A probabilistic signal-strength-based evaluation methodology for sensor network deployment

The deployment of sensor networks have attracted a lot of attention recently. In essence this issue is concerned with how well a sensing field is monitored by sensors to achieve a particular coverage. In this paper, we propose a signal-strength-based approach to evaluate how well a sensing field is covered/monitored. We first formulate object tracking by a single sensor as a Gaussian-error model. Then we establish an error model on location estimation given that the location of an object is known. This leads to a model to evaluate a sensor network with given locations of sensors. We then apply the result to several applications, such as adding more sensor nodes for error reduction and scheduling power modes (awake or sleep) of sensors, and demonstrate our simulation results.