Ensemble of Bayesian Predictors and Decision Trees for Proactive Failure Management in Cloud Computing Systems

Qiang Guan, Ziming Zhang and Song Fu
Department of Computer Science and Engineering
University of North Texas
Denton, Texas 76203, USA
Email: {QiangGuan, ZimingZhang}@my.unt.edu Song.Fu@unt.edu

In this paper, we present an unsupervised failure detection method using an ensemble of Bayesian models. It characterizes normal execution statesof the system and detects anomalous behaviors. After the anomalies are verified by system administrators, labeled data are available. Then, we apply supervised learning based on decision tree classifiers to predict future failure occurrences in the cloud. Experimental results in an institutewide cloud computing system show that our methods can achieve high true positive rate and low false positive rate for proactive failure management.

temp_12020415274902.pdf