AUTHOR=Han Zhihui , Gong Jie TITLE=Status update control based on reinforcement learning in energy harvesting sensor networks JOURNAL=Frontiers in Communications and Networks VOLUME=3 YEAR=2022 URL=https://www.frontiersin.org/journals/communications-and-networks/articles/10.3389/frcmn.2022.933047 DOI=10.3389/frcmn.2022.933047 ISSN=2673-530X ABSTRACT=
With the development of the Internet of Things, more and more sensors are deployed to monitor the environmental status. To reduce deployment costs, a large number of sensors need to be deployed without a stable grid power supply. Therefore, on the one hand, the wireless sensors need to save as much energy as possible to extend their lifetime. On the other hand, they need to sense and transmit timely and accurate information for real-time monitoring. In this study, based on the spatiotemporal correlation of the environmental status monitored by the sensors, status information estimation is considered to effectively reduce the information collection frequency of the sensors, thereby reducing the energy cost. Under an ideal communication model with unlimited and perfect channels, a status update scheduling mechanism based on a