Tree-based energy-efficient data gathering in wireless sensor networks deploying compressive sensing

Compressive sensing (CS) provides a new paradigm for data collection in wireless sensor networks (WSNs). In this paper, we continue to exploit the integration between CS and tree-based data gathering in WSNs. Based on a tree formed as down-stream generations from the sink or base-station (BS), each parent node stores its children's readings and the corresponding measurement vectors through the data collecting process. All sensors send their own readings only once to their parents. The parent nodes generate measurements based on the projection matrix and then forward a certain number of measurements required to the upper nodes or the BS. The CS recovery algorithm implemented at the BS reconstructs precise readings from all sensors. This significantly reduces a certain number of transmissions in routing. Two additional ideas are suggested related to sensor transmission range and the probability of non-zero elements in the projection matrix for the purpose of reducing power consumption for the networks.