The present invention relates generally to communication networks, and particularly to methods and systems for forwarding of adaptive-routing notifications.
Various techniques for routing packets through communication networks are known in the art. Some known techniques select routing paths for packets based on the network state, e.g., traffic load or congestion. Such techniques are sometimes referred to as Adaptive Routing (AR). For example, U.S. Pat. No. 8,576,715, whose disclosure is incorporated herein by reference, describes a method for communication that includes routing a first packet, which belongs to a given packet flow, over a first routing path through a communication network. A second packet, which follows the first packet in the given packet flow, is routed using a time-bounded Adaptive Routing (AR) mode, by evaluating a time gap between the first and second packets, routing the second packet over the first routing path if the time gap does not exceed a predefined threshold, and, if the time gap exceeds the predefined threshold, selecting a second routing path through the communication network that is potentially different from the first routing path, and routing the second packet over the second routing path.
U.S. Patent Application Publication 2015/0372916, whose disclosure is incorporated herein by reference, describes a network element that includes circuitry and one or more interfaces. The interfaces are configured to connect to a communication network. The circuitry is configured to assign multiple egress interfaces corresponding to respective different paths via the communication network for routing packets to a given destination-address group, to hold, for the given destination-address group, respective state information for each of multiple sets of hash results, to receive via an ingress interface a packet destined to the given destination-address group, to calculate a given hash result for the packet and identify a given set of hash results in which the given hash result falls, and to forward the packet via one of the multiple egress interfaces in accordance with the state information corresponding to the given destination-address group and the given set of hash results.
U.S. Pat. No. 9,014,006 and U.S. Patent Application Publication 2015/0195204, whose disclosures are incorporated herein by reference, describe a method including receiving in a network switch of a communication network communication traffic that originates from a source node and arrives over a route through the communication network traversing one or more preceding network switches, for forwarding to a destination node. In response to detecting in the network switch a compromised ability to forward the communication traffic to the destination node, a notification is sent to the preceding network switches. The notification is to be consumed by the preceding network switches and requests the preceding network switches to modify the route so as not to traverse the network switch.
An embodiment that is described herein provides a method for communication including, in a first network switch that is part of a communication network having a topology, detecting a compromised ability to forward a flow of packets originating from a source endpoint to a destination endpoint. In response to detecting the compromised ability, the first network switch identifies, based on the topology, a second network switch that lies on a current route of the flow, and also lies on one or more alternative routes from the source endpoint to the destination endpoint that do not traverse the first network switch. A notification, which is addressed individually to the second network switch and requests the second network switch to reroute the flow, is sent from the first network switch.
In some embodiments, the method further includes receiving the notification by the second network switch, and, in response to the notification, rerouting the flow to one of the alternative routes. In an embodiment, sending the notification includes routing the notification over a route that differs from a reverse of the current route of the flow.
In some embodiments, the topology is a Fat-Tree (FT) topology, in which network switches are arranged in multiple levels including at least a leaf level and a spine level, and in which each route initially traverses an upwards segment that begins at the leaf level and traverses increasing levels, and then traverses a downwards segment that traverses decreasing levels and ends at the leaf level. In an example embodiment, the first network switch belongs to a given level of the FT topology, and identifying the second network switch includes selecting, in an intermediate level that is lower than the given level, an only network switch that lies on the upwards segment of the current route of the flow. In a disclosed embodiment, the intermediate level is one level lower than the given level.
In some embodiments, identifying the second network switch includes holding in the first network switch a data structure that records, per endpoint, a respective network switch in the intermediate level that lies on the upwards segment of a route from that endpoint to the first network switch, and querying the data structure for the network switch associated with the source endpoint. In an embodiment, the data structure is also used for routing packets from the first network switch to destination endpoints. In other embodiments, identifying the second network switch and sending the notification include identifying two or more second switches, and sending respective unicast notifications to the identified two or more second switches.
There is additionally provided, in accordance with an embodiment of the present invention, a network switch in a communication network having a topology. The network switch include multiple ports configured to exchange packets with the communication network, and packet processing circuitry. The packet processing circuitry is configured to detect a compromised ability to forward via the ports a flow of packets originating from a source endpoint to a destination endpoint, to identify, in response to detecting the compromised ability, based on the topology, a second network switch that lies on a current route of the flow, and also lies on one or more alternative routes from the source endpoint to the destination endpoint that do not traverse the network switch, and to send via one of the ports a notification, which is addressed individually to the second network switch and requests the second network switch to reroute the flow.
There is further provided, in accordance with an embodiment of the present invention, a computer software product, the product including a tangible non-transitory computer-readable medium in which program instructions are stored, which instructions, when read by a processor in a first network switch that is part of a communication network having a topology, cause the processor to detect a compromised ability to forward a flow of packets originating from a source endpoint to a destination endpoint, to identify, in response to the compromised ability, based on the topology, a second network switch that lies on a current route of the flow, and also lies on one or more alternative routes from the source endpoint to the destination endpoint that do not traverse the first network switch, and to send from the first network switch a notification, which is addressed individually to the second network switch and requests the second network switch to reroute the flow.
