Video Traffic Modeling using Kolmogorov Smirnov Analysis in Broadband Network

Authors

  • Murizah Kassim Faculty of Electrical Engineering, Universiti Teknologi MARA, 40450 UiTM Shah Alam, Selangor, Malaysia.
  • Rafidah Samsuri Faculty of Electrical Engineering, Universiti Teknologi MARA, 40450 UiTM Shah Alam, Selangor, Malaysia.
  • Mat Ikram Yusof Faculty of Electrical Engineering, Universiti Teknologi MARA, 40450 UiTM Shah Alam, Selangor, Malaysia.
  • Ruhani Ab Rahman Faculty of Electrical Engineering, Universiti Teknologi MARA, 40450 UiTM Shah Alam, Selangor, Malaysia.
  • Naimah Mat Isa Faculty of Electrical Engineering, Universiti Teknologi MARA, 40450 UiTM Shah Alam, Selangor, Malaysia.
  • Roslina Mohamad Faculty of Electrical Engineering, Universiti Teknologi MARA, 40450 UiTM Shah Alam, Selangor, Malaysia.
  • Mahamod Ismail Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia 43600 UKM Bangi, Selangor, Malaysia.

Keywords:

Video Traffic Modeling, Quality of Service, Kolmogorov Smirnov Analysis, Broadband Network,

Abstract

Video Traffic utilization is one of the major issues for Quality of Service (QoS) for network traffic especially in broadband network. Most network administrators are looking at providing best QoS and reliable traffic performances especially on video traffic. Analysis on recent trend and modeling video traffic activity is a crucial task in providing better bandwidth usage. This research presents an analysis on video network traffic in a Broadband Network in Malaysia. Real data from a telecommunications service company based for Business and Home network are collected. Traffic characterization is analyzed and new traffic parameters and model are presented. Goodness of fit (GoF) and Kolmogorov Smirnov (KS) test is used to fit the real traffic in getting the best Traffic distribution model. Results present four top video used in the network traffic which are You Tube, MPEG, TV on Streamyx and Dailymotion using standard video protocol. Fitted traffics presents Pareto model is best fitted on video traffic. Generalized Pareto (GP) with Empirical Cumulative Distribution function (CDF) distribution is identified as the best distribution model. The fitted Generalized Pareto model was identified based on lower Kolmogorov-Smirnov (KS) value and higher probability value (p-value). Test statistics for four particular distribution results at 5% level significance. GP characterization presents three important parameters which are shape, scale and location. A new mathematical formulation is derived based on control parameters gathered for future rate limiting algorithms

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Published

2016-09-01

How to Cite

Kassim, M., Samsuri, R., Yusof, M. I., Ab Rahman, R., Mat Isa, N., Mohamad, R., & Ismail, M. (2016). Video Traffic Modeling using Kolmogorov Smirnov Analysis in Broadband Network. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 8(6), 49–53. Retrieved from https://jtec.utem.edu.my/jtec/article/view/1244

Issue

Vol. 8 No. 6: Emerging Technologies in Communication and Computer Engineering for Smart City Applications II

Section

Articles

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