A Distributed Decision Mechanism for Controller Load Balancing Based on Switch Migration in SDN

Software Defined Networking(SDN) provides flexible network management by decoupling control plane from data plane. And multiple controllers are deployed to improve the scalability and reliability of the control plane, which could divide the network into several subdomains with separate controllers. However, such deployment introduces a new problem of controller load imbalance due to the dynamic traffic and the static configuration between switches and controllers. To address this issue, this paper proposes a Distribution Decision Mechanism(DDM) based on switch migration in the multiple subdomains SDN network. Firstly, through collecting network information, it constructs distributed migration decision fields based on the controller load condition. Then we choose the migrating switches according to the selection probability, and the target controllers are determined by integrating three network costs, including data collection, switch migration and controller state synchronization. Finally, we set the migrating countdown to achieve the ordered switch migration. Through verifying several evaluation indexes, results show that the proposed mechanism can achieve controller load balancing with better performance.

Toward a Scalable SDN Control Mechanism via Switch Migration

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.