Smowton, C., Balla, A., Antoniades, D., Miller, C. , Pallis, G., Dikaiakos, M. D. and Xing, W. (2017) A cost-effective approach to improving performance of big genomic data analyses in clouds. Future Generation Computer Systems, 67, pp. 368-381. (doi: 10.1016/j.future.2015.11.011)
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Abstract
With the rapidly growing demand for DNA analysis, the need for storing and processing large-scale genome data has presented significant challenges. This paper describes how the Genome Analysis Toolkit (GATK) can be deployed to an elastic cloud, and defines policy to drive elastic scaling of the application. We extensively analyse the GATK to expose opportunities for resource elasticity, demonstrate that it can be practically deployed at scale in a cloud environment, and demonstrate that applying elastic scaling improves the performance to cost tradeoff achieved in a simulated environment.
Item Type: | Articles |
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Status: | Published |
Refereed: | Yes |
Glasgow Author(s) Enlighten ID: | Miller, Professor Crispin |
Authors: | Smowton, C., Balla, A., Antoniades, D., Miller, C., Pallis, G., Dikaiakos, M. D., and Xing, W. |
College/School: | College of Medical Veterinary and Life Sciences > School of Cancer Sciences |
Journal Name: | Future Generation Computer Systems |
Publisher: | Elsevier |
ISSN: | 0167-739X |
ISSN (Online): | 1872-7115 |
Published Online: | 17 December 2015 |
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