Resource Scheduling for Timely Wireless Powered Crowdsensing with the Aid of Average Age of Information

In future applications of Internet of Everything (IoE), we need to timely and reliably collect multi-modal sensing data in order to monitor dynamic environment. To this end, we study a timely wireless powered crowdsensing system by enabling cooperative sensing among multiple sensors to increase reliability, by exploiting radio frequency (RF) based wireless power transfer (WPT) to address energy shortage of miniature sensors, and by minimising the average age of information (AoI) to guarantee the timeliness of the sensing data. We jointly optimise the inter-group sensors scheduling and the intra-group sensors scheduling for minimising the weighted AoI among multiple group of sensors. Since the optimisation problem is NP-hard, we propose a joint scheduling algorithm to obtain the optimal scheduling policy. Simulation results demonstrate the superiority of our scheme over the existing state of the art.