Title :
Detecting Behavioral Variations in System Resources of Large Data Centers
Author :
Casolari, Sara ; Colajanni, Michele ; Tosi, Stefania
Author_Institution :
Univ. of Modena & Reggio Emilia, Modena, Italy
fDate :
Aug. 31 2011-Sept. 2 2011
Abstract :
The identification of significant changes in system resource behaviors is mandatory for an efficient management of data centers. As the dimension of modern data centers increases, the evaluation of state change detections through traditional algorithms becomes computationally intractable. We propose a novel approach that characterizes the statistical properties of the resource measures coming from system monitors, classifies them, and signals a change only when there is modification of the resource classification. This method diminishes the computational complexity and reaches the same detection accuracy of traditional approaches as demonstrated by several results obtained in real enterprise data centers.
Keywords :
computational complexity; computer centres; pattern classification; behavioral variation detection; computational complexity; data center management; enterprise data centers; large data centers; resource classification; state change detections; system resources; Eigenvalues and eigenfunctions; Energy measurement; Monitoring; Principal component analysis; Servers; Sun; Time measurement; change detection; private clouds; resource behavior;
Conference_Titel :
Computer and Information Technology (CIT), 2011 IEEE 11th International Conference on
Conference_Location :
Pafos
Print_ISBN :
978-1-4577-0383-6
Electronic_ISBN :
978-0-7695-4388-8
DOI :
10.1109/CIT.2011.22