Cover set formation for target coverage using genetic algorithm in directional sensor networks

Abstract

Maximizing the network lifetime is one important factor in covering a set of targets in directional sensor networks (DSNs). The targets may take time to be located, and a good tracking management system is necessary to locate them. Target coverage problem arises due to limitation in the sensing angle and battery power of directional sensors. The problem becomes more challenging when the targets have different coverage quality requirements. In the present study, this problem is referred to as Priority-based Target Coverage (PTC) that has been proven to be an NP-complete problem. As sensors are often deployed densely, a promising solution to this problem is the use of scheduling technique through which the sensors are partitioned into several cover sets, then the cover sets are activated successively. In this paper, we propose a genetic-based scheduling algorithm to solve the problem. In order to examine the impact of different factors on the size of the resulting subset, three different experiments were performed to test the effectiveness of our algorithm. The results demonstrated that the proposed algorithm was able to contribute to solving the problem significantly.