Simulation of Academic Computer Networks Using Probability Distributions: A Case Study in A Campus Network

ALTUNCU M. A. , Gulaglz F. K. , ÖZCAN H. , İLKİN S. , ŞAHİN S.

TEHNICKI VJESNIK-TECHNICAL GAZETTE, vol.28, no.3, pp.1017-1024, 2021 (Journal Indexed in SCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 28 Issue: 3
  • Publication Date: 2021
  • Doi Number: 10.17559/tv-20200224091110
  • Page Numbers: pp.1017-1024
  • Keywords: local area network, network architecture, network statistical analysis, simulation, statistical distributions


Computer networks are becoming more complex with the advances in technology. Hence, the installation of computer networks becomes more complicated and costly. Therefore, many parameters of the existing or planned networks, such as the requirements, limits and performance are modelled through simulators. Thus, it is possible to save both in terms of time and cost. Campus networks are networks that are established by consolidating many local area networks. The aim of this study is to model campus networks which have a general daily behaviour pattern, through simulators. The data used in the study are collected in real time from Siirt University. The daily behaviour of the network in working hours is divided into four separate time intervals according to the network traffic and in consideration of similar studies in the literature. The most appropriate distributions that model the transmission times of the incoming/outgoing packets at each time zone are identified. The results are presented in comparison with the previous studies conducted to model campus networks. At the same time, the most generic distributions that model the daily incoming / outgoing traffic of the network are identified. The distribution that best models the transmission times of the network packets was identified to be the lognormal distribution for TCP packets and the Generalized Pareto distribution for UDP packets. Compatibility of the distributions was determined through the use of Kolmogorov-Smirnov and Chi-Squared tests.