Tracking and detecting network traffic based on capacity data prediction

Abstract

In order to improve the traffic tracking and monitoring ability of heterogeneous multi-core data migration network, a network traffic tracking and detection method based on capacity data prediction is proposed to construct a parameter structure model of audio and video data information collection and dynamic caching of heterogeneous multi-core data migration network traffic. Linear regression analysis and heterogeneous reorganization are used to reconstruct the time series of heterogeneous multi-core data migration network traffic, and matched filtering and time series analysis are used. The capacity data clustering model of heterogeneous multi-core data migration network traffic is established, and the spatial spectrum frequency-division feature quantity of heterogeneous multi-core data migration network traffic is extracted. The real-time prediction of heterogeneous multi-core data migration network traffic is realized through the traffic transmission channel equilibrium control method, and the transmission prediction of communication traffic is realized through the traffic feature fusion analysis. The simulation results show that the traffic tracking and detection accuracy of heterogeneous multi-core data migration network is high and the transmission reliability of the system is good.