Joint computing and caching in 5G-envisioned Internet of vehicles: A deep reinforcement learning-based traffic control system

Z Ning, K Zhang, X Wang, MS Obaidat… - IEEE Transactions …, 2020 - ieeexplore.ieee.org
Recent developments of edge computing and content caching in wireless networks enable
the Intelligent Transportation System (ITS) to provide high-quality services for vehicles …

Artificial intelligence empowered edge computing and caching for internet of vehicles

Y Dai, D Xu, S Maharjan, G Qiao… - IEEE Wireless …, 2019 - ieeexplore.ieee.org
Recent advances in edge computing and caching have significant impacts on the
developments of vehicular networks. Nevertheless, the heterogeneous requirements of on …

Deep reinforcement learning for social-aware edge computing and caching in urban informatics

K Zhang, J Cao, H Liu, S Maharjan… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Empowered with urban informatics, transportation industry has witnessed a paradigm shift.
These developments lead to the need of content processing and sharing between vehicles …

Integrated networking, caching, and computing for connected vehicles: A deep reinforcement learning approach

Y He, N Zhao, H Yin - IEEE transactions on vehicular …, 2017 - ieeexplore.ieee.org
The developments of connected vehicles are heavily influenced by information and
communications technologies, which have fueled a plethora of innovations in various areas …

Intelligent edge computing in internet of vehicles: A joint computation offloading and caching solution

Z Ning, K Zhang, X Wang, L Guo, X Hu… - IEEE Transactions …, 2020 - ieeexplore.ieee.org
Recently, Internet of Vehicles (IoV) has become one of the most active research fields in
both academic and industry, which exploits resources of vehicles and Road Side Units …

Qoe-based task offloading with deep reinforcement learning in edge-enabled internet of vehicles

X He, H Lu, M Du, Y Mao… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
In the transportation industry, task offloading services of edge-enabled Internet of Vehicles
(IoV) are expected to provide vehicles with the better Quality of Experience (QoE). However …

Urban traffic control in software defined internet of things via a multi-agent deep reinforcement learning approach

J Yang, J Zhang, H Wang - IEEE Transactions on Intelligent …, 2020 - ieeexplore.ieee.org
As the growth of vehicles and the acceleration of urbanization, the urban traffic congestion
problem becomes a burning issue in our society. Constructing a software defined Internet of …

Swarm learning-based dynamic optimal management for traffic congestion in 6G-driven intelligent transportation system

Y Liu, L Huo, J Wu, AK Bashir - IEEE Transactions on Intelligent …, 2023 - ieeexplore.ieee.org
As city boundaries expand and the vehicles continues to proliferate, the transportation
system is increasingly overloaded, greatly increasing people's commuting burden and …

Toward efficient content delivery for automated driving services: An edge computing solution

Q Yuan, H Zhou, J Li, Z Liu, F Yang, XS Shen - IEEE Network, 2018 - ieeexplore.ieee.org
Automated driving is coming with enormous potential for safer, more convenient, and more
efficient transportation systems. Besides onboard sensing, autonomous vehicles can also …

Deep reinforcement learning for cooperative content caching in vehicular edge computing and networks

G Qiao, S Leng, S Maharjan, Y Zhang… - IEEE Internet of Things …, 2019 - ieeexplore.ieee.org
In this article, we propose a cooperative edge caching scheme, a new paradigm to jointly
optimize the content placement and content delivery in the vehicular edge computing and …