GRID '11 Proceedings of the 2011 IEEE/ACM 12th International Conference on Grid Computing
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Scientific workflow is emerging as a promising scientific computing paradigm to offer the convenience for the scientists to resolve complex scientific problems. To successfully execute a scientific workflow, the workflow creation by depending on service discovery techniques should be made in the first place. Particularly, semantics have been proposed as a key to automatically solve service discovery issue for facilitating users to create a workflow. However, most of the semantic service discovery methods still remain at a low-efficiency stage because they generally involve a large number of ontology reasoning that is often time consuming. To address this issue, we present an efficient service discovery method by building Quick Service Query list (QSQL) to support automated service discovery for creating a workflow. QSQL based on graph storage theory is an efficient service index list that is dynamically built by service publication algorithm. In QSQL, semantic relationships between the published services and all related ontology concepts can be processed in advance so that a large number of ontology reasoning can be avoided during service discovery. Further, our proposed discovery algorithm can efficiently select service models from QSQL to match a user query. The final experiments further demonstrate the feasibility and the efficiency of our proposed method. Copyright © 2009 John Wiley & Sons, Ltd. A preliminary version of this paper has been published in the Proceedings of 2007 IEEE Asia–Pacific Service Computing Conference (APSCC 2007), 11–14 December 2007, Tsukuba Science City, Japan.