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Computational intelligence based localization of moving target nodes using single anchor node in wireless sensor networks

Author

Listed:
  • Parulpreet Singh

    (Dr. B.R. Ambedkar National Institute of Technology)

  • Arun Khosla

    (Dr. B.R. Ambedkar National Institute of Technology)

  • Anil Kumar

    (Chandigarh College of Engineering and Technology)

  • Mamta Khosla

    (Dr. B.R. Ambedkar National Institute of Technology)

Abstract

Wireless Sensor Networks (WSNs) have tremendous ability to interact and collect data from the physical world. The main challenges for WSNs regarding performance are data computation, prolong lifetime, routing, task scheduling, security, deployment and localization. In recent years, many Computational Intelligence (CI) based solutions for above mentioned challenges have been proposed to accomplish the desired level of performance in WSNs. Application of CI provides independent and robust solutions to ascertain accurate node position (2D/3D) with minimum hardware requirement (position finding device, i.e., GPS enabled device). The localization of static target nodes can be determined more accurately. However, in the case of moving target nodes, accurate position of each node in network is a challenging problem. In this paper, a novel concept of projecting virtual anchor nodes for localizing the moving target node is proposed using applications of Particle Swarm Intelligence, H-Best Particle Swarm Optimization, Biogeography Based Optimization and Firefly Algorithm separately. The proposed algorithms are implemented for range-based, distributed, non-collaborative and isotropic WSNs. Only single anchor node is used as a reference node to localize the moving target node in the network. Once a moving target node comes under the range of a anchor node, six virtual anchor nodes with same range are projected in a circle around the anchor node and two virtual anchor nodes (minimum three anchor nodes are required for 2D position) in surrounding (anchor and respective moving target node) are selected to find the 2D position. The performance based results on experimental mobile sensor network data demonstrate the effectiveness of the proposed algorithms by comparing the performance in terms of the number of nodes localized, localization accuracy and scalability. In proposed algorithms, problem of Line of Sight is minimized due to projection of virtual anchor nodes.

Suggested Citation

  • Parulpreet Singh & Arun Khosla & Anil Kumar & Mamta Khosla, 2018. "Computational intelligence based localization of moving target nodes using single anchor node in wireless sensor networks," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 69(3), pages 397-411, November.
    • Handle: RePEc:spr:telsys:v:69:y:2018:i:3:d:10.1007_s11235-018-0444-2
    DOI: 10.1007/s11235-018-0444-2
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    Citations

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    Cited by:

    1. 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.
    2. Goldendeep Kaur & Kiran Jyoti & Samer Shorman & Anas Ratib Alsoud & Rohit Salgotra, 2024. "An Efficient Approach for Localizing Sensor Nodes in 2D Wireless Sensor Networks Using Whale Optimization-Based Naked Mole Rat Algorithm," Mathematics, MDPI, vol. 12(15), pages 1-23, July.
    3. 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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