Energy efficient data transmission scheme integrating clustering and compressive sensing in wireless sensor networks

Abstract Aiming at the actual situation where sensor nodes in wireless sensor networks collect and transmit a large amount of redundant data, an energy-efficient data transmission scheme named EETICC has been proposed, which integrates an appropriate clustering algorithm and compressive sensing (CS) technique. EETICC aims to save as much unnecessary energy consumption as possible by reducing the transmission of redundant sensing data. Firstly, a revised K-medoids clustering algorithm considering the rotation of cluster heads organizes sensor nodes into a hierarchical cluster structure. This makes the distribution of sensor nodes more rational and better balances the energy consumption of the sensor nodes. Secondly, cluster heads process the data collected by the sensor nodes within their clusters using CS and transmit the compressed sparse data to the sink node through multi-hop relaying. Finally, the sink node can effectively recover the received data by exploiting a proper data reconstruction algorithm. Compared to other data transmission policies based on classical clustering protocols and CS methods, simulation results in terms of several common performance metrics show that the EETICC can significantly decrease unnecessary data transmission, save valuable network energy, and prolong the network lifetime, all while ensuring the accurate recovery of the original data.