Machine and deep learning for resource allocation in multi-access edge computing: A survey

H Djigal, J Xu, L Liu, Y Zhang - IEEE Communications Surveys …, 2022 - ieeexplore.ieee.org
With the rapid development of Internet-of-Things (IoT) devices and mobile communication
technologies, Multi-access Edge Computing (MEC) has emerged as a promising paradigm …

A survey on mobile edge computing for video streaming: Opportunities and challenges

MA Khan, E Baccour, Z Chkirbene, A Erbad… - IEEE …, 2022 - ieeexplore.ieee.org
5G communication brings substantial improvements in the quality of service provided to
various applications by achieving higher throughput and lower latency. However, interactive …

Deep learning at the mobile edge: Opportunities for 5G networks

M McClellan, C Cervelló-Pastor, S Sallent - Applied Sciences, 2020 - mdpi.com
Mobile edge computing (MEC) within 5G networks brings the power of cloud computing,
storage, and analysis closer to the end user. The increased speeds and reduced delay …

[HTML][HTML] Edge computational task offloading scheme using reinforcement learning for IIoT scenario

MS Hossain, CI Nwakanma, JM Lee, DS Kim - ICT Express, 2020 - Elsevier
In this paper, end devices are considered here as agent, which makes its decisions on
whether the network will offload the computation tasks to the edge devices or not. To tackle …

When 5G meets deep learning: a systematic review

GL Santos, PT Endo, D Sadok, J Kelner - Algorithms, 2020 - mdpi.com
This last decade, the amount of data exchanged on the Internet increased by over a
staggering factor of 100, and is expected to exceed well over the 500 exabytes by 2020. This …

AI and 6G into the metaverse: Fundamentals, challenges and future research trends

M Zawish, FA Dharejo, SA Khowaja… - IEEE Open Journal …, 2024 - ieeexplore.ieee.org
Since Facebook was renamed Meta, a lot of attention, debate, and exploration have
intensified about what the Metaverse is, how it works, and the possible ways to exploit it. It is …

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: A multi-agent deep learning based approach

Y Zhang, B Feng, W Quan, A Tian, K Sood, Y Lin… - IEEE …, 2020 - ieeexplore.ieee.org
Ubiquitous Internet of Things (IoT) devices have fueled plenty of innovations in the emerging
network paradigms. Among them, IoT edge caching has emerged as a promising technique …

Dynamic placement of multiple controllers based on SDN and allocation of computational resources based on heuristic ant colony algorithm

C Li, K Jiang, Y Luo - Knowledge-Based Systems, 2022 - Elsevier
With the rapid development of the Internet and the explosive growth of network applications,
traditional computer networks have ushered in unprecedented challenges and …

The applicability of reinforcement learning methods in the development of industry 4.0 applications

T Kegyes, Z Süle, J Abonyi - Complexity, 2021 - Wiley Online Library
Reinforcement learning (RL) methods can successfully solve complex optimization
problems. Our article gives a systematic overview of major types of RL methods, their …