Strong Barrier Coverage Using Directional Sensors with Arbitrarily Tunable Orientations

Barrier coverage is an important problem for sensor networks to fulfill some given sensing tasks. Barrier coverage guarantees the detection of events happened crossing a barrier of sensors. In majority study of barrier coverage using sensor networks, sensors are assumed to have an isotropic sensing model. However, in many applications such as monitoring an area using video camera, the sensors have directional sensing model. In this paper, we investigate strong barrier coverage using directional sensors, where sensors have arbitrarily tunable orientations to provide good coverage. We investigate the problem of finding appropriate orientations of directional sensors such that they can provide strong barrier coverage. By exploiting geographical relations among directional sensors and deployment region boundaries, we first introduce the concept of virtual node to reduce the solution space from continuous domain to discrete domain. We then construct a directional barrier graph (DBG) to model this barrier coverage question such that we can quickly answer whether there are directional sensors' orientations that can provide strong barrier coverage over a given belt region. If the belt region is strong barrier covered, we then develop energy-efficient solutions to find strong barrier path(s) that will approximately minimize the total or the maximum rotation angles of all directional sensors. Extensive simulations are conducted to verify the effectiveness of our solution.