Informatics and Applications
2016, Volume 10, Issue 2, pp 98106
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 selfsimilarity and longrange 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 ŕstable Levy motion are the wellknown 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 onesided stable distributions.
The properties of this process are investigated and it is proven that it is selfsimilar and has stationary increments.
Next, it is shown that the coordinates of onedimensional 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 98106
Cover Date
20160530
DOI
10.14357/19922264160212
Print ISSN
19922264
Publisher
Institute of Informatics Problems, Russian Academy of Sciences
Additional Links
Key words
fractional Brownian motion; ŕstable subordinator; selfsimilar 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, 152 Leninskiye Gory, Moscow 119991, GSP1, Russian Federation
