Cross-Cluster Federated Learning and Blockchain for Internet of Medical Things
| Autor: | Jiang Xiao, Huichuwu Li, Hai Jin, Xiaohai Dai, Yan Zhang, Baochun Li |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Information privacy
Computer Networks and Communications Computer science business.industry Context (language use) Computer Science Applications Data modeling Data sharing Hardware and Architecture Signal Processing Cluster (physics) The Internet Latency (engineering) business Protocol (object-oriented programming) Information Systems Computer network |
| Zdroj: | IEEE Internet of Things Journal. 8:15776-15784 |
| ISSN: | 2372-2541 |
| DOI: | 10.1109/jiot.2021.3081578 |
| Popis: | Federated learning (FL) has been gaining popularity as a way to provide privacy-preserving data sharing for the Internet of Medical Things (IoMT). As a complementary, blockchain technology is used in recent literature to make FL secure. However, existing blockchain-based FL (BFL) solutions do not perform well when data in a BFL cluster are sparse. A direct solution is to collect as many devices as possible to establish a large BFL cluster. However, these devices may locate in geographically distant areas and be separated by great distance, which further results in high communication latency. The high latency will lead to BFL’s low system efficiency due to frequent communications in the blockchain consensus. In this article, we propose that the large cluster should be divided into multiple smaller clusters, each in its own geographical area and organized with a BFL. In this context, we propose CFL, a cross-cluster FL system facilitated by the cross-chain technique. CFL connects multiple BFL clusters, where only a few aggregated updates are transmitted over long distances across clusters, thus improving the system efficiency. The design of CFL focuses on a cross-chain consensus protocol, which guarantees the model updates to be exchanged securely across clusters. We carry out extensive experiments to evaluate CFL in comparison with BFL, and show both CFL’s feasibility and efficiency. |
| Databáze: | OpenAIRE |
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