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Detection of Fractal Breakdowns by the Novel Real-Time Pattern Detection Model (Enhanced-RTPD+Holder Exponent) for Web Applications

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4 Author(s)
Lin, W.W.K. ; Digital Ecosystems & Bus. Intelligence Inst. (DEBII), Curtin Univ. of Technol. ; Wong, A.K.Y. ; Dillon, Tharam S. ; Chang, E.

The M3RT-based real-time traffic pattern detector 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 of fractality. When 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. The Intel's VTune Performance Analyzer indicates the proposed model can be deployed in real time effectively. This feature is of importance to the reliability improvement of Web applications which run on the Internet

Published in:

Object and Component-Oriented Real-Time Distributed Computing, 2007. ISORC '07. 10th IEEE International Symposium on

Date of Conference:

7-9 May 2007