Abstract
Scientific workflow allows automating the workflow procedure through a compilation of known sequences of actions in distributed environments such as the cloud. Preliminary benefits have been seen in realizing scientific workflows on the cloud. However, there is a notable absence of a holistic view in current scientific workflow systems that, on one hand, capture the evolving context when designing workflow models; and on the other hand, help a specific user interact with the system during QoS prediction and dynamic selection of the relevant cloud services. In this chapter, recent works on designing scientific workflows are first reviewed by discussing the opportunities and challenges respectively. The author then proposes a contextualized approach and research directions to improve the designing of scientific workflows in the user-oriented paradigm. Finally, a case study in drug design process is presented to evaluate the contextualized methodology. The contextualized approach could be considered as an effective way of addressing the socio-technical issues in designing scientific workflows in the cloud.
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Notes
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Eclipse Helios Sr2 Packages. Available via: http://www.eclipse.org/downloads/packages/release/helios/sr2.
- 2.
Java Development Kit 1.6.0. Available via: http://www.java.com/en/download/manual.jsp.
- 3.
ActiveBPEL engine. Available via: http://www.activevos.com.
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Acknowledgments
This work is supported by the grants from Natural Science Foundation of China (61300232), Natural Science Foundation of Gansu Province in China (1208RJZA278), and the Fundamental Research Funds for the Central Universities (lzujbky-2013-40).
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Fan, X. (2014). Contextualized Scientific Workflows in the Cloud. In: Brézillon, P., Gonzalez, A. (eds) Context in Computing. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-1887-4_12
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