ItemArticle

Pearson correlation-based clustering with collaborative task allocation in 5G Industrial Internet of Things divergent health networks

Title
Pearson correlation-based clustering with collaborative task allocation in 5G Industrial Internet of Things divergent health networks
Creator
Vaithianathan, Krishnakumar; Pernabas, Julian Benadit; Lamani, Manjunath Ramanna; Venkatachalam, K.; Askar, S.S.; Abouhawwash, Mohamed
Description
Simultaneous task allocation is crucial for enhancing service quality in Industrial Internet of Things (IIoT) environments. The distribution and management of tasks remain among the biggest challenges in the IIoT era. Efficient allocation strategies are needed to enable transparent network configurations and maximize task throughput. Although recent methods address the dynamic management of objects, they often overlook the correlations between tasks and their associated functionalities. This paper introduces a novel Connected Harmonical Adaptive Task Allocation (CHATA) model for IIoT health networks to ensure fair task distribution. CHATA leverages similarity measures of object functionalities to identify the most suitable object to perform each task. Simulations conducted in NS-3 demonstrate that CHATA achieves up to 90% allocation efficiency in 5G Radio Access Technologies IIoT health environments and significantly outperforms recent approaches in task assignment performance. The Author(s) 2025.
Source
Scientific Reports;Volume;15;Issue;1;Article No.;43344;
Date
01-01-2025
Publisher
Nature Research
Subject
5G; Clustering; IIoT-health; Task allocation
Coverage
Vaithianathan K., Department of Computer Engineering, Karaikal Polytechnic College, Varichikudy, Puducherry, Karaikal, 609609, India; Pernabas J.B., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Kengeri Campus, Karnataka, Bangalore, 560074, India; Lamani M.R., Department of Computer Science and Engineering, Moodlakatte Institute of Technology Kundapura, Karnataka, Moodalkatte, 576217, India; Venkatachalam K., Department of Applied Cybernetics, Faculty of Science, University of Hradec Krov Hradec Krov 50003, Czech Republic; Askar S.S., Department of Statistics and Operations Research, College of Science, King Saud University, P.O. Box 2455, Riyadh, 11451, Saudi Arabia; Abouhawwash M., Department of Industrial and Systems Engineering, King Fahd University of Petroleum & Minerals, Dhahran, 31261, Saudi Arabia, Interdisciplinary Research Center for Smart Mobility and Logistics (IRC-SML), King Fahd University of Petroleum & Minerals, Dhahran, 31261, Saudi Arabia
Rights
All Open Access; Gold Open Access; Green Open Access
Relation
ISSN: 20452322;
Format
online
Language
English
Type
Article

Citation

Vaithianathan, Krishnakumar; Pernabas, Julian Benadit; Lamani, Manjunath Ramanna; Venkatachalam, K.; Askar, S.S.; Abouhawwash, Mohamed, “Pearson correlation-based clustering with collaborative task allocation in 5G Industrial Internet of Things divergent health networks,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 18, 2026, https://archives.christuniversity.in/items/show/22532.

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