Performance Evaluation of Chi-Square and Normal Distributions of Mesh Clients for WMNs Considering Five Router Replacement Methods

Abstract

In our previous work, we implemented a simulation system to solve the node placement problem in WMNs considering Particle Swarm Optimization (PSO) and Distributed Genetic Algorithm (DGA), called WMN-PSODGA. In this paper, we compare Chi-square and Normal distributions of mesh clients for different router replacement methods. The router replacement methods considered are Constriction Method (CM), Random Inertia Weight Method (RIWM), Linearly Decreasing Inertia Weight Method (LDIWM), Linearly Decreasing Vmax Method (LDVM) and Rational Decrement of Vmax Method (RDVM). The simulation results show that for both distributions, the mesh routers cover all mesh clients for all router replacement methods. In terms of load balancing, Normal distribution shows better results than Chi-square. The best router replacement method for this distribution is LDIWM. Thus, the best scenario is the Normal distribution of mesh clients with LDIWM as a router replacement method.