Coverage-Enhancing Algorithm for Directional Sensor Networks

Adequate coverage is very important for sensor networks to fulfill the issued sensing tasks. In traditional sensor networks, the sensors are based on omni-sensing model. However, directional sensing sensors are with great application chances, typically in video sensor networks. Toward this end, this paper addresses the problem of enhancing coverage in a directional sensor network. First, based on a rotatable directional sensing model, we present a method to deterministically estimate the amount of directional nodes for a given coverage rate. We also employ Sensing Connected Sub-graph (SCSG) to divide a directional sensor network into several parts in a distributed manner, in order to decrease time complexity. Moreover, the concept of convex hull is introduced to model each sensing connected sub-graph. According to the characteristic of adjustable sensing directions of directional nodes, we study a coverage-enhancing algorithm to minimize the overlapping sensing area of directional sensors only with local topology information. Extensive simulation is conducted to verify the effectiveness of our solution and we give detailed discussions on the effects of different system parameters.

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