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Cited by 79Vehicular Ad Hoc Networks (VANETs)Blockchain Technology Applications and SecurityBlockchain Technology in Education and Learning

A Blockchain Based Federated Learning for Message Dissemination in Vehicular Networks

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Ayaz, Ferheen, Sheng, Zhengguo, Tian, Daxin, Guan, Yong Liang·2022·IEEE Transactions on Vehicular Technology
DOI 10.1109/tvt.2021.3132226
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Abstract

Message exchange among vehicles plays an important role in ensuring road safety. Emergency message dissemination is usually carried out by broadcasting. However, high vehicle density and mobility lead to challenges in message dissemination such as broadcasting storm and low probability of packet reception. This paper proposes a federated learning based blockchain-assisted message dissemination solution. Similar to the incentive-based Proof-of-Work consensus in blockchain, vehicles compete to become a relay node (miner) by processing the proposed Proof-of-Federated-Learning (PoFL) consensus which is embedded in the smart contract of blockchain. Both theoretical and practical analysis of the proposed solution are provided. Specifically, the proposed blockchain based federated learning results in more vehicles uploading their models in a given time, which can potentially lead to a more accurate model in less time as compared to the same solution without using blockchain. It also outperforms other blockchain approaches in reducing 65.2% of time delay in consensus, improving at least 8.2% message delivery rate and preserving privacy of neighbor vehicle more efficiently. The economic model to incentivize vehicles participating in federated learning and message dissemination is further analyzed using Stackelberg game. The analysis of asymptotic complexity proves PoFL as the most scalable solution compared to other consensus algorithms in vehicular networks.

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Cited by

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Authors
Ayaz, F., Sheng, Z., Tian, D., & Guan, Y. L.
Affiliations
  • University of Sussex (GB)
  • Beihang University (CN)
  • Nanyang Technological University (SG)
ORCID
Venue
IEEE Transactions on Vehicular Technology
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published
2022-02
Volume
71
Issue
2
Pages
1927-1940
ISSN
  • 0018-9545 (ISSN-L)
  • 1939-9359
DOI
10.1109/tvt.2021.3132226
OpenAlex
W3199107099
Cited by
79
References
7
Citations by year
2026: 9 · 2025: 15 · 2024: 20 · 2023: 22 · 2022: 13
FWCI
4.05
Type
journal article
Language
en
Open access
Licence
Locations
  • IEEE Transactions on Vehicular Technology (publishedVersion)
  • arXiv (Cornell University) (submittedVersion)
  • Sussex Research Online (University of Sussex) (submittedVersion)
  • DR-NTU (Nanyang Technological University) (submittedVersion)
  • ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam) (submittedVersion, cc-by-sa)
  • Figshare (submittedVersion, cc-by)
  • arXiv (Cornell University) (public-domain)
Funders
  • Natural Science Foundation of Beijing Municipality (L191001)
  • Agency for Science Technology and Research (A19D6a0053)
  • Newton Advanced Fellowship (62061130221)
  • National Natural Science Foundation of China (61822101, 62173012, U20A20155)
  • H2020 Marie Skodowska-Curie Actions (101006411)
Topics
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Vehicular Ad Hoc Networks (VANETs)
  • Physical Sciences › Computer Science › Information Systems › Blockchain Technology Applications and Security
  • Physical Sciences › Computer Science › Information Systems › Blockchain Technology in Education and Learning
Keywords
blockchain, federated learning, vehicular networks, message dissemination, smart contracts, relay node selection, emergency information dissemination, Stackelberg game, incentive mechanisms, privacy preservation, scalability

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