A new framework for reliable control placement in software-defined networks based on multi-criteria clustering approach

Abstract

In large-scale software-defined networks (SDNs), multiple controllers are deployed. Each controller has a logically centralized vision of the network that is used to manage a set of switches. In SDN, a challenge known as controller placement problem arises which is very important to specify the number of controllers that are needed and where they should be deployed. These specifications affect the performance of the network. Meanwhile, the assignment of switches to the controllers plays key role in the quality of solution in this problem. However, recent studies focus more on simply assigning switches to their closest controllers based on propagation delay between controller and switches. In this paper, a new controller placement framework is designed which considers both control plane architecture and relation between control and data planes. This framework is considered as a multi-objective optimization model with two objective functions to minimize the flow setup time and inter-controller latency. Furthermore, we propose a new model for flow setup time function that considers all affected metrics in the placement. To solve the framework, a multi-objective algorithm called non-dominated sorting moth flame controller placement optimizer is designed. To this end, we adapt the best–worst multi-criteria decision-making method considering three metrics, namely hop count, propagation latency and link utilization, to assign switches to controllers. A heuristic approach is also used to assign a path between switch and its controller using above three metrics and path reliability. We run theses three models iteratively to find the best location for controllers, the best switch assignment to controller and also find the best route in the network. We compare our proposed framework with other models using expected path loss and link load balancing metrics. Our performance evaluations on real wide area network topologies show the efficiency of the proposed framework.