MODELING DATA TRANSMISSION SYSTEMS USING MODERN INFORMATION TECHNOLOGIES

When modeling data transmission systems for various purposes, including computer and telecommunication networks, both components of mathematical modeling are widely used. These are simulation modeling and analytical modeling based on queuing theory. At the same time, researchers can always compare the results obtained by means of simulation and analytical modeling. From modern technologies of simulation modeling, one can single out the IT GURU Academic Edition technologies, represented by the Opnet Modeler and Riverbed Modeler software products with powerful graphical editors. Graphic editors allow you to create simulation models of data transmission systems of any complexity, and launch and run their models to obtain statistics of the main performance indicators of these systems. Comparison of the simulation results with the results of queuing systems (QS) of the G/G/1 type makes it possible to assess the adequacy of those and other mathematical models. This article summarizes the results of the author’s publications on G/G/1 systems based on time-shifted distribution laws such as exponential, hyperexponential, and Erlang distribution. Thus, these distribution laws for the random variables used provide the coefficients of variation less than, equal or greater than one. This fact is important from the point of view of the queuing theory, because the average delay of claims in the system directly depends on the coefficients of variations in the time intervals for the arrival and servicing of claims.