Efficient OpenFlow Flow Table Splitting and Compressing Algorithm
JIANG La-lin(1，2)，ZHANG Ya-nan1，XIONG Bing(1，2)
1(School of Computer & Communication Engineering，Changsha University of Science & Technology，Changsha 410114，China)2(Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation，Changsha University of Science and Technology，Changsha 410114，China）
Abstract：In software-defined networking，OpenFlow offers fine-grained management to network flows with abundant matching fields，which results in explosive growth of flow table size and imposes great challenges on TCAM storage resource in OpenFlow switches.To solve this problem，this paper presents an efficient OpenFlow flow table splitting and compressing algorithm by exploiting the relationships among matching fields.Firstly，the paper analyzes coexistence and conflict relationships among matching fields，and divides a given flow table into multiple sub-flow tables.Then，we compress sub-flow tables by building a condition for each field.Finally，we evaluate the flow table compression performance of our proposed algorithm in virtue of real network traffic traces by experiments.The experimental results indicate that our proposed algorithm performs better than existing compression algorithms in terms of flow table storage compression rate，and effectively saves TCAM storage resources.
2018, Vol. 39 
