Monitoring data noise reduction processing method and device

Abstract

Embodiments of the present invention provide a monitoring data noise reduction processing method and device, which belong to the technical field of communication. The method includes: obtaining monitoring data, the monitoring data is a univariate time series signal; performing phase space reconstruction in the embedded dimensional space based on the univariate time series signal, obtaining the phase space matrix of the prime mover system, and performing singularity on the phase space matrix Value decomposition, calculate the effective reconstruction order rank of the phase space matrix, and obtain the main singular value of the phase space matrix; use the main singular value of the phase space matrix to reconstruct the signal, obtain the signal after noise reduction, and realize the noise reduction of the monitoring data deal with. The monitoring data noise reduction processing method and device provided by the embodiments of the present invention can improve the accuracy of the monitoring data, thereby improving the quality of GTM scheduling.

Description

technical field [0001] The invention relates to the field of communication technology, in particular to a monitoring data noise reduction processing method and device. Background technique [0002] GTM (Global Traffic Manager, global traffic management) is based on intelligent DNS (Domain Name System, domain name system), distributed monitoring system and big data processing platform, analysis lines covering each operator and each region, and a constantly updated IP library to achieve 24-hour automatic detection of downtime and intelligent switching of primary and backup sources, thereby providing users with reliable, stable and safe traffic scheduling services. [0003] At present, GTM scheduling mainly relies on the monitoring and detection of the target host by the monitoring node in the IDC (Internet Data Center, Internet Data Center). Usually, multiple monitoring nodes are selected to monitor and detect a target host, and the monitoring nodes return the monitoring data...

AI Technical Summary

Problems solved by technology

However, the monitoring data returned by the monitoring node is inaccurate, for example, when there are network fluctuations, monitoring node failures, etc.

When the accuracy of the monitoring data returned by the monitoring node is poor, because the GTM dispatch center cannot identify the accuracy of the monitoring data, it will lead to scheduling errors

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