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One of the most challenging aspects of designing Wireless Mesh Networks (WMNs) is the optimal placement of mesh routers, which is classified as an NP-hard problem. To deal with this issue, we propose and implement a hybrid simulation system by combining Particle Swarm Optimization (PSO) and Distributed Genetic Algorithm (DGA) called WMN-PSODGA. We utilize six Router Replacement Methods (RRMs) to optimize the placement of mesh routers in a small-scale WMN considering the Boulevard distribution of mesh clients. Simulation results by WMN-PSODGA show that all six RRMs achieved 100% connectivity, but they performed differently regarding the coverage of mesh clients. Among six RRMs, the Fast Convergence Rational Decrement of Vmax Method (FC-RDVM) demonstrated the best convergence performance.

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Assessment of Six Router Replacement Methods by WMN-PSODGA Simulation System for Boulevard Distribution of Mesh Clients Considering a Small-Scale Wireless Mesh Network

  • 会议论文

  • 发表日期：

    2025年

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  • Yusuke Irie,
  • Paboth Kraikritayakul,
  • Shinji Sakamoto,
  • Makoto Ikeda,
  • Keita Matsuo,
  • Leonard Barolli

摘要

One of the most challenging aspects of designing Wireless Mesh Networks (WMNs) is the optimal placement of mesh routers, which is classified as an NP-hard problem. To deal with this issue, we propose and implement a hybrid simulation system by combining Particle Swarm Optimization (PSO) and Distributed Genetic Algorithm (DGA) called WMN-PSODGA. We utilize six Router Replacement Methods (RRMs) to optimize the placement of mesh routers in a small-scale WMN considering the Boulevard distribution of mesh clients. Simulation results by WMN-PSODGA show that all six RRMs achieved 100% connectivity, but they performed differently regarding the coverage of mesh clients. Among six RRMs, the Fast Convergence Rational Decrement of Vmax Method (FC-RDVM) demonstrated the best convergence performance.