Game Theoretic Switch-Controller Mapping with Traffic Variations in Software Defined Networks

In software-defined networks, distributed controller architectures provide improved scalability and reliability by using multiple controllers, each managing a partition of the network. However, due to the dynamics of network control traffic, static switch-controller mapping causes load imbalance while dynamic mapping causes frequent switch migrations among controllers. In this paper, we present a novel game-theoretic switch-controller mapping approach that considers control traffic variations in distributed-controller software-defined networks. We formulate the problem as a Markov decision process that is a non-cooperative stochastic game in which the players are controllers. They compete to serve the switches within their processing capacity so as to maximize their reward based on the amount of traffic processed and their per-unit price while trying to reduce switch migrations due to traffic variations. We show the existence of a Markov perfect equilibrium for the game. We evaluate the performance of the proposed approach through comprehensive simulations, including comparisons with other alternatives. The results show that the switch-controller mapping solution obtained by the proposed approach is stable against the control traffic dynamics with good load balancing among controllers.