基于FARIMA過程的網(wǎng)絡(luò)業(yè)務(wù)預報與應(yīng)用
Traffic Prediction and Its Application Using FARIMA Models
-
摘要: 在高速網(wǎng)絡(luò)控制與帶寬分配研究中,網(wǎng)絡(luò)業(yè)務(wù)量預報是一個重要的問題。本文首先介紹自回歸分數(shù)整合滑動平均(FARIMA,Fractal Autoregressive Integrated Moving Average)過程的概念及其具體形式,并給出了FARIMA過程的預報方法,然后基于FARIMA過程的最小均方誤差預報方法,提出了一個具有補償功能的網(wǎng)絡(luò)自相似業(yè)務(wù)的預報方法,最后給出這種預報方式在網(wǎng)絡(luò)控制研究中的應(yīng)用。Abstract: Netvrork traffic prediction is important for netvrork control and bandwidth alloca-tion. This paper first introduces how to get optimal forecasting values, and provides prediction procedure for FARIMA models. And then provides a prediction method for self-similar traffic with compensation function and also gives out an example to demonstrate how to use this method in network control.
-
W. Leland, et al., On the self-similar nature of Ethernet traffic (extended version), IEEE/ACM Trans. on Networking, 1994, 2(1), 1-15.[2]J. Beran, et al., Long-range dependence in variable bit rate video traffic, IEEE Trans. on Commun., 1995, COM-43(2/3/4), 1566-1579.[3]W. Willinger, et al., Self-similarity in high-speed packet traffic, Analysis and modeling of Ethernet traffic measurements, Statistical Science, 1995, 10(1), 67-85.[4]C.W.J. Granger, R. Joyeux, An introduction to long-memory time series models and fractional differencing, Journal of Time Series Analysis, 1980, 1(2), 159-169.[5]J.R.M. Hosking, Fractional differencing, Biometrika, 1981, 68(1), 165-176. ［6］薛飛,自相似網(wǎng)絡(luò)業(yè)務(wù)的建模分析與性能評價,博士論文,天津,天津大學,1998年, 6月.[6]G. Box, G. Jenkins, Time Series, Forecasting and Control, revised edn., San Francisco, Holdenday, 1976, Ch.5. -
計量
- 文章訪問數(shù): 2136
- HTML全文瀏覽量: 144
- PDF下載量: 463
- 被引次數(shù): 0
下載:
