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Localization Algorithm in Wireless Sensor Networks Based on Multiobjective Particle Swarm Optimization

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  • Ziwen Sun
  • Li Tao
  • Xinyu Wang
  • Zhiping Zhou

Abstract

Based on multiobjective particle swarm optimization, a localization algorithm named multiobjective particle swarm optimization localization algorithm (MOPSOLA) is proposed to solve the multiobjective optimization localization issues in wireless sensor networks. The multiobjective functions consist of the space distance constraint and the geometric topology constraint. The optimal solution is found by multiobjective particle swarm optimization algorithm. Dynamic method is adopted to maintain the archive in order to limit the size of archive, and the global optimum is obtained according to the proportion of selection. The simulation results show considerable improvements in terms of localization accuracy and convergence rate while keeping a limited archive size by a method using the global optimal selection operator and dynamically maintaining the archive.

Suggested Citation

  • Ziwen Sun & Li Tao & Xinyu Wang & Zhiping Zhou, 2015. "Localization Algorithm in Wireless Sensor Networks Based on Multiobjective Particle Swarm Optimization," International Journal of Distributed Sensor Networks, , vol. 11(8), pages 716291-7162, August.
    • Handle: RePEc:sae:intdis:v:11:y:2015:i:8:p:716291
    DOI: 10.1155/2015/716291
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