Smoothing the Sample Autocorrelation of Long-Range-Dependent Traffic

摘要

This paper depicts our work in smoothing the sample autocorrelation function (ACF) of traffic. The experimental results exhibit that the sample ACF of traffic may be smoothed by the way of average. In addition, the results imply that the sum of sample ACFs of traffic convergences. Considering that the traffic data used in this research is long-range dependent (LRD), the latter may be meaningful for the theoretical research of LRD traffic.