Institute of Information Theories and Applications FOI ITHEA
In this study, we showed various approachs implemented in Artiﬁcial Neural Networks for network
resources management and Internet congestion control. Through a training process, Neural Networks can
determine nonlinear relationships in a data set by associating the corresponding outputs to input patterns.
Therefore, the application of these networks to Trafﬁc Engineering can help achieve its general objective:
“intelligent” agents or systems capable of adapting dataﬂow according to available resources. In this article, we
analyze the opportunity and feasibility to apply Artiﬁcial Neural Networks to a number of tasks related to Trafﬁc
Engineering. In previous sections, we present the basics of each one of these disciplines, which are associated to
Artiﬁcial Intelligence and Computer Networks respectively.