Citation
Mozo Velasco, Bonifacio Alberto and Guadamillas Herranz, Álvaro and López, Miguel Ángel and Pulvirenti, Fabio and Maravitsas, Nikolaos
(2014).
A telecom analytics framework for dynamic quality of service management.
In: "First International Workshop on Big Data Applications and Principles", 11/09/2014 - 12/09/2014, Madrid, Spain. ISBN 978-84-15302-94-0. pp. 103-132.
Abstract
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.