Automated runtime recovery for QoS-based service composition
Service composition uses existing service-based applications as components to achieve a business goal. The composite service operates in a highly dynamic environment; hence, it can fail at any time due to the failure of component services. Service composition languages such as BPEL provide a compens...
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| Main Authors: | , , , , , |
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| Format: | text |
| Language: | English |
| Published: |
Institutional Knowledge at Singapore Management University
2014
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| Subjects: | |
| Online Access: | https://ink.library.smu.edu.sg/sis_research/4994 https://ink.library.smu.edu.sg/context/sis_research/article/5997/viewcontent/2566486.2568048.pdf |
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| Institution: | Singapore Management University |
| Language: | English |
| Summary: | Service composition uses existing service-based applications as components to achieve a business goal. The composite service operates in a highly dynamic environment; hence, it can fail at any time due to the failure of component services. Service composition languages such as BPEL provide a compensation mechanism to rollback the error. But such a compensation mechanism has several issues. For instance, it cannot guarantee the functional properties of the composite service after compensation. In this work, we propose an automated approach based on a genetic algorithm to calculate the recovery plan that could guarantee the satisfaction of functional properties of the composite service after recovery. Given a composite service with large state space, the proposed method does not require exploring the full state space of the composite service; therefore, it allows efficient selection of recovery plan. In addition, the selection of recovery plans is based on their quality of service (QoS). A QoS-optimal recovery plan allows effective recovery from the state of failure. Our approach has been evaluated on real-world case studies, and has shown promising results. |
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