Abstract

Wireless Sensor Networks (WSNs) is a emerging technology of real time embedded systems for a variety of applications. In general, WSNs has great challenges in the factor of limited computation, energy and memory resources. Clustering techniques play a vital role in WSNs to increase the network lifetime and also made energy efficiency. Existing clustering approaches like LEACH uses neighboring information of the nodes for selecting cluster heads and other nodes spent more energy for transmitting data to cluster head. It was not considered the expected residual energy for selecting a cluster head. In this study, Genetic Algorithm (GA) is used to form optimal clusters based on fitness parameters including Cluster Distance (CD), Direct Distance to Base Station (DDBS) and Energy of nodes. Also, fuzzy logic approach is applied to select optimal cluster head by using expected residual energy that increases the network lifetime. The aim of the study is providing a solution for unbalanced energy consumption problem in a WSN. The simulation results show that the proposed protocol performs well than other protocols like LEACH and LEACH_ERE.

Keywords:

Cluster head, expected residual energy, fuzzy logic, genetic algorithm, wireless sensor networks,

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Competing interests

The authors have no competing interests.

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