Enriched Performance on Wireless Sensor Network using Fuzzy based Clustering Technique

TL;DR

This paper proposes a fuzzy-based clustering protocol for wireless sensor networks that enhances energy efficiency, prolongs network lifetime, and improves data routing compared to existing methods like LEACH and HEED.

Contribution

It introduces a fuzzy-based clustering technique combined with energy-efficient cluster head selection and data routing to extend sensor network lifetime.

Findings

Prolongs network lifetime compared to LEACH and HEED.

Increases the number of alive nodes at the end of the network operation.

Fuzzy clustering outperforms K-Means in iteration count and time to first node death.

Abstract

The wireless sensor networks combines sensing, computation, and communication into a single small device. These devices depend on battery power and may be placed in hostile environments replacing them becomes a tedious task. Thus improving the energy of these networks becomes important. Clustering in wireless sensor network looks several challenges such as selection of an optimal group of sensor nodes as cluster, optimum selection of cluster head, energy balanced optimal strategy for rotating the role of cluster head in a cluster, maintaining intra and inter cluster connectivity and optimal data routing in the network. In this paper, we study a protocol supporting an energy efficient clustering, cluster head selection and data routing method to extend the lifetime of sensor network. Simulation results demonstrate that the proposed protocol prolongs network lifetime due to the use of efficient clustering, cluster head selection and data routing. The results of simulation show that at the end of some certain part of running the EECS and Fuzzy based clustering algorithm increases the number of alive nodes comparing with the LEACH and HEED methods and this can lead to an increase in sensor network lifetime. By using the EECS method the total number of messages received at base station is increased when compared with LEACH and HEED methods. The Fuzzy based clustering method compared with the K-Means Clustering by means of iteration count and time taken to die first node in wireless sensor network, as the result shows that the fuzzy based clustering method perform well than kmeans clustering methods.