AoI-Optimal Cellular-Connected UAV Trajectory Planning for IoT Data Collection

Abstract

Unmanned Aerial Vehicles (UAVs) can help data collection from ground sensors or Internet of Things (IoT) devices deployed even in hard to access areas and deliver them to their destinations as relays. However, the UAV trajectories should be planned carefully due to their limited battery lifetimes. Recently, Age of Information (AoI) has also been considered as a metric to quantify the freshness of the data collected during this process and the path of the UAVs are aimed to be optimized considering AoI. However, existing studies have defined the AoI of the collected data in the context of delivering the collected data to a specific destination only. Moreover, they assume the data is available at each IoT device before the UAV is dispatched. In this paper, we consider a set of base stations distributed in the area that a UAV travels through and define the AoI from the moment the data is generated till it is uploaded to any of the base stations by the cellular-connected UAV. We also consider data generation times at each IoT device requiring the UAV's arrival to an IoT device after this time. Our goal is to minimize the maximum AoI of any collected data while also minimizing the mission time and the path of the UAV for energy saving. We model and solve the problem using Integer Linear Programming (ILP) and with a heuristic based solution. The results obtained in different scenarios show that heuristic approach can provide close to optimal ILP based results while running much faster.