Joint deployment and trajectory optimization in UAV-assisted vehicular edge computing networks

Z Wu, Z Yang, C Yang, J Lin, Y Liu… - … of Communications and …, 2021 - ieeexplore.ieee.org
As the general mobile edge computing (MEC) scheme cannot adequately handle the
emergency communication requirements in vehicular networks, unmanned aerial vehicle …

A load-balanced and energy-efficient navigation scheme for UAV-mounted mobile edge computing

Z Wang, H Rong, H Jiang, Z Xiao… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
With the development of Unmanned Aerial Vehicles (UAVs) in recent years, UAV-mounted
Mobile Edge Computing (MEC) systems are widely used for broadband connectivity and …

UAV-assisted task offloading in vehicular edge computing networks

X Dai, Z Xiao, H Jiang, JCS Lui - IEEE Transactions on Mobile …, 2023 - ieeexplore.ieee.org
Vehicular edge computing (VEC) provides an effective task offloading paradigm by pushing
cloud resources to the vehicular network edges, eg, road side units (RSUs). However …

Energy-efficient UAV-assisted mobile edge computing: Resource allocation and trajectory optimization

M Li, N Cheng, J Gao, Y Wang, L Zhao… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
In this paper, we study unmanned aerial vehicle (UAV) assisted mobile edge computing
(MEC) with the objective to optimize computation offloading with minimum UAV energy …

UAV-assisted vehicular edge computing for the 6G internet of vehicles: Architecture, intelligence, and challenges

J Hu, C Chen, L Cai, MR Khosravi… - IEEE Communications …, 2021 - ieeexplore.ieee.org
With the growing intelligence needed on the Internet of Vehicles (IoV), seamless edge
computing services for the sixth generation (6G) vehicle-to-everything (V2X) applications …

Learning based channel allocation and task offloading in temporary UAV-assisted vehicular edge computing networks

C Yang, B Liu, H Li, B Li, K Xie… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
High-level autonomous decision making system is one of the key technologies in intelligent
transportation networks, it requires the traffic information within a certain range of vehicles in …

Bayesian optimization enhanced deep reinforcement learning for trajectory planning and network formation in multi-UAV networks

S Gong, M Wang, B Gu, W Zhang… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
In this paper, we employ multiple UAVs coordinated by a base station (BS) to help the
ground users (GUs) to offload their sensing data. Different UAVs can adapt their trajectories …

Energy-efficient UAV deployment and task scheduling in multi-UAV edge computing

Y Wang, H Wang, X Wei - 2020 International Conference on …, 2020 - ieeexplore.ieee.org
Unmanned Aerial Vehicle (UAV) Edge Computing is expected to be critical for providing
communications, computation, and storage services at areas with weak infrastructures …

Energy-efficient trajectory optimization for UAV-assisted IoT networks

L Zhang, A Celik, S Dang… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
In this paper, we propose and study an energy-efficient trajectory optimization scheme for
unmanned aerial vehicle (UAV) assisted Internet of Things (IoT) networks. In such networks …

UAV-enabled mobile-edge computing for AI applications: Joint model decision, resource allocation, and trajectory optimization

C Deng, X Fang, X Wang - IEEE Internet of Things Journal, 2022 - ieeexplore.ieee.org
Due to the flexible mobility and agility, unmanned aerial vehicles (UAVs) are expected to be
deployed as aerial base stations (BSs) in future air–ground-integrated wireless networks …