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Sensor Localization in Wireless Sensor Networks Using Cultural Algorithm

Author

Listed:
  • Vaishali Raghavendra Kulkarni

    (M. S. Ramaiah University of Applied Sciences, India)

  • Veena Desai

    (KLS Gogte Institute of Technology, India)

Abstract

Evolutionary computing-based cultural algorithm (CA) has been developed for anchor-assisted, range-based, multi-stage localization of sensor nodes of wireless sensor networks (WSNs). The results of CA-based localization have been compared with those of swarm intelligence-based algorithms, namely the artificial bee colony algorithm and the particle swarm optimization algorithm. The algorithms have been compared in terms of mean localization error and computing time. The simulation results show that the CA performs the localization in a more accurate manner and at a higher speed than the other two algorithms.

Suggested Citation

  • Vaishali Raghavendra Kulkarni & Veena Desai, 2020. "Sensor Localization in Wireless Sensor Networks Using Cultural Algorithm," International Journal of Swarm Intelligence Research (IJSIR), IGI Global, vol. 11(4), pages 106-122, October.
    • Handle: RePEc:igg:jsir00:v:11:y:2020:i:4:p:106-122
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