UAV's Visit Scheduling for Age-of-Synchronization Minimization with Random Update Sensors

This paper considers an unmanned aerial vehicle (UAV) collecting status updates from remote sensors to a control center for environmental status monitoring. A fundamental problem is how to schedule the UAV's visits to the sensors according to their status update intensities. We consider a probabilistic scheduling policy by optimizing UAV's visit probability to each sensor. The objective is to minimize average Age-of-Synchronization (AoS), which is derived as a closed-form function of the sensors' update intensities and the UAV's visit probabilities. Our main analytical result is that when a sensor's update intensity is small, the UAV's visit probability to this sensor is approximately proportional to a cubic root function of the sensor's update intensity and the UAV's energy consumption. Based on this, a cubic root approximation algorithm is proposed, which can perform close to the optimal one. The algorithm is extended to the case that the UAV can visit multiple sensors in each round trip. It is found that visiting as many sensors per round trip as possible can perform the same as the optimal one. Numerical results also demonstrate the good performance of the extended cubic root approximation algorithm to multi-sensor per-visit case.