A cost-effective approach to improving performance of big genomic data analyses in clouds

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
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 > Institute 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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