
20160127184 Bursell May 2016 A1
20160134557 Steinder et al. May 2016 A1
20160156708 Jalan et al. Jun 2016 A1
20160164780 Timmons et al. Jun 2016 A1
20160164914 Madhav et al. Jun 2016 A1
20160182378 Basavaraja et al. Jun 2016 A1
20160188527 Cherian et al. Jun 2016 A1
20160234071 Nambiar et al. Aug 2016 A1
20160239399 Babu et al. Aug 2016 A1
20160253078 Ebtekar et al. Sep 2016 A1
20160254968 Ebtekar et al. Sep 2016 A1
20160261564 Foxhoven et al. Sep 2016 A1
20160277368 Narayanaswamy et al. Sep 2016 A1
20170005948 Melander et al. Jan 2017 A1
20170024260 Chandrasekaran et al. Jan 2017 A1
20170026294 Basavaraja et al. Jan 2017 A1
20170026470 Bhargava et al. Jan 2017 A1
20170041342 Efremov et al. Feb 2017 A1
20170054659 Ergin et al. Feb 2017 A1
20170097841 Chang et al. Apr 2017 A1
20170099188 Chang et al. Apr 2017 A1
20170104755 Arregoces et al. Apr 2017 A1
20170147297 Krishnamurthy et al. May 2017 A1
20170149878 Mutnuru May 2017 A1
20170163531 Kumar et al. Jun 2017 A1
20170171158 Hoy et al. Jun 2017 A1
20170264663 Bicket et al. Sep 2017 A1
20170339070 Chang et al. Nov 2017 A1
Foreign Referenced Citations (13)
Number Date Country
101719930 Jun 2010 CN
101394360 Jul 2011 CN
102164091 Aug 2011 CN
104320342 Jan 2015 CN
105740084 Jul 2016 CN
2228716 Sep 2010 EP
2439637 Apr 2012 EP
2645253 Nov 2014 EP
10-2015-0070676 May 2015 KR
M394537 Dec 2010 TW
WO 2009155574 Dec 2009 WO
WO 2010030915 Mar 2010 WO
WO 2013158707 Oct 2013 WO
Non-Patent Literature Citations (66)
Entry
Amedro, Brian, et al., “An Efficient Framework for Running Applications on Clusters, Grids and Cloud,” 2010, 17 pages.
Author Unknown, “5 Benefits of a Storage Gateway in the Cloud,” Blog, TwinStrata, Inc., Jul. 25, 2012, XP055141645, 4 pages, https://web.archive.org/web/20120725092619/http://blog.twinstrata.com/2012/07/10//5-benefits-of-a-storage-gateway-in-the-cloud.
Author Unknown, “Joint Cisco and VMWare Solution for Optimizing Virtual Desktop Delivery: Data Center 3.0: Solutions to Accelerate Data Center Virtualization,” Cisco Systems, Inc. and VMware, Inc., Sep. 2008, 10 pages.
Author Unknown, “A Look at DeltaCloud: The Multi-Cloud API,” Feb. 17, 2012, 4 pages.
Author Unknown, “About Deltacloud,” Apache Software Foundation, Aug. 18, 2013, 1 page.
Author Unknown, “Architecture for Managing Clouds, A White Paper from the Open Cloud Standards Incubator,” Version 1.0.0, Document No. DSP-IS0102, Jun. 18, 2010, 57 pages.
Author Unknown, “Cloud Infrastructure Management Interface—Common Information Model (CIMI—CIM),” Document No. DSP0264, Version 1.0.0, Dec. 14, 2012, 21 pages.
Author Unknown, “Cloud Infrastructure Management Interface (CIMI) Primer,” Document No. DSP2027, Version 1.0.1, Sep. 12, 2012, 30 pages.
Author Unknown, “cloudControl Documentation,” Aug. 25, 2013, 14 pages.
Author Unknown, “Interoperable Clouds, A White Paper from the Open Cloud Standards Incubator,” Version 1.0.0, Document No. DSP-IS0101, Nov. 11, 2009, 21 pages.
Author Unknown, “Microsoft Cloud Edge Gateway (MCE) Series Appliance,” Iron Networks, Inc., 2014, 4 pages.
Author Unknown, “Open Data Center Alliance Usage: Virtual Machine (VM) Interoperability in a Hybrid Cloud Environment Rev. 1.2,” Open Data Center Alliance, Inc., 2013, 18 pages.
Author Unknown, “Real-Time Performance Monitoring on Juniper Networks Devices, Tips and Tools for Assessing and Analyzing Network Efficiency,” Juniper Networks, Inc., May 2010, 35 pages.
