Statistical Analysis of Video Frame Size Distribution Originating from Scalable Video Codec (SVC). (19th March 2017)

• Record Type: Journal Article
• Authors: Ahmadpour, Sima; Wan, Tat-Chee; Toghrayee, Zohreh; HematiGazafi, Fariba
• Other Names: Cordero Alicia Academic Editor.
• Is Part Of: Complexity. Volume 2017(2017)
• Publication Date: 2017-03-19
• Subjects: Chaotic behavior in systems -- Periodicals; Complexity (Philosophy) -- Periodicals; 003
• DOI: 10.1155/2017/8098574
• Languages: English
• ISSNs: 1076-2787

Abstract

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.