Abstract
As a promising tool for monitoring the physical world, directional sensor networks (DSNs) consisting of a large number of directional sensors are attracting increasing attention. As directional sensors in DSNs have limited battery power and restricted angles of sensing range, maximizing the network lifetime while monitoring all the targets in a given area remains a challenge. A major technique to conserve the energy of directional sensors is to use a node wake-up scheduling protocol by which some sensors remain active to provide sensing services, while the others are inactive to conserve their energy. In this paper, we first address a Maximum Set Covers for DSNs (MSCD) problem, which is known to be NP-complete, and present a greedy algorithm-based target coverage scheduling scheme that can solve this problem by heuristics. This scheme is used as a baseline for comparison. We then propose a target coverage scheduling scheme based on a genetic algorithm that can find the optimal cover sets to extend the network lifetime while monitoring all targets by the evolutionary global search technique. To verify and evaluate these schemes, we conducted simulations and showed that the schemes can contribute to extending the network lifetime. Simulation results indicated that the genetic algorithm-based scheduling scheme had better performance than the greedy algorithm-based scheme in terms of maximizing network lifetime.
Highlights
Wireless sensor networks (WSNs) have been employed in various fields such as environmental monitoring, battlefield surveillance, smart spaces, etc. [1]
We will propose a genetic algorithm-based target coverage scheduling scheme that can find the optimal solution to the Maximum Set Covers for DSNs (MSCD) problem by evolutionary global search
Comparing the two schemes with regard to their network lifetime, our genetic algorithm-based target coverage scheduling scheme markedly extends the network lifetime compared with our greedy algorithm-based scheme, regardless of the number of directional sensors. This result indicates that the genetic algorithm-based scheme can find an optimal solution to the MSCD problem by global evolutionary search, in contrast to the greedy algorithm-based scheme, which is dependent on a heuristic search
Summary
Wireless sensor networks (WSNs) have been employed in various fields such as environmental monitoring, battlefield surveillance, smart spaces, etc. [1]. Many attempts have been made to maximize network lifetime based on node wake-up scheduling protocols These studies have assumed that WSNs have omnidirectional sensors, each of which can sense an omnidirectional range at each instance [4,8]. We describe a Maximum Set Covers for DSNs (MSCD) problem, which entails finding the cover sets that monitor all the targets in an energy-efficient way and maximizing the network lifetime by assigning different scheduling times to each cover set. Simulation results verified that these two schemes can solve the MSCD problem They showed that the genetic algorithm-based target scheduling scheme is better capable of finding cover sets with an extended network lifetime as compared with the greedy algorithm-based scheme. This paper is an updated and extended version of [16]
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