The Research Of Network Traffic Detection And Prediction Analysis Technology

Network traffic detection and modeling prediction are the key technologies to manage and control the network. In this paper, the current technologies of network anomaly detection and prediction are analyzed, the self-similar of network traffic and its parameter estimation algorithms are studied in depth, and the related technologies of network traffic modeling have also been detailed analyzed. Then, a refined self-similar parameter estimation algorithm is designed through the combination of wavelet analysis and Hilbert-Huang Transform, which is applied to network traffic anomaly detection, and a set of experiments are run to verify the improvement in the accuracy and availability. A mixture model of network traffic is also designed concurrently through the combination of empirical mode decomposition and discrete wavelet transform, which is applied to network traffic prediction, and a set of experiments are also run to verify the improvement in the accuracy and availability.