[This article belongs to Volume - 56, Issue - 01, 2024]
Gongcheng Kexue Yu Jishu/Advanced Engineering Science
Journal ID : AES-30-04-2024-39

Title : FUZZY GAUSSIAN ADAPTIVE CLUSTERING METHOD FOR IMPROVING ENERGY EFFICIENCY AND LIFESPAN OF NODES IN WIRELESS SENSOR NETWORKS
M.Manoranjani1, Dr. S. Sukumaran2

Abstract :

A Wireless Sensor Networks (WSNs) serves the purpose of sensing and gathering critical information from its environment. The pivotal consideration in this framework is energy consumption, a factor predominantly influenced by the chosen clustering approach. Although numerous clustering techniques have been devised to sustain stable energy levels for sensor nodes in WSNs, their performance has proven to be less than optimal. This work introduces an innovative method, termed Fuzzy Gaussian Adaptive Clustering Algorithm (FGAC), to elevate clustering performance within WSNs. FGAC initiates with a meticulous data preprocessing phase wherein sensor nodes are systematically organized into clusters, and a designated Cluster Lead (CL) is assigned for efficient data collection and transmission to the BS. Especially, FGAC prioritizes the quality and standardization of sensor data. The outcomes yield a comprehensive representation of the inherent structure of sensor networks, adeptly addressing challenges associated with uncertainty. The proposed method is evaluated using WSN-specific metrics, factors such as energy efficiency, throughput, latency and clustering accuracy. The experimental results demonstrate the effectiveness of the proposed approach, revealing best clustering performance contrasted with other methodologies.