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Statistical Analysis of Video Frame Size Distribution Originating from Scalable Video Codec (SVC)

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  • Sima Ahmadpour
  • Tat-Chee Wan
  • Zohreh Toghrayee
  • Fariba HematiGazafi

Abstract

Designing an effective and high performance network requires an accurate characterization and modeling of network traffic. The modeling of video frame sizes is normally applied in simulation studies and mathematical analysis and generating streams for testing and compliance purposes. Besides, video traffic assumed as a major source of multimedia traffic in future heterogeneous network. Therefore, the statistical distribution of video data can be used as the inputs for performance modeling of networks. The finding of this paper comprises the theoretical definition of distribution which seems to be relevant to the video trace in terms of its statistical properties and finds the best distribution using both the graphical method and the hypothesis test. The data set used in this article consists of layered video traces generating from Scalable Video Codec (SVC) video compression technique of three different movies.

Suggested Citation

  • Sima Ahmadpour & Tat-Chee Wan & Zohreh Toghrayee & Fariba HematiGazafi, 2017. "Statistical Analysis of Video Frame Size Distribution Originating from Scalable Video Codec (SVC)," Complexity, Hindawi, vol. 2017, pages 1-12, March.
    • Handle: RePEc:hin:complx:8098574
    DOI: 10.1155/2017/8098574
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    References listed on IDEAS

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    1. Nagahara, Yuichi, 1999. "The PDF and CF of Pearson type IV distributions and the ML estimation of the parameters," Statistics & Probability Letters, Elsevier, vol. 43(3), pages 251-264, July.
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    Cited by:

    1. Jinping Liu & Jiezhou He & Zhaohui Tang & Pengfei Xu & Wuxia Zhang & Weihua Gui, 2018. "Characterization of Complex Image Spatial Structures Based on Symmetrical Weibull Distribution Model for Texture Pattern Classification," Complexity, Hindawi, vol. 2018, pages 1-23, December.

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