Data Flow Driven Scheduling of BPEL Workflows Using Cloud Resources
In this paper, an approach to assign BPEL workflow steps to available resources is presented. The approach takes data dependencies between workflow steps and the utilization of resources at runtime into account. The developed scheduling algorithm simulates whether the makespan of workflows could be...
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| creator | Dörnemann, Tim Juhnke, Ernst Noll, Thomas Seiler, Dominik Freisleben, Bernd |
| description | In this paper, an approach to assign BPEL workflow steps to available resources is presented. The approach takes data dependencies between workflow steps and the utilization of resources at runtime into account. The developed scheduling algorithm simulates whether the makespan of workflows could be reduced by providing additional resources from a Cloud infrastructure. If yes, Cloud resources are automatically set up and used to increase throughput. The proposed approach does not require any changes to the BPEL standard. An implementation based on the ActiveBPEL engine and Amazon's Elastic Compute Cloud is presented. Experimental results for a real-life workflow from a medical application indicate that workflow execution times can be reduced significantly. |
| doi_str_mv | 10.1109/CLOUD.2010.40 |
| format | Conference Proceeding |
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| fulltext | fulltext_linktorsrc |
| identifier | ISSN: 2159-6182 |
| ispartof | 2010 IEEE 3rd International Conference on Cloud Computing, 2010, p.196-203 |
| issn | 2159-6182 2159-6190 |
| language | eng |
| recordid | cdi_ieee_primary_5557994 |
| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | BPEL Business Cloud Clouds Data flow Engines genetic algorithm Runtime scheduling Scheduling algorithm SOA Web services workflow |
| title | Data Flow Driven Scheduling of BPEL Workflows Using Cloud Resources |
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