Markovian Characterisation of H.264/SVC Scalable Video

Authors:
Dieter Fiems;Veronique Inghelbrecht;Bart Steyaert;Herwig Bruneel
Affiliations:
SMACS Research Group Department of Telecommunications and Information Processing, Ghent University, Gent, Belgium 9000;SMACS Research Group Department of Telecommunications and Information Processing, Ghent University, Gent, Belgium 9000;SMACS Research Group Department of Telecommunications and Information Processing, Ghent University, Gent, Belgium 9000;SMACS Research Group Department of Telecommunications and Information Processing, Ghent University, Gent, Belgium 9000
Venue:
ASMTA '08 Proceedings of the 15th international conference on Analytical and Stochastic Modeling Techniques and Applications
Year:
2008

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Abstract

In this paper, a multivariate Markovian traffic model is proposed to characterise H.264/SVC scalable video traces. Parametrisation by a genetic algorithm results in models with a limited state space which accurately capture both the temporal and the inter-layer correlation of the traces. A simulation study further shows that the model is capable of predicting performance of video streaming in various networking scenarios.