A cost-effective approach to improving performance of big genomic data analyses in clouds
Ημερομηνία
2017Συγγραφέας
Smowton, C.Balla, A.
Antoniades, Demetris
Miller, C.
Pallis, George C.
Dikaiakos, Marios D.
Xing, Wei
ISSN
0167-739XSource
Future Generation Computer SystemsVolume
67Pages
368-381Google Scholar check
Keyword(s):
Metadata
Εμφάνιση πλήρους εγγραφήςΕπιτομή
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. © 2015 Elsevier B.V.