Composing geoinformatics workflows with user preferences

ABSTRACT

With the advent of the data grid came a novel distributed scientific computing paradigm known as service-oriented science. Among the plethora of systems included under this framework are scientific workflow management systems, which enable large-scale process scheduling and execution. To ensure quality of service, these systems typically seek to minimize workflow execution time as well as costs for slices of data grid access. The geospatial domain, among other sciences, involves yet another optimization factor, the accuracy of results. The relationship between execution time and workflow accuracy can often be exploited to offer more flexibility in handling user preferences. We present a system which meets user constraints through a dynamic adjustment of the accuracy of workflow results.

REFERENCES

• 1: A. Afzal, J. Darlington, and A. S. McGough. Qos-constrained stochastic workflow scheduling in enterprise and scientific grids. In GRID, pages 1--8, 2006.
• 2: Nadine Alameh, Chaining Geographic Information Web Services, IEEE Internet Computing, v.7 n.5, p.22-29, September 2003 [doi>10.1109/MIC.2003.1232514]
• 3: D. Chiu and G. Agrawal. Enabling ad hoc queries over low-level geospatial datasets. Technical Report OSU-CISRC-01/08--TR01, The Ohio State University, 2008.
• 4: D. Chiu, S. Deshpande, G. Agrawal, and R. Li. Composing geoinformatics workflows with user preferences. Technical Report OSU-CISRC-08/08--TR44, The Ohio State University, 2008.
• 5: D. Chiu, S. Deshpande, G. Agrawal, and R. Li. Cost and accuracy sensitive dynamic workflow composition over grid environments. In Proceedings of the 9th IEEE/ACM International Conference on Grid Computing (Grid'08), 2008.
• 6: N. A. C. Cressie. Statistics for Spatial Data. Wiley Series in Probability and Statistics, 1993.
• 7: L. Di, P. Yue, W. Yang, G. Yu, P. Zhao, and Y. Wei. Ontology-supported automatic service chaining for geospatial knowledge discovery. In Proceedings of American Society of Photogrammetry and Remote Sensing, 2007.
• 8: Metadata ad hoc working group, content standard for digital geospatial metadata, 1998.
• 9: Gobe Hobona , David Fairbairn , Philip James, Semantically-assisted geospatial workflow design, Proceedings of the 15th annual ACM international symposium on Advances in geographic information systems, November 07-09, 2007, Seattle, Washington [doi>10.1145/1341012.1341046]
• 10: Rob Lemmens , Andreas Wytzisk , Rolf de By , Carlos Granell , Michael Gould , Peter van Oosterom, Integrating Semantic and Syntactic Descriptions to Chain Geographic Services, IEEE Internet Computing, v.10 n.5, p.42-52, September 2006 [doi>10.1109/MIC.2006.106]
• 11: R. Raskin and M. Pan. Knowledge representation in the semantic web for earth and environmental terminology (sweet). Computer and Geosciences, 31(9):1119--1125, 2005.
• 12: Marek Wieczorek , Radu Prodan , Thomas Fahringer, Scheduling of scientific workflows in the ASKALON grid environment, ACM SIGMOD Record, v.34 n.3, September 2005 [doi>10.1145/1084805.1084816]
• 13: Peng Yue , Liping Di , Wenli Yang , Genong Yu , Peisheng Zhao, Semantics-based automatic composition of geospatial Web service chains, Computers & Geosciences, v.33 n.5, p.649-665, May, 2007 [doi>10.1016/j.cageo.2006.09.003]
• 14: Liangzhao Zeng , Boualem Benatallah , Anne H.H. Ngu , Marlon Dumas , Jayant Kalagnanam , Henry Chang, QoS-Aware Middleware for Web Services Composition, IEEE Transactions on Software Engineering, v.30 n.5, p.311-327, May 2004 [doi>10.1109/TSE.2004.11]

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.4 Systems and Software

Keywords:
QoS, accuracy awareness, geospatial workflows