Short Bio:

Lei Zhang received the B.S. degree in communication engineering from Anhui University, Hefei, China, in 2009, and the M.S. and Ph.D. (Premio Extraordinario de Doctorado) degrees in telecommunications from the Universidad Politécnica de Madrid (UPM), Madrid, Spain, in 2013 and 2016, respectively. In 2016, he was a Visiting Scholar with the University of South Carolina, Columbia, SC, USA. From 2016 to 2017, he was a Research Assistant Professor with the Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Science, Shanghai, China. Since 2019, he has been an Associate Professor with the College of Information Science and Technology, Donghua University, Shanghai. His research interests include wireless channel modeling and wearable computing.

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

Abstract:
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%.