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 proceedingConference contributionpeer-review

11 Citations (Scopus)


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 languageEnglish
Title of host publicationIntelligent Computing
Subtitle of host publicationProceedings of the 2020 Computing Conference (SAI 2020)
EditorsKohei Arai, Supriya Kapoor, Rahul Bhatia
PublisherSpringer Verlag
Number of pages15
ISBN (Electronic)9783030522469
ISBN (Print)9783030522452
Publication statusPublished - 4 Jul 2020
EventComputing Conference 2020 - Held online due to COVID-19
Duration: 16 Jul 202017 Jul 2020

Publication series

NameAdvances in Intelligent Systems and Computing
VolumeAISC 1229
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365


ConferenceComputing Conference 2020
Abbreviated titleSAI 2020
Internet address


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