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Technology of Network & Communication
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App. Res. of Comp. Printed Article
Vol. 41, 2024 No. 9
2823-2830

Optimization method for communication overhead in federated learning architecture for multi-tenant data center

Cheng Huashenga
Jing Chaoa,b
a. School of Computer Science & Engineering, b. Guangxi Key Laboratory of Embedded Technology & Intelligent System, Guilin University of Technology, Guilin Guangxi 541004, China
DOI: 10.19734/j.issn.1001-3695.2024.01.0002

Abstract

To address the issue of high communication cost under the federated learning framework in multi-tenant data centers, this paper proposed an optimization algorithm based on ternary evolutionary model parameters. Firstly, it constructed a federated learning architecture tailored to multi-tenant data centers for data privacy protection. Secondly, in response to the excessive communication overhead stemming from the implementation of the federated learning framework, which increasing interactions between tenants and the data center, it proposed an optimization algorithm that utilized ternary evolutionary model parameters. This algorithm aimed to reduce redundant communication in the exchange of model parameters between tenants and the data center by integrating the optimal local model with the evolutionary direction of ternary vectorized model parameters. Moreover, by analyzing privacy research based on federated learning, the algorithm effectively ensured the privacy of tenants participating in the training during the communication process. Finally, experimental results demonstrate that, while maintaining training accuracy, the proposed method can effectively reduce redundant communication costs by 30% compared to the federated averaging baseline algorithm.

Foundation Support

国家自然科学基金资助项目(62362018)
广西重点研发计划资助项目(桂科AB23075116,桂科AB23075175)
广西研究生教育创新计划资助项目(YCSW2023350)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2024.01.0002
Publish at: Application Research of Computers Printed Article, Vol. 41, 2024 No. 9
Section: Technology of Network & Communication
Pages: 2823-2830
Serial Number: 1001-3695(2024)09-036-2823-08

Publish History

[2024-05-08] Accepted Paper
[2024-09-05] Printed Article

Cite This Article

程华盛, 敬超. 面向多租户数据中心的联邦学习架构下通信开销优化方法 [J]. 计算机应用研究, 2024, 41 (9): 2823-2830. (Cheng Huasheng, Jing Chao. Optimization method for communication overhead in federated learning architecture for multi-tenant data center [J]. Application Research of Computers, 2024, 41 (9): 2823-2830. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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