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Scalable Multi-Failure Fast Failover via Forwarding Table Compression

Published: 14 March 2016 Publication History

Abstract

In datacenter networks, link and switch failures are a common occurrence. Although most of these failures do not disconnect the underlying topology, they do cause routing failures, disrupting communications between some hosts. Unfortunately, current 1:1 redundancy groups are only partly effective at reducing the impact of these routing failures. In principle, local fast failover schemes, such as OpenFlow fast failover groups, could reduce the impact by preinstalling backup routes that protect against multiple simultaneous failures. However, providing a sufficient number of backup routes within the available space provided by the forwarding tables of datacenter switches is challenging. To solve this problem, we contribute a new forwarding table compression algorithm. Further, we introduce the concept of compression-aware routing to improve the achieved compression ratio. Lastly, we have created Plinko, a new forwarding model that is designed to have more easily compressible forwarding tables. All optimizations combined, we often saw compression ratios ranging from 2.10x to 19.29x.

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  1. Scalable Multi-Failure Fast Failover via Forwarding Table Compression

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      cover image ACM Conferences
      SOSR '16: Proceedings of the Symposium on SDN Research
      March 2016
      178 pages
      ISBN:9781450342117
      DOI:10.1145/2890955
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      Publication History

      Published: 14 March 2016

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      Author Tags

      1. Forwarding Table Compression
      2. Local Fast Failover

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      SOSR '16
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      SOSR '16: Symposium on SDN Research
      March 14 - 15, 2016
      CA, Santa Clara, USA

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      Overall Acceptance Rate 7 of 43 submissions, 16%

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      Cited By

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      • (2024)Robust Routing Made Easy: Reinforcing Networks Against Non-Benign FaultsIEEE/ACM Transactions on Networking10.1109/TNET.2023.328318432:1(283-297)Online publication date: Feb-2024
      • (2023)Traffic-Aware Fast Reroute Mechanism Exploiting Disjoint Subpaths for Named Data NetworksICC 2023 - IEEE International Conference on Communications10.1109/ICC45041.2023.10279628(4013-4019)Online publication date: 28-May-2023
      • (2023)Fast Proactive Re-Route with Detours on Joint Paths in Named-Data Networks for Communications of Smart Electric Power Transmission Grids2023 15th International Conference on COMmunication Systems & NETworkS (COMSNETS)10.1109/COMSNETS56262.2023.10041321(640-648)Online publication date: 3-Jan-2023
      • (2023)A Research Review of OpenFlow for Datacenter NetworkingIEEE Access10.1109/ACCESS.2022.323346611(770-786)Online publication date: 2023
      • (2022)R-MPLSProceedings of the 18th International Conference on emerging Networking EXperiments and Technologies10.1145/3555050.3569140(276-292)Online publication date: 30-Nov-2022
      • (2022)Local Fast Rerouting With Low Congestion: A Randomized ApproachIEEE/ACM Transactions on Networking10.1109/TNET.2022.317473130:6(2403-2418)Online publication date: Dec-2022
      • (2022)Optimistic Fast ReroutingICC 2022 - IEEE International Conference on Communications10.1109/ICC45855.2022.9838260(1692-1697)Online publication date: 16-May-2022
      • (2022)On the Price of Locality in Static Fast Rerouting2022 52nd Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN)10.1109/DSN53405.2022.00032(215-226)Online publication date: Jun-2022
      • (2022)FBR: Dynamic Memory-Aware Fast Rerouting2022 IEEE 11th International Conference on Cloud Networking (CloudNet)10.1109/CloudNet55617.2022.9978819(55-60)Online publication date: 7-Nov-2022
      • (2022)Dynamic Routing and Failure Recovery Approaches for Efficient Resource Utilization in OpenFlow-SDN: A SurveyIEEE Access10.1109/ACCESS.2022.322284910(121791-121815)Online publication date: 2022
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