Automatic scaling range selection for long-range dependent network traffic

Author

Xia, Xiangdong ; Lazarou, Georgios Y. ; Butler, Thomas

Author_Institution

CIMAS/RSMAS, Miami, FL, USA

Volume

9

Issue

10

fYear

2005

Firstpage

954

Lastpage

956

Abstract

In this paper, we present an adaptive search algorithm to automatically select the scaling range in the wavelet-based Hurst parameter estimation method. This algorithm is recursive and adaptive in nature, and it can select a scaling range consistent with human visual selection. In addition, it can be easily extended to automatically find the (approximately) linear regions of any curve. We tested our algorithm on 13 NLANR network traffic traces. The results show that our algorithm works well for the cases of monofractal traffic.

Keywords

Internet; computational complexity; greedy algorithms; recursive estimation; search problems; stochastic processes; telecommunication traffic; wavelet transforms; LRD; NLANR; Theil inequality; adaptive search algorithm; automatic scaling range selection; human visual selection; long-range dependent network; monofractal network traffic; recursive algorithm; wavelet-based Hurst parameter estimation method; Humans; Internet; Linear approximation; Parameter estimation; Stochastic processes; Telecommunication traffic; Testing; Traffic control; Velocity measurement; Wavelet coefficients;

fLanguage

English

Journal_Title

Communications Letters, IEEE

Publisher

ieee

ISSN

1089-7798

Type

jour

DOI

10.1109/LCOMM.2005.10013

Filename

1515681