An Energy-Efficient Distributed Unequal Clustering Approach for Lifetime Maximization in Wireless Sensor Network

Abstract

In Wireless Sensor Networks, higher energy consumption is caused due to gathering and transmission of a large amount of sensor data. In clustering, each sensor node forwards its sensed information to the Cluster Head, which further transmits the processed information to the sink. Thus, such cluster heads have more chances of being affected by node death due to higher workload and therefore rapidly decreases the lifetime of the sensor network and eventually affects the network performance. This research paper introduces a clustering algorithm named Energy-Efficient Distributed Unequal Clustering Approach for balancing the energy depletion among the cluster heads which could eliminate the hot spot problem and thus achieve lifetime maximization in Wireless Sensor Network. It implements unequal clustering technique over the sensor nodes where the cluster head election is based on fuzzy inference system, where the sensor nodes discovered with the higher chance are finalized as cluster heads. Based on the input fuzzy parameters, the cluster size is optimally adjusted to achieve load balancing among the clusters. The simulation is executed to demonstrate the performance of proposed approach with the existing LEACH, CHEF, DUCF energy-efficient clustering approach in various network scenarios.