Design of a fuzzy traffic controller for ATM networks
IEEE/ACM Transactions on Networking (TON)
IEEE/ACM Transactions on Networking (TON)
A QoS-Provisioning neural fuzzy connection admission controller for multimedia high-speed networks
IEEE/ACM Transactions on Networking (TON)
Hierarchical neuro-fuzzy call admission controller for ATM networks
Computer Communications
Fuzzy-based adaptive bandwidth control for loss guarantees
IEEE Transactions on Neural Networks
Dynamic neural-based buffer management for queuing systems with self-similar characteristics
IEEE Transactions on Neural Networks
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The modern intelligent asynchronous transfer mode (ATM) networks need a scheme to maintain quality of service (QoS) towards different traffic constraints in real time environment for effective control and optimal system utilisation. This paper proposes the VHDL implementation of neuro-fuzzy based adaptive bandwidth controller. The intelligent control is used to manage the adaptive bandwidth prediction, congestion control and call admission control (CAC) of ATM networks simultaneously. This integrated hybrid mechanism reduces the decision errors of conventional CAC policies and operating errors occurred on fuzzy based CAC in ATM networks. The individual blocks needed to implement adaptive bandwidth controller for ATM networks are modelled using VHDL. The timing analysis for the validation, functionality and performance of the model is analysed using Altera Quartus II (5.1 version) HDL software and the logic synthesis is performed. The required codes are downloaded into FPGA Cyclone device.