The growing trend of network virtualization results in a widespread adoption of virtual switches in virtualized environments. However, virtual switching is confronted with great performance challenges regarding packet...The growing trend of network virtualization results in a widespread adoption of virtual switches in virtualized environments. However, virtual switching is confronted with great performance challenges regarding packet classification especially in Open Flow-based software defined networks. This paper first takes an insight into packet classification in virtual Open Flow switching, and points out that its performance bottleneck is dominated by flow table traversals of multiple failed mask probing for each arrived packet. Then we are motivated to propose an efficient packet classification algorithm based on counting bloom filters. In particular, counting bloom filters are applied to predict the failures of flow table lookups with great possibilities, and bypass flow table traversals for failed mask probing. Finally, our proposed packet classification algorithm is evaluated with real network traffic traces by experiments. The experimental results indicate that our proposed algorithm outperforms the classical one in Open v Switch in terms of average search length, and contributes to promote virtual Open Flow switching performance.展开更多
基金supported in part by National Natural Science Foundation of China(61272148,61572525,61502056,and 61602525)Hunan Provincial Natural Science Foundation of China(2015JJ3010)Scientific Research Fund of Hunan Provincial Education Department(15B009,14C0285)
文摘The growing trend of network virtualization results in a widespread adoption of virtual switches in virtualized environments. However, virtual switching is confronted with great performance challenges regarding packet classification especially in Open Flow-based software defined networks. This paper first takes an insight into packet classification in virtual Open Flow switching, and points out that its performance bottleneck is dominated by flow table traversals of multiple failed mask probing for each arrived packet. Then we are motivated to propose an efficient packet classification algorithm based on counting bloom filters. In particular, counting bloom filters are applied to predict the failures of flow table lookups with great possibilities, and bypass flow table traversals for failed mask probing. Finally, our proposed packet classification algorithm is evaluated with real network traffic traces by experiments. The experimental results indicate that our proposed algorithm outperforms the classical one in Open v Switch in terms of average search length, and contributes to promote virtual Open Flow switching performance.
