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Neural networks for adaptive traffic control in ATM networks

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4 Author(s)
E. Nordstrom ; Uppsala Univ., Sweden ; J. Carlstrom ; O. Gallmo ; L. Asplund

Neural networks (NNs) have several valuable properties for implementing ATM traffic control. The authors present NN-based solutions for two problems arising in connection admission control, affecting the grade of service (GOS) at both the cell and call levels, and propose that neural networks may increase the network throughput and revenue

Published in:

IEEE Communications Magazine  (Volume:33 ,  Issue: 10 )