期刊名称：International Journal of Hybrid Information Technology
印刷版ISSN：1738-9968
出版年度：2016
卷号：9
期号：2
页码：439-450
DOI：10.14257/ijhit.2016.9.2.39
出版社：SERSC
摘要：Cloud computing platforms are complex system, which consist of a lot of software working together. Because of software defects, cloud computing platforms may has performance anomaly during runtime. In this paper, a data-driven anomaly detection method is proposed to monitor runtime performance for cloud computing platforms. The proposed method can not only detect the performance anomaly of cloud computing platforms during runtime, but also find out which performance metric results in the anomaly. A series of experiments are conducted on a real private cloud computing platform based on OpenStack and experimental results show the proposed method is better than previous anomaly detection methods for cloud computing platforms.
关键词：Data-driven; Anomaly detection; Cloud computing; Local outlier factor
