摘要
Dynamic Controller Provisioning Problem(DCPP) is a key problem for scalable SDN. Previously, the solution to this problem focused on adapting the number of controllers and their locations with changing network conditions, but ignored balancing control loads via switch migration. In this paper, we study a scalable control mechanism to decide which switch and where it should be migrated for more balanced control plane, and we define it as Switch Migration Problem(SMP). The main contributions of this paper are as follows. First, we define a SDN model to describe the relation between controllers and switches from the view of loads. Based on this model, we form SMP as a Network Utility Maximization(NUM) problem with the objective of serving more requests under available control resources. Second, we design a synthesizing distributed algorithm for SMP--- Distributed Hopping Algorithm(DHA), by approximating our optimal objective via Log-Sum-Exp function. In DHA, individual controller performs algorithmic procedure independently. With the solution space F, we prove that the optimal gap caused by approximation is at most 1/βlog|F|, and DHA procedure is equal to implementation of a time-reversible Markov Chain process. Finally, the results are corroborated by several numerical simulations.
Dynamic Controller Provisioning Problem（DCPP） is a key problem for scalable SDN. Previously, the solution to this problem focused on adapting the number of controllers and their locations with changing network conditions, but ignored balancing control loads via switch migration. In this paper, we study a scalable control mechanism to decide which switch and where it should be migrated for more balanced control plane, and we define it as Switch Migration Problem（SMP）. The main contributions of this paper are as follows. First, we define a SDN model to describe the relation between controllers and switches from the view of loads. Based on this model, we form SMP as a Network Utility Maximization（NUM） problem with the objective of serving more requests under available control resources. Second, we design a synthesizing distributed algorithm for SMP--- Distributed Hopping Algorithm（DHA）, by approximating our optimal objective via Log-Sum-Exp function. In DHA, individual controller performs algorithmic procedure independently. With the solution space F, we prove that the optimal gap caused by approximation is at most 1/βlog｜F｜, and DHA procedure is equal to implementation of a time-reversible Markov Chain process. Finally, the results are corroborated by several numerical simulations.
基金
supported by the Foundation for Innovative Research Groups of the National Natural Science Foundation of China (Grant No. 2016YFB0800100, No. 2016YFB0800101)
the National Natural Science Foundation of China (Grant No. 61521003)
the National Key R&D Program of China (Grant No. 61309020)
