| In Asynchronous Transfer Mode (ATM) networks, congestion can be caused by unpredictable statistical fluctuations of traffic flows and fault conditions within the network. If congestion happens, then the network performance for the already established connection will decrease. ATM networks use the preventive congestion control mechanisms such as Usage Parameter Control (UPC) and Connection Admission Control (CAC) to avoid congested conditions. Knowing that many sources in ATM networks have variable traffic stream with different QoS characteristics, traffic management functions become necessary to control the traffic flows within the network. By using the signaling procedures at the call setup phase, the network and source reach an agreement for some traffic characteristic parameters. If the source violates the traffic parameters, then the probability of congestion increases. So the network must control the source traffic streams and detect well the violating cells. Therefore, fast detection of any violating source is one of the most important characteristics of a goodtraffic policer. In this paper we propose a fuzzy traffic policer with high ability in detection of violating sources. Our proposed fuzzy controller has two inputs, current peak cell rate and the current number of the buffer, the output of fuzzy controller is a factor .which is used to adjust token rate so as to change the cell release rate. As the core of fuzzy controller, the fuzzy rule was also optimized by a new proposed self-adaptive genetic algorithm. Simulation results obtained from packetized voice sources based on on-off model, show that the proposed fuzzy leaky controller has better selectivity than the conventional leaky bucket. It is observed that the proposed controller has better ability to detect the violation cell, especially in the detection of peak cell rate. In the meanwhile, the proposed genetic operator was effective in the process of optimizing fuzzy rules.
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