Cooperative task offloading and service caching for digital twin edge networks: A graph attention multi-agent reinforcement learning approach

Z Yao, S Xia, Y Li, G Wu - IEEE Journal on Selected Areas in …, 2023 - ieeexplore.ieee.org
Mobile edge computing (MEC) enables various services to be cached in close proximity to
the user equipments (UEs), thereby reducing the service delay of many emerging …

Digital twin-driven intelligent task offloading for collaborative mobile edge computing

Y Zhang, J Hu, G Min - IEEE Journal on Selected Areas in …, 2023 - ieeexplore.ieee.org
Collaborative mobile edge computing (MEC) is a new paradigm that allows cooperative
peer offloading among distributed MEC servers to balance their computing workloads …

Federated deep reinforcement learning for task offloading in digital twin edge networks

Y Dai, J Zhao, J Zhang, Y Zhang… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Digital twin edge networks provide a new paradigm that combines mobile edge computing
(MEC) and digital twins to improve network performance and reduce communication cost by …

Reducing offloading latency for digital twin edge networks in 6G

W Sun, H Zhang, R Wang… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
6G is envisioned to empower wireless communication and computation through the
digitalization and connectivity of everything, by establishing a digital representation of the …

Mean field game guided deep reinforcement learning for task placement in cooperative multiaccess edge computing

D Shi, H Gao, L Wang, M Pan, Z Han… - IEEE Internet of Things …, 2020 - ieeexplore.ieee.org
Cooperative multiaccess edge computing (MEC) is a promising paradigm for the next-
generation mobile networks. However, when the number of users explodes, the …

Joint server selection, cooperative offloading and handover in multi-access edge computing wireless network: A deep reinforcement learning approach

TM Ho, KK Nguyen - IEEE Transactions on Mobile Computing, 2020 - ieeexplore.ieee.org
Multi-access edge computing (MEC) is the key enabling technology that supports compute-
intensive applications in 5G networks. By deploying powerful servers at the edge of wireless …

Fast adaptive task offloading in edge computing based on meta reinforcement learning

J Wang, J Hu, G Min, AY Zomaya… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Multi-access edge computing (MEC) aims to extend cloud service to the network edge to
reduce network traffic and service latency. A fundamental problem in MEC is how to …

Cooperative task offloading for mobile edge computing based on multi-agent deep reinforcement learning

J Yang, Q Yuan, S Chen, H He… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Driven by the prevalence of the computation-intensive and delay-intensive mobile
applications, Mobile Edge Computing (MEC) is emerging as a promising solution …

Dima: Distributed cooperative microservice caching for internet of things in edge computing by deep reinforcement learning

H Tian, X Xu, T Lin, Y Cheng, C Qian, L Ren, M Bilal - World Wide Web, 2022 - Springer
Abstract The ubiquitous Internet of Things (IoTs) devices spawn growing mobile services of
applications with computationally-intensive and latency-sensitive features, which increases …

Intelligent offloading for multi-access edge computing: A new actor-critic approach

KH Liu, W Liao - ICC 2020-2020 IEEE International Conference …, 2020 - ieeexplore.ieee.org
Multi-access Edge Computing (MEC) is promising to handle computation-intensive and
latency-sensitive applications for 5G and beyond. Users can benefit from task offloading via …