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Volume 2017 (2017), Article ID 8098574, 12 pages
Research Article

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

1Department of Electrical, IT & Computer Sciences, Islamic Azad University, Qazvin Branch, Qazvin, Iran
2National Advanced IPv6 Center, Universiti Sains Malaysia, 11800 Penang, Malaysia
3School of Computer Sciences, Universiti Sains Malaysia (USM), 11800 Penang, Malaysia
4Central Bank of the Islamic Republic of Iran, Tehran, Iran

Correspondence should be addressed to Sima Ahmadpour

Received 30 June 2016; Accepted 15 January 2017; Published 19 March 2017

Academic Editor: Alicia Cordero

Copyright © 2017 Sima Ahmadpour et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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.