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Publicado por VDM Verlag Dr. M�ller 2009-01-04, 2009
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Añadir al carritoTaschenbuch. Condición: Neu. Using Network Application Behavior to Predict Performance | Chunling Ma | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2009 | VDM Verlag Dr. Müller | EAN 9783639059601 | Verantwortliche Person für die EU: OmniScriptum GmbH & Co. KG, Bahnhofstr. 28, 66111 Saarbrücken, info[at]akademikerverlag[dot]de | Anbieter: preigu.
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Añadir al carritoKartoniert / Broschiert. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Ma ChunlingChunling Ma obtained her master s degree in computer science atnWorcester Polytechnic Institute in Worcester,Massachusetts of thenUnited States.She earned her bachelor s degree in computernscience at Shenyang Institute o.
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Añadir al carritoTaschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Today's continuously growing Internet requires usersand network applications to have knowledge of networkmetrics.This knowledge is critical for decisionmaking during the usage of network applications.Thisthesis studies application related networkmetrics.The major approach in this work is to examinethe traffic between a simulated user.We use thehistorical data collected from previous usage ofnetwork applications to make predictions for futureusage of those applications.Prediction mechanismsrequire us to make parameter choices so that certainweights can be placed on historical data versuscurrent data.We study these different choices and usethe values from our best experimental results.Fromthese studies we conclude that our data prediction isquite accurate and remains stable over a range ofparameter choices.The use of shared routing pathsbetween users and network applications are exploredin the performance prediction of applications.Thenetwork applications studied are also varied,including web, streaming, DNS.We see whether sharinginformation obtained from different applications canbe used to make predictions of application performance.