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 …

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 …

Future intelligent and secure vehicular network toward 6G: Machine-learning approaches

F Tang, Y Kawamoto, N Kato, J Liu - Proceedings of the IEEE, 2019 - ieeexplore.ieee.org
As a powerful tool, the vehicular network has been built to connect human communication
and transportation around the world for many years to come. However, with the rapid growth …

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 …

Artificial intelligence powered mobile networks: From cognition to decision

G Luo, Q Yuan, J Li, S Wang, F Yang - IEEE Network, 2022 - ieeexplore.ieee.org
Mobile networks (MNs) are anticipated to provide unprecedented opportunities to enable a
new world of connected experiences and radically shift the way people interact with …

A deep learning based image enhancement approach for autonomous driving at night

G Li, Y Yang, X Qu, D Cao, K Li - Knowledge-Based Systems, 2021 - Elsevier
Images of road scenes in low-light situations are lack of details which could increase crash
risk of connected autonomous vehicles (CAVs). Therefore, an effective and efficient image …

Resource scheduling in edge computing: Architecture, taxonomy, open issues and future research directions

M Raeisi-Varzaneh, O Dakkak, A Habbal… - IEEE Access, 2023 - ieeexplore.ieee.org
The implementation of the Internet of Things and 5G communications has pushed
centralized cloud computing toward edge computing resulting in a paradigm shift in …

Machine learning-based load balancing algorithms in future heterogeneous networks: A survey

E Gures, I Shayea, M Ergen, MH Azmi… - IEEE Access, 2022 - ieeexplore.ieee.org
The massive growth of mobile users and the essential need for high communication service
quality necessitate the deployment of ultra-dense heterogeneous networks (HetNets) …

ESTNet: Embedded spatial-temporal network for modeling traffic flow dynamics

G Luo, H Zhang, Q Yuan, J Li… - IEEE transactions on …, 2022 - ieeexplore.ieee.org
Accurate spatial-temporal prediction is a fundamental building block of many real-world
applications such as traffic scheduling and management, environment policy making, and …

AI empowered communication systems for intelligent transportation systems

Z Lv, R Lou, AK Singh - IEEE Transactions on Intelligent …, 2020 - ieeexplore.ieee.org
Intelligent control of traffic has significant influence on the scheduling efficiency of urban
traffic flow. Therefore, in order to improve the efficiency of vehicles at intersections, first, the …