Assessment of WMN-CS Intelligent Simulation System for Uniform, Weibull and Chi-Square Distribution of Mesh Clients

Wireless Mesh Networks (WMNs) are effective networks because they have high-robustness and rapid deployment capabilities. However, they have some issues such as congestion, interference, diminished data transfer speeds, packet losses, and increased latency. The location of mesh routers is one of the most critical decisions to deal with these problems. However, determining the optimal location of mesh routers in WMNs is difficult task and it is known to be an NP-hard problem. In order to solve this problem, we propose and implement an intelligent simulation system based on Cuckoo Search (CS) algorithm, which is a meta-heuristic approach. In this work, we assess the performance of WMN-CS considering Uniform, Weibull and Chi-square distributions of mesh clients. For evaluation, we carried out computer simulations. The simulation results show that the distribution of mesh clients affects the performance of WMN-CS. In case of Uniform distribution of mesh clients, the convergence speed is faster than the Weibull and Chi-square distributions, but the converged value of NCMC is the lowest among these three distributions. In the case of Weibull distribution, the convergence speed is slower than the Uniform and Chi-square distributions, but the converged value of NCMC is the highest among three of them. The performance of WMN-CS for Chi-square distribution is between Uniform and Weibull distributions.