A Task Offloading Strategy for Compute-Intensive Scenarios in UAV-Assisted IoV

With the development of the low-altitude digital economy and the further improvement of the Internet of Vehicles (IoV), the IoV assisted by Unmanned Aerial Vehicle (UAV) has been promoted in many fields. Under task-intensive scenarios, UAV-assisted Mobile Edge Computing (MEC) has been extensively studied due to its flexibility and efficiency. However, with random distribution of computing data, the deployment of UAV and offloading strategy are important issues to be solved. In this context, this paper proposes a UAV-assisted offloading strategy, considering fixed and mobile edge nodes respectively, to meet the requirements of low latency and high reliability of vehicle users. It has been experimentally verified that our system reduces the delay by 30%.