An intelligent fuzzy routing scheme for improving ATM network performance using violation tagging function
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In ATM networks, traffic control design is major challenge because of the diverse services and the need for efficient network resource engineering. To cope with rapidly changing network conditions, traffic control methods for high speed networks must be adaptive, flexible, and intelligent for efficient network management. The use of intelligent algorithms based on fuzzy logic, neural networks and genetic algorithms can be efficient for traffic control in ATM networks. We propose a routing scheme which is based on fuzzy logic. The proposed scheme of routing the tagged cells can improve network utilization. Performance evaluation via simulations shows that the DPFC decision is very close to the ideal decision. The DPFC and FRM were able to send to the destination node 31% and 54% of tagged cells, respectively.
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