Identifying Long-range Dependent Network Traffic through Autocorrelation Functions

For over a decade researchers have been reporting the impact of self-similar long-range dependent network traffic. Long-range dependence (LRD) is of great significance in traffic engineering problems such as measurement, queuing strategy, buffer sizing and admission and congestion control. In this research, in order to determine the existence of LRD, we apply three different robust versions of the autocorrelation function (ACF), namely weighted ACF (WACF), trimmed ACF (TACF) and variance-ratio of differences and sums, known as the D/S variance estimator (DACF), in conjunction with the sample ACF (which is moment based). Here we define the moment based ACF as MACF. In telecommunications, LRD traffic defines that a similar pattern of traffic persists for a longer span of time. Through ACF, it is possible to detect how long the traffic lasts. The aim of this research is to investigate the performance of ACF in identifying the existence of LRD traffic.

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