Smart sleeping strategies for localization and tracking in sensor networks

We study a tracking problem in sensor networks, in which the object being tracked moves along a random path through the network and the sensors switch between active and sleep states to conserve energy. It is assumed that a sensor that is asleep cannot be communicated with, and hence the sleep duration must be determined at the time the sensor goes to sleep based on all the information available in the network. We consider the design of smart sleeping policies that optimize the tradeoff between the resulting energy savings and tracking performance. This work represents a continuation of our previous work in this area, in which we incorporate a more realistic sensing model than that used previously. The result is a more difficult problem in which the cooperation among the sensors must be appropriately modeled to yield good results. We design several suboptimal policies and characterize their performance via simulations. The results indicate that by more accurately modeling the cooperation among the sensors, the tradeoff between tracking performance and energy savings can be further exploited.