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Research Article | Open Access

Numerical investigation of a wireless sensor network epidemic model with α-stable noise: A case study

Hassan Tahir1,2Anwarud Din3Wajahat Ali Khan4Mati ur Rahman5( )
MSU-BIT-SMBU Joint Research Center of Applied Mathematics, Shenzhen MSU-BIT University, Shenzhen, China
School of Mathematics and Statistics, Beijing Institute of Technology, Beijing, China
Department of Mathematics, Sun Yat-sen University, Guangzhou 510275, China
Department of Mathematics, University of Malakand, Chakdara 18800, KPK, Pakistan
Department of Mathematics and Statistics, College of Science, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Saudi Arabia
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Abstract

This study examines a stochastic susceptible-exposed-infected-recovered-vaccinated ( S E 1 E 2 I R V ) model exhibiting the dynamics of the computer virus within the wireless sensor networks (WSNs) while considering the unpredictability of nodes and the impact of anti-virus measures. The model is formulated with reasonable assumptions, and the stochastic stability is performed with a derivation of a six-dimensional Fokker-Planck equation. To obtain an analytical representation of the probability density functions, a scheme is developed and subsequently implemented in MATLAB. The behavior of the model around the quasi-endemic state is numerically investigated, which reflects the main objective and unique novelty of the present work. On the basis of various parameter settings, graphical illustrations of the model are presented showing the authenticity of the analytical results and complex aspects of the phenomenon. The paper concludes with a brief summary of the study and important insights for future research.

CLC number: 60G51, 60H10, 92D30

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AIMS Mathematics
Pages 20312-20345

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Cite this article:
Tahir H, Din A, Khan WA, et al. Numerical investigation of a wireless sensor network epidemic model with α-stable noise: A case study. AIMS Mathematics, 2025, 10(9): 20312-20345. https://doi.org/10.3934/math.2025908

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Received: 01 July 2025
Revised: 27 August 2025
Accepted: 29 August 2025
Published: 05 September 2025
©2025 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)