doi: 10.4304/jsw.6.12.2379-2390
Design and Evaluation of an Online Anomaly Detector for Distributed Storage Systems
- 1 Department of Electrical and Computer Engineering, Tennessee Technological University, Cookeville, TN, USA
- 2 Department of Electrical and Computer Engineering, Virginia Commonwealth University, Richmond, VA, USA
- 3 School of Software Technology, Dalian University of Technology, Dalian, LiaoNing, China
- 4 School of Computer Science and Technology, Dalian University of Technology, Dalian, LiaoNing, China
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.
Keywords
- performance anomaly detector
- distribute
How to Cite
Xin Chen, Xubin He, He Guo, and 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. https://doi.org/ 10.4304/jsw.6.12.2379-2390
Copyright & License
Copyright © 2011 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).