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Chin. Phys. B, 2009, Vol. 18(6): 2194-2199    DOI: 10.1088/1674-1056/18/6/014
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Small-time scale network traffic prediction based on a local support vector machine regression model

Meng Qing-Fang(孟庆芳)a)b), Chen Yue-Hui(陈月辉)a), and Peng Yu-Hua(彭玉华)b)
a School of Information Science and Engineering, Shandong University, Jinan 250100, China; b School of Information Science and Engineering, University of Jinan, Jinan 250022, China; c School of Information Science and Engineering, University of Jinan, Jinan 250022, China;School of Information Science and Engineering, Shandong University, Jinan 250100, China
Abstract  In this paper we apply the nonlinear time series analysis method to small-time scale traffic measurement data. The prediction-based method is used to determine the embedding dimension of the traffic data. Based on the reconstructed phase space, the local support vector machine prediction method is used to predict the traffic measurement data, and the BIC-based neighbouring point selection method is used to choose the number of the nearest neighbouring points for the local support vector machine regression model. The experimental results show that the local support vector machine prediction method whose neighbouring points are optimized can effectively predict the small-time scale traffic measurement data and can reproduce the statistical features of real traffic measurements.
Keywords:  network traffic      small-time scale      nonlinear time series analysis      support vector machine regression model  
Received:  30 October 2008      Revised:  30 November 2008      Accepted manuscript online: 
PACS:  45.70.Vn (Granular models of complex systems; traffic flow)  
  02.70.Rr (General statistical methods)  
  05.45.Tp (Time series analysis)  
  89.75.Hc (Networks and genealogical trees)  
Fund: Project supported by the National Natural Science Foundation of China (Grant No 60573065), the Natural Science Foundation of Shandong Province, China (Grant No Y2007G33), and the Key Subject Research Foundation of Shandong Province, China (Grant No XTD0708).

Cite this article: 

Meng Qing-Fang(孟庆芳), Chen Yue-Hui(陈月辉), and Peng Yu-Hua(彭玉华) Small-time scale network traffic prediction based on a local support vector machine regression model 2009 Chin. Phys. B 18 2194

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