An Online Auction Approach to UAV Scheduling and Trajectory Planning

In times when ground infrastructure can be disrupted by conflicts or natural events, the use of Unmanned Aerial Vehicle (UAV) trajectories for network services has become a crucial backup plan. Yet, many current methods don't fully optimize how UAVs are scheduled or allocate resources, resulting in less effective service. Our research aims to enhance social welfare by optimizing UAV scheduling and trajectory planning. To tackle this challenging problem, we first set up a non-convex linear programming issue and then restructure it into both its exponential and dual forms. We introduce a two-part solution. The A_OST algorithm manages task bids and UAV resource allocation, considering factors like bid values, resources, and task needs. It ranks tasks based on the value they bring. Next, the A_dual algorithm refines decisions on tasks and UAV planning by weighing task costs against benefits. Our analysis shows our method reaches a balance that boosts social welfare, ensuring the best task and resource decisions. Tests back up these claims, showing improvement in network service, and proving our method's practical value in maximizing social welfare during disruptions. © 2024 IEEE.