Task Scheduling and Trajectory Optimization for UAV-Assisted Wireless Powered Edge Networks

Although edge computing can improve the computing power of terminal devices, its limited battery capacity has become a new network bottleneck. Wireless energy transfer and UAV communication technologies have attracted widespread attention, because they can effectively alleviate equipment energy shortages and improve information transmission efficiency. This talk is based on the UAV-assisted wireless charging edge network, focusing on UAV-assisted IoT device task offloading and UAV-assisted IoT device data update. First, in order to study the task uploading and charging time scheduling issues in the UAV-assisted wireless charging edge network, we formulate a joint optimization of equipment scheduling, charging time scheduling, UAV-scheduling and system energy efficiency maximizition problem for UAV trajectory. Second, in order to study the data collection and energy transmission scheduling problems in the UAV-assisted wireless charging edge network, we formulate a joint optimization problem of associated scheduling variables, UAV trajectory, transmission scheduling variables and energy transmission scheduling based on the constraints of UAV service coverage, and decompose it into two coupled cooperative game sub-problems. Theoretical analysis and experimental results show that our solutions have advantages in terms of information age and convergence speed.