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Linear discriminant analysis in network traffic modelling
Author(s) -
Zhang BingYi,
Sun YaMin,
Bian YuLan,
Zhang HongKe
Publication year - 2006
Publication title -
international journal of communication systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.344
H-Index - 49
eISSN - 1099-1131
pISSN - 1074-5351
DOI - 10.1002/dac.746
Subject(s) - judgement , computer science , autocorrelation , histogram , data mining , hurst exponent , linear discriminant analysis , algorithm , artificial intelligence , statistics , mathematics , political science , law , image (mathematics)
It is difficult to give an accurate judgement of whether the traffic model fit the actual traffic. The traditional method is to compare the Hurst parameter, data histogram and autocorrelation function. The method of comparing Hurst parameter cannot give exact results and judgement. The method of comparing data histogram and autocorrelation only gives a qualitative judgement. Based on linear discriminant analysis we proposed a novel arithmetic. Utilizing this arithmetic we analysed some sets of data with large and little differences. We also analysed some sets of data generated by network simulator. The analysis result is accurate. Comparing with traditional method, this arithmetic is useful and can conveniently give an accurate judgement for complex network traffic trace. Copyright © 2005 John Wiley & Sons, Ltd.