The present invention will be more fully understood from the following detailed description of the embodiments thereof, taken together with the drawings in which:
Embodiments of the present invention that are described herein provide improved methods and systems for adaptive routing of packets in communication networks. The embodiments described herein refer mainly to multi-level full FT networks. The disclosed techniques, however, are also applicable in other suitable network topologies such as quasi-FT networks, networks that use Multi-chassis Link Aggregation (MLAG), and multi-port hosts.
In some embodiments, a FT network comprises multiple interconnected network switches that are arranged in levels. The endpoints, i.e., the hosts served by the network, are connected to the switches in the lowest level, also referred to as leaf switches. The switches in the highest level are referred to as spine switches.
Any route through the FT network comprises an “upwards” segment followed by a “downwards” segment. The upwards segment begins at the leaf switch that serves the source endpoint, and proceeds upwards in the order of levels. The downwards segment proceeds downwards in the order of levels, until reaching the leaf switch that serves the destination endpoint.
As will be shown and demonstrated below, full FT networks have the following properties:
The embodiments described herein provide a high-performance adaptive routing scheme that exploits these properties. The description that follows refers to full FT networks simply as FT networks, for the sake of clarity. Generalization to Quasi-FT and other network topologies is addressed further below.
In some embodiments, a current route is set-up for forwarding a flow of packets from a source endpoint to a destination endpoint. At some point in time, a switch along the downwards segment of the current route identifies congestion on the output port used for forwarding the flow, and is therefore compromised in its ability to continue forwarding the packets of the flow over the current route.
Since the congested switch is part of the downwards segment of a full FT network, it cannot reroute the flow locally via a different port. Instead, the congested switch identifies an alternative switch that will reroute the flow. The identified switch (referred to as the “rerouting switch”) belongs to the next-lower level of the FT network and is part of the upwards segment of the current route. In accordance with the FT properties above, this choice guarantees that the rerouting switch has at least one alternative routing option. Moreover, for the particular congested switch, the identity of the rerouting switch is defined uniquely by the identity of the source endpoint (and thus by the source address specified in the packets of the flow).
Typically, the congested switch holds a database that specifies a respective rerouting switch per source endpoint. The congested switch identifies the rerouting switch by querying the database with the source address extracted from the packets of the flow. In some embodiments the same database already exists in the congested switch, for routing packets in the opposite direction. In such embodiments, the database does not need to be created and maintained for the purpose of adaptive routing. An additional attribute may be added, per source address, specifying the address of the rerouting switch to be selected.
Having identified the rerouting switch, the congested switch generates and sends an Adaptive Routing Notification (ARN) that requests the rerouting switch to reroute the flow. The ARN typically comprises a unicast packet that is addressed individually to the rerouting switch. In response to receiving the ARN, the rerouting switch reroutes the flow to an alternative route that reaches the destination endpoint but does not traverse the congested switch.
Unlike other possible solutions, the techniques described herein do not involve sending a notification hop-by-hop in the reverse direction of the current route, or any multicast notification, in an attempt to find a suitable rerouting switch. Instead, in the disclosed embodiments the congested switch uses its knowledge of the network topology to select the appropriate rerouting switch, and then sends a unicast notification that is addressed to that switch. The disclosed techniques are therefore fast and accurate, and incur little traffic overhead.
Endpoints 32, also referred to as hosts, may comprise any suitable computing platforms such as servers, workstations or personal computers. Network 20 may operate in accordance with any suitable communication protocol, such as Ethernet or Infiniband.
Switches 24 may comprise network switches, routers or any other suitable network elements that route or forward packets. In the context of the present patent application and in the claims, the terms “switch” and “network switch” refer to any such network element. In most of the embodiments described herein, including the example of
An inset at the bottom of
The configurations of network 20 and switches 24 shown in
The different elements of switches 24 may be implemented using any suitable hardware, such as in an Application-Specific Integrated Circuit (ASIC) or Field-Programmable Gate Array (FPGA). Memory 48 may comprise, for example, a Random Access Memory (RAM), a Flash memory or other suitable type of memory. In some embodiments, some elements of switches 24 can be implemented using software, or using a combination of hardware and software elements. In the context of the present patent application and in the claims, fabric 40, control unit 44 and memory 48 are referred to as packet processing circuitry that carries out the disclosed techniques. In alternative embodiments, the packet processing circuitry can be implemented in any other suitable manner.
In some embodiments, control units 44 of switches 24 comprise general-purpose processors, which are programmed in software to carry out the functions described herein. The software may be downloaded to the processors in electronic form, over a network, for example, or it may, alternatively or additionally, be provided and/or stored on non-transitory tangible media, such as magnetic, optical, or electronic memory.
