Edge computing with artificial intelligence: A machine learning perspective

H Hua, Y Li, T Wang, N Dong, W Li, J Cao - ACM Computing Surveys, 2023 - dl.acm.org
Recent years have witnessed the widespread popularity of Internet of things (IoT). By
providing sufficient data for model training and inference, IoT has promoted the development …

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 …

A survey of incentive mechanism design for federated learning

Y Zhan, J Zhang, Z Hong, L Wu, P Li… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Federated learning is promising in enabling large-scale machine learning by massive
clients without exposing their raw data. It can not only enable the clients to preserve the …

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 …

A low-latency edge computation offloading scheme for trust evaluation in finance-level artificial intelligence of things

X Zhu, F Ma, F Ding, Z Guo, J Yang… - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
The finance-level Artificial Intelligence of Things (AIoT) is going to become a novel media in
the 6G-driven digital society. Inside the financial AIoT environment, large-scale crowd credit …

Comprehensive survey on machine learning in vehicular network: Technology, applications and challenges

F Tang, B Mao, N Kato, G Gui - IEEE Communications Surveys …, 2021 - ieeexplore.ieee.org
Towards future intelligent vehicular network, the machine learning as the promising artificial
intelligence tool is widely researched to intelligentize communication and networking …

MEC-assisted immersive VR video streaming over terahertz wireless networks: A deep reinforcement learning approach

J Du, FR Yu, G Lu, J Wang, J Jiang… - IEEE Internet of Things …, 2020 - ieeexplore.ieee.org
Immersive virtual reality (VR) video is becoming increasingly popular owing to its enhanced
immersive experience. To enjoy ultrahigh resolution immersive VR video with wireless user …

Task offloading paradigm in mobile edge computing-current issues, adopted approaches, and future directions

MY Akhlaqi, ZBM Hanapi - Journal of Network and Computer Applications, 2023 - Elsevier
Many enterprise companies migrate their services and applications to the cloud to benefit
from cloud computing advantages. Meanwhile, the rapidly increasing number of connected …

A gentle introduction to reinforcement learning and its application in different fields

M Naeem, STH Rizvi, A Coronato - IEEE access, 2020 - ieeexplore.ieee.org
Due to the recent progress in Deep Neural Networks, Reinforcement Learning (RL) has
become one of the most important and useful technology. It is a learning method where a …

Deep reinforcement learning for dynamic computation offloading and resource allocation in cache-assisted mobile edge computing systems

S Nath, J Wu - Intelligent and Converged Networks, 2020 - ieeexplore.ieee.org
Mobile Edge Computing (MEC) is one of the most promising techniques for next-generation
wireless communication systems. In this paper, we study the problem of dynamic caching …