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An intelligent sleep-awake energy management system for wireless sensor network

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Abstract

The Wireless Sensor Network (WSN) facilities were advanced in several digital wireless applications. However, managing the energy feature constraints is the main concern for maintaining optimal WSN performance. The clustering methods with other energy optimal protocols were implemented in the past, but the problems still do not end because of the movable environment. So, the current article has defined a novel Chimp-based Clustering Vanilla Recurrent Sleep Awake (CbCVRSA) system for the WSN application for upgrading wireless communication services. The work-free nodes have been set to a Sleep state to optimize energy utilization. The status of the present nodes in the WSN framework is forecasted through the Chimp best solution, and the best CH is selected for efficient data transmission. Finally, the reliability of the novel CbCVRSA is measured through the chief communication metrics like data broadcasting score, throughput, and packet falling rate. In addition, the comparative assessment has revealed the improvement and the need for a novel solution for this particular application.

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Data sharing not applicable to this article as no datasets were generated or analyzed during the current study.

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This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

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Authors and Affiliations

  1. Research Scholar, Department of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai, Tamil Nadu, 600124, India

    Sai Srinivas Vellela

  2. Department of Artificial Intelligence, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai, Tamil Nadu, 600124, India

    R. Balamanigandan

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  1. Sai Srinivas Vellela
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Authors SSV and RB have contributed equally to the work.

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Correspondence to Sai Srinivas Vellela.

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Vellela, S.S., Balamanigandan, R. An intelligent sleep-awake energy management system for wireless sensor network. Peer-to-Peer Netw. Appl. 16, 2714–2731 (2023). https://doi.org/10.1007/s12083-023-01558-x

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