Abstract
Using real traffic data, we show that neural network-based prediction techniques can be used to predict the queuing behaviour of highly bursty traffics typical of LAN interconnection in a way accurate enough so as to allow dynamical renegotiation of a DBR traffic contract at the edge of an ATM network.
The performances of predictor-based in service renegotiation are evaluated in terms of renegotiation errors and reserved bandwidth for the the DBR traffic handling capability and are shown to be very encouraging for the use of connectionist prediction techniques for the management of bursty traffics in ATM networks.
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Clérot, F., Gouzien, P., Bengio, S., Gravey, A., Collobert, D. (2000). Dynamical Resource Reservation Scheme in an ATM Network Using Neural Network-Based Traffic Prediction. In: Kouvatsos, D. (eds) Performance Analysis of ATM Networks. ATM 1997. IFIP — The International Federation for Information Processing, vol 29. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-35353-1_21
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DOI: https://doi.org/10.1007/978-0-387-35353-1_21
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