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We analyze traffic traces obtained from measurements at the edge gateway of the campus network of the University of Pavia. These traces have been obtained simply using the tcpdump utility and then analyzed and modeled using two different approaches. The first is based: on a hidden Markov model (HMM) the other on a stochastic generator based on a chaotic attractor. It is shown that the HMM is capable of capturing the general statistics of the observed streams despite poor long term correlation characteristics, while the chaotic model can achieve somewhat better results in long term characteristics and somewhat worse in short term. Moreover, the chaotic model is sensitive to the parameter extraction procedure.