Toward Flexible and Predictable Path Programmability Recovery Under Multiple Controller Failures in Software-Defined WANs
Software-Defined Networking (SDN) promises good network performance in Wide Area Networks (WANs) with the logically centralized control using physically distributed controllers. In Software-Defined WANs (SD-WANs), maintaining path programmability, which enables flexible path change on flows, is cruc...
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Veröffentlicht in: | IEEE/ACM transactions on networking 2023-10, Vol.31 (5), p.1-16 |
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Sprache: | eng |
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Zusammenfassung: | Software-Defined Networking (SDN) promises good network performance in Wide Area Networks (WANs) with the logically centralized control using physically distributed controllers. In Software-Defined WANs (SD-WANs), maintaining path programmability, which enables flexible path change on flows, is crucial for maintaining network performance under traffic variation. However, when controllers fail, existing solutions are essentially coarse-grained switch-controller mapping solutions and only recover the path programmability of a limited number of offline flows, which traverse offline switches controlled by failed controllers. In this paper, we propose () to provide predictable path programmability recovery under multiple controller failures in SD-WANs. The key idea of is to approximately realize flow-controller mappings using hybrid SDN/legacy routing supported by high-end commercial SDN switches. Using the hybrid routing, we can recover programmability by selecting a routing mode for each offline flow at each offline switch in a fine-grained way to fit the given control resource from active controllers and release a few control resource of active controllers by reasonably configuring some normal flows under legacy routing mode. Thus, can promise ample control resource to improve the recovery efficiency and further effectively map offline switches to active controllers. Simulation results show that outperforms existing switch-level solutions by maintaining balanced programmability and increasing the total programmability of recovered offline flows up to 660% under topology and 590% under topology. |
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ISSN: | 1063-6692 1558-2566 |
DOI: | 10.1109/TNET.2022.3227423 |