Federated Deep Reinforcement Learning for Optimal Resource Allocation in Vehicular Edge Computing

Rehmat Ullah; Imran Chowdhury; Md. Abdur Razzaque; Palash Roy; Mohammad Mehedi Hassan

doi:10.1007/978-3-031-92608-2_20

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Federated Deep Reinforcement Learning for Optimal Resource Allocation in Vehicular Edge Computing

Rehmat Ullah Imran Chowdhury Md. Abdur Razzaque Palash Roy Mohammad Mehedi Hassan

Year: 2025 Lecture notes in networks and systems Pages: 279-294 Publisher: Springer International Publishing

DOI: 10.1007/978-3-031-92608-2_20

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Keywords:

Reinforcement learning Computer science Enhanced Data Rates for GSM Evolution Distributed computing Resource allocation Artificial intelligence Edge device Edge computing Human–computer interaction Computer network Operating system Cloud computing

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Topics

Privacy-Preserving Technologies in Data

Physical Sciences → Computer Science → Artificial Intelligence

IoT and Edge/Fog Computing

Physical Sciences → Computer Science → Computer Networks and Communications

Vehicular Ad Hoc Networks (VANETs)

Physical Sciences → Engineering → Electrical and Electronic Engineering

Federated Deep Reinforcement Learning for Optimal Resource Allocation in Vehicular Edge Computing

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