Mobility-aware edge caching and computing in vehicle networks: A deep reinforcement learning

RQ Hu - IEEE Transactions on Vehicular Technology, 2018 - ieeexplore.ieee.org
This paper studies the joint communication, caching and computing design problem for
achieving the operational excellence and the cost efficiency of the vehicular networks …

Twin-timescale artificial intelligence aided mobility-aware edge caching and computing in vehicular networks

RQ Hu, L Hanzo - IEEE Transactions on Vehicular …, 2019 - ieeexplore.ieee.org
In this paper, we propose a joint communication, caching and computing strategy for
achieving cost efficiency in vehicular networks. In particular, the resource allocation policy is …

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 …

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 …

Profit maximization for cache-enabled vehicular mobile edge computing networks

W Zhou, J Xia, F Zhou, L Fan, X Lei… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
In this paper, we investigate a multiuser cache-enabled vehicular mobile edge computing
(MEC) network, where one edge server (ES) has some caching and computing capabilities …

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 …

Toward response time minimization considering energy consumption in caching-assisted vehicular edge computing

C Tang, C Zhu, H Wu, Q Li… - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
The advent of vehicular edge computing (VEC) has generated enormous attention in recent
years. It pushes the computational resources in close proximity to the data sources and thus …

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 …

Task offloading in vehicular edge computing networks via deep reinforcement learning

E Karimi, Y Chen, B Akbari - Computer Communications, 2022 - Elsevier
Given the rapid increase of various applications in vehicular networks, it is crucial to
consider a flexible architecture to improve the Quality of Service (QoS). Utilizing Multi-access …

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 …