GCIP: exploiting the generation and optimization of integration processes

ABSTRACT

As a result of the changing scope of data management towards the management of highly distributed systems and applications, integration processes have gained in importance. Such integration processes represent an abstraction of workflow-based integration tasks. In practice, integration processes are pervasive and the performance of complete IT infrastructures strongly depends on the performance of the central integration platform that executes the specified integration processes. In this area, the three major problems are: (1) significant development efforts, (2) low portability, and (3) inefficient execution. To overcome those problems, we follow a model-driven generation approach for integration processes. In this demo proposal, we want to introduce the so-called GCIP Framework (Generation of Complex Integration Processes) which allows the modeling of integration process and the generation of different concrete integration tasks. The model-driven approach opens opportunities for rule-based and workload-based optimization techniques.

REFERENCES

• 1: A. Albrecht and F. Naumann. Managing etl processes. In Workshop New Trends in Information Integration (NTII), 2008.
• 2: M. Böhm, D. Habich, W. Lehner, and U. Wloka. Dipbench: An independent benchmark for data intensive integration processes. In IIMAS, 2008.
• 3: M. Böhm, D. Habich, W. Lehner, and U. Wloka. Dipbench toolsuite: A framework for benchmarking integration systems. In ICDE, 2008.
• 4: M. Böhm, D. Habich, W. Lehner, and U. Wloka. Model-driven generation and optimization of complex integration processes. In ICEIS, 2008.
• 5: M. Böhm, D. Habich, U. Wloka, J. Bittner, and W. Lehner. Towards self-optimization of message transformation processes. In ADBIS, 2007.
• 6: S. Dessloch, M. A. Hernandez, R. Wisnesky, A. Radwan, and J. Zhou. Orchid: Integrating schema mapping and etl. In ICDE, 2008.
• 7: Zachary G. Ives , Alon Y. Halevy , Daniel S. Weld, Adapting to source properties in processing data integration queries, Proceedings of the 2004 ACM SIGMOD international conference on Management of data, June 13-18, 2004, Paris, France [doi>10.1145/1007568.1007613]
• 8: H. Li and D. Zhan. Workflow timed critical path optimization. Nature and Science, 3(2), 2005.
• 9: Alkis Simitsis , Panos Vassiliadis , Timos Sellis, Optimizing ETL Processes in Data Warehouses, Proceedings of the 21st International Conference on Data Engineering, p.564-575, April 05-08, 2005 [doi>10.1109/ICDE.2005.103]
• 10: Utkarsh Srivastava , Kamesh Munagala , Jennifer Widom , Rajeev Motwani, Query optimization over web services, Proceedings of the 32nd international conference on Very large data bases, September 12-15, 2006, Seoul, Korea
• 11: Marko Vrhovnik , Holger Schwarz , Oliver Suhre , Bernhard Mitschang , Volker Markl , Albert Maier , Tobias Kraft, An approach to optimize data processing in business processes, Proceedings of the 33rd international conference on Very large data bases, September 23-27, 2007, Vienna, Austria