Abstract
Semi-Markov processes (SMPs) are widely used to model various types of data traffic in communication networks. Also, efficient and reliable analysis techniques are available. In this paper, we consider several present methods of deriving the parameters of a discrete-time semi-Markov process from given H.264 video traces in order to model the original traffic adequately. We take the distribution of frame sizes and the autocorrelation of both the original trace and the resulting SMP model into account as key quality indicators. We propose a new evolutionary optimization approach using genetic programming, which is able to significantly improve the accuracy of semi-Markov models of video traces and, at the same time, requires a smaller number of states.
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Kempken, S., Luther, W. (2007). Modeling of H.264 High Definition Video Traffic Using Discrete-Time Semi-Markov Processes. In: Mason, L., Drwiega, T., Yan, J. (eds) Managing Traffic Performance in Converged Networks. ITC 2007. Lecture Notes in Computer Science, vol 4516. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72990-7_8
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DOI: https://doi.org/10.1007/978-3-540-72990-7_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72989-1
Online ISBN: 978-3-540-72990-7
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