Abstract
Many call admission control schemes for ATM-type networks focus on the cell loss rate as the exclusive QoS metric and therefore base their Eb (Effective bandwidth) schemes on cell-loss rate approximations. We use simulation data to train an adaptive logic network (ALN) to estimate cell loss and delay; these estimates can then be used to compute effective bandwidths to satisfy both cell loss and delay. Results indicate that the ALN model is simple, computationally efficient, and sufficiently accurate for practical use.
The original version of this chapter was revised: The copyright line was incorrect. This has been corrected. The Erratum to this chapter is available at DOI: 10.1007/978-0-387-35353-1_28
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© 2000 IFIP International Federation for Information Processing
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Ramaswamy, S., Gburzynski, P. (2000). A neural network approach to effective bandwidth characterization in ATM networks. 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_22
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DOI: https://doi.org/10.1007/978-0-387-35353-1_22
Publisher Name: Springer, Boston, MA
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