Probabilistic Lifetime Maximization of Sensor Networks.

The design of power-aware lifetime maximization algorithms for sensor networks is an active area of research. However, the standard assumption is that the performance of the sensors remains the same throughout the network's lifetime, which is not always true. In this paper, we study the effects of power decay on the performance of individual sensors as well as of the entire network. In particular, we examine networks with decaying footprints, akin to those of RF or radar-based sensors and relate the performance of a sensor to its available power. Moreover, we propose probabilistic scheduling controllers that compensate for the effects of the decrease in power while maintaining an adequate probability of event detection under two sensing models; Boolean and non-Boolean. We simulate the performance of the proposed controllers to establish that the desired performance levels are indeed maintained throughout the lifetime of the network.