An Improved Genetic Algorithm with Haar Lifting for Optimal Sensor Deployment in Target Covers Based Wireless Sensor Networks

Abstract

One of the important concerns in wireless sensor networks has been the coverage, connectivity, and energy parameters in recent days. Sensor placement imposes the continuous maintenance of sensing coverage of target points. Owing to the inadequate energy and battery lifetime of every sensor node, the target coverage problem achieving maximum quality of coverage and connectivity with a limited number of sensor nodes. The quality of maximum coverage can be enhanced by deploying sensors on an optimal location. In this chapter, an improved genetic algorithm with a 2-D discrete Haar lifting wavelet transform is intended for discovering the optimal location of every sensor node. Firstly, the genetic algorithm identifies each sensor coordinate status in the form of a population matrix. Secondly, 2-D discrete Haar lifting improves the quality of coverage and connectivity, while adjusting sensor position optimally. This algorithm retains a track of the quantity of target points, set of sensor nodes where to improve the network lifetime. The significant of experimental outcomes show the ability of the proposed method to discover the optimal location of sensor nodes. The simulation outcomes of the proposed method have been associated with random, GA deployment of the sensor, and the result confirms the superiority of the proposed method.