Remote Access Theory of Probability and Mathematical Statistics

Theory of Probability and Mathematical Statistics

ISSN 1547-7363(online) ISSN 0094-9000(print)

Request Permissions   Purchase Content 
 

 

A limit theorem for non-Markovian multi-channel networks under heavy traffic conditions


Author: H. V. Livinska
Translated by: S. Kvasko
Original publication: Teoriya Imovirnostei ta Matematichna Statistika, tom 93 (2015).
Journal: Theor. Probability and Math. Statist. 93 (2016), 113-122
MSC (2010): Primary 60K25, 90B15
DOI: https://doi.org/10.1090/tpms/997
Published electronically: February 7, 2017
Full-text PDF

Abstract | References | Similar Articles | Additional Information

Abstract: Open multi-channel stochastic networks are considered in the paper. The inputs are assumed to be non-homogeneous Poisson flows whose rates depend on time. Service times are random variables whose distribution functions are of the GI-type. A limit theorem for the service process is proved for such a network under heavy traffic conditions. Characteristics of the limit Gaussian process are expressed in an explicit form in terms of the network parameters.


References [Enhancements On Off] (What's this?)


Similar Articles

Retrieve articles in Theory of Probability and Mathematical Statistics with MSC (2010): 60K25, 90B15

Retrieve articles in all journals with MSC (2010): 60K25, 90B15


Additional Information

H. V. Livinska
Affiliation: Department of Applied Statistics, Faculty for Cybernetics, National Taras Shevchenko University, Academician Glushkov Avenue, 4D, Kyiv 03127, Ukraine
Email: livinskaav@gmail.com

DOI: https://doi.org/10.1090/tpms/997
Keywords: Multi-channel queueing networks, diffusion approximation, heavy traffic regime
Received by editor(s): June 16, 2015
Published electronically: February 7, 2017
Additional Notes: This paper was prepared following the talk at the International conference “Probability, Reliability and Stochastic Optimization (PRESTO-2015)” held in Kyiv, Ukraine, April 7–10, 2015
Article copyright: © Copyright 2017 American Mathematical Society