A Tabu Search Approach for Differentiated Sensor Network Deployment

In this paper, we address the wireless sensor network (WSN) deployment issue. Compared to similar works, we relax some assumptions that were generally considered in the literature. Precisely, instead of the classical binary detection model, we consider a distance-related probabilistic one. Moreover, we assume that the observed area is characterized by the geographical irregularity of the sensed events. Our resulting differentiated WSN deployment problem is formulated as a multi-objectives optimization one. To overcome the computational complexity of an exact resolution, we propose an original pseudo-random approach based on the tabu search heuristic. Our proposal is able to take into consideration the required detection probability threshold of each point in the monitored area while minimizing the number of deployed sensors. Performances evaluations show that our proposal achieves a much better satisfaction rate than several other approaches proposed in the literature.