¹Department of Electrical and Computer Engineering, Tennessee Technological University, Cookeville, TN, USA
²Department of Electrical and Computer Engineering, Virginia Commonwealth University, Richmond, VA, USA
³School of Software Technology, Dalian University of Technology, Dalian, LiaoNing, China
⁴School of Computer Science and Technology, Dalian University of Technology, Dalian, LiaoNing, China

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Abstract—Performance problems, which may stem from different system components, such as network, memory, and storage devices, are difficult to diagnose and isolate in distributed storage systems. In this paper, we present a performance anomaly detector which is able to efficiently detect performance anomaly and accurately identify the faulty sources in a system node of a distributed storage system. Our method exploits the stable relationship between workloads and system resource statistics to detect the performance anomaly and identify faulty sources which cause the performance anomaly in the system. Our experimental results demonstrate the efficiency and accuracy of the proposed performance anomaly detector.

Index Terms—performance anomaly detector, distributed storage systems, parallel file systems

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Cite: Xin Chen, Xubin He, He Guo, Yuxin Wang, "Design and Evaluation of an Online Anomaly Detector for Distributed Storage Systems," Journal of Software vol. 6, no. 12, pp. 2379-2390, 2011.