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Cloud Data Management for Scientific Workflows: Research Issues, Methodologies, and State-of-the-Art
2014
2014 10th International Conference on Semantics, Knowledge and Grids
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
doi:10.1109/skg.2014.37
dblp:conf/skg/YuanCL14
fatcat:suphvnfsujgc3ps2tbvsj6zaya