Fuzzy leaky bucket congestion control in ATM networks with Markovian and self-similar traffic

This paper discusses an ATM congestion control mechanism that introduces a leaky bucket control scheme based on fuzzy logic principles. Network congestion is described linguistically by introducing a fuzzy rule and appropriate fuzzy variables, and is treated mathematically via fuzzy set manipulations. With the application of fuzzy logic the complex mathematical treatment of classical feedback control is avoided, and the “hard” bound effect in the traditional LB is also eliminated in favor of “soft” bound membership functions. In order to evaluate the effectiveness of the fuzzy LB, the performance of the ATM network with a non-fuzzy adaptive LB mechanism is also investigated. Network parameters which affect the performance are identified and optimized for the two control schemes and a comparison of the two approaches is carried out under the same network condition and optimal parameters. Finally, the performance of the fuzzy LB and adaptive LB are also evaluated under self-similar traffic load. The performance analysis in this paper is based on simulation combined with numerical optimization method. Our results indicate that the fuzzy leaky bucket mechanism leads to significant improvement to the system performance