A Hybrid Intelligent Simulation System for Node Placement in WMNs Considering Load Balancing: A Comparison Study for Exponential and Normal Distribution of Mesh Clients

Wireless Mesh Networks (WMNs) are becoming an important networking infrastructure because it has many advantages such as low cost and increased high-speed wireless Internet connectivity. In our previous work, we implemented a Particle Swarm Optimization (PSO) based simulation system, called WMN-PSO, and a simulation system based on Genetic Algorithm (GA), called WMN-GA, for solving node placement problem in WMNs. Then, we implemented a hybrid simulation system based on PSO and distributed GA (DGA), called WMN-PSODGA. Moreover, we added in the fitness function a new parameter for the load balancing of the mesh routers called NCMCpR (Number of Covered Mesh Clients per Router). In this paper, we consider Exponential and Normal distributions of mesh clients and carry out a comparison study. The simulation results show that the performance of the Exponential and Normal distribution was improved by considering load balancing when using WMN-PSODGA. Moreover, for the same number of mesh clients, the Normal distribution has better behavior than the Exponential distribution, because all mesh clients are covered by a smaller number of mesh routers.