Detrended fluctuation analysis of IP-network traffic using a two-dimensional topology map

Masao Masugi

Physica A: Statistical Mechanics and its Applications, 2004, vol. 337, issue 3, 664-678

Abstract: This paper describes an analysis of IP-network traffic in terms of the time variation of self-similarity. To get a comprehensive view of network traffic conditions in analyzing the degree of long-range dependence (LRD) of IP-network traffic, this paper used a self-organizing scheme-based topology 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 apparently non-stationary time-series signals. Based on sequential measurements of IP-network traffic at a 100-Mbps point of interface between an access provider and the Internet, this paper derived corresponding values for the LRD-related parameter α of the traffic. In training the topology map, this paper used three parameters: the α value, average throughput, and a parameter that reflects the degree of non-stationarity for each measured data set. We visually confirmed that the traffic data could be projected onto the topology map in accordance with the traffic properties, resulting in a combined depiction of the effects of the degree of LRD and other factors. The proposed method can deal with multi-dimensional parameters, projecting its results onto a two-dimensional space in which the positions of the projected data give us with an effective depiction of network conditions at different times.

Keywords: Network traffic; Self-similarity; Long-range dependence; Detrended fluctuation analysis; Self-organizing (search for similar items in EconPapers)
Date: 2004
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437104001360
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:337:y:2004:i:3:p:664-678

DOI: 10.1016/j.physa.2004.01.055

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().