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Erschienen in: Automatic Control and Computer Sciences 8/2022

01.12.2022

Immunization of Complex Networks: System of Differential Equations and Dynamic Variation

verfasst von: E. Yu. Pavlenko, A. D. Fatin

Erschienen in: Automatic Control and Computer Sciences | Ausgabe 8/2022

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Abstract

This article discusses new approaches to constructing immunization models of modern computer networks, with a central focus on a P2P static model, a compartmental model, and models of dynamic representation of alternating and growing graphs. The models are considered in terms of their main advantages and areas of application, specifics of application, and novelty.
Literatur
6.
Zurück zum Zitat Prakash, B.A., Tong, H., Valler, N., Faloutsos, M., and Faloutsos, C., Virus propagation on time-varying networks: Theory and immunization algorithms, Machine Learning and Knowledge Discovery in Databases. ECML PKDD 2010, Balcázar, J.L., Bonchi, F., Gionis, A., and Sebag, M., Eds., Lecture Notes in Computer Science, vol. 6323, Berlin: Springer, 2010, pp. 99–114. https://doi.org/10.1007/978-3-642-15939-8_7CrossRef Prakash, B.A., Tong, H., Valler, N., Faloutsos, M., and Faloutsos, C., Virus propagation on time-varying networks: Theory and immunization algorithms, Machine Learning and Knowledge Discovery in Databases. ECML PKDD 2010, Balcázar, J.L., Bonchi, F., Gionis, A., and Sebag, M., Eds., Lecture Notes in Computer Science, vol. 6323, Berlin: Springer, 2010, pp. 99–114. https://​doi.​org/​10.​1007/​978-3-642-15939-8_​7CrossRef
Metadaten
Titel
Immunization of Complex Networks: System of Differential Equations and Dynamic Variation
verfasst von
E. Yu. Pavlenko
A. D. Fatin
Publikationsdatum
01.12.2022
Verlag
Pleiades Publishing
Erschienen in
Automatic Control and Computer Sciences / Ausgabe 8/2022
Print ISSN: 0146-4116
Elektronische ISSN: 1558-108X
DOI
https://doi.org/10.3103/S0146411622080144

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