4.7 Article

Mitigating the impact of controller failures on QoS robustness for software-defined wide area networks

期刊

COMPUTER NETWORKS
卷 238, 期 -, 页码 -

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ELSEVIER
DOI: 10.1016/j.comnet.2023.110096

关键词

Software-defined wide area networks; Quality of Service; Network programmability

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Emerging cloud services and applications have different QoS requirements for the network. SD-WANs play a crucial role in QoS provisioning by introducing network programmability, dynamic flow routing, and low data transmission latency. However, controller failures may degrade QoS. To address this, we propose PREDATOR, a QoS-aware network programmability recovery scheme that achieves fine-grained per-flow remapping without introducing extra delays, ensuring QoS robustness for high-priority flows.
Emerging cloud services and applications pose different Quality of Service (QoS) requirements for the network, where Software-Defined Wide Area Networks (SD-WANs) play a crucial role in QoS provisioning by introducing network programmability into network flows to enable dynamic flow routing and ensure low data transmission latency for these applications. However, controller failures may happen in SD-WANs, and all programmable flows that the failed controller previously controlled will become offline and lose the network programmability, resulting in the degradation of QoS. Existing control recovery solutions propose to remap offline switches/flows to available active controllers but cannot promise good recovery performance due to the following two problems: (1) the recovery performance suffers from either coarse-grained remapping granularity or introducing extra processing delays, and (2) QoS robustness cannot be guaranteed in the design of recovery solution. To this end, we propose PREDATOR, a QoS-aware network programmability recovery scheme that utilizes the P4 Runtime enabled by existing P4 switches to achieve fine-grained per-flow remapping without introducing extra delays. Specifically, our proposed PREDATOR categorizes flows based on their QoS requirements and smartly recovers offline flows based on their priorities to guarantee the QoS robustness for high-priority flows. Simulation results under real-world topology demonstrate that our proposed PREDATOR can improve the recovered network programmability of high-priority flows by up to 505.5%, and substantially reduce the communication overhead of high-priority flows, compared with baselines.

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