Router placement in Wireless Mesh Networks (WMNs) is an NP-hard problem that strongly impacts coverage and load distribution. This study extends the WMN-PSOHCDGA hybrid system by integrating two crossover methods, Simplex Crossover (SPX) and Parallelotope-Shaped Blend Crossover (psBLX), with two router replacement methods: Rational Decreasing Vmax Method (RDVM) and Fast Convergence Rational Decreasing Vmax Method (FC-RDVM). RDVM is established for stable coverage, while FC-RDVM accelerates convergence; thus, their comparison clarifies trade-offs in reliability and efficiency. Likewise, SPX supports broad exploration, whereas psBLX preserves spatial correlations, both relevant for WMN optimization. Simulations on a medium-scale WMN with 96 clients under a two-island distribution showed that RDVM achieved full coverage, while FC-RDVM provided superior load balancing performance.

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A Comparative Study of SPX and psBLX Crossover Methods with RDVM and FC-RDVM Router Replacement Methods for Middle-Scale WMN Considering Two-Islands Mesh Client Distribution

  • Paboth Kraikritayakul,
  • Admir Barolli,
  • Shinji Sakamoto,
  • Shunya Higashi,
  • Phudit Ampririt,
  • Leonard Barolli

摘要

Router placement in Wireless Mesh Networks (WMNs) is an NP-hard problem that strongly impacts coverage and load distribution. This study extends the WMN-PSOHCDGA hybrid system by integrating two crossover methods, Simplex Crossover (SPX) and Parallelotope-Shaped Blend Crossover (psBLX), with two router replacement methods: Rational Decreasing Vmax Method (RDVM) and Fast Convergence Rational Decreasing Vmax Method (FC-RDVM). RDVM is established for stable coverage, while FC-RDVM accelerates convergence; thus, their comparison clarifies trade-offs in reliability and efficiency. Likewise, SPX supports broad exploration, whereas psBLX preserves spatial correlations, both relevant for WMN optimization. Simulations on a medium-scale WMN with 96 clients under a two-island distribution showed that RDVM achieved full coverage, while FC-RDVM provided superior load balancing performance.