Does the TES Stitching Function Merely Stitch?
نویسنده
چکیده
Compared to most of the traffic modeling techniques used today, TES (Transform-Expand-Sample) is among the youngest ones. Its basic scheme consists of creating a randomly governed background sequence, smoothing it and finally adapting it to a given marginal distribution, altogether yielding a foreground sequence. In this scheme, the so-called Stitching Function originally is responsible for removing discontinuities coming from using a modulo-1 arithmetic. In this paper it is demonstrated that the Stitching Function in fact is much more powerful as its shape has crucial influence to the visual appearance of the foreground sequence and the autocorrelation function. Using suitable generalized stitching functions is a very simple way to receive simulated sample paths being visually indistinguishable from the original time series. This method is demonstrated for the case of periodic time series as may appear e.g. during measurements of network utilization. Another typical application is the modeling of MPEG frames. Finally, it turns out that this approach could also be useful for simulating self-similar traffic. Thus, this approach allows to model a couple of characteristic features of given traffic in much more detail while still supporting the main advantages of TES, e.g. the analytic calculability of the autocorrelation function.
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تاریخ انتشار 1998