Author Unknown, “Use Cases and Interactions for Managing Clouds, A White Paper from the Open Cloud Standards Incubator,” Version 1.0.0, Document No. DSP-IS00103, Jun. 16, 2010, 75 pages.
Author Unknown, “Apache Ambari Meetup What's New,” Hortonworks Inc., Sep. 2013, 28 pages.
Author Unknown, “Introduction,” Apache Ambari project, Apache Software Foundation, 2014, 1 page.
Baker, F., “Requirements for IP Version 4 Routers,” Jun. 1995, 175 pages, Network Working Group, Cisco Systems.
Beyer, Steffen, “Module “Data::Locations?!”,” YAPC::Europe, London, UK,ICA, Sep. 22-24, 2000, XP002742700, 15 pages.
Blanchet, M., “A Flexible Method for Managing the Assignment of Bits of an IPv6 Address Block,” Apr. 2003, 8 pages, Network Working Group, Viagnie.
Borovick, Lucinda, et al., “Architecting the Network for the Cloud,” IDC White Paper, Jan. 2011, 8 pages.
Bosch, Greg, “Virtualization,” last modified Apr. 2012 by B. Davison, 33 pages.
Broadcasters Audience Research Board, “What's Next,” http://lwww.barb.co.uk/whats-next, accessed Jul. 22, 2015, 2 pages.
Cisco Systems, Inc. “Best Practices in Deploying Cisco Nexus 1000V Series Switches on Cisco UCS B and C Series Cisco UCS Manager Servers,” Cisco White Paper, Apr. 2011, 36 pages, http://www.cisco.com/en/US/prod/collateral/switches/ps9441/ps9902/white_paper_c11-558242.pdf.
Cisco Systems, Inc., “Cisco Unified Network Services: Overcome Obstacles to Cloud-Ready Deployments,” Cisco White Paper, Jan. 2011, 6 pages.
Cisco Systems, Inc., “Cisco Intercloud Fabric: Hybrid Cloud with Choice, Consistency, Control and Compliance,” Dec. 10, 2014, 22 pages.
Cisco Technology, Inc., “Cisco Expands Videoscape TV Platform Into the Cloud,” Jan. 6, 2014, Las Vegas, Nevada, Press Release, 3 pages.
Citrix, “Citrix StoreFront 2.0” White Paper, Proof of Concept Implementation Guide, Citrix Systems, Inc., 2013, 48 pages.
Citrix, “CloudBridge for Microsoft Azure Deployment Guide,” 30 pages.
Citrix, “Deployment Practices and Guidelines for NetScaler 10.5 on Amazon Web Services,” White Paper, citrix.com, 2014, 14 pages.
CSS Corp, “Enterprise Cloud Gateway (ECG)—Policy driven framework for managing multi-cloud environments,” original published on or about Feb. 11, 2012; 1 page; http://www.css-cloud.com/platform/enterprise-cloud-gateway.php.
Fang K., “LISP MAC-EID-TO-RLOC Mapping (LISP based L2VPN),” Network Working Group, Internet Draft, Cisco Systems, Jan. 2012, 12 pages.
Ford, Bryan, et al., Peer-to-Peer Communication Across Network Address Translators, in USENIX Annual Technical Conference, 2005, pp. 179-192.
Gedymin, Adam, “Cloud Computing with an emphasis on Google App Engine,” Sep. 2011, 146 pages.
Good, Nathan A., “Use Apache Deltacloud to administer multiple instances with a single API,” Dec. 17, 2012, 7 pages.
Herry, William, “Keep It Simple, Stupid: OpenStack nova-scheduler and its algorithm”, May 12, 2012, IBM, 12 pages.
Hewlett-Packard Company, “Virtual context management on network devices”, Research Disclosure, vol. 564, No. 60, Apr. 1, 2011, Mason Publications, Hampshire, GB, Apr. 1, 2011, 524.
Juniper Networks, Inc., “Recreating Real Application Traffic in Junosphere Lab,” Solution Brief, Dec. 2011, 3 pages.
Kenhui, “Musings on Cloud Computing and IT-as-a-Service: [Updated for Havana] Openstack Computer for VSphere Admins, Part 2: Nova-Scheduler and DRS”, Jun. 26, 2013, Cloud Architect Musings, 12 pages.
Kolyshkin, Kirill, “Virtualization in Linux,” Sep. 1, 2006, XP055141648, 5 pages, https://web.archive.org/web/20070120205111/http://download.openvz.org/doc/openvz-intro.pdf.
Kumar, S., et al., “Infrastructure Service Forwarding for NSH,” Service Function Chaining Internet Draft, draft-kumar-sfc-nsh-forwarding-00, Dec. 5, 2015, 10 pages.
