By Topic

Automatic scaling range selection for long-range dependent network traffic

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Xiangdong Xia ; CIMAS/RSMAS, Miami, FL, USA ; Lazarou, G.Y. ; Butler, T.

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.

Published in:

Communications Letters, IEEE  (Volume:9 ,  Issue: 10 )