PTCC: A Privacy-preserving and Trajectory Clustering-based Approach for Cooperative Caching Optimization in Vehicular Networks

T Cao, Z Zhang, X Wang, H Xiao… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
5G vehicular networks provide abundant multimedia services among mobile vehicles.
However, due to the mobility of vehicles, large-scale mobile traffic poses a challenge to the …
相关文章 所有 2 个版本

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 …
被引用次数：29 相关文章
[PDF] arxiv.org

Proactive content caching scheme in urban vehicular networks

B Feng, C Feng, D Feng, Y Wu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
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 …
被引用次数：7 相关文章 所有 3 个版本

Cooperative content caching and delivery in vehicular networks: A deep neural network approach

X Cai, J Zheng, Y Fu, Y Zhang, W Wu - China Communications, 2023 - ieeexplore.ieee.org
The growing demand for low delay vehicular content has put tremendous strain on the
backbone network. As a promising alternative, cooperative content caching among different …
被引用次数：3 相关文章
[PDF] cosafe.org.uk

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 …
被引用次数：298 相关文章 所有 5 个版本

DRL-Based Federated Learning for Efficient Vehicular Caching Management

P Singh, B Hazarika, K Singh, C Pan… - IEEE Internet of …, 2024 - ieeexplore.ieee.org
In this study, we present a hybrid deep reinforcement learning (DRL) algorithm, trained
using vehicular federated learning (VFL), specifically tailored for dynamic vehicular networks …
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Privacy-Preserving Mobility-Aware Federated Collaborative Filtering Framework for Caching Prediction in Vehicular Networks

X Ouyang, C Feng, D Feng… - 2023 20th Annual IEEE …, 2023 - ieeexplore.ieee.org
Recommendation algorithm can effectively reduce the difficulty of proactive edge caching
prediction by excavating users' preferences among the massive contents, which has drawn …
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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 …
被引用次数：3 相关文章

Deep reinforcement learning for cooperative edge caching in vehicular networks

Y Xing, Y Sun, L Qiao, Z Wang, P Si… - 2021 13th International …, 2021 - ieeexplore.ieee.org
In order to enable more and more multimedia content to be shared in the vehicular network,
edge caching is a promising approach to cache content near the vehicles to reduce the …
被引用次数：16 相关文章

Social-Aware Decentralized Cooperative Caching for Internet of Vehicles

H Wu, Y Fan, J Jin, H Ma, L Xing - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
As the industry related to intelligent vehicles becomes increasingly mature, emerging in-
vehicle applications and services are mushrooming. They have strict requirements on …
被引用次数：3 相关文章