Energy-efficient protocols for wireless sensor networks in IoT applications

Authors

  • Anish Bhargav * School of Computer Science Engineering, KIIT University, Bhubaneswar, India

https://doi.org/10.22105/metaverse.v2i1.52

Abstract

Recent developments in low-power communication and signal processing technologies have led to the extensive implementation of Wireless Sensor Networks (WSNs). In a WSN environment, cluster formation and Cluster Head (CH) selection consume significant energy. Typically, the CH is chosen probabilistically without considering real-time factors such as the remaining energy, number of clusters, distance, location, and number of functional nodes to boost network lifetime. Different strategies must be incorporated based on real-time issues to design a generic protocol suited for applications such as environmental and health monitoring, animal tracking, and home automation. Elementary protocols such as Low Energy Adaptive Clustering Hierarchy (LEACH) and centralized LEACH are well proven, but gradually, limitations evolved due to increasing desire and need for proper modification over time. Since the selection of CHs has always been an essential criterion for clustered networks, this paper overviews the modifications in the threshold value of CH selection in the network. With the evolution of bio-inspired algorithms, the CH selection has also been enhanced considering the behavior of the network. This paper briefly describes LEACH-based and bio-inspired protocols, their pros and cons, assumptions, and the criteria for CH selection. Finally, various protocols' performance factors, such as longevity, scalability, and packet delivery ratio, are compared and discussed.

Keywords:

Wireless sensor network, Clustering, Hierarchical routing, LEACH protocol, Threshold-based cluster head selection

References

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Published

2025-03-08

Issue

Vol. 2 No. 1 (2025): Metaversalize

Section

Articles

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How to Cite

Bhargav, A. . (2025). Energy-efficient protocols for wireless sensor networks in IoT applications. Metaversalize, 2(1), 40-50. https://doi.org/10.22105/metaverse.v2i1.52
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