Pitfalls in long range dependence testing and estimation

Author

Molnar, Stephen ; Dang, Trang Dinh

Author_Institution

Dept. of Telecommun. & Telematics, Budapest Univ. of Technol. & Econ., Hungary

Volume

1

fYear

2000

fDate

2000

Firstpage

662

Abstract

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

Keywords

asynchronous transfer mode; fractals; packet switching; parameter estimation; statistical analysis; telecommunication networks; telecommunication traffic; ATM network; Hurst parameter estimation; LRD traffic modeling; level shifts; long range dependence estimation; long range dependence testing; measured traffic traces; nonstationary effects; packet networks; periodogram; polynomial trends; self-similar processes; simulation; traffic analysis; Electronic mail; High-speed networks; Intelligent networks; Laboratories; Parameter estimation; Power generation economics; Telecommunication traffic; Telematics; Testing; Traffic control;

fLanguage

English

Publisher

ieee

Conference_Titel

Global Telecommunications Conference, 2000. GLOBECOM '00. IEEE

Conference_Location

San Francisco, CA

Print_ISBN

0-7803-6451-1

Type

conf

DOI

10.1109/GLOCOM.2000.892099

Filename

892099