Applications of multi-agent reinforcement learning in future internet: A comprehensive survey

T Li, K Zhu, NC Luong, D Niyato, Q Wu… - … Surveys & Tutorials, 2022 - ieeexplore.ieee.org
Future Internet involves several emerging technologies such as 5G and beyond 5G
networks, vehicular networks, unmanned aerial vehicle (UAV) networks, and Internet of …

AI-enhanced cloud-edge-terminal collaborative network: Survey, applications, and future directions

H Gu, L Zhao, Z Han, G Zheng… - … Surveys & Tutorials, 2023 - ieeexplore.ieee.org
The cloud-edge-terminal collaborative network (CETCN) is considered as a novel paradigm
for emerging applications owing to its huge potential in providing low-latency and ultra …

Cooperative edge caching based on elastic federated and multi-agent deep reinforcement learning in next-generation networks

Q Wu, W Wang, P Fan, Q Fan, H Zhu… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Edge caching is a promising solution for next-generation networks by empowering caching
units in small-cell base stations (SBSs), which allows user equipments (UEs) to fetch users' …

A transcoding-enabled 360 VR video caching and delivery framework for edge-enhanced next-generation wireless networks

H **ao, C Xu, Z Feng, R Ding, S Yang… - IEEE Journal on …, 2022 - ieeexplore.ieee.org
Virtual reality (VR) content, including 360° panoramic video, provides users with an
immersive multimedia experience and therefore attracts increasing research and …

Federated deep reinforcement learning for recommendation-enabled edge caching in mobile edge-cloud computing networks

C Sun, X Li, J Wen, X Wang, Z Han… - IEEE Journal on …, 2023 - ieeexplore.ieee.org
To support rapidly increasing services and applications from users, multi-tier computing is
emerged as a promising system-level computing architecture by distributing …

[HTML][HTML] A survey on deploying mobile deep learning applications: A systemic and technical perspective

Y Wang, J Wang, W Zhang, Y Zhan, S Guo… - Digital Communications …, 2022 - Elsevier
With the rapid development of mobile devices and deep learning, mobile smart applications
using deep learning technology have sprung up. It satisfies multiple needs of users, network …

Tailored learning-based scheduling for kubernetes-oriented edge-cloud system

Y Han, S Shen, X Wang, S Wang… - IEEE INFOCOM 2021 …, 2021 - ieeexplore.ieee.org
Kubernetes (k8s) has the potential to merge the distributed edge and the cloud but lacks a
scheduling framework specifically for edge-cloud systems. Besides, the hierarchical …

[BOK][B] Mobile edge computing

Y Zhang - 2022 - library.oapen.org
This is an open access book. It offers comprehensive, self-contained knowledge on Mobile
Edge Computing (MEC), which is a very promising technology for achieving intelligence in …

Intelligence-empowered mobile edge computing: Framework, issues, implementation, and outlook

K Jiang, C Sun, H Zhou, X Li, M Dong… - IEEE Network, 2021 - ieeexplore.ieee.org
Recently, artificial intelligence (AI) is undergoing a sustained success renaissance as it can
substantially improve networks' cognitive performance and intelligence, thereby contributing …

Video super-resolution and caching—An edge-assisted adaptive video streaming solution

A Zhang, Q Li, Y Chen, X Ma, L Zou… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
Edge computing provides the potential to improve users' Quality of Experience (QoE) in ever-
increasing video delivery. However, existing edge-based solutions cannot fully utilize the …