Enhancing Scalability and Reliability in Semi-Decentralized Federated Learning With Blockchain: Trust Penalization and Asynchronous Functionality
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Abstract (arXiv)
The paper presents an innovative approach to address the challenges of scalability and reliability in Distributed Federated Learning by leveraging the integration of blockchain technology. The paper focuses on enhancing the trustworthiness of participating nodes through a trust penalization mechanism while also enabling asynchronous functionality for efficient and robust model updates. By combining Semi-Decentralized Federated Learning with Blockchain (SDFL-B), the proposed system aims to create a fair, secure and transparent environment for collaborative machine learning without compromising data privacy. The research presents a comprehensive system architecture, methodologies, experimental results, and discussions that demonstrate the advantages of this novel approach in fostering scalable and reliable SDFL-B systems.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 10 of its 18 references that are in the map. First posted on arXiv 30 Oct 2023.
Builds on
10 of 18 references.
References · 10
- 2019Towards Federated Learning at Scale: System Designcited by 832
- 2022Decentralized Federated Learning: Fundamentals, State of the Art, Frameworks, Trends, and Challengescited by 138
- 2021Semi-Decentralized Federated Learning with Cooperative D2D Local Model Aggregationscited by 51
- 2021Opportunities of Federated Learning in Connected, Cooperative and Automated Industrial Systemscited by 45
- 2018COLA: Decentralized Linear Learningcited by 30
- 2022Semi-Decentralized Federated Learning with Collaborative Relayingcited by 16
- 2021D-Cliques: Compensating for Data Heterogeneity with Topology in Decentralized Federated Learningcited by 12
- 2021Jointly Learning from Decentralized (Federated) and Centralized Data to Mitigate Distribution Shiftcited by 7
- 2023Blockchain-Based Federated Learning: Incentivizing Data Sharing and Penalizing Dishonest Behaviorcited by 5
- 2019User Data Sharing Frameworks: A Blockchain-Based Incentive Solutioncited by 1
Built on by
Citing papers per year: 2024: 1; 2025: 1; 2026: 1.
3 papers.