Computer Science ›› 2016, Vol. 43 ›› Issue (8): 19-25.doi: 10.11896/j.issn.1002-137X.2016.08.004

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Data Dimension Reduction Method Based on PCA for Monitoring Data of Virtual Resources in Cloud Computing

HONG Bin, DENG Bo, PENG Fu-yang, BAO Yang and FENG Xue-wei   

  • Online:2018-12-01 Published:2018-12-01

Abstract: Cloud computing has become increasingly popular and cloud providers face serious problems as resource monitoring tasks become more and more complicated.As an effective approach to enhancing availability and reliability of cloud infrastructures,state monitoring system aims to detect anomalous state in cloud by analyzing monitoring data.To reduce the processed data volume,we proposed a data dimension reduction method based on PCA(Principal Components Analysis)with high fidelity in this article.The results of experiments carried on VICCI cloud service platform show that,our method can select the kernel metrics from hundreds of monitoring data types and sharply reduce the computing overload incurred by state monitoring tasks.

Key words: Cloud computing,State monitoring,Dimension reduction,Big data,PCA

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