On-Demand Sensing and Wireless Power Transfer for Self-Sustainable Industrial Internet of Things Networks

Abstract

On-demand data sensing and wireless power transfer (WPT) can provide sustainability and robust operations in large-scale industrial Internet of Things (IoT) networks. The efficiency of on-demand data collection and WPT can be increased by efficient scheduling of IoT nodes and dedicated energy transmitters respectively. In this article, we propose an energy-aware mode switching strategy to enable IoT nodes to perform either on-demand sensing or dedicated WPT. For on-demand sensing, we propose an IoT node scheduling scheme to maximize the utility of the IoT nodes comprising residual energy and energy required for sensing operation while considering the reliability of sensing tasks. For WPT, we propose an energy transmitter scheduling scheme for IoT nodes to minimize the cost of charging while keeping IoT nodes sufficiently charged. The simulation results for IoT node scheduling demonstrate that less than 50% IoT nodes need to be activated in all scenarios to complete the tasks. The proposed energy transmitter scheduling scheme shows that less than 60% energy transmitters should be scheduled in all the scenarios which results in significant energy reduction in the overall system.