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Application of Jaya algorithm for solving localization problem in a distributed Wireless Sensor Network

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Abstract

Identifying the location of the sensor nodes is a challenging aspect of Wireless Sensor Networks (WSNs) in a distributed environment. It is vital to understand where data and events come from when sensor nodes collect data and report on them. This paper uses a nature-inspired Jaya algorithm to estimate the location coordinates of target nodes in a distributed architecture of WSNs. The Jaya algorithm handles the nonlinear optimization problem of node localization in a randomly distributed sensor node configuration. The range-based, Received Signal Strength Indicator method is used for the distance estimation. MATLAB software is used to assess the proposed work, and a comparison is made with the Particle Swarm Optimization, Krill Herd Optimization, and Salp Swarm Algorithm based node localization algorithms in terms of localization error and computation time. The localization error analysis is done for the different numbers of anchor nodes and different values of degree of irregularity to verify the effectiveness of the proposed work.

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This manuscript has no associated data. The code that supports the findings of this study is available from the corresponding author upon reasonable request.

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Acknowledgments

Thank you to all the anonymous reviewers for providing valuable suggestions in order to create a better version of the proposed article.

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This research received no specific grant from any funding agency.

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Authors and Affiliations

  1. Department of Electronics and Communication Engineering, Motilal Nehru National Institute of Technology Allahabad, Prayagraj, India

    Shilpi & Arvind Kumar

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  1. Shilpi
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  2. Arvind Kumar
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Shilpi developed the theoretical formalism, performed the simulations, and wrote the manuscript. Both authors contributed to the final version of the manuscript. AK supervised the project.

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Correspondence to Shilpi.

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Shilpi, Kumar, A. Application of Jaya algorithm for solving localization problem in a distributed Wireless Sensor Network. J Supercomput 80, 6017–6041 (2024). https://doi.org/10.1007/s11227-023-05683-5

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