Adaptive device sampling and deadline determination for cloud-based heterogeneous federated learning

Adaptive device sampling and deadline determination for cloud-based heterogeneous federated learning

Abstract As a new approach to machine learning, Federated learning enables distributned traiing on edge devices and aggregates local models into a global model. The edge devices that participate in federated learning are highly heterogeneous in terms of computing power, device state, and data distri...

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Bibliographic Details
Main Authors: Deyu Zhang, Wang Sun, Zi-Ang Zheng, Wenxin Chen, Shiwen He
Format: Article
Language:English
Published: SpringerOpen 2023-11-01
Series:Journal of Cloud Computing: Advances, Systems and Applications
Subjects:
Federated learning
Deep reinforcement learning
State heterogeneity
Online Access:https://doi.org/10.1186/s13677-023-00515-6

Internet

https://doi.org/10.1186/s13677-023-00515-6

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