Classificação de fluxos IP como ferramenta para engenharia de tráfego na internet.

Abstract

The increase in the number of applications and users in the Internet is the current infrastructure problem which decreases the applications performance on these networks. Also, it is a current research challenge for universities and telecommunications companies, which focus their activities to the next generation networks as a solution to the problems previously mentioned. As a possible contribution, in the logic layer of the network, this work proposes the investigation of IP flows classifiers as a tool for Traffic Engineering in the Internet. This process is responsible for conciliating the performance requirements of the network and the traffic that passes by it. The study is held with the Differentiated Services architecture, in which the traffic identification has a certain level of importance to its management as well as the resource establishment for quality provision and connections establishment. Before this, a study only with IP traffic classifiers based on machine learning is presented, which they are referred in academic works as the best in performance. The calibration of the chosen techniques is presented as well as an inter-classifiers performance comparison, which presents evidence that all the set of classifiers is able to be implemented in the DiffServ. Therefore, a performance evaluation of a IP network with DiffServ with the indicated classifiers shows that this new approach increases, in a general way, the performance of applications transmiting information by the network. This is the required conclusion and motivation to increase the use of DiffServ in backbone networks.