FedAHP: A Heterogeneous Client Selection Method for Federated Learning Based on the Analytic Hierarchy Process in Mobile Edge-Reference-Cited by-同舟云学术

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FedAHP: A Heterogeneous Client Selection Method for Federated Learning Based on the Analytic Hierarchy Process in Mobile Edge

Published:2024-05-08 Issue: Volume: Page:968-973
ISSN:
Container-title:2024 27th International Conference on Computer Supported Cooperative Work in Design (CSCWD)
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Author:

Zheng Zhaohua¹,Wang Zizheng¹,Tong Xinyu²,Li Keqiu²,Chen Qiquan³

Affiliation:

1. Hainan University,School of CyberSpace Security (School of Cryptology),Haikou,China,570228

2. Tianjin University,College of Intelligence and Computing,Tianjin,China,300350

3. Luoniushan Co., Ltd,Information Technology Research Department,Haikou,China,570208

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10579968/10579982/10580393.pdf?arnumber=10580393

Reference21 articles.

1. A Survey on Federated Learning Systems: Vision, Hype and Reality for Data Privacy and Protection

2. Federated Learning on Non-IID Data Silos: An Experimental Study

3. Communication-efficient learning of deep networks from decentralized data;McMahan,2017

4. Energy Efficient Computation Offloading in Mobile Edge Computing

5. Applications of federated learning in smart cities: recent advances, taxonomy, and open challenges

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