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3-Dimensional Manifold and Machine Learning Based Localization Algorithm for Wireless Sensor Networks

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Abstract

The minimized amount of Localization accuracy is one of the common issues in Wireless sensor networks. The determination of unknown nodes in a network needs good localization approach. This paper proposes a 3-dimensional Manifold and Machine Learning based Localization algorithm for providing the solution to the localization problem. The Machine Learning uses to identify the faulty nodes in the network for better efficiency and computes the optimal solution to the real-time localization problems in WSNs. The mobility model is deployed within the sensor node and the sensor node is computed to estimate the position of the sensor node. This technique is utilized to identify the position of the unknown nodes according to the transmission range. Machine Learning technique utilizes to identify the faulty nodes from the sensor nodes for obtaining the maximum efficiency. RMSE is used to measure the errors for providing better accuracy and also increase the level of quantization for WSN localization approach. The simulation results prove that the proposed technique has high accuracy, reduced energy consumption compared with the relevant techniques.

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Acknowledgements

This work was supported by the National Research Foundation of Korea(NRF) Grant funded by the Korea government(MSIT) (NRF-2019R1F1A1060668).

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Authors and Affiliations

  1. School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, India

    Y. Harold Robinson

  2. Department of Computer Science and Engineering, Ramco Institute of Technology, Rajapalayam, Tamilnadu, India

    S. Vimal

  3. Department of Computer Science and Engineering, Anna University Regional Campus, Tirunelveli, India

    E. Golden Julie

  4. Department of Electronics and Communication Engineering, Francis Xavier Engineering College Tirunelveli, Tirunelveli, India

    K. Lakshmi Narayanan

  5. Department of Industrial Security, Chung-Ang University, Seoul, 06974, Korea

    Seungmin Rho

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Correspondence to Seungmin Rho.

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Robinson, Y.H., Vimal, S., Julie, E.G. et al. 3-Dimensional Manifold and Machine Learning Based Localization Algorithm for Wireless Sensor Networks. Wireless Pers Commun 127, 523–541 (2022). https://doi.org/10.1007/s11277-021-08291-9

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