Smart Path-Finding with Local Information in a Sensory Field

Field surveillance is one of the most important applications for wireless sensor networks. Many sensors are deployed in a region of concern to detect any potential targets. On the contrary, intelligent target looks for the best path to traverse the sensing field for fear of being detected and leads to defunct surveillance. In this paper, we focus on how an intelligent target traverses the sensing field. We model this traversing problem, design, implement and evaluate a number of path-finding algorithms. Different from previous works which assume complete information of the sensing field, we assume that the target only can detect part of the sensor network in its detection radius. This makes the proposed methods more practical. Extensive experiments with a target and a sensor network confirm the validity of the approach.