Energy-Efficient Data Gathering in Wireless Sensor Network Using Compressive Sensing

Wireless Sensor Network (WSN) is wildly used for a range of applications, one of the most important issues is to improve network lifetime of the sensor node powered by battery. Inspired by Compressive Sensing theory, we proposed an energy-balanced scheme of data gathering denoted by Changeable Probability Compressive Sensing (CPCS). In the proposed approach, we use Compressive Sensing to reduce the transmission costs. Moreover, we design a method for sensors to dynamically adjust their probability involved in every CS measurement according to the received average in-network residual energy. With extensive experiments over real sensory data, we demonstrate that the proposed method can effectively prolong the network lifetime. Keywords— ―Wireless Sensor Network‖, ―Compressive Sensing‖, ―Data collection‖, ―Energy-balanced‖, ―residual power‖