Multi-agent driven resource allocation and interference management for deep edge networks

Y Gong, H Yao, J Wang, L Jiang… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Sixth generation mobile networks (6G) may experience a huge evolution on vertical industry
scenarios, where deep edge networks () become an important network structure for the …

Distributed multi-agent empowered resource allocation in deep edge networks

Y Gong, J Wang, H Yao - 2021 International Wireless …, 2021 - ieeexplore.ieee.org
The sixth generation wireless communication networks (6G) are anticipated to bring a
disruptive innovation on multiple scenarios, where deep edge networks (DENs) turn into a …

Collaborative machine learning for energy-efficient edge networks in 6G

X Huang, K Zhang, F Wu, S Leng - IEEE Network, 2021 - ieeexplore.ieee.org
To fulfill the diversified requirements of the emerging Internet of Everything (IoE)
applications, the future sixth generation (6G) mobile network is envisioned as a …

Joint optimization of task offloading and resource allocation via deep reinforcement learning for augmented reality in mobile edge network

X Chen, G Liu - 2020 IEEE International Conference on Edge …, 2020 - ieeexplore.ieee.org
Mobile edge computing (MEC) has been recognized as emerging techniques in 5G to
provide powerful computing capabilities for the Ultra Reliable Low Latency Communication …

Multi-agent deep reinforcement learning for end—edge orchestrated resource allocation in industrial wireless networks

X Liu, C Xu, H Yu, P Zeng - Frontiers of Information Technology & …, 2022 - Springer
Edge artificial intelligence will empower the ever simple industrial wireless networks (IWNs)
supporting complex and dynamic tasks by collaboratively exploiting the computation and …

Joint task offloading and resource allocation for mobile edge computing in ultra-dense network

Z Cheng, M Min, Z Gao, L Huang - GLOBECOM 2020-2020 …, 2020 - ieeexplore.ieee.org
Mobile edge computing (MEC) enabled user-centric ultra-dense network (UDN) is a
promising solution to the energy constrained mobile users with delay-sensitive and …

Deep-deterministic policy gradient based multi-resource allocation in edge-cloud system: a distributed approach

A Qadeer, MJ Lee - IEEE Access, 2023 - ieeexplore.ieee.org
Edge Cloud (EC) empowers the beyond 5G (B5G) wireless networks to cope with large-
scale and real-time traffics of Internet-of-Things (IoT) by minimizing the latency and providing …

Improved DDPG Based Two-Timescale Multi-Dimensional Resource Allocation for Multi-Access Edge Computing Networks

Q Liu, H Zhang, X Zhang, D Yuan - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Due to the dependence of task processing on the task-related models and databases, edge
service caching and multi-access edge computing (MEC) are tightly coupled. The service …

[HTML][HTML] Multi-agent deep reinforcement learning-based partial task offloading and resource allocation in edge computing environment

H Ke, H Wang, H Sun - Electronics, 2022 - mdpi.com
In the dense data communication environment of 5G wireless networks, with the dramatic
increase in the amount of request computation tasks generated by intelligent wireless …

Deep reinforcement learning for edge computing and resource allocation in 5G beyond

Y Dai, D Xu, K Zhang, Y Lu… - 2019 IEEE 19th …, 2019 - ieeexplore.ieee.org
By extending computation capacity to the edge of wireless networks, edge computing has
the potential to enable computation-intensive and delay-sensitive applications in 5G and …