Angular Mobility Assisted Coverage in Directional Sensor Networks

In this paper, we consider the issue of angular mobility assisted coverage enhancement in directional camera sensor networks. In our model, each sensor can visually capture (i.e. sense) events within a sector in its field of view, and can also rotate about a fixed axis to enhance its coverage. The problem we particularly address is how to enhance blanket coverage leveraging angular mobility of the sensors in the network starting from an arbitrary initial deployment. The core idea of our algorithm, called the Face Away algorithm, is to use the known directions of neighboring sensors to find the direction with the least density of neighbors for each sensor, in an attempt to minimize the sensing range overlap between neighboring sensors. The algorithm is localized, light-weight and purely distributed. Simulation results are presented to illustrate the performance of our algorithm as a function of various parameters like number of sensor nodes, sensing range, and angle of view.