A hybrid intelligent approach for optimising software-defined networks performance

Abstract

A new hybrid intelligent approach for optimising the performance of Software-Defined Networks (SDN), based on heuristic optimisation methods integrated with neural network paradigm, is presented. Evolutionary Optimisation techniques, such as Particle Swarm Optimisation (PSO) and Genetic Algorithms (GA), are employed to find the best set of inputs that give the maximum performance of an SDN. The Neural Network model is trained and applied as an approximator of SDN behaviour. An analytical investigation has been conducted to distinguish the optimal optimisation approach based on SDN performance as an objective function as well as the computational time. After getting the general model of the Neural Network through testing it with unseen data, this model has been implemented with PSO and GA to find the best performance of SDN. The PSO approach combined with SDN, represented by ANN, is identified as a comparatively better configuration regarding its performance index as well as its computational efficiency.