A energy efficient scheduling scheme for target tracking in wireless sensor networks

In wireless sensor networks (WSNs), an important issue for object tracking is how to schedule sensor nodes efficiently. In order to conserve energy, the sensor may be put into a sleep mode with a timer that determines the sleep duration. However, sleep scheduling inevitably increases the probability of losing track of the object when the sensor nodes that should be active are asleep. Therefore, there is a tradeoff between losing probability and energy efficiency. In this paper, we propose a predictive sleep scheduling scheme that optimize this tradeoff by utilizing positioning and road topology information. We choose the cluster hierarchy model as our network model, the individual cluster-heads are responsible for the computations, which are shown to be simple enough to be performed. Simulation results show that our scheme can leverage between energy saving and tracking error effectively.