Cost-efficient barrier coverage with a hybrid sensor network under practical constraints

Barrier coverage is a natural application of sensor networks in which sensors are deployed to detect intruders or protect crucial resources. In this paper, we consider a hybrid sensor network with a two-phase deployment, in which less-expensive static sensors are first randomly deployed in an area, and then more-expensive mobile sensors are deployed to fill coverage gaps. We use a probabilistic model to take into account the practical constraints of detection probability and false positives. We propose an iterative scheme that finds a sensor deployment strategy that minimizes the total sensor cost. Our scheme makes use of a graph transformation and includes speed-up strategies. We present simulation results that verify the correctness of the proposed scheme and demonstrate the effectiveness of the speed-up strategies.