Joint Optimization for Volatile Federated Learning in Vehicular Edge Computing: A Deep Reinforcement Learning Approach

Yawei Li; Li Feng; Muyu Mei; Amjad Ali; Zubair Shah

doi:10.1109/tvt.2025.3564013

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JOURNAL ARTICLE

Joint Optimization for Volatile Federated Learning in Vehicular Edge Computing: A Deep Reinforcement Learning Approach

Yawei Li Li Feng Muyu Mei Amjad Ali Zubair Shah

Year: 2025 Journal: IEEE Transactions on Vehicular Technology Vol: 74 (9)Pages: 14632-14644 Publisher: Institute of Electrical and Electronics Engineers

DOI: 10.1109/tvt.2025.3564013

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Keywords:

Reinforcement learning Joint (building) Computer science Edge computing Enhanced Data Rates for GSM Evolution Artificial intelligence Deep learning Edge device Distributed computing Engineering Cloud computing Operating system Structural engineering

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Privacy-Preserving Technologies in Data

Physical Sciences → Computer Science → Artificial Intelligence

Vehicular Ad Hoc Networks (VANETs)

Physical Sciences → Engineering → Electrical and Electronic Engineering

Blockchain Technology Applications and Security

Physical Sciences → Computer Science → Information Systems

Joint Optimization for Volatile Federated Learning in Vehicular Edge Computing: A Deep Reinforcement Learning Approach

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