Enhancing Barrier Coverage in Surveillance Applications Through Hybrid Directional Sensor Networks

Abstract

Directional sensor networks (DSNs) have possibility to provide more precise surveillance than conventional omni-directional sensor networks since the captured data can be of a visual nature. Therefore, the coverage problem in DSNs is completely different from that of traditional scalar sensors. Barrier coverage is a specific type of coverage that is emerged in DSNs to ensure a high-level monitoring application. In this paper, we focus on solving the barrier coverage problem in hybrid DSNs using stationary and mobile directional sensors. Our aim is to ensure a high barrier coverage specially developed for surveillance applications by proposing two approaches. In the first one, we implement a distributed algorithm based on a geometric mathematical model to calculate the new orientation of directional sensors to maximize barrier coverage. The purpose of using a geometric mathematical model is to compute, after a random deployment, the most appropriate angle of rotation for each directional sensor so that the novel DSN configuration ensures a high level of intrusion detection across the barrier. In the second one, we enhance the first approach by extending its algorithm to further improve barrier coverage using mobile directional sensors deployed far from the barrier. This solution allows us to achieve a strong barrier coverage with a minimum number of active directional sensors. Extensive simulation experiments with different scenarios are conducted to show the effectiveness of the proposed algorithms in hybrid DSNs, such as those varying the number of stationary and mobile directional sensors with different angles of view.