Research on cloud-edge-end collaborative computing offloading strategy in the internet of vehicles based on the M-TSA algorithm

Q Xu, G Zhang, J Wang - Sensors, 2023 - mdpi.com
In the Internet of Vehicles scenario, the in-vehicle terminal cannot meet the requirements of
computing tasks in terms of delay and energy consumption; the introduction of cloud …

URLLC resource slicing and scheduling in 5G vehicular edge computing

M Hao, D Ye, S Wang, B Tan… - 2021 IEEE 93rd Vehicular …, 2021 - ieeexplore.ieee.org
The 5th generation (5G) mobile network technology is accelerating the development of
autonomous vehicles by significantly shortening the communication latency and improving …

Deep reinforcement learning-based computation offloading for 5G vehicle-aware multi-access edge computing network

Z Wu, D Yan - China Communications, 2021 - ieeexplore.ieee.org
Multi-access Edge Computing (MEC) is one of the key technologies of the future 5G network.
By deploying edge computing centers at the edge of wireless access network, the …

Optimal task offloading and resource allocation in software-defined vehicular edge computing

S Choo, J Kim, S Pack - 2018 International conference on …, 2018 - ieeexplore.ieee.org
In vehicular edge computing (VEC), resource-intensive tasks are offloaded to computing
nodes at the network edge. Owing to high mobility and distributed nature, optimal task …

Collaborative computing in vehicular networks: A deep reinforcement learning approach

M Li, J Gao, N Zhang, L Zhao… - ICC 2020-2020 IEEE …, 2020 - ieeexplore.ieee.org
Mobile edge computing (MEC) has been recognized as a promising technology to support
various emerging services in vehicular networks. With MEC, vehicle users can offload their …

RMDDQN-Learning: Computation Offloading Algorithm Based on Dynamic Adaptive Multi-Objective Reinforcement Learning in Internet of Vehicles

X Zhang, W Wu, Z Zhao, J Wang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
As a promising computing paradigm driven by 5G, mobile edge computing (MEC) empowers
smart vehicles to offload computation-intensive tasks to edge devices in the Internet of …

RtDS: real-time distributed strategy for multi-period task offloading in vehicular edge computing environment

C Liu, K Liu, H Ren, X Xu, R Xie, J Cao - Neural Computing and …, 2023 - Springer
With recent advances in sensing technologies and the emerging intelligent transportation
system applications, smart vehicles impose huge requirements on processing computation …

An efficient computation offloading strategy based on cloud-edge collaboration in vehicular edge computing

S Wang, N Xin, Z Luo, T Lin - 2022 International Conference on …, 2022 - ieeexplore.ieee.org
Computation-intensive and latency-sensitive vehi-cle tasks continue to emerge with the
repaid development of the Internet of Vehicles (IoV). Traditional cloud servers and single …

Delay-optimized V2V-based computation offloading in urban vehicular edge computing and networks

C Chen, L Chen, L Liu, S He, X Yuan, D Lan… - IEEE …, 2020 - ieeexplore.ieee.org
The Internet of Vehicles (IoV) is an emerging paradigm, driven by recent advancements in
vehicular communications and networking. Meanwhile, the capability and intelligence of …

Learning based task offloading in digital twin empowered internet of vehicles

J Zheng, TH Luan, L Gao, Y Zhang, Y Wu - arXiv preprint arXiv …, 2021 - arxiv.org
Mobile edge computing has become an effective and fundamental paradigm for futuristic
autonomous vehicles to offload computing tasks. However, due to the high mobility of …