Implementation of an intelligent hybrid simulation systems for WMNs based on particle swarm optimization and simulated annealing: performance evaluation for different replacement methods

Abstract

Wireless mesh networks (WMNs) have many advantages such as low-cost and increased high- speed wireless Internet connectivity; therefore, WMNs are becoming an important networking infrastructure. In our previous work, we implemented a particle swarm optimization (PSO)-based simulation system for node placement in WMNs, called WMN-PSO. Also, we implemented a simulation system based on simulated annealing (SA) called WMN-SA. In this paper, we implement a hybrid simulation system based on PSO and SA, called WMN-PSOSA. We evaluate the performance of WMN-PSOSA by conducting computer simulations considering four different replacement methods. The simulation results show that the rational decrement of Vmax method and linearly decreasing inertia weight method have better performance compared with constriction method and random inertia weight method.

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Acknowledgements

This work is supported by a Grant-in-Aid for Scientific Research from Japanese Society for the Promotion of Science (JSPS KAKENHI Grant Number 15J12086). The authors would like to thank JSPS for the financial support.

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Correspondence to Shinji Sakamoto.

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Communicated by V. Loia.

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Sakamoto, S., Ozera, K., Barolli, A. et al. Implementation of an intelligent hybrid simulation systems for WMNs based on particle swarm optimization and simulated annealing: performance evaluation for different replacement methods. Soft Comput 23, 3029–3035 (2019). https://doi.org/10.1007/s00500-017-2948-1

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Keywords

  • Wireless mesh networks
  • Node placement problem
  • Particle swarm optimization
  • Simulated annealing
  • Intelligent hybrid system
  • Replacement methods