A telecom analytics framework for dynamic quality of service management
Data(s) |
01/09/2014
|
---|---|
Resumo |
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. |
Formato |
application/pdf |
Identificador | |
Idioma(s) |
eng |
Publicador |
E.T.S.I de Sistemas Informáticos (UPM) |
Relação |
http://oa.upm.es/35324/1/INVE_MEM_2014_192364.pdf http://ict-ontic.eu/bigdap14/bigdap14_PROCEEDINGS.pdf info:eu-repo/semantics/altIdentifier/doi/null |
Direitos |
http://creativecommons.org/licenses/by-nc-nd/3.0/es/ info:eu-repo/semantics/openAccess |
Fonte |
First International Workshop on Big Data Applications and Principles : Proceedings | First International Workshop on Big Data Applications and Principles | 11/09/2014 - 12/09/2014 | Madrid, Spain |
Palavras-Chave | #Telecomunicaciones #Informática |
Tipo |
info:eu-repo/semantics/conferenceObject Ponencia en Congreso o Jornada PeerReviewed |