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A Multi-Objective DV-Hop Localization Algorithm Based on NSGA-II in Internet of Things

Author

Listed:
  • Penghong Wang

    (Complex System and Computational Intelligent Laboratory, Taiyuan University of Science and Technology, Taiyuan 030024, China)

  • Fei Xue

    (School of Information, Beijing Wuzi University, Beijing 101149, China)

  • Hangjuan Li

    (Complex System and Computational Intelligent Laboratory, Taiyuan University of Science and Technology, Taiyuan 030024, China)

  • Zhihua Cui

    (Complex System and Computational Intelligent Laboratory, Taiyuan University of Science and Technology, Taiyuan 030024, China)

  • Liping Xie

    (Complex System and Computational Intelligent Laboratory, Taiyuan University of Science and Technology, Taiyuan 030024, China)

  • Jinjun Chen

    (Department of Computer Science and Software Engineering, Swinburne University of Technology, Melbourne 3000, Australia)

Abstract

Locating node technology, as the most fundamental component of wireless sensor networks (WSNs) and internet of things (IoT), is a pivotal problem. Distance vector-hop technique (DV-Hop) is frequently used for location node estimation in WSN, but it has a poor estimation precision. In this paper, a multi-objective DV-Hop localization algorithm based on NSGA-II is designed, called NSGA-II-DV-Hop. In NSGA-II-DV-Hop, a new multi-objective model is constructed, and an enhanced constraint strategy is adopted based on all beacon nodes to enhance the DV-Hop positioning estimation precision, and test four new complex network topologies. Simulation results demonstrate that the precision performance of NSGA-II-DV-Hop significantly outperforms than other algorithms, such as CS-DV-Hop, OCS-LC-DV-Hop, and MODE-DV-Hop algorithms.

Suggested Citation

  • Penghong Wang & Fei Xue & Hangjuan Li & Zhihua Cui & Liping Xie & Jinjun Chen, 2019. "A Multi-Objective DV-Hop Localization Algorithm Based on NSGA-II in Internet of Things," Mathematics, MDPI, vol. 7(2), pages 1-20, February.
    • Handle: RePEc:gam:jmathe:v:7:y:2019:i:2:p:184-:d:206366
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    Citations

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    Cited by:

    1. Tapan Kumar Mohanta & Dushmanta Kumar Das, 2022. "Improved DV-Hop localization algorithm based on social learning class topper optimization for wireless sensor network," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 80(4), pages 529-543, August.
    2. Dezhi Han & Mengxiao Liu & Tien-Hsiung Weng & Canren Tang & Mario Donato Marino & Kuan-Ching Li, 2022. "A novel secure DV-Hop localization algorithm against wormhole attacks," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 80(3), pages 413-430, July.

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