Joint routing and scheduling for data collection with compressive sensing to achieve order-optimal latency

We consider a joint routing and scheduling scheme for data collection in wireless sensor networks leveraging compressive sensing under the protocol interference model. We propose the construction of a connected dominating set as a network backbone for efficient routing. A hybrid compressive sensing technique, which combines conventional and compressive data gathering schemes, is used to aggregate data over the backbone. Pipelined scheduling is developed for fast aggregation of compressed data over the backbone. We set the communication range of sensor nodes to an appropriate value to control the size of the backbone and demonstrate that the proposed scheme can achieve order-optimal latency for data gathering. We extend the proposed scheme to the physical interference model and show that comparable latency is achievable under physical interference model. In addition, the proposed scheme is shown to be energy-efficient, in that it can achieve order-optimal energy consumption given that the sensor data sparsity is of constant order. Simulation results show the effectiveness of the proposed scheme in terms of latency and energy consumption.