Trend Early Warning Technology for Real-Time Computer Network Based on Dynamic Data Flow under the Background of Big Data

摘要

Effective trend extraction can provide early warning of monitoring objects, assessment of monitoring object status and decision support information. Based on incremental recursive least squares regression parameter estimation and generalized likelihood ratio change point detection algorithm, a dynamic data flow trend is proposed. It is the analytic algorithm. Its computational real-time performance and analysis accuracy are significantly improved compared with existing algorithms. The simulation experiment results verify the effectiveness of the algorithm.