In an FT network, any route from a source endpoint to a destination endpoint comprises an “upwards” segment followed by a “downwards” segment. The upwards segment begins at the switch that serves the source endpoint in the leaf level L0, and proceeds upwards in the order of levels (but not necessarily all the way to the spine level). The downwards segment proceeds downwards in the order of levels, until reaching the switch that serves the destination endpoint in the leaf level L0.
Consider, for example, a route shown in bold in
Generally, the full-FT topology has the following properties:
In some embodiments of the present invention, switches 24 carry out an adaptive routing scheme that exploits the above properties. Consider a flow of packets that originates from a source endpoint S and is destined to a destination endpoint D. The flow is initially routed through FT network 20 along a certain route having an upwards segment and a downwards segment.
In an example embodiment, a switch 24 that lies on the downwards segment of the route encounters congestion at the output port it uses to forward the flow downwards. The congestion prevents the switch from continuing to forward the packets of the flow over the current route. Since the switch in question is on the downwards segment, it cannot choose an alternative route that reaches the same destination endpoint (see PROPERTY I above).
In order to recover from this situation, the switch selects an alternative switch along the current route, and requests the alternative switch to reroute the flow. In the description that follows, the former switch is referred to as the congested switch, and the latter switch is referred to as the rerouting switch.
Because of PROPERTY I above, the rerouting switch should lie on the upwards segment of the current route, so that it will have at least one alternative routing option. In an embodiment, the congested switch is on level X of the FT network. The congested switch chooses a switch in level X−1 that lies on the upwards segment of the current route, to serve as the rerouting switch. In accordance with PROPERTY III above, only a single switch in level X−1 lies on the upwards segment of the current route, and, for a given congested switch, the identity of this rerouting switch is uniquely defined by the identity of the source endpoint (and thus by the source address of the packets in the flow).
In some embodiments, each switch 24 holds a database or any other suitable data structure that records, per source address, the identity of the switch in the next-lower level that will serve as the rerouting switch. The database is typically stored in memory 48 of the switch. Note that a given source address may be mapped to different rerouting switches in the databases of different switches. In a given switch, however, each source address is mapped to a unique respective rerouting switch.
Each switch 24 may use any suitable technique for constructing the database, i.e., for obtaining a mapping between each source address and a respective rerouting switch in the next-lower level. In one embodiment, this mapping already exists in the switch—It is the same mapping used for forwarding packets in the opposite direction to this endpoint. Alternatively, the database may be pre-programmed into each switch, or learned adaptively during operation. In some embodiments, the addressing scheme used in network 20 is location-based, in which case database 24 may be simplified.
Thus, when a need arises to reroute a flow, the congested switch queries its database with the source address of the flow, and retrieves the identity (e.g., the address) of the rerouting switch. The congested switch then generates a notification packet, referred to as “adaptive routing notification (ARN),” “congestion notification” or simply “notification.” The ARN comprises a unicast packet that is addressed individually to the specific rerouting switch selected by the congested switch.
The congested switch sends the ARN to the rerouting switch. The rerouting switch receives the ARN, and in response may reroute the flow to an alternative route that reaches the destination endpoint but does not traverse the congested switch. Note that, since the ARN is addressed explicitly to the rerouting switch, it can be forwarded to the rerouting switch over any desired route, not necessarily over the reverse direction of the route of the flow.
For example, with reference to
At a congestion checking step 64, the switch checks for congestion at the egress port designated for forwarding the packets of the flow. If no congestion exists, the method loops back to step 60 above.
If congestion is detected, the congested switch queries its database to identify the appropriate rerouting switch in level X−1, at a rerouting identification step 68. At a notification step 72, the congested switch generates and sends a unicast ARN, which is addressed individually to the identified rerouting switch. Subsequently, the rerouting switch receives the ARN and reroutes the flow.
In the example above, a congested switch in level X of the FT network selects a rerouting switch in level X−1. In alternative embodiments, a congested switch in level X may select a rerouting switch in any level that is lower than X, e.g., in level X−2 or X−3 (if such levels exist). The latter choice of rerouting switch will also result in a route that does not traverse the congested switch, but may also reroute some additional traffic that did not traverse the congested switch in the first place.
The examples above refer mainly to a congested switch in the downstream segment. In alternative embodiments, the disclosed techniques can also be carried out in a switch that is part of the upstream segment, but is nevertheless unable to reroute the traffic locally. For example, in such a switch all possible egress ports leading to the possible alternative routes may be congested. For example, the aggregate bandwidth over the upstream ports of the switch (the ports connecting to upper-level switches) may be smaller than the aggregate bandwidth over the downstream ports (the ports connecting to lower-level switches). This scenario is sometimes referred to as oversubscription. In such an embodiment, being aware of the network topology, the congested switch may select the previous switch in the upwards segment as the rerouting switch, and send a unicast ARN to that switch.
