A hybrid intelligent system based on particle swarm optimization and distributed genetic algorithm for WMNs: a comparison study of boulevard and stadium distributions considering different router replacement methods and load balancing.

The development of various communication technologies has made it possible to connect any intelligent device with each other and to the Internet. However, with the proliferation of such devices, the need for dynamic networks that require less efforts in managing and optimizing end users experience is mounting at a fast pace. Wireless Mesh Networks (WMNs) are a good choice not only to meeting users demands but also to reducing maintenance and upfront costs. Nevertheless, deploying a reliable highly connected WMN at low cost requires the utilization of the least possible mesh routers, yet fully interconnected and able to cover all mesh clients. To cope with these challenges, we have previously implemented a hybrid intelligent system, called WMN-PSODGA, which combines two intelligent algorithms: Particle Swarm Optimization and Distributed Genetic Algorithm. In this paper, we consider Boulevard and Stadium distributions of mesh clients and evaluate the performance of the WMN for different router replacement methods. By comparing the simulation results for each distribution and router replacement method, we conclude that the best scenario in terms of client coverage, router connectivity and load balancing is Stadium distribution with Rational Decrement of Vmax Method as a router replacement method. [ABSTRACT FROM AUTHOR]