Bandwidth Control Algorithm on YouTube Video Traffic in Broadband Network

Authors

  • Murizah Kassim Faculty of Electrical Engineering, Universiti Teknologi MARA, 40450 UiTM Shah Alam, Selangor, Malaysia.
  • Aini Azmi 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.
  • Mat Ikram Yusof 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.
  • Azlina Idris Faculty of Electrical Engineering, Universiti Teknologi MARA, 40450 UiTM Shah Alam, Selangor, Malaysia.

Keywords:

Bandwidth Control, Cumulative Distribution Function, Eeibull, Extreme Value, Maximum Likelihood Estimator, Video Traffic Model, Youtube,

Abstract

This paper presents an analysis of YouTube video traffic and fitted to best distribution traffic model to control bandwidth usage in a broadband network. The study scope comprised of collections of inbound YouTube video traffic for 7 days with the time-interval of each day is 3 hours. The broadband network is supported at 10Gbps line speed to Wide Area Network (WAN). The objective of this research is to characterize YouTube video traffic on broadband network, to fit the original traffic to best traffic model and bandwidth control algorithm called Policing and Shaping is developed based on time based threshold for 0.5Gbps at night and 1.0Gbps in day time. Performance shows the bandwidth controlled as bandwidth save, reduced traffic burst and processing time. Results present benefits of the developed algorithms where enhancement in processing time is 25.25% and the bandwidth is saved about 7.1668Mbps with Policing algorithms. Shaping algorithm process presents performance of processing time is increased up to 55.26% and the bandwidth is saved for about 25.548Mbps. Results also present best Cumulative Distribution Functions (CDF) traffic model using Maximum Likelihood Estimator (MLE) technique four best traffic models is identified which are Extreme Value, Weibull, Normal and Rician traffic model. Among the four, Weibull shown as the best fitted model that presents value of MLE=-1178.4 with the Scale α=9.49411e+08 and Shape β=2.81324 for 2 parameters traffic modeling. Research benefits in the development of design algorithm for Network Quality of Services (QoS) especially for bandwidth control and performance.

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Published

2018-02-05

How to Cite

Kassim, M., Azmi, A., Ab.Rahman, R., Yusof, M. I., Mohamad, R., & Idris, A. (2018). Bandwidth Control Algorithm on YouTube Video Traffic in Broadband Network. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 10(1-5), 151–156. Retrieved from https://jtec.utem.edu.my/jtec/article/view/3647

Issue

Vol. 10 No. 1-5: Breakthrough To Excellence in Communication and Computer Engineering II

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Articles

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