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Article

Self-Similar Markovian Sources

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Faculty of Automatic Control, Electronics and Computer Science, Department of Distributed Systems and Informatic Devices, Silesian University of Technology, Akademicka 16, 44-100 Gliwice, Poland
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Institute of Theoretical and Applied Informatics, Polish Academy of Sciences, Bałtycka 5, 44-100 Gliwice, Poland
*
Author to whom correspondence should be addressed.
Appl. Sci. 2020, 10(11), 3727; https://doi.org/10.3390/app10113727
Received: 14 April 2020 / Revised: 7 May 2020 / Accepted: 25 May 2020 / Published: 28 May 2020
(This article belongs to the Section Electrical, Electronics and Communications Engineering)
Markov queueing models are a powerful tool to evaluate the performance of computer networks and have been used in telecommunication studies for over 100 years. To apply them to the evaluation of the modern Internet, we should not only adapt them to the contemporary network structures but also include a description of the complex stochastic patterns (self-similarity and long-range dependance) of transmitted flows. We examine the features of two Markov models of an almost self-similar process, keeping in mind the modeling of Internet traffic. We have found that the obtained results are comparable with those achieved using a well-known generator of self-similar traffic. View Full-Text
Keywords: long-range dependence (LRD); self-similarity; traffic sources; Hurst parameter; Markov models long-range dependence (LRD); self-similarity; traffic sources; Hurst parameter; Markov models
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MDPI and ACS Style

Domański, A.; Domańska, J.; Filus, K.; Szyguła, J.; Czachórski, T. Self-Similar Markovian Sources. Appl. Sci. 2020, 10, 3727. https://doi.org/10.3390/app10113727

AMA Style

Domański A, Domańska J, Filus K, Szyguła J, Czachórski T. Self-Similar Markovian Sources. Applied Sciences. 2020; 10(11):3727. https://doi.org/10.3390/app10113727

Chicago/Turabian Style

Domański, Adam, Joanna Domańska, Katarzyna Filus, Jakub Szyguła, and Tadeusz Czachórski. 2020. "Self-Similar Markovian Sources" Applied Sciences 10, no. 11: 3727. https://doi.org/10.3390/app10113727

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