Abstract
Sensory data in Wireless Sensor Networks have many redundancies. For this problem, the paper presents a sparse data gathering framework, which adopts Compressive Sensing(CS) to reduce data redundancies, and utilizes Unmanned Aerial Vehicle (UAV) as the mobile relay to collect the compressed data. In this framework, the UAV is only required to collect data of the fewer nodes to generate the measurement matrix, and joins the covariance matrix to design the sensing matrix in CS. To reduce energy consumption, we use greedy algorithm to plan the route of the UAV. The experiments demonstrate that the proposed framework can make data be sparser and the recovery performance be better.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have