As noted above, the disclosed techniques are not limited to full FT networks. For example, in some embodiments the disclosed techniques are implemented in a quasi-FT network. Unlike full FT, in a quasi-FT network a switch in the downwards segment of a route may have one or more options for rerouting in case of congestion on the current egress port. In such cases, the terms “congestion” or “compromised ability to forward packets” refers to congestion or compromised ability on all possible egress ports. Moreover, in a quasi-FT network, for a given congested switch and a given source address, there may exist two or more rerouting switches. Thus, in some embodiments the congested switch identifies two or more rerouting switches, and sends a respective unicast ARN to each of them.
In some embodiments, source endpoint S is connected to two or more leaf switches in level L0, for example using different ports of a multi-port Network Interface Controller (NIC) of the endpoint. This sort of configuration is sometimes referred to as Multi-chassis Link Aggregation (MLAG). When using MLAG, packets originating from the source endpoint may enter network 20 via two or more different switches, and thus traverse two or more different routes to the destination endpoint D. Therefore, in these embodiments the congested switch identifies two or more rerouting switches (one per each of the two or more current routes from S to D), and sends the ARN to each of the rerouting switches.
Although the embodiments described herein refer mainly to congestion control, the disclosed techniques can also be used for mitigating failures such as port failure or link failure. In the present context, both congestion and failure are referred to herein as “compromised ability” of a switch to forward packets to a destination endpoint. Upon detecting compromised ability to forward packets, a switch may use the disclosed techniques for identifying a rerouting switch and sending a unicast ARN to the rerouting switch.
It will be appreciated that the embodiments described above are cited by way of example, and that the present invention is not limited to what has been particularly shown and described hereinabove. Rather, the scope of the present invention includes both combinations and sub-combinations of the various features described hereinabove, as well as variations and modifications thereof which would occur to persons skilled in the art upon reading the foregoing description and which are not disclosed in the prior art. Documents incorporated by reference in the present patent application are to be considered an integral part of the application except that to the extent any terms are defined in these incorporated documents in a manner that conflicts with the definitions made explicitly or implicitly in the present specification, only the definitions in the present specification should be considered.
Number | Name | Date | Kind |
---|---|---|---|
4312064 | Bench et al. | Jan 1982 | A |
6115385 | Vig | Sep 2000 | A |
6169741 | Lemaire et al. | Jan 2001 | B1 |
6480500 | Erimli et al. | Nov 2002 | B1 |
6532211 | Rathonyi et al. | Mar 2003 | B1 |
6553028 | Tang et al. | Apr 2003 | B1 |
6614758 | Wong | Sep 2003 | B2 |
6665297 | Harigochi et al. | Dec 2003 | B1 |
6775268 | Wang et al. | Aug 2004 | B1 |
6795886 | Nguyen | Sep 2004 | B1 |
6804532 | Moon et al. | Oct 2004 | B1 |
6807175 | Jennings et al. | Oct 2004 | B1 |
6831918 | Kavak | Dec 2004 | B1 |
6912589 | Jain et al. | Jun 2005 | B1 |
6912604 | Tzeng et al. | Jun 2005 | B1 |
6950428 | Horst et al. | Sep 2005 | B1 |
7010607 | Bunton | Mar 2006 | B1 |
7076569 | Bailey et al. | Jul 2006 | B1 |
7234001 | Simpson et al. | Jun 2007 | B2 |
7274869 | Pan et al. | Sep 2007 | B1 |
7286535 | Ishikawa et al. | Oct 2007 | B2 |
7676597 | Kagan et al. | Mar 2010 | B2 |
7746854 | Ambe et al. | Jun 2010 | B2 |
7899930 | Turner et al. | Mar 2011 | B1 |
7924837 | Shabtay et al. | Apr 2011 | B1 |
