A survey of collaborative machine learning using 5G vehicular communications

SV Balkus, H Wang, BD Cornet… - … Surveys & Tutorials, 2022 - ieeexplore.ieee.org
By enabling autonomous vehicles (AVs) to share data while driving, 5G vehicular
communications allow AVs to collaborate on solving common autonomous driving tasks …

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 …

Mobility-aware cooperative caching in vehicular edge computing based on asynchronous federated and deep reinforcement learning

Q Wu, Y Zhao, Q Fan, P Fan, J Wang… - IEEE Journal of …, 2022 - ieeexplore.ieee.org
Vehicular edge computing (VEC) can learn and cache most popular contents for vehicular
users (VUs) in the roadside units (RSUs) to support real-time vehicular applications …

Distributed deep multi-agent reinforcement learning for cooperative edge caching in internet-of-vehicles

H Zhou, K Jiang, S He, G Min… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Edge caching is a promising approach to reduce duplicate content transmission in Internet-
of-Vehicles (IoVs). Several Reinforcement Learning (RL) based edge caching methods have …

A hierarchical blockchain-enabled federated learning algorithm for knowledge sharing in internet of vehicles

H Chai, S Leng, Y Chen, K Zhang - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Internet of Vehicles (IoVs) is highly characterized by collaborative environment data sensing,
computing and processing. Emerging big data and Artificial Intelligence (AI) technologies …

Mobility-aware proactive edge caching for connected vehicles using federated learning

Z Yu, J Hu, G Min, Z Zhao, W Miao… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Content Caching at the edge of vehicular networks has been considered as a promising
technology to satisfy the increasing demands of computation-intensive and latency-sensitive …

AoI-energy-aware UAV-assisted data collection for IoT networks: A deep reinforcement learning method

M Sun, X Xu, X Qin, P Zhang - IEEE Internet of Things Journal, 2021 - ieeexplore.ieee.org
Thanks to the inherent characteristics of flexible mobility and autonomous operation,
unmanned aerial vehicles (UAVs) will inevitably be integrated into 5G/B5G cellular networks …

Green Internet of Vehicles (IoV) in the 6G era: Toward sustainable vehicular communications and networking

J Wang, K Zhu, E Hossain - IEEE Transactions on Green …, 2021 - ieeexplore.ieee.org
As one of the most promising applications in future Internet of Things, Internet of Vehicles
(IoV) has been acknowledged as a fundamental technology for develo** the Intelligent …

Joint service caching and computation offloading scheme based on deep reinforcement learning in vehicular edge computing systems

Z Xue, C Liu, C Liao, G Han… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Vehicular edge computing (VEC) is a new computing paradigm that enhances vehicular
performance by introducing both computation offloading and service caching, to resource …

Novel edge caching approach based on multi-agent deep reinforcement learning for internet of vehicles

D Zhang, W Wang, J Zhang, T Zhang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Along with the development of Internet of Vehicles (IoV) and wireless technology, the usage
of applications that require low latency, such as autonomous driving and intelligent …