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

机译:使用概率分布仿真学术计算机网络 - 校园网的案例研究

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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.
机译:随着技术进步,计算机网络变得越来越复杂。因此,计算机网络的安装变得更加复杂和昂贵。因此,现有或计划网络的许多参数,例如要求,限制和性能通过模拟器建模。因此,可以在时间和成本方面省去。校园网络是通过整合许多局域网来建立的网络。本研究的目的是通过模拟器模拟具有一般日常行为模式的校园网络。研究中使用的数据从Siirt University实时收集。根据网络流量,网络在工作时间的日常行为分为四个单独的时间间隔,并考虑到文献中的类似研究。识别在每个时区中模拟传入/输出分组的传输时间的最合适的分布。与以模型校园网络进行的先前研究相比,结果表明了结果。同时,识别模型网络日常传入/传出流量的最通用分布。最佳模型的分布被识别为TCP分组的逻辑正式分布以及UDP分组的广义帕吻码分布。通过使用Kolmogorov-Smirnov和Chi平方测试来确定分布的兼容性。

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