An efficient energy management for solar-powered wireless visual sensor networks

Abstract

Energy harvesting is required for uninterrupted operation of WVSNs (Wireless Visual Sensor Net-works) in many applications. Solar energy is considered one of the effective energy harvesting sources for WVSN applications. In this paper, we propose an efficient energy management scheme for solar-powered WVSNs. The proposed scheme aims to maximize the overall quality of captured video while maximizing the network operation time. Our energy management is based on the prediction of energy supply and de-mand. We predict solar energy supply and demand using information from the weather forecasting center and previous events occurrence statistics at each node. The controlling knobs for the node-level and clus-ter-level energy management are video sampling rates and transferring the energy and video data among nodes with wired links The simulation results show that the proposed method achieves higher sampling quality of video data and longer WVSN operation time by 26.66% on average (up to 33.14%) compared to the greedy energy distribution approaches.