WMN-PSODGA hybrid intelligent simulation system and its web GUI tool: performance evaluation considering different parameters of genetic algorithm

被引:0
|
作者
Barolli, Admir [1 ]
Sakamoto, Shinji [2 ]
机构
[1] Aleksander Moisiu Univ Durres, Dept Informat Technol, L1, Durres, Albania
[2] Kanazawa Inst Technol KIT, Dept Informat & Comp Sci, 7-1 Ohgigaoka, Nonoichi, Ishikawa 9218501, Japan
关键词
wireless mesh network; WMN; node placement problem; hybrid intelligent system; particle swarm optimisation; PSO; distributed genetic algorithm; DGA; PARTICLE SWARM; WIRELESS; OPTIMIZATION;
D O I
10.1504/IJWGS.2022.121967
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:213 / 228
页数:16
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