Power Aware Wireless Sensor Networks based on Compressive Sensing

This paper presents a novel approach based on the compressive sensing (CS) in order to reduce the energy consumption in a wireless sensor network (WSN). The proposed method exploits the compressibility of the signal to reduce the number of samples required to recover the sampled signal at the sink node and so reduce the energy consumption of the sensors. We applied different types of compressive sensing and tried to add a compression method at the sparsification level to optimize the energy reduction. In addition, we propose a feedback scheme to enable the sensor to adjust its sampling rate to maintain an acceptable reconstruction performance while minimizing the energy consumption. For evaluation purposes, the approach is implemented on one of the commercially available wireless sensor modules, referred to as panStamps. A reduction of 79% in energy consumption is obtained on a common sensing scenario.