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Detection of fractal breakdowns by the holder filter in the novel real-time traffic pattern detector for the internet applications

机译:用于互联网应用的新型实时交通模式检测器中的支架过滤器检测分形故障

摘要

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.
机译:提出的新型实时流量模式检测器(RTPD)可以实时识别Internet流量模式。首先,它确定时间序列集合是否稳定。其次,它确定聚集体是表现出短程依赖性(SRD)还是长程依赖性(LRD)。第三,它检测系统的平稳运行是否突然变得不规则和混乱。通过计算Holder指数的瞬时值(具有(0,1)范围以适应不同程度的分形性)来实现此检测。由于系统动力学的原因,诸如时间序列之类的平滑性能分布可能会在不同时间嵌入变化的分形。如果Holder指数徘徊在(0,1)区域之外,则会发生分形分解。实时应用程序检测此类故障的能力使其能够避免突发故障。此功能对于驻留在Internet上的数字生态系统的可靠性至关重要。

著录项

  • 作者

    Lin WWK; Dillon T; Wong AKY;

  • 作者单位
  • 年度 2007
  • 总页数
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类

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