Data-Oriented Scheduling with Dynamic-Clustering Fault-Tolerant Technique for Scientific Workflows in Clouds
Author:
Publisher
Pleiades Publishing Ltd
Subject
Software
Link
http://link.springer.com/content/pdf/10.1134/S0361768819080097.pdf
Reference44 articles.
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3. Lifka, D., et al., XSEDE Cloud Survey Report, Urbana, IL: Natl. Center Supercomput. Appl., 2013.
4. Li, X., Song, J., and Huang, B., A scientific workflow management system architecture and its scheduling based on cloud service platform for manufacturing big data analytics, Int. J. Adv. Manuf. Technol., 2016, vol. 84, nos. 1–4, pp. 119–131.
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