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An Adaptive Monitoring Method for Cloud Computing System Based on Fault Prediction

A fault prediction and cloud computing technology, applied in computing, hardware monitoring, error detection/correction, etc., can solve problems such as difficult to meet online error detection, and achieve the effect of low computing overhead

Active Publication Date: 2018-01-26
INST OF SOFTWARE - CHINESE ACAD OF SCI
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  • Description
  • Claims
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Problems solved by technology

At the same time, due to the need to collect a large number of log files and extract fixed patterns from them, it is difficult to meet the needs of online error detection

Method used

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  • An Adaptive Monitoring Method for Cloud Computing System Based on Fault Prediction
  • An Adaptive Monitoring Method for Cloud Computing System Based on Fault Prediction
  • An Adaptive Monitoring Method for Cloud Computing System Based on Fault Prediction

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Embodiment Construction

[0043] The present invention will be described in detail below in conjunction with specific embodiments and accompanying drawings.

[0044] The cloud computing system adaptive monitoring method based on fault prediction proposed by the present invention, such as figure 1 The following steps are shown, (1) the monitoring agent is deployed on each host / virtual machine to collect relevant monitoring data such as host, virtual machine, container, middleware, and application; (2) real-time collection and Store the monitoring data; (3) the abnormality degree evaluator calculates the abnormality degree of the system according to the collected monitoring data, (4) adjust the monitoring cycle according to the abnormality degree of the system operation status obtained from the evaluation.

[0045] As the use environment of the method of the embodiment of the present invention, such as figure 2 As shown, six Xen virtual machines are deployed on the physical host, among which one virtua...

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Abstract

The invention relates to a method for adaptive monitoring of a cloud computing system based on failure prediction. Characteristic vectors of monitoring data are calculated through a principal component analysis technology so as to depict a system running state, and the abnormal degree of the system is estimated by calculation of the deviation between characteristic vectors of current monitoring data and characteristic vectors of historical monitoring data. When the abnormal degree of the monitored system is high, a monitoring period is shortened so as to closely track a running state of the monitored system, and thus error prediction and detection accuracy and timeliness are improved. In contrast, when the abnormal degree of the monitored system is low, the monitoring period is prolonged, and thus the monitoring overhead is reduced.

Description

technical field [0001] The invention relates to a monitoring method of a cloud computing system, in particular to a method for dynamically adjusting a monitoring period based on an abnormal degree evaluation of a cloud computing system, and belongs to the field of software technology. Background technique [0002] The cloud computing system is huge in scale and complex in structure, and the monitoring system needs to collect the monitoring of various resources at multiple levels (such as network layer, hardware layer, virtual machine layer, operating system layer, middleware layer, application software layer) from many nodes. data to continuously track the running status of the cloud computing system. However, collecting and processing a large amount of monitoring data will bring huge resource overhead, which will affect system performance. Therefore, commercial monitoring systems only support fixed monitoring cycles (for example, data collection every minute), such as Amaz...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F11/30
CPCG06F11/3006
Inventor 王焘张文博魏峻钟华
Owner INST OF SOFTWARE - CHINESE ACAD OF SCI
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