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 …

Resource scheduling in edge computing: A survey

Q Luo, S Hu, C Li, G Li, W Shi - IEEE Communications Surveys …, 2021‏ - ieeexplore.ieee.org
With the proliferation of the Internet of Things (IoT) and the wide penetration of wireless
networks, the surging demand for data communications and computing calls for the …

Towards 6G wireless communication networks: Vision, enabling technologies, and new paradigm shifts

X You, CX Wang, J Huang, X Gao, Z Zhang… - Science China …, 2021‏ - Springer
The fifth generation (5G) wireless communication networks are being deployed worldwide
from 2020 and more capabilities are in the process of being standardized, such as mass …

AI-based fog and edge computing: A systematic review, taxonomy and future directions

S Iftikhar, SS Gill, C Song, M Xu, MS Aslanpour… - Internet of Things, 2023‏ - Elsevier
Resource management in computing is a very challenging problem that involves making
sequential decisions. Resource limitations, resource heterogeneity, dynamic and diverse …

Offloading using traditional optimization and machine learning in federated cloud–edge–fog systems: A survey

B Kar, W Yahya, YD Lin, A Ali - IEEE Communications Surveys …, 2023‏ - ieeexplore.ieee.org
The huge amount of data generated by the Internet of Things (IoT) devices needs the
computational power and storage capacity provided by cloud, edge, and fog computing …

Applications of artificial intelligence and machine learning in smart cities

Z Ullah, F Al-Turjman, L Mostarda… - Computer Communications, 2020‏ - Elsevier
Smart cities are aimed to efficiently manage growing urbanization, energy consumption,
maintain a green environment, improve the economic and living standards of their citizens …

Artificial intelligence for edge service optimization in internet of vehicles: A survey

X Xu, H Li, W Xu, Z Liu, L Yao… - Tsinghua Science and …, 2021‏ - ieeexplore.ieee.org
The Internet of Vehicles (IoV) plays a crucial role in providing diversified services because of
its powerful capability of collecting real-time information. Generally, collected information is …

EEDTO: An energy-efficient dynamic task offloading algorithm for blockchain-enabled IoT-edge-cloud orchestrated computing

H Wu, K Wolter, P Jiao, Y Deng… - IEEE Internet of Things …, 2020‏ - ieeexplore.ieee.org
With the proliferation of compute-intensive and delay-sensitive mobile applications, large
amounts of computational resources with stringent latency requirements are required on …

Fast adaptive task offloading in edge computing based on meta reinforcement learning

J Wang, J Hu, G Min, AY Zomaya… - IEEE Transactions on …, 2020‏ - ieeexplore.ieee.org
Multi-access edge computing (MEC) aims to extend cloud service to the network edge to
reduce network traffic and service latency. A fundamental problem in MEC is how to …

On 5G-V2X use cases and enabling technologies: A comprehensive survey

A Alalewi, I Dayoub, S Cherkaoui - Ieee Access, 2021‏ - ieeexplore.ieee.org
5G technologies promise faster connections, lower latency, higher reliability, more capacity
and wider coverage. We are looking to rely on these technologies to achieve Vehicle-to …