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Artificial-Intelligence-Based Charger Deployment in Wireless Rechargeable Sensor Networks

Author

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  • Hsin-Hung Cho

    (Department of Computer Science and Information Engineering, National Ilan University, Yilan 260, Taiwan)

  • Wei-Che Chien

    (Department of Computer Science and Information Engineering, National Dong Hwa University, Hualien 974, Taiwan)

  • Fan-Hsun Tseng

    (Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan 701, Taiwan)

  • Han-Chieh Chao

    (Department of Electrical Engineering, National Dong Hwa University, Hualien 974, Taiwan
    Institute of Computer Science and Innovation, UCSI University, Kuala Lumpur 5600, Malaysia)

Abstract

To extend a network’s lifetime, wireless rechargeable sensor networks are promising solutions. Chargers can be deployed to replenish energy for the sensors. However, deployment cost will increase when the number of chargers increases. Many metrics may affect the final policy for charger deployment, such as distance, the power requirement of the sensors and transmission radius, which makes the charger deployment problem very complex and difficult to solve. In this paper, we propose an efficient method for determining the field of interest (FoI) in which to find suitable candidate positions of chargers with lower computational costs. In addition, we designed four metaheuristic algorithms to address the local optima problem. Since we know that metaheuristic algorithms always require more computational costs for escaping local optima, we designed a new framework to reduce the searching space effectively. The simulation results show that the proposed method can achieve the best price–performance ratio.

Suggested Citation

  • Hsin-Hung Cho & Wei-Che Chien & Fan-Hsun Tseng & Han-Chieh Chao, 2023. "Artificial-Intelligence-Based Charger Deployment in Wireless Rechargeable Sensor Networks," Future Internet, MDPI, vol. 15(3), pages 1-18, March.
    • Handle: RePEc:gam:jftint:v:15:y:2023:i:3:p:117-:d:1103910
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    References listed on IDEAS

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    1. Fred Glover, 1990. "Tabu Search—Part II," INFORMS Journal on Computing, INFORMS, vol. 2(1), pages 4-32, February.
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    Cited by:

    1. Peng Wang & Yonghua Xiong, 2024. "A Method to Optimize Deployment of Directional Sensors for Coverage Enhancement in the Sensing Layer of IoT," Future Internet, MDPI, vol. 16(8), pages 1-22, August.

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