Efficient Vehicular Edge Computing: A Novel Approach With Asynchronous Federated and Deep Reinforcement Learning for Content Caching in VEC

Efficient Vehicular Edge Computing: A Novel Approach With Asynchronous Federated and Deep Reinforcement Learning for Content Caching in VEC

Vehicular Edge Computing (VEC) technology holds great promise, but also poses significant challenges to the limited computing power of in-vehicle devices and the capacity of Roadside Units (RSUs). At the same time, the highly mobile nature of vehicles and the frequent changes in the content of reque...

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Bibliographic Details
Main Authors: Wentao Yang, Zhibin Liu
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Caching
asynchronous federated learning
vehicular edge computing
deep reinforcement learning
Online Access:https://ieeexplore.ieee.org/document/10403820/

Internet

https://ieeexplore.ieee.org/document/10403820/

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