Kunz, Thomas, et al., “OmniCloud—The Secure and Flexible Use of Cloud Storage Services,” 2014, 30 pages.
Lerach, S.R.O., “Golem,” http://www.lerach.cz/en/products/golem, accessed Jul. 22, 2015, 2 pages.
Linthicum, David, “VM Import could be a game changer for hybrid clouds”, InfoWorld, Dec. 23, 2010, 4 pages.
Logan, Marcus, “Hybrid Cloud Application Architecture for Elastic Java-Based Web Applications,” F5 Deployment Guide Version 1.1, 2016, 65 pages.
Lynch, Sean, “Monitoring cache with Claspin” Facebook Engineering, Sep. 19, 2012, 5 pages.
Meireles, Fernando Miguel Dias, “Integrated Management of Cloud Computing Resources,” 2013-2014, 286 pages.
Meraki, “meraki releases industry's first cloud-managed routers,” Jan. 13, 2011, 2 pages.
Mu, Shuai, et al., “uLibCloud: Providing High Available and Uniform Accessing to Multiple Cloud Storages,” 2012 IEEE, 8 pages.
Naik, Vijay K., et al., “Harmony: A Desktop Grid for Delivering Enterprise Computations,” Grid Computing, 2003, Fourth International Workshop on Proceedings, Nov. 17, 2003, pp. 1-11.
Nair, Srijith K. et al., “Towards Secure Cloud Bursting, Brokerage and Aggregation,” 2012, 8 pages, www.flexiant.com.
Nielsen, “SimMetry Audience Measurement—Technology,” http://www.nielsen-admosohere.eu/products-and-services/simmetry-audience-measurement-technology/, accessed Jul. 22, 2015, 6 pages.
Nielsen, “Television,” http://www.nielsen.com/us/en/solutions/measurement/television.html, accessed Jul. 22, 2015, 4 pages.
Open Stack, “Filter Scheduler,” updated Dec. 17, 2017, 5 pages, accessed on Dec. 18, 2017, https://docs.openstack.org/nova/latest/user/filter-scheduler.html.
Quinn, P., et al., “Network Service Header,” Internet Engineering Task Force Draft, Jul. 3, 2014, 27 pages.
Quinn, P., et al., “Service Function Chaining (SFC) Architecture,” Network Working Group, Internet Draft, draft-quinn-sfc-arch-03.txt, Jan. 22, 2014, 21 pages.
Rabadan, J., et al., “Operational Aspects of Proxy-ARP/ND in EVPN Networks,” BESS Worksgroup Internet Draft, draft-snr-bess-evpn-proxy-arp-nd-02, Oct. 6, 2015, 22 pages.
Saidi, Ali, et al., “Performance Validation of Network-Intensive Workloads on a Full-System Simulator,” Interaction between Operating System and Computer Architecture Workshop, (IOSCA 2005), Austin, Texas, Oct. 2005, 10 pages.
Shunra, “Shunra for HP Software; Enabling Confidence in Application Performance Before Deployment,” 2010, 2 pages.
Son, Jungmin, “Automatic decision system for efficient resource selection and allocation in inter-clouds,” Jun. 2013, 35 pages.
Sun, Aobing, et al., “IaaS Public Cloud Computing Platform Scheduling Model and Optimization Analysis,” Int. J. Communications, Network and System Sciences, 2011, 4, 803-811, 9 pages.
Szymaniak, Michal, et al., “Latency-Driven Replica Placement”, vol. 47 No. 8, IPSJ Journal, Aug. 2006, 12 pages.
Toews, Everett, “Introduction to Apache jclouds,” Apr. 7, 2014, 23 pages.
Von Laszewski, Gregor, et al., “Design of a Dynamic Provisioning System for a Federated Cloud and Bare-metal Environment,” 2012, 8 pages.
Wikipedia, “Filter (software)”, Wikipedia, Feb. 8, 2014, 2 pages, https://en.wikipedia.org/w/index.php?title=Filter_%28software%29&oldid=594544359.
Wikipedia; “Pipeline (Unix)”, Wikipedia, May 4, 2014, 4 pages, https://en.wikipedia.org/w/index.php?title=Pipeline2/028Unix%29&oldid=606980114.
Ye, Xianglong, et al., “A Novel Blocks Placement Strategy for Hadoop,” 2012 IEEE/ACTS 11th International Conference on Computer and Information Science, 2012 IEEE, 5 pages.
Related Publications (1)
Number Date Country
20200112481 A1 Apr 2020 US
Continuations (1)
Number Date Country
Parent 15658945 Jul 2017 US
Child 16711997 US