7936770 | Frattura et al. | May 2011 | B1 |
7969980 | Florit et al. | Jun 2011 | B1 |
8094569 | Gunukula et al. | Jan 2012 | B2 |
8175094 | Bauchot et al. | May 2012 | B2 |
8195989 | Lu et al. | Jun 2012 | B1 |
8213315 | Crupnicoff et al. | Jul 2012 | B2 |
8401012 | Underwood et al. | Mar 2013 | B2 |
8489718 | Brar et al. | Jul 2013 | B1 |
8495194 | Brar et al. | Jul 2013 | B1 |
8576715 | Bloch et al. | Nov 2013 | B2 |
8605575 | Gunukula et al. | Dec 2013 | B2 |
8621111 | Marr et al. | Dec 2013 | B2 |
8625427 | Terry et al. | Jan 2014 | B1 |
8681641 | Sajassi et al. | Mar 2014 | B1 |
8755389 | Poutievski et al. | Jun 2014 | B1 |
8774063 | Beecroft | Jul 2014 | B2 |
8873567 | Mandal et al. | Oct 2014 | B1 |
8908704 | Koren et al. | Dec 2014 | B2 |
9014006 | Haramaty et al. | Apr 2015 | B2 |
9042234 | Liljenstolpe et al. | May 2015 | B1 |
9571400 | Mandal et al. | Feb 2017 | B1 |
20010043614 | Viswanadham et al. | Nov 2001 | A1 |
20020009073 | Furukawa et al. | Jan 2002 | A1 |
20020013844 | Garrett et al. | Jan 2002 | A1 |
20020026525 | Armitage | Feb 2002 | A1 |
20020039357 | Lipasti et al. | Apr 2002 | A1 |
20020071439 | Reeves et al. | Jun 2002 | A1 |
20020085586 | Tzeng | Jul 2002 | A1 |
20020136163 | Kawakami et al. | Sep 2002 | A1 |
20020138645 | Shinomiya | Sep 2002 | A1 |
20020141412 | Wong | Oct 2002 | A1 |
20020165897 | Kagan et al. | Nov 2002 | A1 |
20020176363 | Durinovic-Johri et al. | Nov 2002 | A1 |
20030016624 | Bare | Jan 2003 | A1 |
20030039260 | Fujisawa | Feb 2003 | A1 |
20030065856 | Kagan et al. | Apr 2003 | A1 |
20030079005 | Myers et al. | Apr 2003 | A1 |
20030097438 | Bearden et al. | May 2003 | A1 |
20030223453 | Stoler et al. | Dec 2003 | A1 |
20040024903 | Costatino et al. | Feb 2004 | A1 |
20040062242 | Wadia et al. | Apr 2004 | A1 |
20040111651 | Mukherjee et al. | Jun 2004 | A1 |
20040202473 | Nakamura et al. | Oct 2004 | A1 |
20050013245 | Sreemanthula et al. | Jan 2005 | A1 |
20050154790 | Nagata et al. | Jul 2005 | A1 |
20050157641 | Roy | Jul 2005 | A1 |
20050259588 | Preguica | Nov 2005 | A1 |
20060126627 | Diouf | Jun 2006 | A1 |
20060143300 | See et al. | Jun 2006 | A1 |
20060182034 | Klinker et al. | Aug 2006 | A1 |
20060215645 | Kangyu | Sep 2006 | A1 |
20060291480 | Cho et al. | Dec 2006 | A1 |
20070030817 | Arunachalam et al. | Feb 2007 | A1 |
20070058536 | Vaananen et al. | Mar 2007 | A1 |
20070058646 | Hermoni | Mar 2007 | A1 |
20070070998 | Sethuram et al. | Mar 2007 | A1 |
20070091911 | Watanabe et al. | Apr 2007 | A1 |
20070104192 | Yoon et al. | May 2007 | A1 |
20070183418 | Riddoch et al. | Aug 2007 | A1 |
20070223470 | Stahl | Sep 2007 | A1 |
20070237083 | Oh et al. | Oct 2007 | A9 |
20080002690 | Ver Steeg et al. | Jan 2008 | A1 |
20080101378 | Krueger | May 2008 | A1 |
20080112413 | Pong | May 2008 | A1 |
20080165797 | Aceves | Jul 2008 | A1 |
20080186981 | Seto et al. | Aug 2008 | A1 |
20080189432 | Abali et al. | Aug 2008 | A1 |
20080267078 | Farinacci et al. | Oct 2008 | A1 |
20080298248 | Roeck et al. | Dec 2008 | A1 |
20090010159 | Brownell et al. | Jan 2009 | A1 |
20090022154 | Kiribe et al. | Jan 2009 | A1 |
20090097496 | Nakamura et al. | Apr 2009 | A1 |
20090103534 | Malledant et al. | Apr 2009 | A1 |
20090119565 | Park et al. | May 2009 | A1 |
20090262741 | Jungck et al. | Oct 2009 | A1 |
20100020796 | Park et al. | Jan 2010 | A1 |
20100039959 | Gilmartin | Feb 2010 | A1 |
20100049942 | Kim et al. | Feb 2010 | A1 |
20100111529 | Zeng et al. | May 2010 | A1 |
20100141428 | Mildenberger et al. | Jun 2010 | A1 |
20100216444 | Mariniello et al. | Aug 2010 | A1 |
20100284404 | Gopinath et al. | Nov 2010 | A1 |
20100290385 | Ankaiah et al. | Nov 2010 | A1 |
20100290458 | Assarpour et al. | Nov 2010 | A1 |
20100315958 | Luo et al. | Dec 2010 | A1 |
20110019673 | Fernandez | Jan 2011 | A1 |
20110080913 | Liu et al. | Apr 2011 | A1 |
20110085440 | Owens et al. | Apr 2011 | A1 |
