Prediction-Based Strategies for Energy Saving in Object Tracking Sensor Networks

In order to fully realize the potential of sensor networks, energy awareness should be incorporated into every stage of the network design and operation. In this paper, we address the energy management issue in a sensor network killer application - object tracking sensor networks (OTSNs). Based on the fact that the movements of the tracked objects are sometimes predictable, we propose a Prediction-based Energy Saving scheme, called PES, to reduce the energy consumption for object tracking under acceptable conditions. We compare PES against the basic schemes we proposed in the paper to explore the conditions under which PES is most desired. We also test the effect of some parameters related to the system workload, object moving behavior and sensing operations on PES through extensive simulation. Our results show that PES can save significant energy under various conditions.

• Type: Conference
• Year: 2004
• Where: MDM
• Authors: Yingqi Xu, Julian Winter, Wang-Chien Lee
• Keywords: MDM 2004, Object Tracking, Object Tracking Sensor, Sensor Networks