Abstract
A NOVEL METAHEURISTIC GRAY WOLF OPTIMIZATION (GWO) ALGORITHM TO ENHANCE THE LIFE TIME OF WIRELESS SENSOR NETWORKS
Rakhi Kashyap*, Baldev Raj and Sameru Sharma
ABSTRACT
Wireless sensor networks (WSNs) are made up of several sensors (a few tens to thousands), with characteristics such as self-organizing, low cost, and random deployment. They have predominantly been used for habitat monitoring, disaster prevention, health care, agriculture, monitoring regions, and fire tracking. Researchers have studiednumerous energy-efficient WSN operation strategies using clustering. Clustering has been an efficient technique for reducing energy utilization, increasing the stabilization of topology of network and the life time of the network. Energy efficient operation is a captious issue that has to be addressed with wireless sensor network deployments. Cluster based protocols are developed to tackle this problem, and the Low energy adaptive clustering hierarchy (LEACH) is the best-known protocol of this type. However, certain aspects of LEACH offer room for improvement, one such aspect is the arrangement of sensor networks with the fixed base station location. In this paper, an algorithm known as Gray Wolf Optimization (GWO) algorithm is used to compute the effective performance based on energy consumption, packet delivery ratio, end-to-end delay and network lifetime. The proposed algorithm is compared with previous algorithms such as PSO, ACO and GA on the basis of the given parameters to show that the proposed algorithm is better for network life enhancement of WSN. The result is carried out in MATLAB.
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