Age-optimal Trajectory Planning for Multiple-UAVAssisted Data Collectio

Abstract: Unmanned Aerial Vehicles (UAVs), or drones, have become a primary tool for data collection due to their rapid and easy mobility, particularly in the current era with a high demand for real-time information updates. To serve this need, optimizing data freshness during information collection is necessary. The Age of Information (AoI) is a novel metric that considers the elapsed time from data sensing at a node to its delivery to the data center as a measure of data freshness. It is clear that the UAV's trajectory significantly affects this freshness metric. Prior research conducted by students at Ningbo University focused on ground-to-UAV wireless communication and the age-optimal trajectory planning for a single UAV in data collection, emphasizing minimizing the maximum Age of Information (Max-AoI) and the average Age of Information (Ave-AoI) across all sensor nodes. Building on this, our research broadens the scope to include multiple UAVs in the network. The objective is to design optimal trajectories for these UAVs using various optimization methods to achieve age-optimal trajectories. A subsequent comparative analysis will be carried out to identify the most effective approach