Low cost flow statistics collection in software defined networking
ZHAO Jun1, BAO Congxiao2, LI Xing1
1. Department of Electronic Engineering, Tsinghua University, Beijing 100084, China;(; 2. Information Technology Center, Tsinghua University, Beijing 100084, China
Abstract：Many monitoring methods have been proposed for network measurements that are essential in software defined networking. However, periodically or adaptively collecting statistics from software switches using per-flow queries incurs significant communication costs thus increase the loads on switches. This paper presents an approach called OpenCost that decides which switch us used to collect statistics in software defined networks based on a non-linear integer programming (NLIP) model. However, the NLIP problem is NP-hard; therefore, the problem is solved using an approximation algorithm based on a greedy algorithm. Extensive simulations were used to benchmark the algorithm with the results showing that OpenCost reduces the communication costs by 55% on average compared with other methods.
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2019, Vol. 59 
