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

作者：Smowton Christopher; Balla Andoena; Antoniades Demetris; Miller Crispin; Pallis George; Dikaiakos Marios D; Xing Wei^*

来源：Future Generation Computer Systems-The International Journal of eScience, 2017, 67: 368-381.

DOI：10.1016/j.future.2015.11.011

• Big data
• Clouds
• Performance

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.

• 出版日期2017-2