[HTML][HTML] Deep reinforcement learning for edge caching with mobility prediction in vehicular networks

Y Choi, Y Lim - Sensors, 2023 - mdpi.com
As vehicles are connected to the Internet, various services can be provided to users.
However, if the requests of vehicle users are concentrated on the remote server, the …

Edge Caching Based on Deep Reinforcement Learning in Vehicular Networks

Y Choi, Y Lim - 2022 IEEE 4th Eurasia Conference on IOT …, 2022 - ieeexplore.ieee.org
As vehicles are connected to the Internet, various services such as infotainment and
automated driving can be provided. However, these services require a large amount of data …

Mobility prediction based vehicular edge caching: a deep reinforcement learning based approach

K An, X Yan, T Liang, W Lu - 2019 IEEE 19th International …, 2019 - ieeexplore.ieee.org
Caching on edge nodes can effectively reduce the burden on the Internet of Vehicles (IoV)
networks. However, the inherent limitations of IoV networks, such as restricted storage …

Cooperative caching strategy based mobile vehicle social‐aware in internet of vehicles

C Kan, H Wu, L Xing, H Ma - Transactions on Emerging …, 2023 - Wiley Online Library
The dramatic growth of smart in‐vehicle applications in the Internet of Vehicles and the
increasing quality of experience for vehicle users have put a huge traffic load on the mobile …

Federation-based Deep Reinforcement Learning Cooperative Cache in Vehicular Edge Networks

H Wu, J Jin, H Ma, L Xing - IEEE Internet of Things Journal, 2023 - ieeexplore.ieee.org
With the emergence of a large number of computing resource-intensive applications and a
variety of content delivery services, data in Internet of Vehicles (IoV) is exploding. In order to …

Multi-Agent Federated Deep Reinforcement Learning Based Collaborative Caching Strategy for Vehicular Edge Networks

H Wu, B Wang, H Ma, X Zhang… - IEEE Internet of Things …, 2024 - ieeexplore.ieee.org
With the rapid advancement of in-vehicle communication technology, vehicular edge
caching has garnered considerable attention as a pivotal technology to improve the …

A -Learning-Based Proactive Caching Strategy for Non-Safety Related Services in Vehicular Networks

L Hou, L Lei, K Zheng, X Wang - IEEE Internet of Things …, 2018 - ieeexplore.ieee.org
Content caching has brought huge potential for the provisioning of non-safety related
infotainment services in future vehicular networks. Assisted by multiaccess edge computing …

[PDF][PDF] Deep Reinforcement Learning Empowered Edge Collaborative Caching Scheme for Internet of Vehicles.

X Liu, S Xu, C Yang, Z Wang, H Zhang… - Comput. Syst. Sci …, 2022 - cdn.techscience.cn
With the development of internet of vehicles, the traditional centralized content caching
mode transmits content through the core network, which causes a large delay and cannot …

[HTML][HTML] Meta-reinforcement learning for edge caching in vehicular networks

H Sakr, M Elsabrouty - Journal of Ambient Intelligence and Humanized …, 2023 - Springer
Content caching to local repositories closer to the user can significantly improve the
utilization of the backbone network, reduce latency, and improve reliability. Nevertheless …

Collaborative caching relay algorithm based on recursive deep reinforcement learning in mobile vehicle edge network

H Wu, B Wang, H Ma, L Xing - Ad Hoc Networks, 2024 - Elsevier
With the rapid development of Internet of vehicles (IoV) and the continuous emergence of
vehicle information applications, the demand for content in vehicle networking is growing at …