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Estimating service quality in industrial internet-of-things monitoring applications with blockchain


Maiti, A and Raza, A and Kang, BH and Hardy, L, Estimating service quality in industrial internet-of-things monitoring applications with blockchain, IEEE Access, 7 pp. 155489-155503. ISSN 2169-3536 (2019) [Refereed Article]


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Licensed under Creative Commons Attribution 4.0 International (CC BY 4.0)

DOI: doi:10.1109/ACCESS.2019.2948269


Internet of Things (IoT) plays a big role in automating information generation and consumption in industrial monitoring applications. Blockchain can allow this information to be stored in a manner that is both accessible and reliable for the IoT devices to work with. Blockchain has the capability to collect data from IoT devices and store it in a distributed manner that prevents tampering with the data. This paper discusses the use of blockchain to calculate the Service Quality (SQ) in an Industrial IoT for monitoring application. The proposed framework looks at the blockchain as a finite number of fragmented pieces of data corresponding to a specific industrial process. The SQ is expressed as penalties which is the difference between the expected IoT sensor values and the actual sensor data in reported events from the IoT devices. It also moderates the penalty between similar industrial processes based on each other. The moderation allows better understanding of the system functions and identification of specific problems rather than simply recording the sensor data for a single process. Furthermore, this paper analyzes private blockchains for suitability in IIoT and summarizes some key challenges for IoT to be used with blockchain in context of the proposed framework. The paper uses supply chain as a use case scenario for describing the proposed framework and presents results on its technical feasibility.

Item Details

Item Type:Refereed Article
Keywords:blockchain, internet of things, cyber-physical systems, logistics, p2p network, smart contract
Research Division:Information and Computing Sciences
Research Group:Artificial intelligence
Research Field:Knowledge representation and reasoning
Objective Division:Information and Communication Services
Objective Group:Information systems, technologies and services
Objective Field:Information systems, technologies and services not elsewhere classified
UTAS Author:Maiti, A (Dr Ananda Maiti)
UTAS Author:Raza, A (Dr Ali Raza)
UTAS Author:Kang, BH (Professor Byeong Kang)
UTAS Author:Hardy, L (Mr Lachlan Hardy)
ID Code:137262
Year Published:2019
Web of Science® Times Cited:11
Deposited By:Information and Communication Technology
Deposited On:2020-02-06
Last Modified:2020-08-19
Downloads:26 View Download Statistics

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