Statistical Techniques for Online Anomaly Detection in Data Centers
Wang, Chengwei; Viswanathan, Krishnamurthy; Choudur, Lakshminarayan; Talwar, Vanish; Satterfield, Wade; Schwan, Karsten
Keyword(s): Anomaly Detection, Data Center Management, Statistics, Algorithms
Abstract: Online anomaly detection is an important step in data center management, requiring light-weight techniques that provide sufficient accuracy for subsequent diagnosis and management actions. This paper presents statistical techniques based on the Tukey and Relative Entropy statistics, and applies them to data collected from a production environment and to data captured from a testbed for multi-tier web applications running on server class machines. The proposed techniques are lightweight and improve over standard Gaussian assumptions in terms of performance.
Additional Publication Information: To be published and presented at IFIP/IEEE International Symposium on Integrated Network Management (1M) 2011, 23 May - 27 May 2011
External Posting Date: May 21, 2011 [Fulltext]. Approved for External Publication
Internal Posting Date: May 21, 2011 [Fulltext]