The research of fuzzy dynamic Bayesian network in cognitive network QoS student study assessment

Author(s): Jiang Hao, Zhang Liang

In terms of network operating QoS analysis, we propose a cascading network QoS analyzing algorithm based on K-means and C4.5 algorithm. The algorithm was testified to be suitable for multiple analyze requirements. Also based on the monitoring data captured from the real Internet, the algorithm was proved to be effective and efficient The algorithm processes the data captured from the project “User-oriented Active 4G Network Measurement System. The system is deployed at multiple wireless network accessing points; conducting 4G network QoS monitoring 24 hours. The paper covers experiments to find a proper K and C4.5 discrete value, and use the KKZ algorithm to initialize the cluster center values. Based on the six traces of monitoring data, we compared the performances of cascading network QoS analyzing algorithm, K-mean algorithm and C4.5 algorithm. As a result, the cascading algorithm was highly efficient and reduces the noise of single algorithm; also it proved to be suitable to several types of monitoring data

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