Fuzzy based Hierachical Unequal Clustering in Wireless Sensor Networks

Abstract

Objectives: Sensor nodes in Wireless Sensor Networks are battery powered and non rechargeable, and hence in most of the real time applications energy consumption is a major problem. The lifetime of the network also depends upon the energy consumption model which may affect the entire performance of the networks. The main aim of the proposed Hierarchical Unequal Clustering Fuzzy Algorithm (HUCFA) is to reduce the energy consumption of over all networks. Methods/Statistical Analysis: Clustering is an important technique used for energy efficient data communication in WSN. Fuzzy logic is applied in the proposed algorithm to choose the cluster head, which enhances the energy efficiency. To choose a better cluster head, the characteristics of the nodes are taken as input for fuzzy inference system. Based on the fuzzy rules, best nodes are selected as cluster heads. Fuzzy Logic Toolbox in Matlab R2010a is utilized for the simulation. Findings: Total Energy Consumption of the network (TEC) in HUCFA is 7.05% less when compared to LEACH. Standard deviation of energy distribution among all the clusters in the HUCFA is 10.46% less than that of LEACH protocol and 0.79% less than Hierarchical Unequal Clustering Algorithm. Application/Improvements: The proposed HUCFA using Fuzzy Logic is found to be better and more energy efficient for the applications involving low powered sensor nodes which is proved through simulation results.