Low cost flow statistics collection in software defined networking

ZHAO Jun; BAO Congxiao; LI Xing

doi:10.16511/j.cnki.qhdxxb.2018.25.049

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Journal of Tsinghua University(Science and Technology) ›› 2019, Vol. 59 ›› Issue (2) : 148-153. DOI: 10.16511/j.cnki.qhdxxb.2018.25.049

COMPUTER SCIENCE AND TECHNOLOGY

Low cost flow statistics collection in software defined networking

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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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software defined networking / network measurement / non-linear integer programming / OpenFlow

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ZHAO Jun, BAO Congxiao, LI Xing. Low cost flow statistics collection in software defined networking[J]. Journal of Tsinghua University(Science and Technology). 2019, 59(2): 148-153 https://doi.org/10.16511/j.cnki.qhdxxb.2018.25.049

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