Fuzzy Logic for controlling call admission in ATM networks

  • M. Fontaine
  • D. G. Smith
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT)


An essential function of ATM is Connection admission control (CAC). To achieve higher network utilisation, bursty calls are statistically multiplexed on a common link. We present a new CAC scheme based on fuzzy logic (FL) and artificial neural networks (ANNs) to exploit this key feature of ATM networks. Defining a hybrid intelligent system enables us to take advantage of both the learning capabilities of ANNs and the interpretability properties of FL. The ANN is used in the learning phase to automatically tune the fuzzy system (i.e. to define the fuzzy rules and the membership functions) whilst during the control phase, the fuzzy system forecasts the QoS values. The CAC procedure is able to determine on line the cell loss probability (CLP) that a connection will exhibit when accepted into the ATM network. Because of its possible hardware implementation as well as its adaptive and learning capabilities, this scheme constitutes a good candidate for a robust real-time CAC.


ATM networks CAC Fuzzy Logic Artificial Neural Networks 


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Copyright information

© IFIP 1998

Authors and Affiliations

  • M. Fontaine
    • 1
  • D. G. Smith
    • 1
  1. 1.University of StrathclydeDepartment of Electronic & Electrical EngineeringUK

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