Deep reinforcement learning-based joint optimization model for vehicular task offloading and resource allocation

ZY Li, ZX Zhang - Peer-to-Peer Networking and Applications, 2024 - Springer
With the rapid advancement of Internet of vehicles and autonomous driving technology,
there is a growing need for increased computing power in vehicle operations. However, the …

Advanced deep learning-based computational offloading for multilevel vehicular edge-cloud computing networks

M Khayyat, IA Elgendy, A Muthanna… - IEEE …, 2020 - ieeexplore.ieee.org
The promise of low latency connectivity and efficient bandwidth utilization has driven the
recent shift from vehicular cloud computing (VCC) towards vehicular edge computing (VEC) …

Deep Reinforcement Learning Based Computation Offloading in UAV-Assisted Vehicular Edge Computing Networks

J Yan, X Zhao, Z Li - IEEE Internet of Things Journal, 2024 - ieeexplore.ieee.org
Vehicular edge computing (VEC) is considered to be a key technology to improve the
processing efficiency of computing tasks for the Internet of Vehicles (IoV). Using roadside …

VEC Collaborative Task Offloading and Resource Allocation Based on Deep Reinforcement Learning Under Parking Assistance

J Xue, F Shao, T Zhang, G Tian, H Jiang - Wireless Personal …, 2024 - Springer
With the emergence of autonomous vehicles, meeting the vehicle's computing needs for
computationally intensive and latency-sensitive tasks has become a challenge. Cellular …

Chimera: An Energy-Efficient and Deadline-Aware Hybrid Edge Computing Framework for Vehicular Crowdsensing Applications

L Pu, X Chen, G Mao, Q Xie, J Xu - IEEE Internet of Things …, 2018 - ieeexplore.ieee.org
In this paper, we propose Chimera, a novel hybrid edge computing framework, integrated
with the emerging edge cloud radio access network, to augment network-wide vehicle …

Trusted Task Offloading in Vehicular Edge Computing Networks: A Reinforcement Learning Based Solution

L Zhang, H Guo, X Zhou, J Liu - GLOBECOM 2023-2023 IEEE …, 2023 - ieeexplore.ieee.org
Mobile edge computing (MEC) has emerged as a promising approach to address the time-
sensitive requirements of mobile Internet of Vehicles (IoVs) systems. Unfortunately, the …

Deep reinforcement learning-based adaptive computation offloading for MEC in heterogeneous vehicular networks

H Ke, J Wang, L Deng, Y Ge… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
The vehicular network needs efficient and reliable data communication technology to
maintain low latency. It is very challenging to minimize the energy consumption and data …

Parking edge computing: Parked-vehicle-assisted task offloading for urban VANETs

C Ma, J Zhu, M Liu, H Zhao, N Liu… - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
Vehicular edge computing has been a promising paradigm to offer low-latency and high
reliability vehicular services for users. Nevertheless, for compute-intensive vehicle …

System-Wide Energy Efficient Computation Offloading in Vehicular Edge Computing With Speed Adjustment

H Li, X Li, M Zhang, B Ulziinyam - IEEE Transactions on Green …, 2024 - ieeexplore.ieee.org
Vehicle-to-everything (V2X) communications in future 6G intelligent transportation systems
are expected to enable various convenience applications which consume amount of …

[HTML][HTML] Joint offloading decision and resource allocation in vehicular edge computing networks

S Wang, X Song, H Xu, T Song, G Zhang… - Digital Communications …, 2023 - Elsevier
With the rapid development of Intelligent Transportation Systems (ITS), many new
applications for Intelligent Connected Vehicles (ICVs) have sprung up. In order to tackle the …