Fuzzy logic tool and genetic algorithms for CAC in ATM networks

Fuzzy logic tool and genetic algorithms for CAC in ATM networks

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A fuzzy logic decision support system for CAC is presented which predicts the maximum expected cell loss for each ATM connection when an incoming connection is added to the existing connections. Genetic algorithms are used to automatically design the fuzzy system and to tune it using online measurements of the traffic statistics including cell loss values.


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      • ITU-TS: Recommendation I.371, Study Group 13, ‘Trafficcontrol and congestioncontrol in B-ISDN’, Geneva, 1995.
    2. 2)
      • Herrera, F., Lozano, M., Verdegay, J.: `A learning process for fuzzy control rulesusing genetic algorithms', DECSAI-95108, Technical Report, February 1995.
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      • L.M. Campos , A. Gonzalez . A fuzzy inference model based on an uncertaintyforward propagation approach. Int. J. Approx. Reason. , 2 , 139 - 164
    4. 4)
      • EXPLOIT-RACE2061/EXP/SW3/DS/P/028/B1, ‘Results ofexperiments on trafficcontrol using real applications’, 31 December 1994.

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