Federated-learning-based energy-efficient load balancing for UAV-enabled MEC system in vehicular networks

A Shin, Y Lim - Energies, 2023 - mdpi.com
At present, with the intelligence that has been achieved in computer and communication
technologies, vehicles can provide many convenient functions to users. However, it is …

An efficient scheduling scheme for intelligent driving tasks in a novel vehicle-edge architecture considering mobility and load balancing

N Wang, S Pang, X Ji, H Gui, X He - Future Generation Computer Systems, 2024 - Elsevier
With the continuous popularization and evolution of 5G and 6G, mobile edge computing has
achieved rapid development. This study explores the New Generation Mobile Edge …

Computational resources allocation and vehicular application offloading in VEC networks

F Gu, X Yang, X Li, H Deng - Electronics, 2022 - mdpi.com
With the advances in wireless communications and the Internet of Things (IoT), various
vehicular applications such as image-aided navigation and autonomous driving are …

Resource management for intelligent vehicular edge computing networks

W Duan, X Gu, M Wen, Y Ji, J Ge… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
To overcome the inherent defect of centralized data processing in cloud computing, the
mobile edge computing (MEC) brings data storage and computing capacities, to the edge …

A dependency-aware offloading algorithm based on deep reinforcement learning for vehicular networks

Y Wang, H Zhao, H Liu, L Geng - … International Conference on …, 2021 - ieeexplore.ieee.org
Recent years have witnessed the explosive growth of ubiquitous vehicles with extremely
intelligent systems, which results in large amounts of data generated. Most of these vehicle …

Asynchronous deep reinforcement learning for collaborative task computing and on-demand resource allocation in vehicular edge computing

L Liu, J Feng, X Mu, Q Pei, D Lan… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Vehicular Edge Computing (VEC) is enjoying a surge in research interest due to the
remarkable potential to reduce response delay and alleviate bandwidth pressure. Facing the …

DRL-Based Hybrid Task Offloading and Resource Allocation in Vehicular Networks

Z Liu, Z Jia, X Pang - Electronics, 2023 - mdpi.com
With the explosion of delay-sensitive and computation-intensive vehicular applications,
traditional cloud computing has encountered enormous challenges. Vehicular edge …

Com-DDPG: Task offloading based on multiagent reinforcement learning for information-communication-enhanced mobile edge computing in the internet of vehicles

H Gao, X Wang, W Wei, A Al-Dulaimi… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
The emergence of the Internet of Vehicles (IoV) introduces challenges regarding
computation-intensive and time-sensitive related services for data processing and …

Computing offloading in vehicular edge computing networks: Full or partial offloading?

C Ren, G Zhang, X Gu, Y Li - 2022 IEEE 6th Information …, 2022 - ieeexplore.ieee.org
With the surge of vehicular users and the development of mobile applications, the
management of big data has become a challenge for the Internet of Vehicle (IoV) …

Federated Double Deep Q-learning Based Computation Offloading in Mobility-Aware Vehicle Clusters

W Ye, K Zheng, Y Wang, Y Tang - IEEE Access, 2023 - ieeexplore.ieee.org
On the edge side of internet of vehicles (IoV), mobile edge computing (MEC) servers with
certain computational resources are deployed to provide computational service for vehicles …