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 …

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 …

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 …

A3c-based and dependency-aware computation offloading and service caching in digital twin edge networks

L Chen, Q Gu, K Jiang, L Zhao - IEEE Access, 2023 - ieeexplore.ieee.org
The combination of Mobile Edge Computing (MEC) and Digital Twin (DT) is anticipated to
enhance the quality of mobile application services in the 6G era. However, current research …

Deep reinforcement learning-based cloud-edge collaborative mobile computation offloading in industrial networks

S Chen, J Chen, Y Miao, Q Wang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
With the rapid development of mobile industrial applications and due to the limited coverage
of static edge servers, traditional edge computing technology has great limitations in …

Digital-twin-assisted task offloading based on edge collaboration in the digital twin edge network

T Liu, L Tang, W Wang, Q Chen… - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
Emerging digital twin (DT) and mobile-edge computing (MEC) are crucial for enabling the
rapid development of 6G. However, the existing works ignore the edge collaboration, which …

D2D-Assisted Multi-User Cooperative Partial Offloading in MEC Based on Deep Reinforcement Learning

X Guan, T Lv, Z Lin, P Huang, J Zeng - Sensors, 2022 - mdpi.com
Mobile edge computing (MEC) and device-to-device (D2D) communication can alleviate the
resource constraints of mobile devices and reduce communication latency. In this paper, we …

Smart collaborative optimizations strategy for mobile edge computing based on deep reinforcement learning

J Fang, M Zhang, Z Ye, J Shi, J Wei - Computers & Electrical Engineering, 2021 - Elsevier
With the arrival of the 5th generation mobile networks (5 G) era, the data needed by mobile
devices (MDs) is explosively growing. High-consumption, low-latency applications are huge …

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 …

Dynamic task offloading for digital twin-empowered mobile edge computing via deep reinforcement learning

Y Chen, W Gu, J Xu, Y Zhang, G Min - China Communications, 2023 - ieeexplore.ieee.org
Limited by battery and computing resources, the computing-intensive tasks generated by
Internet of Things (IoT) devices cannot be processed all by themselves. Mobile edge …