Energy-efficient data gathering scheme based on Kalman prediction and compressed sensing

Abstract

A novel Kalman prediction and compressed sensing based energy-efficient data gathering scheme was proposed. Specially, in the intra-cluster transmission, the cluster members utilized the Kalman prediction to selectively send the data to their cluster heads. In the inter-cluster transmission, the cluster heads leveraged the hybrid compressed sensing to transfer the data to the sink via multi-hop links. Moreover, the communication cost was derived to verify the efficiency of the proposed method. Simulation results show that the proposed method has higher energy efficiency compared with the available schemes, and the sink can obtain measurements with reasonable quality by using the proposed method.

Keywords

• wireless sensor network;Kalman prediction;compressed sensing;spatial-temporal correlation;energy efficiency