Joint Optimization of Resource Scheduling and Mobility for UAV-Assisted Vehicle Platoons

Liu, Y., Zhou, J., Tian, D., Sheng, Z., Duan, X., Qu, G. and Zhao, D. (2021) Joint Optimization of Resource Scheduling and Mobility for UAV-Assisted Vehicle Platoons. IEEE 94th Vehicular Technology Conference: VTC2021-Fall, Online only, 27-30 September 2021. ISBN 9781665413688 (doi: 10.1109/VTC2021-Fall52928.2021.9625397)

Abstract

In the era of the Internet of Everything, autonomous driving has put forward a higher ambition for data transmission capabilities. This paper studies joint scheduling of computation and communication resources in the collaborative networking of unmanned aerial vehicles (UAV s) and platooning vehicles in mobile edge computing (MEC) framework to maximize the energy efficiency. Considering the movement characteristics of vehicles, we integrate mobility, communication, computation, and energy consumption to establish a collective optimization problem. Since this multivariate coupled model is non-convex, we further propose a joint optimization method (JOM) algorithm based on the convex approximation theory, particularly quadratic programming. Experimental results verify that this algorithm converges quickly within a dozen iterations and proves to be superior to several other benchmark schemes.

• Item Type: Conference or Workshop Item
• Additional Information: This research was supported in part by the National Postdoctoral Program for Innovative Talents under Grant No. BX2021027, the China Postdoctoral Science Foundation under Grant No. 2020M680299, the “Zhuoyue” Program of Beihang University under Grant No. 262716, the National Natural Science Foundation of China under Grant No. 61822101 and U20A20155, the Beijing Municipal Natural Science Foundation under Grant No. L191001, the Newton Advanced Fellowship under Grant No. 62061130221, and the Young Elite Scientists Sponsorship Program by Hunan Provincial Department of Education under Grant No. 18B142.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Zhao, Dr Dezong
• Authors: Liu, Y., Zhou, J., Tian, D., Sheng, Z., Duan, X., Qu, G., and Zhao, D.
• College/School: College of Science and Engineering > School of Engineering > Autonomous Systems and Connectivity
• ISSN: 2577-2465
• ISBN: 9781665413688
• Copyright Holders: Copyright © 2021 IEEE
• First Published: First published in Y. Liu et al., "Joint Optimization of Resource Scheduling and Mobility for UAV-Assisted Vehicle Platoons," 2021 IEEE 94th Vehicular Technology Conference (VTC2021-Fall), Norman, OK, USA, 2021, pp. 1-5
• Publisher Policy: Reproduced in accordance with publisher policy

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