A Multi-Objective Particle Swarm Optimization for Wireless Sensor Network Deployment

  • Authors

    • Mohammed s. Ibrahem
    • mohd zakree ahmad nazri
    • zalinda othman
    2018-12-09
    https://doi.org/10.14419/ijet.v7i4.36.23734
  • Genetic Algorithm, Multi-Objective, Pareto-based, Particle Swarm Optimization, Region of Interest, Wireless Sensor Network.

  • Abstract

    The use of wireless sensor networks nowadays is imperative for different domain of interests. One of the challenging task in deploying such networks lies on the efficient deployment that guarantees least number of sensors while assuring the connectivity and the coverage among these sensors. This would significantly contribute toward longer lifetime of the network. Several studies have addressed this problem by proposing various meta-heuristic approaches. One of these approaches is the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) which has been extensively used for WSN deployment. However, such approach suffers of the inaccurate fitness values provided for criteria in the same front. Therefore, this paper aims to propose an alternative approach which is called Multi-Objective Particle Swarm Optimization (MOPSO). The proposed method has been compared against the NSGA-II and the results showed that the proposed method has superior performance.

     

     

     

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  • How to Cite

    s. Ibrahem, M., zakree ahmad nazri, mohd, & othman, zalinda. (2018). A Multi-Objective Particle Swarm Optimization for Wireless Sensor Network Deployment. International Journal of Engineering & Technology, 7(4.36), 140-146. https://doi.org/10.14419/ijet.v7i4.36.23734

    Received date: 2018-12-12

    Accepted date: 2018-12-12

    Published date: 2018-12-09