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Cloud data management for scientific workflows: research issues, methodologies, and state-of-the-art

Yuan, Dong, Cui, Lizhen and Liu, Xiao 2014, Cloud data management for scientific workflows: research issues, methodologies, and state-of-the-art, in SKG 2014 : Proceedings of the 2014 10th International Conference on Semantics, Knowledge and Grids, IEEE, Piscataway, N.J., pp. 21-28, doi: 10.1109/SKG.2014.37.

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Title Cloud data management for scientific workflows: research issues, methodologies, and state-of-the-art
Author(s) Yuan, Dong
Cui, Lizhen
Liu, XiaoORCID iD for Liu, Xiao orcid.org/0000-0001-8400-5754
Conference name Semantics, Knowledge and Grids. International Conference (10th : 2014 : Beijing, China)
Conference location Beijing, China
Conference dates 2014/08/27 - 2014/08/29
Title of proceedings SKG 2014 : Proceedings of the 2014 10th International Conference on Semantics, Knowledge and Grids
Publication date 2014
Conference series Semantics, Knowledge and Grids International Conference
Start page 21
End page 28
Total pages 8
Publisher IEEE
Place of publication Piscataway, N.J.
Keyword(s) scientific workflow
data management
cloud computing
research issues
Summary Data-intensive scientific applications are posing many challenges in distributed computing systems. In the scientific field, the application data are expected to double every year over the next decade and further. With this continuing data explosion, high performance computing systems are needed to store and process data efficiently, and workflow technologies are facilitated to automate these scientific applications. Scientific workflows are typically very complex. They usually have a large number of tasks and need a long time for execution. Running scientific workflow applications usually need not only high performance computing resources but also massive storage. The emergence of cloud computing technologies offers a new way to develop scientific workflow systems. Scientists can upload their data and launch their applications on the scientific cloud workflow systems from everywhere in the world via the Internet, and they only need to pay for the resources that they use for their applications. As all the data are managed in the cloud, it is easy to share data among scientists. This kind of model is very convenient for users, but remains a big challenge to the system. This paper proposes several research topics of data management in scientific cloud workflow systems, and discusses their research methodologies and state-of-the-art solutions.
ISBN 9781479967155
Language eng
DOI 10.1109/SKG.2014.37
Field of Research 080608 Information Systems Development Methodologies
HERDC Research category E1.1 Full written paper - refereed
ERA Research output type E Conference publication
Copyright notice ©2014, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30087746

Document type: Conference Paper
Collection: School of Information Technology
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