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Blockchain-enabled K-harmonic framework for industrial IoT-based systems.

Authors :
Baalamurugan, K. M.
P., Prabu
Bacanin, Nebojsa
Venkatachalam, K.
Askar, S. S.
Abouhawwash, Mohamed
Source :
Scientific Reports; 1/21/2023, Vol. 13 Issue 1, p1-13, 13p
Publication Year :
2023

Abstract

Industrial Internet of Things (IIoT)-based systems have become an important part of industry consortium systems because of their rapid growth and wide-ranging application. Various physical objects that are interconnected in the IIoT network communicate with each other and simplify the process of decision-making by observing and analyzing the surrounding environment. While making such intelligent decisions, devices need to transfer and communicate data with each other. However, as devices involved in IIoT networks grow and the methods of connections diversify, the traditional security frameworks face many shortcomings, including vulnerabilities to attack, lags in data, sharing data, and lack of proper authentication. Blockchain technology has the potential to empower safe data distribution of big data generated by the IIoT. Prevailing data-sharing methods in blockchain only concentrate on the data interchanging among parties, not on the efficiency in sharing, and storing. Hence an element-based K-harmonic means clustering algorithm (CA) is proposed for the effective sharing of data among the entities along with an algorithm named underweight data block (UDB) for overcoming the obstacle of storage space. The performance metrics considered for the evaluation of the proposed framework are the sum of squared error (SSE), time complexity with respect to different m values, and storage complexity with CPU utilization. The results have experimented with MATLAB 2018a simulation environment. The proposed model has better sharing, and storing based on blockchain technology, which is appropriate IIoT. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20452322
Volume :
13
Issue :
1
Database :
Complementary Index
Journal :
Scientific Reports
Publication Type :
Academic Journal
Accession number :
161417320
Full Text :
https://doi.org/10.1038/s41598-023-27739-5