Long-range dependence analysis of Internet traffic

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dc.contributor.authorPark, Cheolwooko
dc.contributor.authorHernandez-Campos, Felixko
dc.contributor.authorLe, Longko
dc.contributor.authorMarron, J. S.ko
dc.contributor.authorPark, Juhyunko
dc.contributor.authorPipiras, Vladasko
dc.contributor.authorSmith, F. D.ko
dc.contributor.authorSmith, Richard L.ko
dc.contributor.authorTrovero, Micheleko
dc.contributor.authorZhu, Zhengyuanko
dc.date.accessioned2021-06-11T01:30:39Z-
dc.date.available2021-06-11T01:30:39Z-
dc.date.created2021-06-11-
dc.date.created2021-06-11-
dc.date.issued2011-
dc.identifier.citationJOURNAL OF APPLIED STATISTICS, v.38, no.7, pp.1407 - 1433-
dc.identifier.issn0266-4763-
dc.identifier.urihttp://hdl.handle.net/10203/285760-
dc.description.abstractLong-range-dependent time series are endemic in the statistical analysis of Internet traffic. The Hurst parameter provides a good summary of important self-similar scaling properties. We compare a number of different Hurst parameter estimation methods and some important variations. This is done in the context of a wide range of simulated, laboratory-generated, and real data sets. Important differences between the methods are highlighted. Deep insights are revealed on how well the laboratory data mimic the real data. Non-stationarities, which are local in time, are seen to be central issues and lead to both conceptual and practical recommendations.-
dc.languageEnglish-
dc.publisherTAYLOR & FRANCIS LTD-
dc.titleLong-range dependence analysis of Internet traffic-
dc.typeArticle-
dc.identifier.wosid000290406300008-
dc.identifier.scopusid2-s2.0-79956369960-
dc.type.rimsART-
dc.citation.volume38-
dc.citation.issue7-
dc.citation.beginningpage1407-
dc.citation.endingpage1433-
dc.citation.publicationnameJOURNAL OF APPLIED STATISTICS-
dc.identifier.doi10.1080/02664763.2010.505949-
dc.contributor.localauthorPark, Cheolwoo-
dc.contributor.nonIdAuthorHernandez-Campos, Felix-
dc.contributor.nonIdAuthorLe, Long-
dc.contributor.nonIdAuthorMarron, J. S.-
dc.contributor.nonIdAuthorPark, Juhyun-
dc.contributor.nonIdAuthorPipiras, Vladas-
dc.contributor.nonIdAuthorSmith, F. D.-
dc.contributor.nonIdAuthorSmith, Richard L.-
dc.contributor.nonIdAuthorTrovero, Michele-
dc.contributor.nonIdAuthorZhu, Zhengyuan-
dc.description.isOpenAccessN-
dc.type.journalArticleArticle-
dc.subject.keywordAuthorHurst parameter-
dc.subject.keywordAuthorInternet traffic-
dc.subject.keywordAuthorlong-range dependence-
dc.subject.keywordAuthormultiscale analysis-
dc.subject.keywordAuthornon-stationarity-
dc.subject.keywordPlusFRACTIONAL BROWNIAN-MOTION-
dc.subject.keywordPlusROBUST ESTIMATION-
dc.subject.keywordPlusWAVELET ANALYSIS-
dc.subject.keywordPlusSELF-SIMILARITY-
dc.subject.keywordPlusHURST PARAMETER-
dc.subject.keywordPlusSIZER-
dc.subject.keywordPlusSIMULATION-
dc.subject.keywordPlusSELECTION-
dc.subject.keywordPlusONSET-
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