A Novel Genetic Algorithm with db4 Lifting for Optimal Sensor Node Placements

Abstract

Target coverage algorithms have considerable attention for monitoring the target point by dividing sensor nodes into cover groups, with each sensor cover group containing the target points. When the number of sensors is restricted, optimal sensor node placement becomes a key task. By placing sensors in the ideal position, the quality of maximum target coverage and node connectivity can be increased. In this paper, a novel genetic algorithm based on the 2-D discrete Daubechies 4 (db4) lifting wavelet transform is proposed for determining the optimal sensor position. Initially, the genetic algorithm identifies the population-based sensor location and 2-D discrete db4 lifting adjusts the sensor location into an optimal position where each sensor can cover a maximum number of targets that are connected to another sensor. To demonstrate that the suggested model outperforms the existing method, A series of experiments are carried out using various situations to achieve maximum target point coverage, node interconnectivity, and network lifetime with a limited number of sensor nodes.