自相似網(wǎng)絡(luò)流量Hurst指數(shù)的迭代估計(jì)算法

李林峰; 裘正定

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自相似網(wǎng)絡(luò)流量Hurst指數(shù)的迭代估計(jì)算法

李林峰, 裘正定

文章導(dǎo)航 > 電子與信息學(xué)報(bào) > 2006 > 28(12): 2371-2373

李林峰, 裘正定. 自相似網(wǎng)絡(luò)流量Hurst指數(shù)的迭代估計(jì)算法[J]. 電子與信息學(xué)報(bào), 2006, 28(12): 2371-2373.

引用本文:

李林峰, 裘正定. 自相似網(wǎng)絡(luò)流量Hurst指數(shù)的迭代估計(jì)算法[J]. 電子與信息學(xué)報(bào), 2006, 28(12): 2371-2373.

Li Lin-feng, Qiu Zheng-ding. An Iterative Method to Estimate Hurst Index of Self-similar Network Traffic[J]. Journal of Electronics & Information Technology, 2006, 28(12): 2371-2373.

Citation:

Li Lin-feng, Qiu Zheng-ding. An Iterative Method to Estimate Hurst Index of Self-similar Network Traffic[J]. Journal of Electronics & Information Technology, 2006, 28(12): 2371-2373.

李林峰, 裘正定. 自相似網(wǎng)絡(luò)流量Hurst指數(shù)的迭代估計(jì)算法[J]. 電子與信息學(xué)報(bào), 2006, 28(12): 2371-2373.

引用本文:

李林峰, 裘正定. 自相似網(wǎng)絡(luò)流量Hurst指數(shù)的迭代估計(jì)算法[J]. 電子與信息學(xué)報(bào), 2006, 28(12): 2371-2373.

Li Lin-feng, Qiu Zheng-ding. An Iterative Method to Estimate Hurst Index of Self-similar Network Traffic[J]. Journal of Electronics & Information Technology, 2006, 28(12): 2371-2373.

Citation:

Li Lin-feng, Qiu Zheng-ding. An Iterative Method to Estimate Hurst Index of Self-similar Network Traffic[J]. Journal of Electronics & Information Technology, 2006, 28(12): 2371-2373.

自相似網(wǎng)絡(luò)流量Hurst指數(shù)的迭代估計(jì)算法

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出版歷程
- 收稿日期: 2005-04-14
- 修回日期: 2005-08-31
- 刊出日期: 2006-12-19

An Iterative Method to Estimate Hurst Index of Self-similar Network Traffic

摘要

摘要: 該文提出了一種快速估計(jì)Hurst指數(shù)的迭代算法，并將它應(yīng)用于分形高斯噪聲和真實(shí)網(wǎng)絡(luò)流量數(shù)據(jù)。實(shí)驗(yàn)結(jié)果表明，與傳統(tǒng)方法相比，該算法有著較快的速度和較小的置信區(qū)間，并且不易受時(shí)間尺度變化影響，可作為一種在線估計(jì)Hurst指數(shù)的方法。
- 自相似; Hurst指數(shù); 迭代; 小波
Abstract: In this paper, an iterative method is presented to estimate Hurst index, and it is applied to both FGN (Fractional Gaussian Noise) data and real traffic data. Experimental results demonstrate that this method is much faster and has smaller confidence interval compared with traditional method. Moreover, the method is stable on different scales, so it can be used as an on-line Hurst index estimator.