Energy-efficient Data Aggregation Scheme for Underwater Acoustic Sensor Networks

Energy-efficient data aggregation becomes important for underwater acoustic sensor networks due to its energy constrained character. In this paper, we propose a new energy-efficient data aggregation scheme derived from distributed compressed sensing (DCS) theory to reduce communication cost and prolong network lifetime. First, we introduce a distributed compressed sensing model for cluster-based UASNs. Second, we propose a kind of measurement matrix with strictly restricted isometry property (RIP), namely block upper triangular matrix, which takes multi-hop communication cost into account. Finally, a distributed compressed sensing reconstruction algorithm called DCS-SOMP is adopted to recover sensor readings at the sink. We carry out simulations on real sensor readings. The results demonstrate that the new data aggregation scheme can preserve sensor readings fidelity at a reduced communication cost.