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

Tariq Alsboui; Yongrui Qin; Richard Hill; Hussain Al-Aqrabi

doi:10.1007/978-3-030-52246-9_35

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

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

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

11 Citations (Scopus)

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.

Original language	English
Title of host publication	Intelligent Computing
Subtitle of host publication	Proceedings of the 2020 Computing Conference (SAI 2020)
Editors	Kohei Arai, Supriya Kapoor, Rahul Bhatia
Publisher	Springer Verlag
Pages	487-501
Number of pages	15
Volume	2
Edition	1st
ISBN (Electronic)	9783030522469
ISBN (Print)	9783030522452
DOIs	https://doi.org/10.1007/978-3-030-52246-9_35
Publication status	Published - 4 Jul 2020
Event	Computing Conference 2020 - Held online due to COVID-19 Duration: 16 Jul 2020 → 17 Jul 2020 https://saiconference.com/Computing

Publication series

Name	Advances in Intelligent Systems and Computing
Publisher	Springer
Volume	AISC 1229
ISSN (Print)	2194-5357
ISSN (Electronic)	2194-5365

Conference

Conference	Computing Conference 2020
Abbreviated title	SAI 2020
Period	16/07/20 → 17/07/20
Internet address	https://saiconference.com/Computing

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1007/978-3-030-52246-9_35Licence: Unspecified

Towards_a_Scalable_IOTA_Tangle_Based_Distributed_Intelligence_Approach_for_the_Internet_of_ThingsAccepted author manuscript, 1.19 MBLicence: Unspecified

Cite this

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 K. Arai, S. Kapoor, & R. Bhatia (Eds.), Intelligent Computing: Proceedings of the 2020 Computing Conference (SAI 2020) (1st ed., Vol. 2, pp. 487-501). (Advances in Intelligent Systems and Computing; Vol. AISC 1229). Springer Verlag. https://doi.org/10.1007/978-3-030-52246-9_35

Alsboui, Tariq ; Qin, Yongrui ; Hill, Richard et al. / Towards a Scalable IOTA Tangle-Based Distributed Intelligence Approach for the Internet of Things. Intelligent Computing: Proceedings of the 2020 Computing Conference (SAI 2020). editor / Kohei Arai ; Supriya Kapoor ; Rahul Bhatia. Vol. 2 1st. ed. Springer Verlag, 2020. pp. 487-501 (Advances in Intelligent Systems and Computing).

@inproceedings{339fbdd48c8e414fa2b383a5fec75ac8,

title = "Towards a Scalable IOTA Tangle-Based Distributed Intelligence Approach for the Internet of Things",

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.",

keywords = "Internet of Things (IoT), Tangle, distributed ledger, Scalability, Distributed Ledger Technology (DLT), IOTA Tangle, Distributed Intelligence (DI)",

author = "Tariq Alsboui and Yongrui Qin and Richard Hill and Hussain Al-Aqrabi",

year = "2020",

month = jul,

day = "4",

doi = "10.1007/978-3-030-52246-9_35",

language = "English",

isbn = "9783030522452",

volume = "2",

series = "Advances in Intelligent Systems and Computing",

publisher = "Springer Verlag",

pages = "487--501",

editor = "Kohei Arai and Supriya Kapoor and Rahul Bhatia",

booktitle = "Intelligent Computing",

address = "Germany",

edition = "1st",

note = "Computing Conference 2020, SAI 2020 ; Conference date: 16-07-2020 Through 17-07-2020",

url = "https://saiconference.com/Computing",

}

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 K Arai, S Kapoor & R Bhatia (eds), Intelligent Computing: Proceedings of the 2020 Computing Conference (SAI 2020). 1st edn, vol. 2, Advances in Intelligent Systems and Computing, vol. AISC 1229, Springer Verlag, pp. 487-501, Computing Conference 2020, 16/07/20. https://doi.org/10.1007/978-3-030-52246-9_35

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

Intelligent Computing: Proceedings of the 2020 Computing Conference (SAI 2020). ed. / Kohei Arai; Supriya Kapoor; Rahul Bhatia. Vol. 2 1st. ed. Springer Verlag, 2020. p. 487-501 (Advances in Intelligent Systems and Computing; Vol. AISC 1229).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Towards a Scalable IOTA Tangle-Based Distributed Intelligence Approach for the Internet of Things

AU - Alsboui, Tariq

AU - Qin, Yongrui

AU - Hill, Richard

AU - Al-Aqrabi, Hussain

PY - 2020/7/4

Y1 - 2020/7/4

N2 - 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.

AB - 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.

KW - Internet of Things (IoT)

KW - Tangle

KW - distributed ledger

KW - Scalability

KW - Distributed Ledger Technology (DLT)

KW - IOTA Tangle

KW - Distributed Intelligence (DI)

UR - https://www.springer.com/gp/book/9783030522452

UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85088506346&doi=10.1007%2f978-3-030-52246-9_35&partnerID=40&md5=cc5b89eb5f86dc02ae6d20abe50d936a

U2 - 10.1007/978-3-030-52246-9_35

DO - 10.1007/978-3-030-52246-9_35

M3 - Conference contribution

SN - 9783030522452

VL - 2

T3 - Advances in Intelligent Systems and Computing

SP - 487

EP - 501

BT - Intelligent Computing

A2 - Arai, Kohei

A2 - Kapoor, Supriya

A2 - Bhatia, Rahul

PB - Springer Verlag

T2 - Computing Conference 2020

Y2 - 16 July 2020 through 17 July 2020

ER -

Alsboui T, Qin Y, Hill R, Al-Aqrabi H. Towards a Scalable IOTA Tangle-Based Distributed Intelligence Approach for the Internet of Things. In Arai K, Kapoor S, Bhatia R, editors, Intelligent Computing: Proceedings of the 2020 Computing Conference (SAI 2020). 1st ed. Vol. 2. Springer Verlag. 2020. p. 487-501. (Advances in Intelligent Systems and Computing). Epub 2020 Jul 4. doi: 10.1007/978-3-030-52246-9_35

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

Abstract

Publication series

Conference

UN SDGs

Access to Document

Other files and links

Fingerprint

Keynote: Realising Smart Manufacturing with the Industrial Internet of Things

Cite this

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

Abstract

Publication series

Conference

UN SDGs

Access to Document

Other files and links

Fingerprint

Activities

Keynote: Realising Smart Manufacturing with the Industrial Internet of Things

Cite this