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An Improved PSO Algorithm for Distributed Localization in Wireless Sensor Networks

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  • Dan Li
  • Xian bin Wen

Abstract

Accurate and quick localization of randomly deployed nodes is required by many applications in wireless sensor networks and always formulated as a multidimensional optimization problem. Particle swarm optimization (PSO) is feasible for the localization problem because of its quick convergence and moderate demand for computing resources. This paper proposes a distributed two-phase PSO algorithm to solve the flip ambiguity problem, and improve the efficiency and precision. In this work, the initial search space is defined by bounding box method and a refinement phase is put forward to correct the error due to flip ambiguity. Moreover, the unknown nodes which only have two references or three near-collinear references are tried to be localized in our research. Simulation results indicate that the proposed distributed localization algorithm is superior to the previous algorithms.

Suggested Citation

  • Dan Li & Xian bin Wen, 2015. "An Improved PSO Algorithm for Distributed Localization in Wireless Sensor Networks," International Journal of Distributed Sensor Networks, , vol. 11(7), pages 970272-9702, July.
    • Handle: RePEc:sae:intdis:v:11:y:2015:i:7:p:970272
    DOI: 10.1155/2015/970272
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