Presentation 2011-12-16
Adaptive Short Term Prediction of JPIX Traffic Volume based on the Singular Value Decomposition
Hirohisa HAMADA, Hirotaka ISHIBASHI, Masato YAMASHITA, Kazuo YANA,
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Abstract(in English) This paper proposes an adaptive method for the JPIX (Japan Internet Exchange) network traffic prediction. Singular value decomposition is applied to the daily JPIX traffic data for a certain time period (1-2 months) to extract the orthogonal time series underlying the traffic data. Then an adaptive algorithm is applied for updating the weight vector characterize the current network traffic which enable the traffic prediction. The method was applied to the JPIX traffic data for May 30, 2011-July 31, 2011 to predict the subsequent week. The method achieved a good prediction accuracy of average 1.85%.
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Keyword(in English) Network traffic prediction / JPIX / Japan Internet exchange / Singular value decomposition
Paper # IN2011-116
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Conference Date 2011/12/8(1days)
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Language JPN
Title (in Japanese) (See Japanese page)
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Title (in English) Adaptive Short Term Prediction of JPIX Traffic Volume based on the Singular Value Decomposition
Sub Title (in English)
Keyword(1) Network traffic prediction
Keyword(2) JPIX
Keyword(3) Japan Internet exchange
Keyword(4) Singular value decomposition
1st Author's Name Hirohisa HAMADA
1st Author's Affiliation Graduate School of Engineering, Hosei University()
2nd Author's Name Hirotaka ISHIBASHI
2nd Author's Affiliation Graduate School of Engineering, Hosei University
3rd Author's Name Masato YAMASHITA
3rd Author's Affiliation Faculty of Science and Engineering, Hosei University
4th Author's Name Kazuo YANA
4th Author's Affiliation Graduate School of Engineering, Hosei University:Faculty of Science and Engineering, Hosei University
Date 2011-12-16
Paper # IN2011-116
Volume (vol) vol.111
Number (no) 346
Page pp.pp.-
#Pages 5
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