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Tytuł artykułu

Towards Scalable and Cost-aware Bioinformatics Workflow Execution in the Cloud : Recent Advances to the Tavaxy Workflow System

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Języki publikacji
EN
Abstrakty
EN
Cloud-based scientific workflow systems can play an important role in the development of cost effective bioinformatics analysis applications. So far, most efforts for supporting cloud computing in such workflow systems have focused on simply porting them to the cloud environment. The next due steps are to optimize these systems to exploit the advantages of the cloud computing model, basically in terms of managing resource elasticity and the associated business model. In this paper, we introduce new advancements in designing scalable and cost-effective workflows in the cloud using the Tavaxy workflow system, focusing on genome analysis applications. We provide an overview of the system and describe its key cloud features including the configuration and execution of complete workflows and/or specific sub-workflows in the cloud. Taking real world examples, we demonstrate the key elasticity management features of the system. These features are designed to support two common scenarios: (1) minimizing workflow execution time under budget constraints and (2) minimizing budget spend under workflow deadline constraints. We evaluate the effectiveness of our approach by conducting experiments on the Amazon EC2 cloud with dynamic pricing and variable heterogeneous resource allocation.
Wydawca
Rocznik
Strony
255--280
Opis fizyczny
Bibliogr. 48 poz., rys., tab.
Twórcy
  • Faculty of Engineering, Cairo Unviersity, Giza, Egypt
autor
  • Center for Informatics Sciences, Nile University, Giza, Egypt
autor
  • Department of Computing, Imperial College London, London, England
Bibliografia
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  • [23]. Juve, G., Deelman, E., Vahi, K., Mehta, G., Berriman, B., Berman, B., Maechling, P.: Data Sharing Options for Scientific Workflows on Amazon EC2, Proceedings of the 2010 ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis, 2010.
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  • [26]. Kuehn, H., Liberzon, A., Reich, M., Mesirov, J.: Using GenePattern for gene expression analysis, Current Protocols in Bioinformatics, 12(7), 2008.
  • [27]. Langmead, B., Hansen, K., Leek, J.: Cloud-scale RNA-sequencing differential expression analysis with Myrna, Genome Biology, 11(8), 2010, R83+.
  • [28]. Langmead, B., Schatz, M., Lin, J., Pop, M., Salzberg, S.: Searching for SNPs with cloud computing, Genome Biology, 10(R134), 2009.
  • [29]. Langmead, B., Trapnell, C., Pop, M., Salzberg, S.: Ultrafast and memory-efficient alignment of short DNA sequences to the human genome, Genome Biology, 10(3), 2009, R25+.
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  • [34]. Oinn, T., Addis, M., Ferris, J., Marvin, D., et al.: Taverna: a tool for the composition and enactment of bioinformatics workflows, Bioinformatics, 20(17), 2004, 3045-54.
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  • [37]. Reich, M., Liefeld, T., Gould, J., Lerner, J., Tamayo, P., Mesirov, J.: GenePattern 2.0., Nature Genetics, 38, 2006, 500-501.
  • [38]. Rowe, A., Kalaitzopoulos, D., Osmond, M., Ghanem, M., Guo, Y.: The discovery net system for high throughput bioinformatics, Bioinformatics, 19(90001), 2003, 225i-231.
  • [39]. Schatz, M., Langmead, B., Salzberg, S.: Cloud computing and the DNA data race, Nature Biotechnology, 28, 2010, 691-693.
  • [40]. Shah, S., He, D., Sawkins, J., Druce, J., Quon, G., Lett, D., Zheng, G., Xu, T., Ouellette, B.: Pegasys: software for executing and integrating analyses of biological sequences, BMC Bioinformatics, 5(40), 2004.
  • [41]. Shields, M.: Control-versus data-driven workflows, Springer, 2007, 167-173.
  • [42]. Stein, L.: The case for cloud computing in genome informatics, Genome, 11(207), 2010.
  • [43]. Taylor, I., Shields, M., Wang, I., Harrison, A.: Visual Grid Workflow in Triana, J. Grid Computing, 3(3-4), 2005, 153-169.
  • [44]. Taylor, I., Shields, M., Wang, I., Harrison, A.: The Triana Workflow Environment: Architecture and Applications, in: Workflows for e-Science, Springer, 2007, 320-339.
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  • [47]. Wall, D., Kudtarkar, P., Fusaro, V., Pivovarov, R., Patil, P., Tonellato, P.: Cloud computing for comparative genomics, BMC Bioinformatics, 11, 2010, 259.
  • [48]. Zhang, Z., Schwartz, S., Wagner, L., Miller, W.: A greedy algorithm for aligning DNA sequences, Journal of Computational biology, 7(1-2), 2000, 203-214.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-bf57973e-f822-4d28-be7f-162d2b83cc4e
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