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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Qinghua Lu Xiwei Xu Liming Zhu Bass, L. Zhanwen Li Sakr, S. Bannerman, P.L. Liu, A. |
| Copyright Year | 2013 |
| Description | Author affiliation: Software Syst. Res. Group, NICTA, Sydney, NSW, Australia (Qinghua Lu; Xiwei Xu; Liming Zhu; Bass, L.; Zhanwen Li; Sakr, S.; Bannerman, P.L.; Liu, A.) |
| Abstract | Cloud consumers have a variety of deployment related techniques, such as auto-scaling policies and recovery strategies, for dealing with the uncertainties in the cloud. Uncertainties can be characterized as stochastic (such as failures, disasters, and workload spikes) and subjective (such as choice among various deployment options). Cloud consumers must consider both stochastic and subjective uncertainties. Analytic support for consumers in selecting appropriate techniques and setting the required parameters in the face of different types of uncertainty is currently limited. In this paper, we propose a set of application availability analysis models that capture subjective uncertainties in addition to stochastic uncertainties. We built and validated the models by using industry best practices on deployment, and actual commercial products for disaster recovery and live migration. Our results show that the models permit more informed and quantitative availability analysis than industry best practices under a wide range of scenarios. |
| Starting Page | 454 |
| Ending Page | 461 |
| File Size | 653343 |
| Page Count | 8 |
| File Format | |
| ISSN | 21596190 |
| e-ISBN | 9780769550282 |
| DOI | 10.1109/CLOUD.2013.87 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2013-06-28 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Availability Industries Analytical models Cloud computing Uncertainty Databases Stochastic processes Deployment architecture Stochastic reward nets Best practices |
| Content Type | Text |
| Resource Type | Article |
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