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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Hlavní autoři:	Wentao Yang, Zhibin Liu
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	IEEE 2024-01-01
Edice:	IEEE Access
Témata:	Caching asynchronous federated learning vehicular edge computing deep reinforcement learning
On-line přístup:	https://ieeexplore.ieee.org/document/10403820/
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