Smoothing the Sample Autocorrelation of Long-Range-Dependent Traffic

Smoothing the Sample Autocorrelation of Long-Range-Dependent Traffic

This paper depicts our work in smoothing the sample autocorrelation function (ACF) of traffic. The experimental results exhibit that the sample ACF of traffic may be smoothed by the way of average. In addition, the results imply that the sum of sample ACFs of traffic convergences. Considering that t...

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Bibliographic Details
Main Authors: Ming Li, Wei Zhao
Format: Article
Language:English
Published: Hindawi Limited 2013-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2013/631498
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spelling doaj-244d40e94b9a437d8949d8493c41d2962020-11-24T22:37:14ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472013-01-01201310.1155/2013/631498631498Smoothing the Sample Autocorrelation of Long-Range-Dependent TrafficMing Li0Wei Zhao1School of Information Science & Technology, East China Normal University, No. 500 Dongchuan Road, Shanghai 200241, ChinaDepartment of Computer and Information Science, University of Macau, Avenida Padre Tomas Pereira, Taipa 1356, Macau, ChinaThis paper depicts our work in smoothing the sample autocorrelation function (ACF) of traffic. The experimental results exhibit that the sample ACF of traffic may be smoothed by the way of average. In addition, the results imply that the sum of sample ACFs of traffic convergences. Considering that the traffic data used in this research is long-range dependent (LRD), the latter may be meaningful for the theoretical research of LRD traffic.http://dx.doi.org/10.1155/2013/631498
collection DOAJ
language English
format Article
sources DOAJ
author Ming Li
Wei Zhao
spellingShingle Ming Li
Wei Zhao
Smoothing the Sample Autocorrelation of Long-Range-Dependent Traffic
Mathematical Problems in Engineering
author_facet Ming Li
Wei Zhao
author_sort Ming Li
title Smoothing the Sample Autocorrelation of Long-Range-Dependent Traffic
title_short Smoothing the Sample Autocorrelation of Long-Range-Dependent Traffic
title_full Smoothing the Sample Autocorrelation of Long-Range-Dependent Traffic
title_fullStr Smoothing the Sample Autocorrelation of Long-Range-Dependent Traffic
title_full_unstemmed Smoothing the Sample Autocorrelation of Long-Range-Dependent Traffic
title_sort smoothing the sample autocorrelation of long-range-dependent traffic
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2013-01-01
description This paper depicts our work in smoothing the sample autocorrelation function (ACF) of traffic. The experimental results exhibit that the sample ACF of traffic may be smoothed by the way of average. In addition, the results imply that the sum of sample ACFs of traffic convergences. Considering that the traffic data used in this research is long-range dependent (LRD), the latter may be meaningful for the theoretical research of LRD traffic.
url http://dx.doi.org/10.1155/2013/631498
work_keys_str_mv AT mingli smoothingthesampleautocorrelationoflongrangedependenttraffic
AT weizhao smoothingthesampleautocorrelationoflongrangedependenttraffic
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