A Novel Architecture Combining Oracle With Decentralized Learning for IIoT

【Author】 Lin, Yijing; Gao, Zhipeng; Shi, Weisong; Wang, Qian; Li, Huangqi; Wang, Miaomiao; Yang, Yang; Rui, Lanlan

【Source】IEEE INTERNET OF THINGS JOURNAL

【影响因子】10.238

【Abstract】The rapid development of digital technology is reshaping the architecture of the Industrial Internet of Things (IIoT). The traditional architecture cannot process vast amounts of data exchanges and provide entities with trust. The future IIoT is expected to be a decentralized architecture in which blockchain and digital twin-driven IIoT can enable trusted data exchanges. However, this architecture cannot obtain huge amounts of external real-time data and isolated data. Moreover, it cannot handle complex industrial computing tasks. Therefore, we combine oracle with decentralized learning to propose a novel IIoT-oriented digital twin architecture. We also propose an effective decentralized collaboration mechanism to support external data and resources exchanges. Moreover, we propose a novel computing collaboration mechanism to expand the learning capabilities of the industrial ecology. Experiments show that our proposed paradigm has less processing time, a more stable process, and better learning ability compared to other paradigms.

【Keywords】Blockchains; Collaboration; Computer architecture; Industrial Internet of Things; Digital twin; Task analysis; Edge computing; Blockchain; digital twin; Industrial Internet of Things (IIoT); oracle

【发表时间】2023 1-Mar

【收录时间】2023-05-16

【文献类型】理论模型

【主题类别】

区块链应用-实体经济-工业互联网