Intelligent edge computing in internet of vehicles: A joint computation offloading and caching solution

Z Ning, K Zhang, X Wang, L Guo, X Hu… - IEEE Transactions …, 2020 - ieeexplore.ieee.org
Recently, Internet of Vehicles (IoV) has become one of the most active research fields in
both academic and industry, which exploits resources of vehicles and Road Side Units …

Artificial intelligence empowered edge computing and caching for internet of vehicles

Y Dai, D Xu, S Maharjan, G Qiao… - IEEE Wireless …, 2019 - ieeexplore.ieee.org
Recent advances in edge computing and caching have significant impacts on the
developments of vehicular networks. Nevertheless, the heterogeneous requirements of on …

Knowledge-driven service offloading decision for vehicular edge computing: A deep reinforcement learning approach

Q Qi, J Wang, Z Ma, H Sun, Y Cao… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
The smart vehicles construct Internet of Vehicle (IoV), which can execute various intelligent
services. Although the computation capability of a vehicle is limited, multi-type of edge …

Qoe-based task offloading with deep reinforcement learning in edge-enabled internet of vehicles

X He, H Lu, M Du, Y Mao… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
In the transportation industry, task offloading services of edge-enabled Internet of Vehicles
(IoV) are expected to provide vehicles with the better Quality of Experience (QoE). However …

A computation offloading method for edge computing with vehicle-to-everything

X Xu, Y Xue, X Li, L Qi, S Wan - IEEE access, 2019 - ieeexplore.ieee.org
Nowadays, for improving the increasingly crowded traffic conditions, internet of vehicles
(IoV) emerges. In IoV, the increase of smart vehicle applications produces computation …

Dynamic edge computation offloading for internet of vehicles with deep reinforcement learning

L Yao, X Xu, M Bilal, H Wang - IEEE Transactions on Intelligent …, 2022 - ieeexplore.ieee.org
Recent developments in the Internet of Vehicles (IoV) enabled the myriad emergence of a
plethora of data-intensive and latency-sensitive vehicular applications, posing significant …

Double deep Q-network based dynamic framing offloading in vehicular edge computing

H Tang, H Wu, G Qu, R Li - IEEE Transactions on Network …, 2022 - ieeexplore.ieee.org
With the rapid development of Artificial Intelligence (AI) and the Internet of Vehicles (IoV),
there is an increasing demand for deploying various intelligent applications on vehicles …

Deep reinforcement learning for offloading and resource allocation in vehicle edge computing and networks

Y Liu, H Yu, S Xie, Y Zhang - IEEE Transactions on Vehicular …, 2019 - ieeexplore.ieee.org
Mobile Edge Computing (MEC) is a promising technology to extend the diverse services to
the edge of Internet of Things (IoT) system. However, the static edge server deployment may …

Service offloading with deep Q-network for digital twinning-empowered internet of vehicles in edge computing

X Xu, B Shen, S Ding, G Srivastava… - IEEE Transactions …, 2020 - ieeexplore.ieee.org
With the potential of implementing computing-intensive applications, edge computing is
combined with digital twinning (DT)-empowered Internet of vehicles (IoV) to enhance …

Efficient computation offloading for Internet of Vehicles in edge computing-assisted 5G networks

S Wan, X Li, Y Xue, W Lin, X Xu - The Journal of Supercomputing, 2020 - Springer
Abstract The Internet of Vehicles (IoV) is employed to gather real-time traffic information for
drivers, and base stations in 5G systems are used to assist in traffic data transmission. For …