Investigation of the Properties of the HEAF Estimator Using Simulation Experiments and MPEG-encoded Video Traces

It was discovered that some LAN traffic exhibits self-similar rather than Poisson behaviour and there is ongoing research towards finding and improving suitable estimators which may help to characterize various types of network traffic. Such characterization can be potentially applied for control purposes such as traffic shaping, load balancing, etc. The Hurst exponent is used to measure the intensity of long-range dependence (LRD) in the network traffic. Despite having several existing estimators, LRD analysis is still impeded by the difficulty of actual identification of its intensity. This paper continues work on estimating the Hurst exponent from the autocorrelation function, a so-called HEAF estimator introduced earlier by the authors. It also compares HEAF with a few existing estimators such as wavelet, Higuchi, aggregated variance time (V/T) and rescaled-range (R/S). The simulation studies show that HEAF can be used to capture the LRD in the network traffic if true process is fGn and FARIMA