Name
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. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/ICDCS.2012.65 | ICDCS |
Keywords | Field | DocType |
human intervention,performance anomaly penalty,prepare,performance anomaly prevention,data stream processing system,virtual reality,virtualized cloud computing infrastructures,performance anomaly,inference mechanisms,learning (artificial intelligence),ibm system,predictive performance anomaly prevention,online anomaly prediction,cloud infrastructure,online auction benchmark,virtualized cloud systems,predictive prevention actuation,learning-based cause inference,virtual computing lab,program diagnostics,virtualized cloud computing infrastructure,ibm system s,cloud computing,rubis,virtualized cloud system,automatic performance anomaly prevention,benchmark testing,measurement,bayesian methods,learning artificial intelligence,markov processes,predictive models | IBM,Virtual reality,Markov process,Cloud systems,Computer science,Inference,Software bug,Operating system,Benchmark (computing),Cloud computing | Conference |
ISSN | ISBN | Citations |
1063-6927 | 978-1-4577-0295-2 | 69 |
PageRank | References | Authors |
2.17 | 26 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yongmin Tan | 1 | 169 | 7.58 |
| Hiep Nguyen | 2 | 277 | 10.84 |
| Zhiming Shen | 3 | 482 | 16.67 |
| Xiaohui Gu | 4 | 1975 | 103.57 |
| Chitra Venkatramani | 5 | 499 | 31.95 |
| Deepak Rajan | 6 | 460 | 30.64 |