Applicability of Deep Reinforcement Learning for Efficient Federated Learning in Massive IoT Communications

Applicability of Deep Reinforcement Learning for Efficient Federated Learning in Massive IoT Communications

To build intelligent model learning in conventional architecture, the local data are required to be transmitted toward the cloud server, which causes heavy backhaul congestion, leakage of personalization, and insufficient use of network resources. To address these issues, federated learning (FL) is...

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Bibliographic Details
Main Authors:	Prohim Tam, Riccardo Corrado, Chanthol Eang, Seokhoon Kim
Format:	Article
Language:	English
Published:	MDPI AG 2023-02-01
Series:	Applied Sciences
Subjects:	communication-efficient learning deep reinforcement learning federated learning massive Internet of Things policy optimization self-organizing networks
Online Access:	https://www.mdpi.com/2076-3417/13/5/3083

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