An evolutionary controllers' placement algorithm for reliable SDN networks

SDN controllers placement in TelCo networks are generally multi-objective and multi-constrained problems. The solutions proposed in the literature usually model the placement problem by providing a mixed integer linear program (MILP). Their performances are, however, quickly limited for large sized networks, due to the significant increase in the computational delays. In order to avoid the inherent complexity of optimal approaches and the lack of flexibility of heuristics, we propose in this paper a genetic algorithm designed from the NSGA II framework that aims to deal with the controller placement problem. Genetic algorithms can, indeed, be both multi-objective, multi-constraints and can be designed to be computed in parallel. They constitute a real opportunity to find good solutions to this category of problems. Furthermore, the proposed algorithm can be easily adapted to manage dynamic placements scenarios. The goal chosen, in this work, is to maximize the clusters average connectivity and to balance the control's load between clusters, in a way to improve the networks' reliability. The evaluation results on a set of network topologies demonstrated very good performances, which achieve optimal results for small networks.