Zero touch management: A survey of network automation solutions for 5G and 6G networks

E Coronado, R Behravesh… - … Surveys & Tutorials, 2022 - ieeexplore.ieee.org
Mobile networks are facing an unprecedented demand for high-speed connectivity
originating from novel mobile applications and services and, in general, from the adoption …

Convergence of edge computing and deep learning: A comprehensive survey

X Wang, Y Han, VCM Leung, D Niyato… - … Surveys & Tutorials, 2020 - ieeexplore.ieee.org
Ubiquitous sensors and smart devices from factories and communities are generating
massive amounts of data, and ever-increasing computing power is driving the core of …

A survey of multi-access edge computing in 5G and beyond: Fundamentals, technology integration, and state-of-the-art

QV Pham, F Fang, VN Ha, MJ Piran, M Le, LB Le… - IEEE …, 2020 - ieeexplore.ieee.org
Driven by the emergence of new compute-intensive applications and the vision of the
Internet of Things (IoT), it is foreseen that the emerging 5G network will face an …

Machine learning for 6G wireless networks: Carrying forward enhanced bandwidth, massive access, and ultrareliable/low-latency service

J Du, C Jiang, J Wang, Y Ren… - IEEE Vehicular …, 2020 - ieeexplore.ieee.org
To satisfy the expected plethora of demanding services, the future generation of wireless
networks (6G) has been mandated as a revolutionary paradigm to carry forward the …

UAV communications for 5G and beyond: Recent advances and future trends

B Li, Z Fei, Y Zhang - IEEE Internet of Things Journal, 2018 - ieeexplore.ieee.org
Providing ubiquitous connectivity to diverse device types is the key challenge for 5G and
beyond 5G (B5G). Unmanned aerial vehicles (UAVs) are expected to be an important …

Applications of deep reinforcement learning in communications and networking: A survey

NC Luong, DT Hoang, S Gong, D Niyato… - … surveys & tutorials, 2019 - ieeexplore.ieee.org
This paper presents a comprehensive literature review on applications of deep
reinforcement learning (DRL) in communications and networking. Modern networks, eg …

Deep reinforcement learning for Internet of Things: A comprehensive survey

W Chen, X Qiu, T Cai, HN Dai… - … Surveys & Tutorials, 2021 - ieeexplore.ieee.org
The incumbent Internet of Things suffers from poor scalability and elasticity exhibiting in
communication, computing, caching and control (4Cs) problems. The recent advances in …

Deep reinforcement learning for online computation offloading in wireless powered mobile-edge computing networks

L Huang, S Bi, YJA Zhang - IEEE Transactions on Mobile …, 2019 - ieeexplore.ieee.org
Wireless powered mobile-edge computing (MEC) has recently emerged as a promising
paradigm to enhance the data processing capability of low-power networks, such as …

Deep learning in mobile and wireless networking: A survey

C Zhang, P Patras, H Haddadi - IEEE Communications surveys …, 2019 - ieeexplore.ieee.org
The rapid uptake of mobile devices and the rising popularity of mobile applications and
services pose unprecedented demands on mobile and wireless networking infrastructure …

Transformative effects of IoT, Blockchain and Artificial Intelligence on cloud computing: Evolution, vision, trends and open challenges

SS Gill, S Tuli, M Xu, I Singh, KV Singh, D Lindsay… - Internet of Things, 2019 - Elsevier
Cloud computing plays a critical role in modern society and enables a range of applications
from infrastructure to social media. Such system must cope with varying load and evolving …