WMN-PSODGA hybrid intelligent simulation system and its web GUI tool: performance evaluation considering different parameters of genetic algorithm. (28th February 2022)

• Record Type: Journal Article
• Authors: Barolli, Admir; Sakamoto, Shinji
• Is Part Of: International journal of web and grid services. Volume 18:Number 2(2022)
• Page Start: 213
• Page End: 228
• Publication Date: 2022-02-28
• Subjects: wireless mesh network -- WMN -- node placement problem -- hybrid intelligent system -- particle swarm optimisation -- PSO -- distributed genetic algorithm -- DGA; Web services -- Periodicals; Computational grids (Computer systems) -- Periodicals; 006.78
• Languages: English
• ISSNs: 1741-1106

Abstract

Wireless mesh networks (WMNs) have many advantages compared with the conventional wireless local area networks (WLANs) such as system resiliency, low cost, flexible coverage areas, rapid deployment, easy deployment, easy maintenance and high robustness. However, WMNs have some problems such as hidden and exposed node problems, which are related with the node placement problem that affect the network connectivity and user coverage. In order to solve these problems, we consider to optimise the location of mesh routers in WMNs. However, the mesh router placement is known to be an NP-hard problem. For this reason, we consider meta-heuristic algorithms. In this paper, we propose and evaluate a hybrid intelligent simulation system based on distributed genetic algorithm (DGA) and particle swarm optimisation (PSO). The simulation results show that the proposed system has a good performance to solve the node placement problem in WMNs. The best performance is achieved for 64 GA islands. Also, the SPX method has better performance than other crossover methods for the considered scenarios.