Descripción
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Since the beginning of Internet, Internet Service Providers (ISP) have seen the need of giving to users? traffic different treatments defined by agree- ments between ISP and customers. This procedure, known as Quality of Service Management, has not much changed in the last years (DiffServ and Deep Pack-et Inspection have been the most chosen mechanisms). However, the incremen-tal growth of Internet users and services jointly with the application of recent Ma- chine Learning techniques, open up the possibility of going one step for-ward in the smart management of network traffic. In this paper, we first make a survey of current tools and techniques for QoS Management. Then we intro-duce clustering and classifying Machine Learning techniques for traffic charac-terization and the concept of Quality of Experience. Finally, with all these com-ponents, we present a brand new framework that will manage in a smart way Quality of Service in a telecom Big Data based scenario, both for mobile and fixed communications. | |
Internacional
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Si |
Nombre congreso
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First International Workshop on Big Data Applications and Principles |
Tipo de participación
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960 |
Lugar del congreso
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Madrid, Spain |
Revisores
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Si |
ISBN o ISSN
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84-15302-94-0 |
DOI
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Fecha inicio congreso
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11/09/2014 |
Fecha fin congreso
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12/09/2014 |
Desde la página
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103 |
Hasta la página
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134 |
Título de las actas
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Proceedings First International Workshop on Big Data Applications and Principles |