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sis 20(26): e8

Research Article

A Swarm Intelligence Based Coverage Hole Healing Approach for Wireless Sensor Networks

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  • @ARTICLE{10.4108/eai.13-7-2018.163132,
        author={Shalu Mehta and Amita Malik},
        title={A Swarm Intelligence Based Coverage Hole Healing Approach for Wireless Sensor Networks},
        journal={EAI Endorsed Transactions on Scalable Information Systems},
        volume={7},
        number={26},
        publisher={EAI},
        journal_a={SIS},
        year={2020},
        month={2},
        keywords={WSN, ROI, PSO, Chaotic, GSA},
        doi={10.4108/eai.13-7-2018.163132}
    }
    
  • Shalu Mehta
    Amita Malik
    Year: 2020
    A Swarm Intelligence Based Coverage Hole Healing Approach for Wireless Sensor Networks
    SIS
    EAI
    DOI: 10.4108/eai.13-7-2018.163132
Shalu Mehta1,*, Amita Malik2
  • 1: MSIT, Janakpuri, New Delhi, India
  • 2: DCRUST, Murthal, Sonipat, Haryana, India
*Contact email: ershalu2003@gmail.com

Abstract

In the WSN network, nodes are always deprived of battery and can’t be in operation for a long time. Some nodes may die sooner than others, creating a void in the area. Our work in this article covered this hole area efficiently with the introduction of a novel hybrid optimization algorithm. Our algorithm makes the locally converging particle swarm optimization to a global optimization algorithm by ensembling it with the Gravitational search algorithm. The perturbation in this algorithm is also reduced by logistic chaotic mapping. The current solution has detected the holes and healed them with additional redundant nodes. The Delaunay triangulation method detected the number of holes with the improved algebraic approach. The results are validated by extensive experimentation with different sensing range and node's density. Our method seems to perform well than state of the art schemes. We have also shown that increasing the redundant nodes, more coverage can be achieved.

Keywords
WSN, ROI, PSO, Chaotic, GSA
Received
2019-11-19
Accepted
2020-02-08
Published
2020-02-11
Publisher
EAI
http://dx.doi.org/10.4108/eai.13-7-2018.163132

Copyright © 2020 Shalu Mehta et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.

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