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Informatika i Ee Primeneniya [Informatics and its Applications], 2007, Volume 1, Issue 1, Pages 40–53 (Mi ia119)  

This article is cited in 6 scientific papers (total in 6 papers)

A new method for the probabilistic and statistical analysis of information flows in telecommunication networks

D. A. Batrakovaa, V. Yu. Korolevab, S. Ya. Shorgina

a Institute for Problems of Informatics RAS
b M. V. Lomonosov Moscow State University, Faculty of Computational Mathematics and Cybernetics
Full-text PDF (899 kB) Citations (6)
References:
Abstract: A new method is proposed for the analysis of the stochastic structure of chaotic information flows in convergent telecommunication networks. The proposed method is based on a stochastic model of a telecommunication network which has the form of a superposition of some simple sequential-parallel structures. This model quite naturally generates mixtures of gamma-distributions for the network operation execution time. The parameters of the mixture of gamma-distributions characterize the stochastic structure of chaotic information flows in the network. The problem of statistical estimation of the parameters of gamma-distributions is solved by the EM-algorithm. To trace the variation of the stochastic structure of information flows in time, the EM-algorithm is applied for the moving window. The software for the division of distribution mixtures is developed and documented. The real input data is used. The interpretation of results is given.
Keywords: telecommunication networks; information flows; division of mixes of distributions; method of a moving window; software for division of distribution mixtures.
Document Type: Article
Language: Russian
Citation: D. A. Batrakova, V. Yu. Korolev, S. Ya. Shorgin, “A new method for the probabilistic and statistical analysis of information flows in telecommunication networks”, Inform. Primen., 1:1 (2007), 40–53
Citation in format AMSBIB
\Bibitem{BatKorSho07}
\by D.~A.~Batrakova, V.~Yu.~Korolev, S.~Ya.~Shorgin
\paper A new method for the probabilistic and statistical analysis of information flows in telecommunication networks
\jour Inform. Primen.
\yr 2007
\vol 1
\issue 1
\pages 40--53
\mathnet{http://mi.mathnet.ru/ia119}
Linking options:
  • https://www.mathnet.ru/eng/ia119
  • https://www.mathnet.ru/eng/ia/v1/i1/p40
  • This publication is cited in the following 6 articles:
    1. Morozov E., Pagano M., Peshkova I., Rumyantsev A., “Sensitivity Analysis and Simulation of a Multiserver Queueing System With Mixed Service Time Distribution”, Mathematics, 8:8 (2020), 1277  crossref  isi  scopus
    2. A. V. Lebedev, “Netranzitivnye triplety nepreryvnykh sluchainykh velichin i ikh prilozheniya”, Inform. i ee primen., 13:3 (2019), 20–26  mathnet  crossref
    3. Fedotova I.M., Vaynshtein V.I., Tsibul'skii G.M., Vaynshtein Yu.V., “Renewal Function Under Prefailure Lives Distributed as a Mixture of N Exponential Distributions: Obtaining the Parameters of Mixtures Using the Method of Moments”, J. Mach. Manuf. Reliab., 48:3 (2019), 275–282  crossref  isi  scopus
    4. A. V. Borisov, B. M. Miller, K. V. Siemenikhin, “Filtering of the Markov jump process given the observations of multivariate point process”, Autom. Remote Control, 76:2 (2015), 219–240  mathnet  crossref  isi  elib  elib
    5. V. Yu. Korolev, V. A. Krylov, V. Yu. Kuzmin, “Ustoichivost konechnykh smesei obobschennykh gamma-raspredelenii otnositelno vozmuschenii parametrov”, Inform. i ee primen., 5:1 (2011), 31–38  mathnet
    6. A. V. Bosov, “Zadachi analiza i optimizatsii dlya modeli polzovatelskoi aktivnosti. Chast 1. Analiz i prognozirovanie”, Inform. i ee primen., 5:4 (2011), 40–52  mathnet
    Citing articles in Google Scholar: Russian citations, English citations
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