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A Blockchain-Driven Smart Broker for Data Quality Assurance of the Tagged Periodic IoT Data in Publisher-Subscriber Model

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journal contribution
posted on 2024-08-05, 00:41 authored by Rabbia Idrees, Ananda MaitiAnanda Maiti
The Publisher-Subscriber model of data exchange has been a popular method for many Internet-based applications, including the Internet of Things (IoT). A traditional PS system consists of publishers, subscribers, and a broker. The publishers create new data for a registered topic, and the data broker relays the data to the corresponding subscribers. This paper introduces a blockchain-based smart broker for the publisher-subscriber (PS) framework for the IoT network. As IoT data comes from devices operating in various environments, it may suffer from multiple challenges, such as hardware failures, connectivity issues, and external vulnerabilities, thereby impacting data quality in terms of accuracy and timeliness. It is important to monitor this data and inform subscribers about its quality. The proposed smart broker is composed of multiple smart contracts that continuously monitor the quality of the topic data by assessing its relationship with other related topics and its drift or delay in publishing intervals. It assigns a reputation score to each topic computed based on its quality and drifts, and it passes both the original data and the reputation score as a measure of quality to the subscriber. Furthermore, the smart broker can suggest substitute topics to subscribers when the requested topic data are unavailable or of very poor quality. The evaluation shows that a smart broker efficiently monitors the reputation of the topic data, and its efficiency increases notably when the data quality is worse. As the broker is run inside the blockchain, it automatically inherits the advantages of the blockchain, and the quality scoring is indisputable based on immutable data.

History

Journal

Applied Sciences

Volume

14

Article number

5907

Pagination

1-27

Location

Basel, Switzerland

Open access

  • Yes

ISSN

2076-3417

eISSN

2076-3417

Language

eng

Publication classification

C1 Refereed article in a scholarly journal

Issue

13

Publisher

MDPI

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