Server fault monitoring method and system based on density clustering algorithm

A density clustering algorithm and fault monitoring technology, applied in non-redundant fault processing, instrumentation, computing, etc., can solve problems such as downtime and fault reset, and achieve the effect of improving stability

Pending Publication Date: 2020-11-17
SHANDONG CHAOYUE DATA CONTROL ELECTRONICS CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The technical task of the present invention is to address the above deficiencies and provide a server fault monitoring method and system based on the density clustering algorithm to solve the problem of how to monitor and warn the server through the density-based clustering algorithm and reset the downtime fault. question

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  • Server fault monitoring method and system based on density clustering algorithm
  • Server fault monitoring method and system based on density clustering algorithm

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Embodiment 1

[0051] A server fault monitoring method based on the density clustering algorithm of the present invention analyzes the health information data of the server and predicts the operating status of the server through the density clustering algorithm, performs fault warning on the server and resets the server when the server is down, the method includes Follow the steps below:

[0052] S100. Obtain the health information data of the server through the BMC and construct samples. The above samples are divided into training samples and test samples. The sample data in the above training samples need to mark the current server status. The above server status includes fault types and various fault types corresponding numeric data;

[0053] S200. Perform normalization processing on the above sample data;

[0054] S300. Construct a monitoring model based on the DBSCAN algorithm, and use training samples as input to optimize parameters of the monitoring model to obtain a trained monitori...

Embodiment 2

[0071] A server fault monitoring system based on a density clustering algorithm of the present invention includes a data acquisition module, a data preprocessing module, a model training module and a result output module, and the data acquisition module is used to obtain the health information data of the server through the BMC and construct a sample , the above samples are divided into training samples and test samples. The sample data in the above training samples need to mark the current server status. The above server status includes fault types and numerical data corresponding to various fault types; the data preprocessing module is used to The data is normalized; the model training module is used to build a monitoring model based on the DBSCAN algorithm, and uses the training samples as input to optimize the parameters of the above monitoring model to obtain a post-training monitoring model; the result output module is used to input the test samples into the post-training ...

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Abstract

The invention discloses a server fault monitoring method and system based on a density clustering algorithm, belongs to the technical field of server fault monitoring, and aims to solve the technicalproblem of how to perform fault monitoring and early warning on a server and reset a downtime fault through the density-based clustering algorithm. The method comprises the following steps: acquiringhealth information data of a server through a BMC and constructing a sample; normalizing the sample data; constructing a monitoring model based on a DBSCAN algorithm, optimizing parameters of the monitoring model, and obtaining a trained monitoring model; analyzing the sample data in the test sample through the trained monitoring model and outputting a monitoring result; if the server has a faultin the monitoring result, feeding back the monitoring result is to a to-be-displayed web page, and if the server crashes, resetting the server through BMC. The system comprises a data acquisition module, a data preprocessing module, a model training module and a result output module.

Description

technical field [0001] The invention relates to the technical field of server fault monitoring, in particular to a server fault monitoring method and system based on a density clustering algorithm. Background technique [0002] The server is a computer with fast operation, high load and strong performance. Long-term operation is an important performance index of the server. Monitoring the operation status of the server is an important method to ensure the long-term reliable operation of the server. Once the server fails and cannot operate normally, It is necessary to reset the server with the help of the remote controller BMC of the server. The BMC can not only control the server, but also obtain health information such as voltage, temperature, fan speed, and process-related information from the server. Class and other machine learning algorithms analyze the BMC to obtain information in real time to predict whether there is a potential failure of the server. [0003] At pre...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F11/07G06F11/34G06K9/62
CPCG06F11/0793G06F11/079G06F11/3447G06F11/3476G06F18/2321
Inventor 杨柳马晓光赖一鹏张永健
Owner SHANDONG CHAOYUE DATA CONTROL ELECTRONICS CO LTD
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