Joint Optimization of Flow Table and Group Table for Default Paths in SDNs
Software-defined networking (SDN) separates the control plane from the data plane to ease network management and provide flexibility in packet routing. The control plane interacts with the data plane through an interface that configures the forwarding tables, usually including a flow table and a gro...
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Veröffentlicht in: | IEEE/ACM transactions on networking 2018-08, Vol.26 (4), p.1837-1850 |
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Sprache: | eng |
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Zusammenfassung: | Software-defined networking (SDN) separates the control plane from the data plane to ease network management and provide flexibility in packet routing. The control plane interacts with the data plane through an interface that configures the forwarding tables, usually including a flow table and a group table, at each switch. Due to high cost and power consumption of ternary content addressable memory, commodity switches can only support flow/group tables of limited size, which presents serious challenge for SDN to scale to large networks. One promising approach to address the scalability problem is to deploy aggregate default paths specified by wildcard forwarding rules. However, the multi-dimensional interaction among numerous system parameters and performance/scalability considerations makes the problem of setting up the flow/group tables at all switches for optimal overall layout of default paths very challenging. This paper studies the joint optimization of flow/group tables in the complex setting of large-scale SDNs. We formulate this problem as an integer linear program, and prove its NP-hardness. An efficient algorithm with bounded approximation factors is proposed to solve the problem. The properties of our algorithm are formally analyzed. We implement the proposed algorithm on an SDN test bed for experimental studies and use simulations for large-scale investigation. The experimental results and simulation results show that, under the same number of flow entries, our method can achieve better network performance than the equal cost multipath while reducing the use of group entries by about 74%. Besides, our method can reduce the link load ratio and the number of flow entries by approximately 13% and 60% compared with DevoFlow with 10% additional group entries. |
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ISSN: | 1063-6692 1558-2566 |
DOI: | 10.1109/TNET.2018.2853587 |