Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/30323
Title: Detection of fractal breakdowns by the holder filter in the novel real-time traffic pattern detector for the internet applications
Authors: Lin, WWK
Dillon, T
Wong, AKY
Keywords: Internet
Filtering theory
Fractals
Pattern recognition
Telecommunication traffic
Time series
Issue Date: 2007
Publisher: IEEE
Source: 2007 Inaugural IEEE International Conference on Digital Ecosystems and Technologies : 21-23 February 2007, venue: Cairns, Australia, p. 473-478 How to cite?
Abstract: The novel real-time traffic pattern detector (RTPD) proposed identifies the Internet traffic pattern on the fly. Firstly it determines if a time series aggregate is stationary. Secondly it confirms if the aggregate exhibits short-range dependence (SRD) or long-range dependence (LRD). Thirdly it detects if the smooth system operation has suddenly become irregular and chaotic. This detection is achieved by computing the instantaneous value of the Holder exponent that has a (0,1) range to accommodate different degrees fractality. A smooth performance distribution such as a time series may embed a varying fractality at different times due to the system dynamics. If the Holder exponent has wandered outside the (0,1) region, fractal breakdown has occurred. The capability of detecting such breakdowns by a real-time application enables it to avoid sudden failure. This feature is of importance to the reliability of digital ecosystems, which reside on the Internet.
URI: http://hdl.handle.net/10397/30323
ISBN: 1-4244-0470-3
1-4244-0470-3 (E-ISBN)
DOI: 10.1109/DEST.2007.372021
Appears in Collections:Conference Paper

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