20110085449 | Jeyachandran et al. | Apr 2011 | A1 |
20110090784 | Gan | Apr 2011 | A1 |
20110164496 | Loh et al. | Jul 2011 | A1 |
20110164518 | Daraiseh | Jul 2011 | A1 |
20110225391 | Burroughs et al. | Sep 2011 | A1 |
20110249679 | Lin et al. | Oct 2011 | A1 |
20110255410 | Yamen et al. | Oct 2011 | A1 |
20110265006 | Morimura et al. | Oct 2011 | A1 |
20110299529 | Olsson et al. | Dec 2011 | A1 |
20120020207 | Corti | Jan 2012 | A1 |
20120075999 | Ko et al. | Mar 2012 | A1 |
20120082057 | Welin et al. | Apr 2012 | A1 |
20120144064 | Parker et al. | Jun 2012 | A1 |
20120144065 | Parker et al. | Jun 2012 | A1 |
20120147752 | Ashwood-Smith et al. | Jun 2012 | A1 |
20120163797 | Wang | Jun 2012 | A1 |
20120170582 | Abts et al. | Jul 2012 | A1 |
20120207175 | Raman et al. | Aug 2012 | A1 |
20120287791 | Xi et al. | Nov 2012 | A1 |
20120300669 | Zahavi | Nov 2012 | A1 |
20120314706 | Liss | Dec 2012 | A1 |
20130044636 | Koponen et al. | Feb 2013 | A1 |
20130071116 | Ong | Mar 2013 | A1 |
20130083701 | Tomic et al. | Apr 2013 | A1 |
20130114599 | Arad | May 2013 | A1 |
20130114619 | Wakumoto | May 2013 | A1 |
20130159548 | Vasseur | Jun 2013 | A1 |
20130170451 | Krause et al. | Jul 2013 | A1 |
20130204933 | Cardona et al. | Aug 2013 | A1 |
20130208720 | Ellis et al. | Aug 2013 | A1 |
20130242745 | Umezuki | Sep 2013 | A1 |
20130297757 | Han et al. | Nov 2013 | A1 |
20130301646 | Bogdanski et al. | Nov 2013 | A1 |
20130315237 | Kagan et al. | Nov 2013 | A1 |
20130322256 | Bader et al. | Dec 2013 | A1 |
20130329727 | Rajagopalan et al. | Dec 2013 | A1 |
20130336116 | Vasseur et al. | Dec 2013 | A1 |
20130336164 | Yang et al. | Dec 2013 | A1 |
20140016457 | Enyedi | Jan 2014 | A1 |
20140022942 | Han et al. | Jan 2014 | A1 |
20140043959 | Owens et al. | Feb 2014 | A1 |
20140059440 | Sasaki et al. | Feb 2014 | A1 |
20140105034 | Sun | Apr 2014 | A1 |
20140140341 | Bataineh et al. | May 2014 | A1 |
20140169173 | Naouri | Jun 2014 | A1 |
20140192646 | Mir et al. | Jul 2014 | A1 |
20140198636 | Thayalan et al. | Jul 2014 | A1 |
20140211631 | Haramaty | Jul 2014 | A1 |
20140269305 | Nguyen | Sep 2014 | A1 |
20140313880 | Lu et al. | Oct 2014 | A1 |
20140328180 | Kim et al. | Nov 2014 | A1 |
20140343967 | Baker | Nov 2014 | A1 |
20150030033 | Vasseur et al. | Jan 2015 | A1 |
20150052252 | Gilde et al. | Feb 2015 | A1 |
20150092539 | Sivabalan et al. | Apr 2015 | A1 |
20150098466 | Haramaty et al. | Apr 2015 | A1 |
20150124815 | Beliveau et al. | May 2015 | A1 |
20150127797 | Attar et al. | May 2015 | A1 |
20150131663 | Brar et al. | May 2015 | A1 |
20150163144 | Koponen et al. | Jun 2015 | A1 |
20150172070 | Csaszar | Jun 2015 | A1 |
20150194215 | Douglas et al. | Jul 2015 | A1 |
20150195204 | Haramaty et al. | Jul 2015 | A1 |
20150249590 | Gusat | Sep 2015 | A1 |
20150372898 | Haramaty et al. | Dec 2015 | A1 |
20150372916 | Haramaty et al. | Dec 2015 | A1 |
20160014636 | Bahr et al. | Jan 2016 | A1 |
20160043933 | Gopalarathnam | Feb 2016 | A1 |
20160080120 | Unger et al. | Mar 2016 | A1 |
20160080321 | Pan et al. | Mar 2016 | A1 |
20160182378 | Basavaraja et al. | Jun 2016 | A1 |
20170054591 | Hyoudou | Feb 2017 | A1 |
20170358111 | Madsen | Dec 2017 | A1 |
20180139132 | Edsall et al. | May 2018 | A1 |
20200042667 | Swaminathan et al. | Feb 2020 | A1 |
Number | Date | Country |
---|---|---|
2012037494 | Mar 2012 | WO |
2016105446 | Jun 2016 | WO |
Entry |
---|
Leiserson, C E., “Fat-Trees: Universal Networks for Hardware Efficient Supercomputing”, IEEE Transactions on Computers, vol. C-34, No. 10, pp. 892-901, Oct. 1985. |
Ohring et al., “On Generalized Fat Trees”, Proceedings of the 9th International Symposium on Parallel Processing, pp. 37-44, Santa Barbara, USA, Apr. 25-28, 1995. |
Zahavi, E., “D-Mod-K Routing Providing Non-Blocking Traffic for Shift Permutations on Real Life Fat Trees”, CCIT Technical Report #776, Technion—Israel Institute of Technology, Haifa, Israel, Aug. 2010. |
