Performance Analysis of Clustering Protocol Using Fuzzy Logic for Wireless Sensor Network

TL;DR

This paper evaluates a fuzzy logic-based clustering algorithm for wireless sensor networks, demonstrating its effectiveness in prolonging network lifetime and improving energy efficiency compared to traditional methods like LEACH.

Contribution

It introduces a fuzzy clustering algorithm that considers residual energy and distance to the base station, enhancing energy efficiency and stability in WSNs.

Findings

FCA outperforms LEACH in network lifetime metrics.

FCA reduces intra-cluster work for nodes near the base station.

Simulation shows improved energy efficiency with FCA.

Abstract

In order to gather information more efficiently, wireless sensor networks (WSNs) are partitioned into clusters. Most proposed clustering algorithms do not consider the location of the base station. This situation causes hot spot problems in multi-hop WSNs. In this paper, we analyze a fuzzy clustering algorithm (FCA) which aims to prolong the lifetime of WSNs. This algorithm adjusts the cluster-head radius considering the residual energy and distance to the base station parameters of the sensor nodes. This helps to decrease the intra-cluster work of the sensor nodes which are closer to the base station or have lower battery level. Fuzzy logic is utilized for handling the uncertainties in cluster-head radius estimation. We compare this algorithm with the low energy adaptive clustering hierarchy (LEACH) algorithm according to the parameters of first node dies half of the nodes alive and energy-efficiency metrics. Our simulation results show that the fuzzy clustering approach performs better than LEACH. Therefore, the FCA is a stable and energy-efficient clustering algorithm.