Large deviations, moderate deviations, and queues with long-range dependent input
Long-range dependence has been recently asserted to be an important characteristic in modeling telecommunications traffic. Inspired by the integral relationship between the fractional Brownian motion and the standard Brownian motion, we model a process with long-range dependence, Y , as a fractional...
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Veröffentlicht in: | Advances in applied probability 1999-03, Vol.31 (1), p.254-278 |
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creator | Chang, Cheng-Shang Yao, David D. Zajic, Tim |
description | Long-range dependence has been recently asserted to be an important characteristic in modeling telecommunications traffic. Inspired by the integral relationship between the fractional Brownian motion and the standard Brownian motion, we model a process with long-range dependence,
Y
, as a fractional integral of Riemann-Liouville type applied to a more standard process
X
—one that does not have long-range dependence. When
X
takes the form of a sample path process with bounded stationary increments, we provide a criterion for
X
to satisfy a moderate deviations principle (MDP). Based on the MDP of
X
, we then establish the MDP for
Y
. Furthermore, we characterize, in terms of the MDP, the transient behavior of queues when fed with the long-range dependent input process
Y
. In particular, we identify the most likely path that leads to a large queue, and demonstrate that unlike the case where the input has short-range dependence, the path here is nonlinear. |
doi_str_mv | 10.1017/S0001867800009058 |
format | Article |
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Y
, as a fractional integral of Riemann-Liouville type applied to a more standard process
X
—one that does not have long-range dependence. When
X
takes the form of a sample path process with bounded stationary increments, we provide a criterion for
X
to satisfy a moderate deviations principle (MDP). Based on the MDP of
X
, we then establish the MDP for
Y
. Furthermore, we characterize, in terms of the MDP, the transient behavior of queues when fed with the long-range dependent input process
Y
. In particular, we identify the most likely path that leads to a large queue, and demonstrate that unlike the case where the input has short-range dependence, the path here is nonlinear.</description><identifier>ISSN: 0001-8678</identifier><identifier>EISSN: 1475-6064</identifier><identifier>DOI: 10.1017/S0001867800009058</identifier><language>eng</language><ispartof>Advances in applied probability, 1999-03, Vol.31 (1), p.254-278</ispartof><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c175t-445e0e437eed26bcf90d6dc0546c5ec113cfd3ab7085690285f312dc861ad5c03</citedby><cites>FETCH-LOGICAL-c175t-445e0e437eed26bcf90d6dc0546c5ec113cfd3ab7085690285f312dc861ad5c03</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><creatorcontrib>Chang, Cheng-Shang</creatorcontrib><creatorcontrib>Yao, David D.</creatorcontrib><creatorcontrib>Zajic, Tim</creatorcontrib><title>Large deviations, moderate deviations, and queues with long-range dependent input</title><title>Advances in applied probability</title><description>Long-range dependence has been recently asserted to be an important characteristic in modeling telecommunications traffic. Inspired by the integral relationship between the fractional Brownian motion and the standard Brownian motion, we model a process with long-range dependence,
Y
, as a fractional integral of Riemann-Liouville type applied to a more standard process
X
—one that does not have long-range dependence. When
X
takes the form of a sample path process with bounded stationary increments, we provide a criterion for
X
to satisfy a moderate deviations principle (MDP). Based on the MDP of
X
, we then establish the MDP for
Y
. Furthermore, we characterize, in terms of the MDP, the transient behavior of queues when fed with the long-range dependent input process
Y
. In particular, we identify the most likely path that leads to a large queue, and demonstrate that unlike the case where the input has short-range dependence, the path here is nonlinear.</description><issn>0001-8678</issn><issn>1475-6064</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1999</creationdate><recordtype>article</recordtype><recordid>eNplUMtKxDAUDaLgOPoB7voBRm-aZ5cy-IKCiLoumeR2rMykNUkV_95W3Yirw3kuDiGnDM4ZMH3xCADMKG0mhAqk2SMLJrSkCpTYJ4vZprN_SI5Sep0on7IL8lDbuMHC43tnc9eHdFbseo_R5r-iDb54G3HEVHx0-aXY9mFDow3f3QGDx5CLLgxjPiYHrd0mPPnFJXm-vnpa3dL6_uZudVlTx7TMVAiJgIJrRF-qtWsr8Mo7kEI5iY4x7lrP7VqDkaqC0siWs9I7o5j10gFfEvaz62KfUsS2GWK3s_GzYdDMnzT_PuFf9xVU4Q</recordid><startdate>199903</startdate><enddate>199903</enddate><creator>Chang, Cheng-Shang</creator><creator>Yao, David D.</creator><creator>Zajic, Tim</creator><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>199903</creationdate><title>Large deviations, moderate deviations, and queues with long-range dependent input</title><author>Chang, Cheng-Shang ; Yao, David D. ; Zajic, Tim</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c175t-445e0e437eed26bcf90d6dc0546c5ec113cfd3ab7085690285f312dc861ad5c03</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1999</creationdate><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Chang, Cheng-Shang</creatorcontrib><creatorcontrib>Yao, David D.</creatorcontrib><creatorcontrib>Zajic, Tim</creatorcontrib><collection>CrossRef</collection><jtitle>Advances in applied probability</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Chang, Cheng-Shang</au><au>Yao, David D.</au><au>Zajic, Tim</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Large deviations, moderate deviations, and queues with long-range dependent input</atitle><jtitle>Advances in applied probability</jtitle><date>1999-03</date><risdate>1999</risdate><volume>31</volume><issue>1</issue><spage>254</spage><epage>278</epage><pages>254-278</pages><issn>0001-8678</issn><eissn>1475-6064</eissn><abstract>Long-range dependence has been recently asserted to be an important characteristic in modeling telecommunications traffic. Inspired by the integral relationship between the fractional Brownian motion and the standard Brownian motion, we model a process with long-range dependence,
Y
, as a fractional integral of Riemann-Liouville type applied to a more standard process
X
—one that does not have long-range dependence. When
X
takes the form of a sample path process with bounded stationary increments, we provide a criterion for
X
to satisfy a moderate deviations principle (MDP). Based on the MDP of
X
, we then establish the MDP for
Y
. Furthermore, we characterize, in terms of the MDP, the transient behavior of queues when fed with the long-range dependent input process
Y
. In particular, we identify the most likely path that leads to a large queue, and demonstrate that unlike the case where the input has short-range dependence, the path here is nonlinear.</abstract><doi>10.1017/S0001867800009058</doi><tpages>25</tpages></addata></record> |
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title | Large deviations, moderate deviations, and queues with long-range dependent input |
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