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A Multigraph-Defined Distribution Function in a Simulation Model of a Communication Network.

Slobodan Miletic1, Ivan Pokrajac1, Karelia Pena-Pena2

  • 1Electronic Systems Department, Military Technical Institute, 11000 Belgrade, Serbia.

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Summary
This summary is machine-generated.

This study introduces a multigraph-based method for precisely modeling data exchange in communication networks (CNs). This approach enhances the accuracy of simulation models for integrated telecommunications and computer networks (ITCN) by defining traffic distribution functions.

Keywords:
adjacency matrixcommunication networkdistribution functionmultigraphsnetwork simulationnetwork traffic

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Area of Science:

  • Computer Science
  • Network Engineering
  • Applied Mathematics

Background:

  • Accurate modeling of network traffic is crucial for designing and simulating communication networks (CNs).
  • Existing methods struggle to precisely define the mathematical model for data distribution in complex integrated telecommunications and computer networks (ITCN).

Purpose of the Study:

  • To develop a novel mathematical method for defining the time-dependent distribution function of data exchange in special-purpose communication networks.
  • To improve the accuracy of simulation models for integrated telecommunications and computer networks (ITCN).

Main Methods:

  • Utilized multigraphs to represent data exchange processes over time.
  • Formed adjacency matrices for each multigraph to capture data distribution characteristics.
  • Applied matrix estimation techniques to define the mathematical distribution function values.

Main Results:

  • The multigraph approach effectively displays data distribution time and quantity as operational procedures.
  • The method allows for a more accurate mathematical description of real-world network traffic.
  • Enabled precise definition of data generation and exchange patterns.

Conclusions:

  • Multigraphs provide a robust framework for mathematically defining data distribution functions in communication networks.
  • This method significantly enhances the fidelity of simulation models for ITCN.
  • The proposed technique offers a more accurate representation of network traffic dynamics.