This thesis concerns measuring, understanding and modelling Internet traffic. We first study the origins of the statistical properties of Internet traffic, in particular its scaling behaviour, and propose a constructive model of packet traffic with physically motivated parameters. We base our analysis on a large amount of empirical data measured on different networks, and use a so called semi-experimental approach to isolate certain features of traffic we seek to model. These results lead to the choice of a particular Poisson cluster process, known as Bartlett-Lewis point process, for a new packet traffic model. This model has a small number of parameters with simple networking meaning, and is mathematically tractable. It allows us to gain valuable insight on the underlying mechanisms creating the observed statistics. / In practice, Internet traffic measurements are limited by the very large amount of data generated by high bandwidth links. This leads us to also investigate traffic sampling strategies and their respective inversion methods. We argue that the packet sampling mechanism currently implemented in Internet routers is not practical when one wants to infer the statistics of the full traffic from partial measurements. We advocate the use of flow sampling for many purposes. We show that such sampling strategy is much easier to invert and can give reasonable estimates of higher order traffic statistics such as distribution of number of packets per flow and spectral density of the packet arrival process. This inversion technique can also be used to fit the Bartlett-Lewis point process model from sampled traffic. / We complete our understanding of Internet traffic by focusing on the small scale behaviour of packet traffic. To do so, we use data from a fully instrumented Tier-1 router and measure the delays experienced by all the packets crossing it. We present a simple router model capable of simply reproducing the measured packet delays, and propose a scheme to export router performance information based on busy periods statistics. We conclude this thesis by showing how the Bartlett-Lewis point process can model the splitting and merging of packet streams in a router.
| Identifer | oai:union.ndltd.org:ADTP/245083 |
| Creators | Hohn, Nicolas |
| Source Sets | Australiasian Digital Theses Program |
| Language | English |
| Detected Language | English |
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