School of Computer Science, South China Normal University, Guangzhou 510631, China;Key Laboratory on Cloud Security and Assessment Technology of Guangzhou, Guangzhou 510631, China 在期刊界中查找 在百度中查找 在本站中查找
School of Computer Science, South China Normal University, Guangzhou 510631, China;Key Laboratory on Cloud Security and Assessment Technology of Guangzhou, Guangzhou 510631, China 在期刊界中查找 在百度中查找 在本站中查找
School of Computer Science, South China Normal University, Guangzhou 510631, China;Key Laboratory on Cloud Security and Assessment Technology of Guangzhou, Guangzhou 510631, China 在期刊界中查找 在百度中查找 在本站中查找
School of Computer Science, South China Normal University, Guangzhou 510631, China;Key Laboratory on Cloud Security and Assessment Technology of Guangzhou, Guangzhou 510631, China 在期刊界中查找 在百度中查找 在本站中查找
In software-defined wide area networks (SD-WANs), link failures can result in substantial packet loss, leading to partial network paralysis in severe cases. The existing traffic engineering approaches can expedite failure recovery by installing backup paths in advance on the data plane. However, it is difficult to adapt to various network failures with limited resources, which degrades the network performance after recovery. To maintain the network performance after failure recovery and reduce the consumption of backup resources, this study proposes a proactive failure recovery scheme based on congestion and memory awareness (CAMA), which can not only redirect the affected data flows quickly but also realize the load balancing to avoid the potential link congestion after recovery. Experimental results demonstrate that compared with existing schemes, CAMA can effectively utilize backup resources, performs well in load balancing, and requires only a small number of backup rules to cover all single-link failure scenarios.
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