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공공누리This item is licensed Korea Open Government License

Title
Towards effective science cloud provisioning for a large-scale high-throughput computing
Author(s)
김서영김직수황순욱
Publication Year
2014-04-19
Abstract
The science cloud paradigm has been actively developed and investigated, but still requires a suitable model for science cloud system in order to support increasing scientific computation needs with high performance. This paper presents an effective provisioning model of science cloud, particularly for large-scale high throughput computing applications. In this model, we utilize job traces where a statistical method is applied to pick the most influential features to improve application performance. With these features, a system determines where VM is deployed (allocation) and which instance type is proper (provisioning). An adaptive evaluation step which is subsequent to the job execution enables our model to adapt to dynamical computing environments. We show performance achievements by comparing the proposed model with other policies through experiments and expect noticeable improvements on performance as well as reduction of cost from resource consumption through our model.
Keyword
Science cloud; High-throughput computing; Job profiling; Cloud provisioning; PCA (Principal components analysis)
Journal Title
Cluster computing : the journal of networks, software tools and applications
ISSN
1386-7857
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Appears in Collections:
7. KISTI 연구성과 > 학술지 발표논문
URI
https://repository.kisti.re.kr/handle/10580/14326
http://www.ndsl.kr/ndsl/search/detail/article/articleSearchResultDetail.do?cn=NART70661179
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