Federated Learning-Based Resource Management with Blockchain Trust Assurance in Smart IoT

Fu, Xiuhua; Peng, Rongqun; Yuan, Wenhao; Ding, Tian; Zhang, Zhe; Yu, Peng; Kadoch, Michel

doi:10.3390/electronics12041034

Open AccessArticle

Federated Learning-Based Resource Management with Blockchain Trust Assurance in Smart IoT

by

Xiuhua Fu

^1,*,

Rongqun Peng

^1,2

,

Wenhao Yuan

^1,2,*,

Tian Ding

¹,

Zhe Zhang

¹,

Peng Yu

²

and

Michel Kadoch

³

¹

School of Computer Science and Technology, Shandong University of Technology, Zibo 255000, China

²

State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China

³

Department of Electrical Engineering, ETS, University of Quebec, Montreal, QC H3C 3J7, Canada

^*

Authors to whom correspondence should be addressed.

Electronics 2023, 12(4), 1034; https://doi.org/10.3390/electronics12041034

Submission received: 17 January 2023 / Revised: 16 February 2023 / Accepted: 17 February 2023 / Published: 19 February 2023

(This article belongs to the Section Networks)

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Abstract

Resource management is a key issue that needs to be addressed in the future smart Internet of Things (IoT). This paper focuses on a Federated Learning (FL)-based resource management mechanism in IoT. It incorporates blockchain technology to guarantee the security of the FL model parameters exchange. We propose an IoT resource management framework incorporating blockchain and federated learning technologies; then, a specific FL-based resource management with a blockchain trust assurance algorithm is given. We use a Support Vector Machine (SVM) classifier to detect malicious nodes in order to avoid the impact on the performance of the FL-based algorithm. Finally, we perform simulation to verify the SVM classification effect and the proposed algorithm performance. The results show that the SVM-based malicious node identification accuracy can be acceptable. Moreover, the proposed algorithm obtains better performance when malicious nodes are excluded from the FL selected participant.

Keywords: Internet of Things (IoT); federated learning (FL); blockchain; resource management; malicious nodes

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MDPI and ACS Style

Fu, X.; Peng, R.; Yuan, W.; Ding, T.; Zhang, Z.; Yu, P.; Kadoch, M. Federated Learning-Based Resource Management with Blockchain Trust Assurance in Smart IoT. Electronics 2023, 12, 1034. https://doi.org/10.3390/electronics12041034

AMA Style

Fu X, Peng R, Yuan W, Ding T, Zhang Z, Yu P, Kadoch M. Federated Learning-Based Resource Management with Blockchain Trust Assurance in Smart IoT. Electronics. 2023; 12(4):1034. https://doi.org/10.3390/electronics12041034

Chicago/Turabian Style

Fu, Xiuhua, Rongqun Peng, Wenhao Yuan, Tian Ding, Zhe Zhang, Peng Yu, and Michel Kadoch. 2023. "Federated Learning-Based Resource Management with Blockchain Trust Assurance in Smart IoT" Electronics 12, no. 4: 1034. https://doi.org/10.3390/electronics12041034

APA Style

Fu, X., Peng, R., Yuan, W., Ding, T., Zhang, Z., Yu, P., & Kadoch, M. (2023). Federated Learning-Based Resource Management with Blockchain Trust Assurance in Smart IoT. Electronics, 12(4), 1034. https://doi.org/10.3390/electronics12041034

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

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Federated Learning-Based Resource Management with Blockchain Trust Assurance in Smart IoT

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