Compressed Data Aggregation: Energy-Efficient and High-Fidelity Data Collection
The authors focus on Wireless Sensor Networks (WSNs) that perform data collection with the objective of obtaining the whole dataset at the sink (as opposed to a function of the dataset). In this case, energy-efficient data collection requires the use of data aggregation. Whereas many data aggregation schemes have been investigated, they either compromise the fidelity of the recovered data or require complicated in-network compressions. In this paper, they propose a novel data aggregation scheme that exploits Compressed Sensing (CS) to achieve both recovery fidelity and energy efficiency in WSNs with arbitrary topology.