casa 15(4): e3

Research Article

Model Integrating Fuzzy Argument with Neural Network Enhancing the Performance of Active Queue Management

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  • @ARTICLE{10.4108/eai.4-8-2015.150042,
        author={Nguyen  Kim Quoc and Vo  Thanh Tu and Nguyen  Thuc Hai},
        title={Model Integrating Fuzzy Argument with Neural Network Enhancing the Performance of Active Queue Management},
        journal={EAI Endorsed Transactions on Context-aware Systems and Applications},
        volume={2},
        number={4},
        publisher={ICST},
        journal_a={CASA},
        year={2015},
        month={8},
        keywords={Congestion Control, Active Queue Management, Fuzzy Logic, Neural Network},
        doi={10.4108/eai.4-8-2015.150042}
    }
    
  • Nguyen Kim Quoc
    Vo Thanh Tu
    Nguyen Thuc Hai
    Year: 2015
    Model Integrating Fuzzy Argument with Neural Network Enhancing the Performance of Active Queue Management
    CASA
    ICST
    DOI: 10.4108/eai.4-8-2015.150042
Nguyen Kim Quoc1,*, Vo Thanh Tu1, Nguyen Thuc Hai2
  • 1: College of Sciences, Hue University, Vietnam
  • 2: Ha Noi University of Science and Technology, Vietnam
*Contact email: quocnknet@yahoo.com

Abstract

The bottleneck control by active queue management mechanisms at network nodes is essential. In recent years, some researchers have used fuzzy argument to improve the active queue management mechanisms to enhance the network performance. However, the projects using the fuzzy controller depend heavily on professionals and their parameters cannot be updated according to changes in the network, so the effectiveness of this mechanism is not high. Therefore, we propose a model combining the fuzzy controller with neural network (FNN) to overcome the limitations above. Results of the training of the neural networks will find the optimal parameters for the adaptive fuzzy controller well to changes of the network. This improves the operational efficiency of the active queue management mechanisms at network nodes.