Pitfalls in long range dependence testing and estimation

Measured traffic traces from live packet networks often contain non-stationary effects like level shifts or polynomial trends. In these cases the popular tests for long range dependence (LRD) can result in wrong conclusions and unreliable estimation of the Hurst (1950) parameter. We investigate the implications of these effects on several LRD tests. The use of these results can be utilized to avoid pitfalls in LRD traffic modeling. Our results are supported by both analytical and simulation studies with examples taken from traffic analysis of a live ATM network.