M.Ing. / Recent traffic analyses have shown the existence of long-range dependencies in network traffic, specifically self-similar long-range dependencies. Due to the inability of traditional traffic models to capture these long-range dependencies, new network traffic models were developed that are able to capture it. In this paper we compare three self-similar long-range dependent traffic models, namely the FARIMA model, the wavelet independent Gaussian model and the multifractal wavelet model. We present results on their marginal distributions, their correlation matching to real traffic and their queuing behaviour. We show that the multifractal wavelet model is the best of the three models in all of the test aspects.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:uj/uj:8154 |
| Date | 26 February 2009 |
| Creators | Du Plessis, Adriaan |
| Source Sets | South African National ETD Portal |
| Detected Language | English |
| Type | Thesis |
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