Informatics and Applications
2016, Volume 10, Issue 2, pp 98-106
MULTIVARIATE FRACTIONAL LEVY MOTION AND ITS APPLICATIONS
Abstract
Since the beginning of the 1990s, many empirical studies of real telecoomunication systems traffic have been conducted. It was found that traffic has some specific properties, which are different from common voice traffic, namely, it has the properties of self-similarity and long-range dependence and the distribution of loading size from one source has heavy tails. Some new models have been constructed, where these features were captured. Brownian fractional motion and ŕ-stable Levy motion are the well-known examples. But both of these models do not have all of the above properties. More complicated models have been proposed using some combination of these ones. In particular, the authors have proposed a variant of univariate fractional Levy motion. This paper considers a multivariate analog of fractional Levy motion. This process is multivariate fractional Brownian motion with random change of time, where random change of time is Levy motion with one-sided stable distributions.
The properties of this process are investigated and it is proven that it is self-similar and has stationary increments.
Next, it is shown that the coordinates of one-dimensional sections of this process have the distributions which are not stable. But asymptotic of tails for these distributions is the same as for the stable ones. This model is applied to analyze heterogeneous traffic and to get a lower asymptotic bound of the probability of overflow of at least one buffer. There are other possible applications.
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[+] About this article
Title
MULTIVARIATE FRACTIONAL LEVY MOTION AND ITS APPLICATIONS
Journal
Informatics and Applications
2016, Volume 10, Issue 2, pp 98-106
Cover Date
2016-05-30
DOI
10.14357/19922264160212
Print ISSN
1992-2264
Publisher
Institute of Informatics Problems, Russian Academy of Sciences
Additional Links
Key words
fractional Brownian motion; ŕ-stable subordinator; self-similar processes; buffer overflow probability
Authors
Yu. S. Khokhlov
Author Affiliations
Department of Mathematical Statistics, Faculty of Computational Mathematics and Cybernetics, M.V. Lomonosov Moscow State University, 1-52 Leninskiye Gory, Moscow 119991, GSP-1, Russian Federation
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