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An Implementation of Blockchain Decentralized Application for Industrial IoT Scenarios

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Implementing Industry 4.0

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 202))

Abstract

Blockchain Decentralized Applications (Blockchain Dapps or Dapps in short) have been implemented in many different industrial applications, including recent Industrial Internet-of-Things (IIoT) and Cyber Physical Systems (CPS). In this paper, we propose an architectural design that integrates both a permissioned blockchain network and an IIoT infrastructure for establishing a decentralized IIoT data marketplace. The decentralized IIoT data marketplace allows both data providers and data consumers, to share the available IIoT datasets without any centralized third-party user authorization. First, our proposed Dapp is enabled to connect with a time series database that is considered as a persistent storage of IIoT machine and sensor data. Second, by defining the written data via a smart contract, we ensure that all transactional records between data providers and data consumers are traceable and immutable. Third, we deploy a distributed file system in our proposed architecture to strengthen data privacy by converting the output results into cryptographic hashes. Besides, we demonstrate the designated role-based web user interfaces (UIs) for our proposed Dapp. Finally, we perform an experimental study by utilizing a time series database benchmark tool as an exemplary IIoT system to evaluate the effectiveness and efficiency of our proposed Dapp.

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Acknowledgements

This research is supported by the Agency for Science, Technology and Research (A*STAR) under its Advanced Manufacturing & Engineering (AME) Industry Alignment Funding—Pre-positioning funding scheme (Project No: A1723a0035).

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Correspondence to Wei Chit Tan .

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Tan, W.C., Fu, W., Tan, S.Z. (2021). An Implementation of Blockchain Decentralized Application for Industrial IoT Scenarios. In: Toro, C., Wang, W., Akhtar, H. (eds) Implementing Industry 4.0. Intelligent Systems Reference Library, vol 202. Springer, Cham. https://doi.org/10.1007/978-3-030-67270-6_14

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