The Role of Communication Time in the Convergence of Federated Edge Learning-Reference-Cited by-同舟云学术

The Role of Communication Time in the Convergence of Federated Edge Learning

Published:2022-03 Issue:3 Volume:71 Page:3241-3254
ISSN:0018-9545
Container-title:IEEE Transactions on Vehicular Technology
language:
Short-container-title:IEEE Trans. Veh. Technol.

Author:

Zhou Yipeng¹^ORCID,Fu Yao²,Luo Zhenxiao²^ORCID,Hu Miao²,Wu Di²^ORCID,Sheng Quan Z.¹^ORCID,Yu Shui³^ORCID

Affiliation:

1. Department of Computing, FSE, Macquarie University, Macquarie, NSW, Australia

2. School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China

3. School of Computer Science, University of Technology Sydney, Ultimo, NSW, Australia

Funder

National Natural Science Foundation of China

Science and Technology Planning Project of Guangdong Province

Science and Technology Program of Guangzhou

Natural Science Foundation of Guangdong Province

Australian Research Council

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Aerospace Engineering,Automotive Engineering

Link

http://xplorestaging.ieee.org/ielx7/25/9735425/09684971.pdf?arnumber=9684971

Reference47 articles.

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3. Federated learning with additional mechanisms on clients to reduce communication costs;yao,2019

4. CMFL: Mitigating communication overhead for federated learning;luping;Proc IEEE 39th Int Conf Distrib Comput Syst,0

5. Communication-efficient on-device machine learning: Federated distillation and augmentation under non-IID private data;jeong;Proc 32nd Conf Neural Inf Process Syst (NIPS) 2nd Workshop Mach Learn Phone Consum Devices (MLPCD 2),0

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