Modeling internet traffic

OData support
Supervisor:
Dr. Telek Miklós
Department of Networked Systems and Services

Markov arrival processes (MAPs) are used extensively in traffic modeling.

Consequently a wide variety of fitting procedures have been developed.

Most of these however are computationally demanding or not general enough.

To resolve this problem, a specific type two-step procedure have been made,

in which a phase-type distribution (PH) is fitted to static parameters

(to distribution or moments of arrival intervals) in the first step, then,

in the second step a MAP is generated from this PH, with fitting to dynamic parameters (autocorrelation, joint moments).

A general problem of these methods is that it may severely restrict the attainable range of dynamic parameters.

In this thesis I present an optimization method, that aims at providing a favorable starting point for the second step,

by using equivalent transformations of the PH that was produced by the first step.

During the transformations, the method maximizes a chosen goal function.

In this work I examine a couple of goal functions, comparing them with an other PH transformation method developed before.

I evaluate the results and mention a few possible directions of improvement.

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