A QoS-aware exception handling method in scientific workflow execution

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Title: A QoS-aware exception handling method in scientific workflow execution
Author(s): Qi, Lianyong; Lin, Wenmin; Dou, Wanchun; Jiang, Jian; Chen, Jinjun
Abstract: Scientific workflow is gaining ever-increasing attention as it integrates a wide range of heterogeneous services to enable and accelerate the scientific discovery processes. However, the exception occurred in a scientific workflow execution often decreases the robustness of a scientific workflow system. For example, if a service engaged in a scientific workflow schedule becomes unavailable during its execution, an exception might be raised and the whole workflow execution may be interrupted unexpectedly. In this situation, it is a challenge to smooth the interrupted workflow execution. In view of this challenge, an exception handling method, named RelaxingMe (constraints Relaxing Method, RelaxingMe) is proposed in this paper. This method aims at relaxing the original QoS constraint values requested by the interrupted task node, in order to find a near-to-optimal candidate service to replace the unavailable one. At last, the feasibility of our method is evaluated by an experiment.
Publication type: Journal article
Research centre: Swinburne University of Technology. Faculty of Information and Communication Technologies
Source: Concurrency and Computation: Practice and Experience: selected papers from the Fourth International Workshop on Workﬂow Management (ICWM2009), Geneva, Switzerland, 04 May 2009, Vol. 23, no. 16 (Nov 2011), pp. 1951-1968
Publication year: 2011
FOR Code(s): 0805 Distributed Computing
Keyword(s): Exception handling; QoS; Quality of service; Relaxed solution; Scientific workflow; Service re-selection
Publisher: John Wiley & Sons
ISSN: 1532-0626
Publisher URL: http://dx.doi.org/10.1002/cpe.1737
Additional information: The authors acknowledge support from the National Science Foundation of China under Grant Nos. 61021062, 61073032 and 60736015, and Jiangsu Provincial NSF Project under Grants BK2008017.
Peer reviewed