Optimizing deployment cost in camera-based wireless sensor networks

Abstract

We discuss in this paper a deployment optimization problem in camera-based wireless sensor networks. In particular, we propose a mathematical model to solve the problem of minimizing the number of cameras required to cover a set of targets with a given level of quality. Since solving this kind of problems with exact methods is computationally expensive, we rather rely on an adapted version of Binary Particle Swarm Optimization (BPSO). Our preliminary results are motivating since we obtain near-optimal solutions in few iterations of the algorithm. We discuss also the relevance of hybrid meta-heuristics and parallel algorithms in this context.