Abstract
The advancement of Grid and Web service technologies greatly facilitates the aggregation of distributed applications. As the grid workflow generally involves long lasting execution tasks, the quality optimization for grid workflow has much significant importance. In order to accurately define the quality of grid workflow, an extended quality model is proposed which takes account of message compositionality and composition rationality between Web services. Based on the extended quality model, a distributed multi-objective genetic algorithm to optimize the quality of grid workflow is proposed. This approach focuses on the distributed nature of grid environment that consists of autonomous domains and can deal with the global multiple objectives and constrains. The experimental results show that the distributed multi-objective genetic algorithm proposed in this paper can effectively optimize the services selection for grid workflow and has ideal performance.
This work is supported by National Science Foundation of China under grant 60503041, Shanghai Commission of Science and Technology/International Cooperation Project under grand 05SN07114, Scientific Research Project for Shanghai 2010 World Expo under grand 2005BA908B09 and National High-Tech Research and Development Plan of China under grand 2006AA04Z152.
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Tong, H., Cao, J., Zhang, S. (2007). A Distributed Genetic Algorithm for Optimizing the Quality of Grid Workflow. In: Chang, K.CC., et al. Advances in Web and Network Technologies, and Information Management. APWeb WAIM 2007 2007. Lecture Notes in Computer Science, vol 4537. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72909-9_44
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DOI: https://doi.org/10.1007/978-3-540-72909-9_44
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