An adaptive multi-objective evolutionary algorithm for constrained workflow scheduling in Clouds-Reference-Cited by-同舟云学术

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An adaptive multi-objective evolutionary algorithm for constrained workflow scheduling in Clouds

Published:2017-12-02 Issue:2 Volume:36 Page:339-368
ISSN:0926-8782
Container-title:Distributed and Parallel Databases
language:en
Short-container-title:Distrib Parallel Databases

Author:

Zhang Miao,Li Huiqi,Liu Li,Buyya Rajkumar

Publisher

Springer Science and Business Media LLC

Subject

Information Systems and Management,Hardware and Architecture,Information Systems,Software

Link

http://link.springer.com/article/10.1007/s10619-017-7215-z/fulltext.html

Reference41 articles.

1. Vöckler, J.S., Juve, G., Deelman, E., et al.: Experiences using cloud computing for a scientific workflow application, pp. 15–24. International Workshop on Scientific Cloud, Computing (2011)

2. Zhu, Z., Zhang, G., Li, M., et al.: Evolutionary multi-objective workflow scheduling in cloud. IEEE Trans. Parallel Distrib. Syst. 27(5), 1344–1357 (2016)

3. Juve, G., Chervenak, A., Deelman, E., et al.: Characterizing and profiling scientific workflows. Future Gener. Comput. Syst. 29(3), 682–692 (2013)

4. Buyya, R., Yeo, C.S., Venugopal, S., et al.: Cloud computing and emerging IT platforms: vision, hype, and reality for delivering computing as the 5th utility. Future Gener. Comput. Syst. 25(6), 599–616 (2009)

5. Foster, I., Zhao, Y., Raicu, I., et al.: Cloud computing and grid computing 360-degree compared. Grid Computing Environments Workshop, 2008. GCE ’08, pp. 1–10. IEEE, New York (2009)

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