Yuan et al., “Oblivious Routing for Fat-Tree Based System Area Networks with Uncertain Traffic Demands”, Proceedings of ACM SIGMETRICS—the International Conference on Measurement and Modeling of Computer Systems, pp. 337-348, San Diego, USA, Jun. 12-16, 2007. |
Matsuoka S., “You Don't Really Need Big Fat Switches Anymore—Almost”, IPSJ SIG Technical Reports, vol. 2003, No. 83, pp. 157-162, year 2003. |
Kim et al., “Technology-Driven, Highly-Scalable Dragonfly Topology”, 35th International Symposium on Computer Architecture, pp. 77-78, Beijing, China, Jun. 21-25, 2008. |
Jiang et al., “Indirect Adaptive Routing on Large Scale Interconnection Networks”, 36th International Symposium on Computer Architecture, pp. 220-231, Austin, USA, Jun. 20-24, 2009. |
Minkenberg et al., “Adaptive Routing in Data Center Bridges”, Proceedings of 17th IEEE Symposium on High Performance Interconnects, New York, USA, pp. 33-41, Aug. 25-27, 2009. |
Kim et al., “Adaptive Routing in High-Radix Clos Network”, Proceedings of the 2006 ACM/IEEE Conference on Supercomputing (SC2006), Tampa, USA, Nov. 2006. |
Infiniband Trade Association, “InfiniBandTM Architecture Specification vol. 1”, Release 1.2.1, Nov. 2007. |
Culley et al., “Marker PDU Aligned Framing for TCP Specification”, IETF Network Working Group, RFC 5044, Oct. 2007. |
Shah et al., “Direct Data Placement over Reliable Transports”, IETF Network Working Group, RFC 5041, Oct. 2007. |
Martinez et al., “Supporting fully adaptive routing in Infiniband networks”, Proceedings of the International Parallel and Distributed Processing Symposium (IPDPS'03),Apr. 22-26, 2003. |
Joseph, S., “Adaptive routing in distributed decentralized systems: NeuroGrid, Gnutella & Freenet”, Proceedings of Workshop on Infrastructure for Agents, MAS and Scalable MAS, Montreal, Canada, 11 pages, year 2001. |
Gusat et al., “R3C2: Reactive Route & Rate Control for CEE”, Proceedings of 18th IEEE Symposium on High Performance Interconnects, New York, USA, pp. 50-57, Aug. 10-27, 2010. |
Wu et al., “DARD: Distributed adaptive routing datacenter networks”, Proceedings of IEEE 32nd International Conference Distributed Computing Systems, pp. 32-41, Jun. 18-21, 2012. |
Ding et al., “Level-wise scheduling algorithm for fat tree interconnection networks”, Proceedings of the 2006 ACM/IEEE Conference on Supercomputing (SC 2006), 9 pages, Nov. 2006. |
U.S. Appl. No. 14/046,976 Office Action dated Jun. 2, 2015. |
Li et al., “Multicast Replication Using Dual Lookups in Large Packet-Based Switches”, 2006 IET International Conference on Wireless, Mobile and Multimedia Networks, pp. 1-3, Nov. 6-9, 2006. |
Nichols et al., “Definition of the Differentiated Services Field (DS Field) in the IPv4 and IPv6 Headers”, Network Working Group, RFC 2474, 20 pages, Dec. 1998. |
Microsoft., “How IPv4 Multicasting Works”, 22 pages, Mar. 28, 2003. |
Suchara et al., “Network Architecture for Joint Failure Recovery and Traffic Engineering”, Proceedings of the ACM SIGMETRICS joint international conference on Measurement and modeling of computer systems, pp. 97-108, Jun. 7-11, 2011. |
IEEE 802.1Q, “IEEE Standard for Local and metropolitan area networks Virtual Bridged Local Area Networks”, IEEE Computer Society, 303 pages, May 19, 2006. |
Plummer, D., “An Ethernet Address Resolution Protocol,” Network Working Group ,Request for Comments (RFC) 826, 10 pages, Nov. 1982. |
Hinden et al., “IP Version 6 Addressing Architecture,” Network Working Group ,Request for Comments (RFC) 2373, 26 pages, Jul. 1998. |
U.S. Appl. No. 12/910,900 Office Action dated Apr. 9, 2013. |
U.S. Appl. No. 14/046,976 Office Action dated Jan. 14, 2016. |
Raindel et al., U.S. Appl. No. 14/673,892, filed Mar. 31, 2015. |
“Equal-cost multi-path routing”, Wikipedia, 2 pages, Oct. 13, 2014. |
Thaler et al., “Multipath Issues in Unicast and Multicast Next-Hop Selection”, Network Working Group, RFC 2991, 9 pages, Nov. 2000. |
