A novel data gathering algorithm based on compressed sensing for heterogeneous wireless sensor networks

As an emerging technique for signal processing, compressed sensing (CS) is being widely used in wireless sensor networks (WSNs). Unlike prior studies only apply CS theory to homogeneous WSNs, we develop a new data gathering algorithm based on CS for a particular heterogenous WSN. The main challenge of our scheme is how to combine CS with the heterogenous characteristic of the network. To solve this problem, we first formulate a cobweb model to structure this heterogenous WSN. Then we ameliorate the sampling stage of CS and propose a directed random routing to gather data based on the model. A simple simulate experiment is finally conducted to examine the efficiency of our work.