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Towards a Scalable IOTA Tangle-Based Distributed Intelligence Approach for the Internet of Things

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Intelligent Computing (SAI 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1229))

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Abstract

Distributed Ledger Technology (DLT) brings a set of opportunities for the Internet of Things (IoT), which leads to innovative solutions for existing components at all levels of existing architectures. IOTA Tangle has the potential to overcome current technical challenges identified for the IoT domain, such as data processing, infrastructure scalability, security, and privacy. Scaling is a serious challenge that influences the deployment of IoT applications. We propose a Scalable Distributed Intelligence Tangle-based approach (SDIT), which aims to address the scalability problem in IoT by adapting the IOTA Tangle architecture. It allows the seamless integration of new IoT devices across different applications. In addition, we describe an offloading mechanism to perform proof-of-work (PoW) computation in an energy-efficient way. A set of experiments has been conducted to prove the feasibility of the Tangle in achieving better scalability, while maintaining energy efficiency. The results indicate that our proposed solution provides highly-scalable and energy efficient transaction processing for IoT DLT applications, when compared with an existing DAG-based distributed ledger approach.

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Notes

  1. 1.

    https://github.com/iotaledger/iri/releases/tag/v1.8.1-RELEASE.

  2. 2.

    https://www.digitalocean.com.

  3. 3.

    Due to resource constraints, we could only run up to 290 nodes.

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Authors and Affiliations

  1. School of Computing and Engineering, University of Huddersfield, Huddersfield, UK

    Tariq Alsboui, Yongrui Qin, Richard Hill & Hussain Al-Aqrabi

Authors
  1. Tariq Alsboui
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  2. Yongrui Qin
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  3. Richard Hill
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  4. Hussain Al-Aqrabi
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Corresponding author

Correspondence to Tariq Alsboui .

Editor information

Editors and Affiliations

  1. Faculty of Science and Engineering, Saga University, Saga, Japan

    Kohei Arai

  2. The Science and Information (SAI) Organization, Bradford, West Yorkshire, UK

    Supriya Kapoor

  3. The Science and Information (SAI) Organization, Bradford, West Yorkshire, UK

    Rahul Bhatia

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Alsboui, T., Qin, Y., Hill, R., Al-Aqrabi, H. (2020). Towards a Scalable IOTA Tangle-Based Distributed Intelligence Approach for the Internet of Things. In: Arai, K., Kapoor, S., Bhatia, R. (eds) Intelligent Computing. SAI 2020. Advances in Intelligent Systems and Computing, vol 1229. Springer, Cham. https://doi.org/10.1007/978-3-030-52246-9_35

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