Multicenter Hierarchical Federated Learning With Fault-Tolerance Mechanisms for Resilient Edge Computing Networks-Reference-Cited by-同舟云学术

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Multicenter Hierarchical Federated Learning With Fault-Tolerance Mechanisms for Resilient Edge Computing Networks

Published:2024 Issue: Volume: Page:1-15
ISSN:2162-237X
Container-title:IEEE Transactions on Neural Networks and Learning Systems
language:
Short-container-title:IEEE Trans. Neural Netw. Learning Syst.

Author:

Chen Xiaohong¹,Xu Guanying¹^ORCID,Xu Xuesong²^ORCID,Jiang Haichong³^ORCID,Tian Zhiping³,Ma Tao⁴

Affiliation:

1. Business School of Central South University, Xiang Jiang Laboratory, Changsha, China

2. Changsha Social Laboratory of Artificial Intelligence, Hunan University of Technology and Business, Changsha, China

3. School of Advanced Interdisciplinary Studies, Hunan University of Technology and Business, Changsha, China

4. Hope Innovation Company Ltd, Changsha, China

Funder

Basic Science Center Project of the National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/5962385/6104215/10483107.pdf?arnumber=10483107

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Client Selection in Hierarchical Federated Learning;IEEE Internet of Things Journal;2024-09-01

2. Optimizing execution time and cost while scheduling scientific workflow in edge data center with fault tolerance awareness;Nonlinear Engineering;2024-01-01

3. Analysis of Fault Management Techniques for Edge-Enabled Distributed Metaverse Applications;2024

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