Enhanced Statistical Modelling For Variable Bit Rate Video Traffic Generated From Scalable Video Codec

Ahmadpour, Sima (2016) Enhanced Statistical Modelling For Variable Bit Rate Video Traffic Generated From Scalable Video Codec. PhD thesis, Universiti Sains Malaysia.

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    Abstract

    Mereka bentuk rangkaian yang berkesan dan berprestasi tinggi memerlukan pencirian dan pemodela punca trafik rangkaian yang tepat. Tesis ini menyediakan satu kajian tentang penghantaran, pemodelan dan analisis video variable bit rate (VBR) yang merupakan asas reka bentuk protokol dan penggunaan rangkaian yang cekap dalam penghantaran video. Dengan ini, satu model trafik video VBR yang dikodkan oleh scalable video codec (SVC) telah dicadangkan. EDAR (1) dapat menjana siri video dengan tepat di mana siri ini bersifat seakan-akan trafik video yang sebenar. Model ini telah disahkan dengan menggunakan pelbagai statistik untuk membandingkan jejak simulasi da asal. Pengesahan ini telah dilakukan melalui pengukuran grafik (Quantile-Quantile plot) dan statistik (Kolmogorov-Smirnov, Jumlah Ralat Berganda (SSE), dan Kecekapan Relatif (RE)) serta pengesahan secara bersilang. Designing an effective and high performance network requires an accurate characterization and modelling of the network traffic. This work involves the analysis and modelling of the Variable Bit Rate (VBR) of video traffic, usually described as the core of the protocol design and efficient network utilization for video transmissions. In this context, an Enhanced Discrete Autoregressive (EDAR (1)) model for the VBR video traffic model, which is encoded by a Scalable Video Codec (SVC), has been proposed. The EDAR (1) model was able to accurately generate video sequences, which are very close to the actual video traffic in terms of accuracy. The model is validated using statistical tests in order to compare simulated and original traces. The validation is done using graphical (Quantile-Quantile plot) and statistical measurements (Kolmogorov-Smirnov, Sum of Squared Error, and Relative Efficiency), as well as cross-validation.

    Item Type: Thesis (PhD)
    Subjects: Q Science > QA Mathematics > QA75.5-76.95 Electronic computers. Computer science
    Divisions: Pusat Pengajian Sains Komputer (School of Computer Sciences) > Thesis
    Depositing User: Mr Noorazilan Noordin
    Date Deposited: 25 Jan 2017 12:30
    Last Modified: 14 Apr 2017 20:18
    URI: http://eprints.usm.my/id/eprint/31806

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