Characterization of traffic of the video streaming service based on lexical analyzers

The video streaming service, besides offering interactivity by users' actions through pauses, backwards, and forwards, is the highest generator of traffic on data networks. Hence, it is necessary to characterize this behavior for network dimensioning. This article presents the conceptual models of the service and a lexical analyzer whose function is the automatic extraction of the different frames of traffic streams and identification of interactivity processes. Through the lexical analyzer, the information from each of the components of the service such as the I, P, and B frames is extracted; and so is the audio component. This means that the lexical analyzer provides granularity to the characterization process. Thus, it is expected that the lexical tool allows studying the behavior of traffic based on distribution functions obtained in situ, not relying on assumptions or studies from other researchers.