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

Tariq Alsboui, Yongrui Qin, Richard Hill

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Recently, Distributed Ledger Technology (DLT) started to play an important role in ensuring scalability, privacy, and security for the Internet of Things (IoT). It brings a whole new world of opportunities by potentially bringing innovative solutions for existing components at all levels of existing IoT architectures. IOTA Tangle has the potential to overcome the current technical challenges identified in the IoT domain, such as data processing, massive infrastructure scalability, security, and privacy. Scaling is a serious challenge that influences the deployment of IoT applications. Therefore, any solution should be fit and scale when needed to accommodate larger numbers of IoT devices. In this paper, a Scalable Distributed Intelligence Tangle-based approach (SDIT) is put forward, which aims to address the scalability problem in IoT by adapting the IOTA Tangle architecture. It allows seamless integration of new IoT devices across different IoT applications. In addition, we propose an offloading mechanism to perform the proof of work (PoW) computation on more powerful devices in order to save energy consumption of IoT devices. Based on the proposed solution, a set of experiments have been conducted to prove the feasibility of the Tangle in achieving better scalability without loss of efficiency. From the results, we found that our proposed solution provides a highly scalable and energy efficient transaction processing to IoT DLT applications compared with the existing DAG-based distributed ledger approach. This demonstrates that the proposed SDIT approach is a feasible solution for building scalable IoT applications while ensuring security and privacy.
Original languageEnglish
Title of host publicationIntelligent Computing
Subtitle of host publicationProceedings of the 2020 Computing Conference
PublisherSpringer Verlag
Number of pages16
Publication statusAccepted/In press - 31 Oct 2019
EventComputing Conference 2020 - London, United Kingdom
Duration: 16 Jul 202017 Jul 2020
https://saiconference.com/Computing

Publication series

NameAdvances in Intelligent Systems and Computing
PublisherSpringer
ISSN (Electronic)2194-5357

Conference

ConferenceComputing Conference 2020
CountryUnited Kingdom
CityLondon
Period16/07/2017/07/20
Internet address

Fingerprint

Scalability
Internet of things
Energy utilization
Processing
Experiments

Cite this

Alsboui, T., Qin, Y., & Hill, R. (Accepted/In press). Towards Building a Scalable Tangle-Based Distributed Intelligence Approach for the Internet of Things. In Intelligent Computing: Proceedings of the 2020 Computing Conference (Advances in Intelligent Systems and Computing). Springer Verlag.
Alsboui, Tariq ; Qin, Yongrui ; Hill, Richard. / Towards Building a Scalable Tangle-Based Distributed Intelligence Approach for the Internet of Things. Intelligent Computing: Proceedings of the 2020 Computing Conference. Springer Verlag, 2019. (Advances in Intelligent Systems and Computing).
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Alsboui, T, Qin, Y & Hill, R 2019, Towards Building a Scalable Tangle-Based Distributed Intelligence Approach for the Internet of Things. in Intelligent Computing: Proceedings of the 2020 Computing Conference. Advances in Intelligent Systems and Computing, Springer Verlag, Computing Conference 2020, London, United Kingdom, 16/07/20.

Towards Building a Scalable Tangle-Based Distributed Intelligence Approach for the Internet of Things. / Alsboui, Tariq; Qin, Yongrui; Hill, Richard.

Intelligent Computing: Proceedings of the 2020 Computing Conference. Springer Verlag, 2019. (Advances in Intelligent Systems and Computing).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Alsboui T, Qin Y, Hill R. Towards Building a Scalable Tangle-Based Distributed Intelligence Approach for the Internet of Things. In Intelligent Computing: Proceedings of the 2020 Computing Conference. Springer Verlag. 2019. (Advances in Intelligent Systems and Computing).