Self-Organizing Map-Based Analysis of IP-Network Traffic in Terms of Time Variation of Self-Similarity : A Detrended Fluctuation Analysis Approach(Nonlinear Problems)

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概要

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• This paper describes an analysis of IP-network traffic in terms of the time variation of self-similarity. To get a comprehensive view in analyzing the degree of long-range dependence (LRD) of IP-network traffic, this paper used a self-organizing map, which provides a way to map high-dimensional data onto a low-dimensional domain. Also, in the LRD-based analysis, this paper employed detrended fluctuation analysis (DFA), which is applicable to the analysis of long-range power-law correlations or LRD in non-stationary time-series signals. In applying this method to traffic analysis, this paper performed two kinds of traffic measurement: one based on IP-network traffic flowing into NTT Musashino R&D center (Tokyo, Japan) from the Internet and the other based on IP-network traffic flowing through at an interface point between an access provider (Tokyo, Japan) and the Internet. Based on sequential measurements of IP-network traffic, this paper derived corresponding values for the LRD-related parameter a of measured traffic. As a result, we found that the characteristic of self-similarity seen in the measured traffic fluctuated over time, with different time variation patterns for two measurement locations. In training the self-organizing map, this paper used three parameters: two a values for different plot ranges, and Shannon-based entropy, which reflects the degree of concentration of measured time-series data. We visually confirmed that the traffic data could be projected onto the map in accordance with the traffic properties, resulting in a combined depiction of the effects of the degree of LRD and network utilization rates. The proposed method can deal with multi-dimensional parameters, projecting its results onto a two-dimensional space in which the projected data positions give us an effective depiction of network conditions at different times.

• 社団法人電子情報通信学会の論文
• 2004-06-01

著者

• Masugi M

  Ntt Network Service Systems Laboratories Ntt Corporation

• Masugi Masao

  Ntt Network Service System Laboratories Ntt Corporation

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• QoS Evaluation of VoIP Communication Employing Self-Organizing Neural Network
• Self-Organizing Map-Based Analysis of IP-Network Traffic in Terms of Time Variation of Self-Similarity : A Detrended Fluctuation Analysis Approach(Nonlinear Problems)

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