The Importance of Data Compression for Energy Efficiency in Sensor Networks

First, we demonstrate that not only does data compression help reduce the communication latency in a sensor network (as one would expect) but that it can also be used to gain energy efficiency since data compression reduces the energy spent transmitting data – which is one of the most energyhungry tasks in a sensor network. Through simulations we show that data compression can bring more energy efficiency to a network than does recently proposed combinations of routing and data aggregation. Second, we propose a new viewpoint for data compression in sensor networks that measures distortion based on the compression scheme’s impact on statistical inference tasks (e.g., detection, estimation, recognition, etc.) and makes trades in a RateEnergy-Accuracy design space. The usefulness of this idea is demonstrated through a particular sensor network application: object location in sensorgathered images.