A UAV-based compressive algorithm for minimizing the energy consumption of large-scale WSNs

Abstract

In large-scale environmental monitoring, massive sensor nodes regularly collect data and transmit them over long distances, which burdens the network and leads to the increased energy consumption. To deal with this problem, we develop an Unmanned Aerial Vehicle (UAV)-based compressive algorithm. In this algorithm, the network clustering technologies and Compressive Sensing are exploited to decrease the amount of data throughout the network. Monte Carlo method is used to group sensor nodes into clusters. The UAV is dispatched as a mobile agent to collect data from the cluster heads. Compared with the benchmark algorithms, the simulations demonstrate that the algorithm proposed in this paper can decrease the network’s energy consumption and obtain better environmental monitoring results.