Markovian Modeling of Real Data Traffic: Heuristic Phase Type and MAP Fitting of Heavy Tailed and Fractal Like Samples
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In order to support the effective use of telecommunication infrastructure, the “random” behavior of traffic sources has been studied since the early days of telephony. Strange new features, like fractal like behavior and heavy tailed distributions were observed in high speed packet switched data networks in the early ’90s. Since that time a fertile research aims to find proper models to describe these strange traffic features and to establish a robust method to design, dimension and operate such networks.
In this paper we give an overview of methods that, on the one hand, allow us to capture important traffic properties like slow decay rate, Hurst parameter, scaling factor, etc., and, on the other hand, makes possible the quantitative analysis of the studied systems using the effective analysis approach called matrix geometric method.
The presentation of this analysis approach is associated with a discussion on the properties and limits of Markovian fitting of the typical non- Markovian behavior present in telecommunication networks.
KeywordsPartition Function Arrival Process Fractional Brownian Motion Interarrival Time Haar Wavelet
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