Mobility-aware multiobjective task offloading for vehicular edge computing in digital twin environment

B Cao, Z Li, X Liu, Z Lv, H He - IEEE Journal on Selected Areas …, 2023 - ieeexplore.ieee.org
In vehicular edge computing (VEC), vehicle users (VUs) can offload their computation-
intensive tasks to edge server (ES) that provides additional computation resources. Due to …

Mobility-aware cooperative caching in vehicular edge computing based on asynchronous federated and deep reinforcement learning

Q Wu, Y Zhao, Q Fan, P Fan, J Wang… - IEEE Journal of …, 2022 - ieeexplore.ieee.org
Vehicular edge computing (VEC) can learn and cache most popular contents for vehicular
users (VUs) in the roadside units (RSUs) to support real-time vehicular applications …

Coherent taxonomy of vehicular ad hoc networks (vanets)-enabled by fog computing: a review

ZG Al-Mekhlafi, SA Lashari… - IEEE Sensors …, 2024 - ieeexplore.ieee.org
Vehicular ad hoc networks (VANETs) are evolving rapidly with the advent of fog computing
(FC), which enhances their capabilities by bringing computational resources closer to the …

A comprehensive survey on using fog computing in vehicular networks

K Behravan, N Farzaneh, M Jahanshahi… - Vehicular …, 2023 - Elsevier
With the advent of fog computing, its use to provide real-time services at the network's edge
has increased. However, running computationally-demanding applications in smart vehicles …

Joint service caching and computation offloading scheme based on deep reinforcement learning in vehicular edge computing systems

Z Xue, C Liu, C Liao, G Han… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Vehicular edge computing (VEC) is a new computing paradigm that enhances vehicular
performance by introducing both computation offloading and service caching, to resource …

Energy-aware coded caching strategy design with resource optimization for satellite-UAV-vehicle-integrated networks

S Gu, X Sun, Z Yang, T Huang… - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
The Internet of Vehicles (IoV) can offer safe and comfortable driving experience, by the
enhanced advantages of space–air–ground-integrated networks (SAGINs), ie, global …

Efficient caching in vehicular edge computing based on edge-cloud collaboration

F Zeng, K Zhang, L Wu, J Wu - IEEE Transactions on Vehicular …, 2022 - ieeexplore.ieee.org
In vehicular edge computing (VEC), the execution of offloading task needs not only the task
data uploaded by the requesting vehicle, but also the additional data to support the task to …

Joint optimization of caching placement and power allocation in virtualized satellite-terrestrial network

H Zhang, J Xu, X Liu, K Long… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
With the rapid development of mobile services and applications, the transmitting of massive
data makes low-cost communication a challenge. Edge-based wireless communication …

Proactive content caching for internet-of-vehicles based on peer-to-peer federated learning

Z Yu, J Hu, G Min, H Xu, J Mills - 2020 IEEE 26th International …, 2020 - ieeexplore.ieee.org
To cope with the increasing content requests from emerging vehicular applications, caching
contents at edge nodes is imperative to reduce service latency and network traffic on the …

DRL-based federated learning for efficient vehicular caching management

P Singh, B Hazarika, K Singh, C Pan… - IEEE Internet of …, 2024 - ieeexplore.ieee.org
In this study, we present a hybrid deep reinforcement learning (DRL) algorithm, trained
using vehicular federated learning (VFL), specifically tailored for dynamic vehicular networks …