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Improved DV-Hop localization algorithm based on social learning class topper optimization for wireless sensor network

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  • Tapan Kumar Mohanta

    (ICFAI University)

  • Dushmanta Kumar Das

    (National Institute of Technology Nagaland)

Abstract

The process of locating nodes is really a challenging problem in the field of wireless sensor networks. Wireless sensor network localization is commonly followed by the distance vector algorithm. All beacon nodes are currently using DV-Hop algorithms to locate the dumb node. On the other hand, the approximate distance from the dumb node to certain beacon nodes contains a significant error, resulting in a large finished dumb node localization problem. To improve localization error an efficient DV-Hop method on social learning class topper optimization for wireless sensor networks is implemented in this paper. The proposed algorithm reduces communication between unknown or dumb and beacon nodes by measuring the dimensions of all the beacons at dumb nodes. The network imbalance model is frequently used to show the applicability of the proposed approach in anisotropic networks. Simulations are performed on LabVIEW 2015 platform. The results show that our proposed method outperforms some existing algorithms in terms of computing time (2%), localization error (6.6%), and localization error variance (8.3%).

Suggested Citation

  • 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.
  • Handle: RePEc:spr:telsys:v:80:y:2022:i:4:d:10.1007_s11235-022-00922-1
    DOI: 10.1007/s11235-022-00922-1
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    References listed on IDEAS

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    1. 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.
    2. Gaurav Sharma & Ashok Kumar, 2018. "Improved DV-Hop localization algorithm using teaching learning based optimization for wireless sensor networks," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 67(2), pages 163-178, February.
    3. H. Peyton Young, 2009. "Innovation Diffusion in Heterogeneous Populations: Contagion, Social Influence, and Social Learning," American Economic Review, American Economic Association, vol. 99(5), pages 1899-1924, December.
    4. Gulshan Kumar & Mritunjay Kumar Rai & Rahul Saha & Hye-jin Kim, 2018. "An improved DV-Hop localization with minimum connected dominating set for mobile nodes in wireless sensor networks," International Journal of Distributed Sensor Networks, , vol. 14(1), pages 15501477187, January.
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