Adaptive digital twin and multiagent deep reinforcement learning for vehicular edge computing and networks

K Zhang, J Cao, Y Zhang - IEEE Transactions on Industrial …, 2021 - ieeexplore.ieee.org
Technological advancements of urban informatics and vehicular intelligence have enabled
connected smart vehicles as pervasive edge computing platforms for a plethora of powerful …

A digital twin-assisted intelligent partial offloading approach for vehicular edge computing

L Zhao, Z Zhao, E Zhang, A Hawbani… - IEEE Journal on …, 2023 - ieeexplore.ieee.org
Vehicle Edge Computing (VEC) is a promising paradigm that exposes Mobile Edge
Computing (MEC) to road scenarios. In VEC, task offloading can enable vehicles to offload …

Optimized computation offloading performance in virtual edge computing systems via deep reinforcement learning

X Chen, H Zhang, C Wu, S Mao, Y Ji… - IEEE Internet of Things …, 2018 - ieeexplore.ieee.org
To improve the quality of computation experience for mobile devices, mobile-edge
computing (MEC) is a promising paradigm by providing computing capabilities in close …

HetMEC: Heterogeneous multi-layer mobile edge computing in the 6 G era

Y Zhang, B Di, P Wang, J Lin… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Driven by an increasing number of mobile applications, mobile edge computing (MEC) has
been considered as a promising candidate to support the huge amount of data processing …

Edge intelligence for energy-efficient computation offloading and resource allocation in 5G beyond

Y Dai, K Zhang, S Maharjan… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
5G beyond is an end-edge-cloud orchestrated network that can exploit heterogeneous
capabilities of the end devices, edge servers, and the cloud and thus has the potential to …

Computation offloading for distributed mobile edge computing network: A multiobjective approach

F Sufyan, A Banerjee - IEEE Access, 2020 - ieeexplore.ieee.org
Mobile edge computing (MEC) is emerging as a cornerstone technology to address the
conflict between resource-constrained smart devices (SDs) and the ever-increasing …

Efficient multi-vehicle task offloading for mobile edge computing in 6g networks

Y Chen, F Zhao, X Chen, Y Wu - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
With the development of 6G wireless communication technologies, various resource-
intensive and delay-sensitive vehicle application tasks are generated. These application …

Dynamic task offloading for internet of things in mobile edge computing via deep reinforcement learning

Y Chen, W Gu, K Li - International Journal of Communication …, 2022 - Wiley Online Library
With the development of Internet of Things (IoT), more and more computation‐intensive
tasks are generated by IoT devices. Due to the limitation of battery and computing capacity …

NOMA-based multi-user mobile edge computation offloading via cooperative multi-agent deep reinforcement learning

Z Chen, L Zhang, Y Pei, C Jiang… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Mobile edge computing (MEC) is a promising solution to enable resource-limited mobile
devices to offload computation-intensive tasks to nearby edge servers. In this paper …

Joint resource allocation and multi-part collaborative task offloading in MEC systems

H Zhang, Y Yang, B Shang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
This paper investigates the multi-part collaborative task offloading with multiple servers in
mobile edge computing (MEC) systems by considering server overload and long-term …