Fault detection through multi-fractal nature of traffic

Yajuan Tang, Xiapu Luo, Zijie Yang

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

5 Citations (Scopus)

Abstract

Significant progress has been developed previously in modeling network traffic with fractals. These developments have given rise to a new insight and physical understanding of the effects of scaling properties in measured network traffic. Among them, multi-fractal models fit measured data more naturally. This paper takes advantage of multi-fractal model to detect fault in network traffic. Faults in a self-similar traffic destroy the singularity structure at the time points they occur, resulting in a significant deviation from those of normal traffic. For fault detection, we measure the degree of deviation of singularity exponent at every time segment through a deviation indicator Q based on structure function Sj(q). Since faults usually bring out abnormal bursts against natural ones in traffic, the proposed algorithm is thereby able to detect them. As demonstrated on simulated and real network traffic data, this algorithm can detect abnormal traffic loads with natural traffic bursts in the background.
Original languageEnglish
Title of host publication2002 International Conference on Communications, Circuits and Systems and West Sino Exposition, ICCCAS 2002 - Proceedings
PublisherIEEE
Pages695-699
Number of pages5
ISBN (Electronic)0780375475, 9780780375475
DOIs
Publication statusPublished - 1 Jan 2002
Externally publishedYes
Event1st International Conference on Communications, Circuits and Systems, ICCCAS 2002 - Tibet Hotel, Chengdu, China
Duration: 29 Jun 20021 Jul 2002

Conference

Conference1st International Conference on Communications, Circuits and Systems, ICCCAS 2002
Country/TerritoryChina
CityChengdu
Period29/06/021/07/02

Keywords

  • fault detection
  • multi-fractal
  • network traffic
  • wavelet

ASJC Scopus subject areas

  • Hardware and Architecture
  • Computer Networks and Communications
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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