Analytical Optimal Control of Delayed Worm Propagation Model in Heterogeneous IoT Systems
This paper presents a mathematical model for worm propagation, where infectivity is influenced by latency within heterogeneous Internet of Things (IoT) systems. The model incorporates the heterogeneity of susceptible-exposed-infected-recovered (SEIR) compartments and considers the varying negative i...
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| Format: | Article |
| Language: | English |
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IEEE
2025-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10960516/ |
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| author | B. S. N. Murthy V. Madhusudanan M. N. Srinivas L. Guerrini Anwar Zeb Nhu-Ngoc Dao Sungrae Cho |
| author_facet | B. S. N. Murthy V. Madhusudanan M. N. Srinivas L. Guerrini Anwar Zeb Nhu-Ngoc Dao Sungrae Cho |
| author_sort | B. S. N. Murthy |
| collection | DOAJ |
| description | This paper presents a mathematical model for worm propagation, where infectivity is influenced by latency within heterogeneous Internet of Things (IoT) systems. The model incorporates the heterogeneity of susceptible-exposed-infected-recovered (SEIR) compartments and considers the varying negative impacts of worms spread across these groups. Sufficient conditions for the persistence of worm propagation are derived using the optimistic equilibrium point. By selecting latency as a bifurcation parameter, the study reveals a specific latency value critical for maintaining worm propagation’s stability in these systems. The normal form approach and central manifold theory are employed to analyze the direction and stability of Hopf bifurcation. Furthermore, this study addresses strategies for mitigating the spread of worms by employing best practices to minimize the number of devices exposed and infected across systems. We analyze the effects of control measures, such as vaccination and treatment, which should be applied promptly during a worm proliferation outbreak and gradually scaled down over time as the outbreak decreases. Numerical findings expose that latency significantly impacts system stability, however, optimally managing the latency below a deterministic threshold may maintain system stabilization. |
| format | Article |
| id | doaj-art-3ea3e1e0321540a1bd5da061e49b87bb |
| institution | OA Journals |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-3ea3e1e0321540a1bd5da061e49b87bb2025-08-20T02:18:24ZengIEEEIEEE Access2169-35362025-01-0113633496336610.1109/ACCESS.2025.355914610960516Analytical Optimal Control of Delayed Worm Propagation Model in Heterogeneous IoT SystemsB. S. N. Murthy0https://orcid.org/0000-0002-8588-1876V. Madhusudanan1https://orcid.org/0000-0002-9148-1350M. N. Srinivas2L. Guerrini3https://orcid.org/0000-0001-8489-5531Anwar Zeb4Nhu-Ngoc Dao5https://orcid.org/0000-0003-1565-4376Sungrae Cho6https://orcid.org/0000-0003-1879-688XDepartment of Mathematics, Aditya University, Surampalem, Andhra Pradesh, IndiaDepartment of Mathematics, S. A. Engineering College, Chennai, Tamil Nadu, IndiaDepartment of Mathematics, School of Advanced Sciences, Vellore Institute of Technology, Vellore, Tamil Nadu, IndiaDepartment of Management, Polytechnic University of Marche, Ancona, ItalyDepartment of Mathematics, COMSATS University Islamabad, Abbottabad, Khyber Pakhtunkhwa, PakistanDepartment of Computer Science and Engineering, Sejong University, Seoul, South KoreaSchool of Computer Science and Engineering, Chung-Ang University, Seoul, South KoreaThis paper presents a mathematical model for worm propagation, where infectivity is influenced by latency within heterogeneous Internet of Things (IoT) systems. The model incorporates the heterogeneity of susceptible-exposed-infected-recovered (SEIR) compartments and considers the varying negative impacts of worms spread across these groups. Sufficient conditions for the persistence of worm propagation are derived using the optimistic equilibrium point. By selecting latency as a bifurcation parameter, the study reveals a specific latency value critical for maintaining worm propagation’s stability in these systems. The normal form approach and central manifold theory are employed to analyze the direction and stability of Hopf bifurcation. Furthermore, this study addresses strategies for mitigating the spread of worms by employing best practices to minimize the number of devices exposed and infected across systems. We analyze the effects of control measures, such as vaccination and treatment, which should be applied promptly during a worm proliferation outbreak and gradually scaled down over time as the outbreak decreases. Numerical findings expose that latency significantly impacts system stability, however, optimally managing the latency below a deterministic threshold may maintain system stabilization.https://ieeexplore.ieee.org/document/10960516/Internet of Thingstime delayHopf bifurcationoptimal control |
| spellingShingle | B. S. N. Murthy V. Madhusudanan M. N. Srinivas L. Guerrini Anwar Zeb Nhu-Ngoc Dao Sungrae Cho Analytical Optimal Control of Delayed Worm Propagation Model in Heterogeneous IoT Systems IEEE Access Internet of Things time delay Hopf bifurcation optimal control |
| title | Analytical Optimal Control of Delayed Worm Propagation Model in Heterogeneous IoT Systems |
| title_full | Analytical Optimal Control of Delayed Worm Propagation Model in Heterogeneous IoT Systems |
| title_fullStr | Analytical Optimal Control of Delayed Worm Propagation Model in Heterogeneous IoT Systems |
| title_full_unstemmed | Analytical Optimal Control of Delayed Worm Propagation Model in Heterogeneous IoT Systems |
| title_short | Analytical Optimal Control of Delayed Worm Propagation Model in Heterogeneous IoT Systems |
| title_sort | analytical optimal control of delayed worm propagation model in heterogeneous iot systems |
| topic | Internet of Things time delay Hopf bifurcation optimal control |
| url | https://ieeexplore.ieee.org/document/10960516/ |
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