Analysis of Enhanced Deployment Models for Sensor Networks

We present the estimation and evaluation of deployment models for sensor networks that exploit different amounts of a-priori information. Topologies generated from the models exhibit minimum energy consumption at maximum sensing coverage. The applied energy model makes use of measurements obtained from real experiments. We consider general sets of interesting points in the phenomena since those exhibit most of the information content. The estimated models lead to significantly optimized initial network deployments which can be subsequently used with other existing optimization techniques. Overall the energy-efficiency, sensing coverage and operational lifetime of Wireless Sensor Networks (WSNs) are strongly improved by our suggested deployment model. Furthermore, we derive a novel metric from our analysis enabling the estimation of the performance of WSNs. This metric makes use of both measures describing the similarity of probability distributions and measures characterizing spatial correlations.