Nkposong et al., “Experiences with BGP in Large Scale Data Centers:Teaching an old protocol new tricks”, 44 pages, Jan. 31, 3014. |
Mahalingam et al., “VXLAN: A Framework for Overlaying Virtualized Layer 2 Networks over Layer 3 Networks”, Internet Draft, 20 pages, Aug. 22, 2012. |
Sinha et al., “Harnessing TCP's Burstiness with Flowlet Switching”, 3rd ACM SIGCOMM Workshop on Hot Topics in Networks (HotNets), 6 pages, Nov. 11, 2004. |
Vishnu et al., “Hot-Spot Avoidance With Multi-Pathing Over InfiniBand: An MPI Perspective”, Seventh IEEE International Symposium on Cluster Computing and the Grid (CCGrid'07), 8 pages, year 2007. |
NOWLAB—Network Based Computing Lab, 2 pages, years 2002-2015 http://nowlab.cse.ohio-state.edu/publications/conf-presentations/2007/vishnu-ccgrid07.pdf. |
Alizadeh et al.,“CONGA: Distributed Congestion-Aware Load Balancing for Datacenters”, Cisco Systems, 12 pages, Aug. 9, 2014. |
Geoffray et al., “Adaptive Routing Strategies for Modern High Performance Networks”, 16th IEEE Symposium on High Performance Interconnects (HOTI '08), pp. 165-172, Aug. 26-28, 2008. |
Anderson et al., “On the Stability of Adaptive Routing in the Presence of Congestion Control”, IEEE INFOCOM, 11 pages, 2003. |
Perry et al., “Fastpass: A Centralized “Zero-Queue” Datacenter Network”, M.I.T. Computer Science & Artificial Intelligence Lab, 12 pages, year 2014. |
Glass et al., “The turn model for adaptive routing”, Journal of the ACM, vol. 41, No. 5, pp. 874-903, Sep. 1994. |
U.S. Appl. No. 14/662,259 Office Action dated Sep. 22, 2016. |
Afek et al., “Sampling and Large Flow Detection in SDN”, SIGCOMM '15, pp. 345-346, Aug. 17-21, 2015, London, UK. |
Haramaty et al., U.S. Appl. No. 14/970,608, filed Dec. 16, 2015. |
U.S. Appl. No. 14/745,488 Office Action dated Dec. 6, 2016. |
U.S. Appl. No. 14/337,334 Office Action dated Oct. 20, 2016. |
Dally et al., “Deadlock-Free Message Routing in Multiprocessor Interconnection Networks”, IEEE Transactions on Computers, vol. C-36, No. 5, May 1987, pp. 547-553. |
Prisacari et al., “Performance implications of remote-only load balancing under adversarial traffic in Dragonflies”, Proceedings of the 8th International Workshop on Interconnection Network Architecture: On-Chip, Multi-Chip, 4 pages, Jan. 22, 2014. |
Garcia et al., “On-the-Fly 10 Adaptive Routing in High-Radix Hierarchical Networks,” Proceedings of the 2012 International Conference on Parallel Processing (ICPP), pp. 279-288, Sep. 10-13, 2012. |
Zahavi et al., “Distributed Adaptive Routing for Big-Data Applications Running on Data Center Networks,” Proceedings of the Eighth ACM/IEEE Symposium on Architectures for Networking and Communication Systems, New York, USA, pp. 99-110, Oct. 29-30, 2012. |
U.S. Appl. No. 14/732,853 Office Action dated Jan. 26, 2017. |
U.S. Appl. No. 14/970,608 Office Action dated May 30, 2017. |
U.S. Appl. No. 14/673,892 Office Action dated Jun. 1, 2017. |
U.S. Appl. No. 14/970,608 office action dated Nov. 1, 2017. |
U.S. Appl. No. 15/152,077 office action dated Dec. 1, 2017. |
U.S. Appl. No. 15/387,718 office action dated Mar. 9, 2018. |
U.S. Appl. No. 15/356,588 office action dated Jul. 11, 2018. |
U.S. Appl. No. 15/152,077 office action dated Jul. 16, 2018. |
U.S. Appl. No. 15/356,588 office action dated Feb. 7, 2019. |
U.S. Appl. No. 15/218,028 office action dated Feb. 6, 2019. |
U.S. Appl. No. 15/356,588 Advisory Action dated May 23, 2019. |
U.S. Appl. No. 15/896,088 office action dated Jun. 12, 2019. |
U.S. Appl. No. 15/356,588 office action dated Aug. 12, 2019. |
U.S. Appl. No. 15/218,028 office action dated Jun. 26, 2019. |
CN Application # 2017100777076 office action dated Nov. 1, 2019. |
Cao et al., “Implementation Method for High-radix Fat-tree Deterministic Source-routing Interconnection Network”, Computer Science ,vol. 39, Issue 12, pp. 33-37, 2012. |
U.S. Appl. No. 16/240,749 office action dated Jul. 28, 2020. |
Number | Date | Country | |
---|---|---|---|
20170244630 A1 | Aug 2017 | US |