Energy-aware routing algorithm in wireless sensor networks using water-cycle algorithm and fuzzy logic system

Yinghua  Li

doi:10.6180/jase.202412_27(12).0004

Energy-aware routing algorithm in wireless sensor networks using water-cycle algorithm and fuzzy logic system

Environmental Engineering Water Resources Engineering

Yinghua LiThis email address is being protected from spambots. You need JavaScript enabled to view it.

XI’AN MingDe Institute of Technology, Xi’an, Shanxi 710124, China

Received: July 29, 2023
Accepted: December 16, 2023
Publication Date: February 20, 2024

Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.

Download Citation: ||https://doi.org/10.6180/jase.202412_27(12).0004

Clustering in Wireless Sensor Networks (WSNs) has emerged as a critical strategy for improving network efficiency and extending the network’s lifespan. Optimizing energy efficiency becomes paramount as the demand for WSNs grows in applications such as underground mining, healthcare, security surveillance, and environmental monitoring. This work introduces a novel hybrid clustering approach that combines the WaterCycle Algorithm (WCA) with a fuzzy logic system to address the inherent challenges in clustering WSNs. The primary motivation for this research is to enhance energy efficiency, prolong network operation, and address the shortcomings of traditional clustering methods. These shortcomings include unbalanced clusters, suboptimal cluster head selection, and limited adaptability to diverse application requirements. The proposed approach aims to overcome these limitations by utilizing the WCA’s inspiration from the natural water cycle coupled with a dynamic fuzzy logic system for cluster head selection. The proposed approach is tested for different network sizes and compared with existing algorithms. The results suggested that the suggested algorithm is superior to its competitors regarding network lifetime and energy consumption.

Keywords: WSN; Routing; Clustering; Energy efficiency; Optimization.

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