Two Scheduling Schemes for Extending the Lifetime of Directional Sensor Networks

Abstract

Since directional sensor networks (DSNs) are composed of a large number of sensors equipped with a limited battery and limited angles of sensing range, maximizing network lifetime while covering all the targets in a given area is still a challenge problem. In this paper, we first address the MSCD (Maximum Set Cover for DSNs) problem that is known as NP-complete. We then present a new target coverage scheduling scheme to solve this problem with a greedy algorithm. We also present another target coverage scheduling scheme based on a genetic algorithm that can find an optimal solution for target coverage by evolutionary global search technique. To verify and evaluate these schemes, we conduct simulations and show that they can contribute to extending the network lifetime. Simulation results indicate that a genetic algorithm-based scheduling scheme has a better performance than a greedy algorithm-based one in terms of the maximization of the network lifetime.