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ICDCS
2012
IEEE

PREPARE: Predictive Performance Anomaly Prevention for Virtualized Cloud Systems

11 years 9 months ago
PREPARE: Predictive Performance Anomaly Prevention for Virtualized Cloud Systems
Abstract—Virtualized cloud systems are prone to performance anomalies due to various reasons such as resource contentions, software bugs, and hardware failures. In this paper, we present a novel PREdictive Performance Anomaly pREvention (PREPARE) system that provides automatic performance anomaly prevention for virtualized cloud computing infrastructures. PREPARE integrates online anomaly prediction, learning-based cause inference, and predictive prevention actuation to minimize the performance anomaly penalty without human intervention. We have implemented PREPARE on top of the Xen platform and tested it on the NCSU’s Virtual Computing Lab using a commercial data stream processing system (IBM System S) and an online auction benchmark (RUBiS). The experimental results show that PREPARE can effectively prevent performance anomalies while imposing low overhead to the cloud infrastructure.
Yongmin Tan, Hiep Nguyen, Zhiming Shen, Xiaohui Gu
Added 29 Sep 2012
Updated 29 Sep 2012
Type Journal
Year 2012
Where ICDCS
Authors Yongmin Tan, Hiep Nguyen, Zhiming Shen, Xiaohui Gu, Chitra Venkatramani, Deepak Rajan
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