DocumentCode :
1966484
Title :
auto-AID: A data mining framework for autonomic anomaly identification in networked computer systems
Author :
Guan, Qiang ; Fu, Song
Author_Institution :
Dept. of Comput. Sci. & Eng., Univ. of North Texas, Denton, TX, USA
fYear :
2010
fDate :
9-11 Dec. 2010
Firstpage :
73
Lastpage :
80
Abstract :
Networked computer systems continue to grow in scale and in the complexity of their components and interactions. Component failures become norms instead of exceptions in these environments. A failure will cause one or multiple computer(s) to be unavailable, which affects the resource utilization and system throughput. When a computer fails to function properly, health-related data are valuable for troubleshooting. However, it is challenging to effectively identify anomalies from the voluminous amount of noisy, high-dimensional data. In this paper, we present auto-AID, an autonomic mechanism for anomaly identification in networked computer systems. It is composed of a set of data mining techniques that facilitates automatic analysis of system health data. The identification results are very valuable for the system administrators to manage systems and schedule the available resources. We implement a prototype of auto-AID and evaluate it on a production institution-wide compute grid. The results show that auto-AID can effectively identify anomalies with little human intervention.
Keywords :
data analysis; data mining; distributed processing; security of data; auto-AID; automatic system health data analysis; autonomic anomaly identification; data mining framework; function properly; networked computer systems; production institution-wide compute grid; resource utilization; system throughput; Computers; Data mining; Hardware; Monitoring; Mutual information; Prototypes; Temperature sensors; Anomaly identification; Data mining; Parallel and distributed systems; System dependability;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Performance Computing and Communications Conference (IPCCC), 2010 IEEE 29th International
Conference_Location :
Albuquerque, NM
ISSN :
1097-2641
Print_ISBN :
978-1-4244-9330-2
Type :
conf
DOI :
10.1109/PCCC.2010.5682334
Filename :
5682334
Link To Document :
بازگشت