A Comparison Study by WMN-PSODGA System for LDIWM, RIWM, FC-RDVM Router Replacement Methods Considering a Smal Scale WMN and Boulevard Distribution of Mesh Clients

The Wireless Mesh Networks (WMNs) are a very good innovative technolog. They can provide enhanced scalability, flexibility, and robustness, making them ideal for a wide range of applications. However, WMNs have several challenges such as efficient routing, maintaining network security, managing scalability, and mitigating interference. Addressing these challenges is crucial for improving the performance and reliability of WMNs in practical deployments. The deployment of mesh routers at appropriate locations is important to deal with these issues. However, finding the best locations of mesh routers in WMNs is difficult and is classified as NP-hard problem. There are some studies that considers meta-heuristic algorithms for optimization of mesh routers in WMNs. Some of them use simple intelligent algorithms. In this paper, we propose and implement a hybrid simulation system based on Particle Swarm Oprimization (PSO) and Genetic Algorithm (GA) using Linearly Decreasing Inertia Weight Method (LDIWM), Random Inertia Weight Method (RIWM) and Fast Convergence Rational Decrement of Vmax Method (FC-RDVM). We consider Boulevard distribution of mesh clients and a small scale WMN. The simulation results show that for Boulevard distribution, LDIWMs, RIWMs, and FC-RDVMs provide 100% connectivity. However, they have different performance for NCMC parameter. The convergence of NCMC for FC-RDVM is better than LDIWM and RIWM and is 100%. Thus, the performance of FC-RDVM is better compared with other two methods.