Compressive sensing based random walk routing in wireless sensor networks

Random walk (RW) routing for monitoring purposes in Wireless Sensor Networks (WSNs) has been proven to be an energy-efficient method. In this paper, we exploit the integration between Compressive Sensing (CS) and RW to reduce energy consumption for such networks. All the sensory data is reconstructed at the base-station (BS) based on a smaller number of CS measurements compared to the total number of sensor nodes. Each CS measurement is collected through a RW routing with a predefined length. All random CS measurements are forwarded to the BS for the CS recovery process in two either ways: directly or by relaying through intermediate nodes. A trade-off between the sensor transmission range and the length of RWs is investigated for the networks to achieve the smallest energy consumption. We further formulate the average consumed energy of each random walk based on the sensor transmission range. The average consumed energy to send the measurements from RWs to the BS either directly or by relaying in multi-hop are formulated and analyzed. We calculate the total energy consumption in different conditions and suggest the optimal case for the networks to spend the least energy that significantly prolongs the network lifetime.

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