Open AccessModels of group poisson flows in telecommunica-tion traffic control
Author(s) -
B. Ya. Likhttsinder,
Yulia O. Bakai
Publication year - 2020
Publication title -
vestnik samarskogo gosudarstvennogo tehničeskogo universiteta. seriâ: tehničeskie nauki/vestnik samarskogo gosudarstvennogo tehničeskogo universiteta. seriâ, tehničeskie nauki
Language(s) - English
Resource type - Journals
eISSN - 2712-8938
pISSN - 1991-8542
DOI - 10.14498/tech.2020.3.5
Subject(s) - poisson distribution , queueing theory , queue , computer science , traffic flow (computer networking) , interval (graph theory) , flow (mathematics) , channel (broadcasting) , layered queueing network , group (periodic table) , multiplexing , perspective (graphical) , computer network , mathematics , telecommunications , statistics , physics , geometry , combinatorics , quantum mechanics , artificial intelligence
The lack of effectiveness of the use of models of self-similar processes to the analysis of queues telecommunications systems is presented. The evolution of the flow models managed by Markovs chain is considered. The specifics of the use of Markovs flows as models of telecommunications traffic systems are considered. Models of single-channel queueing systems with input flows that have an arbitrary correlation are presented. Generalizations of the Khinchin-Pollaczek formula are given for these systems. The perspective of the application of interval methods developed by the author for queue analysis in queueing systems with correlated input flows is shown. It is suggested to use the group Poisson extraordinary flow as a model of telecommunication traffic. Interval characteristics of the given flows are reviewed and the prospects of their application are shown. The issues of multiplexing these flows during processing in queueing systems are considered. It is demonstrated that the resulting flow is also a group Poisson flow when summing up several group Poisson flows. The conclusions are confirmed by the simulation modeling results. The examples show the validity of such models to the characteristics of real video traffic flows.