LAUSR

With advances in sensing technologies and wireless sensor networks, energy consumption is a key factor for data collection in sensor network. Compressive sensing has attracted more attention for reducing energy cost due to its enabled sub-Nyquist sampling rate. In this paper, the JSM-2 model was introduced for data compressed collection for sensor network based on distribution compressive sensing theory. And we deem that the quantization configuration is also a critical factor for energy efficiency for data communication. Then, we constructed energy consumption configuration model joint distribution compressive sensing and quantization compressive sensing. The experimental results showed that the proposed algorithm can gain more energy performance than conventional QCS architecture for sensor network data collection.