Random routing algorithm for rhombic-deployed sensor networks based on compressed sensing

Joint routing and compression has been the research hotspot in practical sensor networks. Compressed sensing provides a radically different view of the structure of data and a promising new approach for jointly acquiring and aggregating data from distributed data sources. Therefore, the random routing algorithm is proposed combined with compressive sensing for energy efficient data gathering in rhombic-deployed sensor networks, which satisfies the basic principles of compressed sensing, and can effective reconstruct the original signal. The performance of reconstruction on the basis of reconstruction error, energy consumption, and running time of data reconstruction is analyzed. The experiment results validate its rationality and efficiency.