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Fuzzy logic based 3D localization in wireless sensor networks using invasive weed and bacterial foraging optimization

Author

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  • Gaurav Sharma

    (National Institute of Technology)

  • Ashok Kumar

    (National Institute of Technology)

Abstract

The purpose of this paper is to improve the performance of node localization in 3D space for wireless sensor network. To achieve this objective, we propose two range free localization algorithms for 3D space in anisotropic environment using the application of bacterial foraging optimization (BFO) and invasive weed optimization (IWO). In proposed methods, only received signal strength (RSS) information between nodes is sufficient for estimating target nodes locations. The RSS information gives clue to find out the distances between target nodes and anchor nodes. To overcome the non-linearity between RSS and distance, edge weights between target nodes and their neighbouring anchor nodes are considered to estimate the positions of target nodes. To further reduce the computational complexity and to model the edge weights, we use fuzzy logic system in this paper. BFO and IWO techniques are used to further optimize the edge weights separately to achieve the better localization accuracy. The simulation results show the superiority of the proposed algorithms as compared to centroid method, weighted centroid and existing 3D localization algorithms in terms of localization accuracy, stability, positioning coverage and scalability.

Suggested Citation

  • Gaurav Sharma & Ashok Kumar, 2018. "Fuzzy logic based 3D localization in wireless sensor networks using invasive weed and bacterial foraging optimization," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 67(2), pages 149-162, February.
    • Handle: RePEc:spr:telsys:v:67:y:2018:i:2:d:10.1007_s11235-017-0333-0
    DOI: 10.1007/s11235-017-0333-0
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    References listed on IDEAS

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    1. Xuan Liu & Shigeng Zhang & Kai Bu, 2016. "A locality-based range-free localization algorithm for anisotropic wireless sensor networks," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 62(1), pages 3-13, May.
    2. Shrawan Kumar & D. K. Lobiyal, 2017. "Novel DV-Hop localization algorithm for wireless sensor networks," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 64(3), pages 509-524, March.
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    Cited by:

    1. Soumya J. Bhat & K. V. Santhosh, 2022. "Localization of isotropic and anisotropic wireless sensor networks in 2D and 3D fields," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 79(2), pages 309-321, February.
    2. Prabhjot Singh & Nitin Mittal & Parulpreet Singh, 2022. "A novel hybrid range-free approach to locate sensor nodes in 3D WSN using GWO-FA algorithm," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 80(3), pages 303-323, July.
    3. Hilary I. Okagbue & Muminu O. Adamu & Timothy A. Anake & Ashiribo S. Wusu, 2019. "Nature inspired quantile estimates of the Nakagami distribution," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 72(4), pages 517-541, December.
    4. Shilpi & Arvind Kumar, 2023. "A localization algorithm using reliable anchor pair selection and Jaya algorithm for wireless sensor networks," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 82(2), pages 277-289, February.

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