A -Learning-Based Proactive Caching Strategy for Non-Safety Related Services in Vehicular Networks
Content caching has brought huge potential for the provisioning of non-safety related
infotainment services in future vehicular networks. Assisted by multiaccess edge computing …
infotainment services in future vehicular networks. Assisted by multiaccess edge computing …
A novel deep Q-learning-based air-assisted vehicular caching scheme for safe autonomous driving
The safety driving-related content demands of vehicle users increase rapidly, especially with
the development of autonomous driving. It is significantly necessary to obtain the safety …
the development of autonomous driving. It is significantly necessary to obtain the safety …
Deep learning based caching for self-driving cars in multi-access edge computing
Without steering wheel and driver's seat, the self-driving cars will have new interior outlook
and spaces that can be used for enhanced infotainment services. For traveling people, self …
and spaces that can be used for enhanced infotainment services. For traveling people, self …
Mobility-aware proactive edge caching for connected vehicles using federated learning
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 …
technology to satisfy the increasing demands of computation-intensive and latency-sensitive …
Mobility-aware cooperative caching in vehicular edge computing based on asynchronous federated and deep reinforcement learning
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 …
users (VUs) in the roadside units (RSUs) to support real-time vehicular applications …
Deep reinforcement learning for cooperative content caching in vehicular edge computing and networks
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 …
optimize the content placement and content delivery in the vehicular edge computing and …
Towards cooperative caching for vehicular networks with multi-level federated reinforcement learning
L Zhao, Y Ran, H Wang, J Wang… - ICC 2021-IEEE …, 2021 - ieeexplore.ieee.org
Content caching in vehicular networks is a promising technology to dramatically reduce the
request-response time and transmission delay. The existing caching policies often suffer …
request-response time and transmission delay. The existing caching policies often suffer …
Proactive content caching for internet-of-vehicles based on peer-to-peer federated learning
To cope with the increasing content requests from emerging vehicular applications, caching
contents at edge nodes is imperative to reduce service latency and network traffic on the …
contents at edge nodes is imperative to reduce service latency and network traffic on the …
Proactive content caching scheme in urban vehicular networks
Stream media content caching is a key enabling technology to promote the value chain of
future urban vehicular networks. Nevertheless, the high mobility of vehicles, intermittency of …
future urban vehicular networks. Nevertheless, the high mobility of vehicles, intermittency of …
QoE-driven edge caching in vehicle networks based on deep reinforcement learning
C Song, W Xu, T Wu, S Yu, P Zeng… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
The Internet of vehicles (IoV) is a large information interaction network that collects
information on vehicles, roads and pedestrians. One of the important uses of vehicle …
information on vehicles, roads and pedestrians. One of the important uses of vehicle …