Clustering In Wireless Sensor Networks Using Agglomerative Algorithm: An Energy-Efficient and Flexible Approach

Abstract

In this work, Hierarchical Agglomerative Clustering (HAC) Algorithm is utilised to enhance cluster formation in Wireless Sensor Networks (WSNs), addressing the energy efficiency challenge. WSNs consist of multiple sensor nodes with limited energy resources, which necessitates effective methods for data aggregation and transmission to extend network lifespan. The HAC algorithm begins with each sensor node as a separate cluster and repeatedly merges them using the Average Linkage criteria until the desired number of clusters is achieved. Cluster Heads (CHs) are selected based on residual energy and node centrality to ensure even energy distribution across the network. The energy consumption model employs a simple radio model that includes both free space and multipath fading models, with energy costs proportional to transmission distance. The proposed clustering strategy aims to conserve energy during data transmission and processing, thereby enhancing the functionality of the WSN. This technology is expected to improve the network's energy efficiency and reliability, making it suitable for various applications, including environmental monitoring, healthcare, and industrial automation.