The ubiquitous use of smart devices all over the world has contributed to an explosive increase in network traffic. Thus, methods for characterizing and predicting application-level traffic patterns from both individual and operator perspectives have received a lot of attention recently. Working along these lines, the authors of this paper make two important contributions: (1) they propose a systematic approach to group users into different profiles, along with identifying their traffic patterns at the application level; and (2) they propose an effective model for predicting application-level traffic usage of an individual.
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