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Data-Intensive Scientific Workflows for Grid Computing with CSCL

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1 Author(s)
Rurui Zhou ; Sch. of Comput. Sci., Yangtze Univ., Jingzhou, China

In terms of several new technologies, such as ubiquitous computing, ontology engineering, semantic web and grid computing, this paper proposes a kind of flexible educational platform architecture for Computer-Supported Collaborative Learning (CSCL). With data-intensive scientific workflows, it is promising to gain concept reusability, device and user adaptability, automatic composition, function and performance scalability. In the meantime, the grid-based system design of workflow creation simulation is also proposed. Experiments indicate that this architecture is viable and flexible. At last, the author discusses some problems of CSCL and the next work.

Published in:

Genetic and Evolutionary Computing (ICGEC), 2010 Fourth International Conference on

Date of Conference:

13-15 Dec. 2010