Preventing Temporal Violations in Scientific Workflows: Where and How

Due to the dynamic nature of the underlying high-performance infrastructures for scientific workflows such as grid and cloud computing, failures of timely completion of important scientific activities, namely, temporal violations, often take place. Unlike conventional exception handling on functiona...

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Bibliographic Details
Published in:IEEE transactions on software engineering 2011-11, Vol.37 (6), p.805-825
Main Authors: Liu, Xiao, Yang, Yun, Jiang, Yuanchun, Chen, Jinjun
Format: Article
Language:English
Subjects:
Analysis
Cloud computing
Communication
Communications technology
Computer simulation
Consistency
Decision support systems
Digital Object Identifier
Disaster recovery
Exception handling
Exceptions
Failure
Infrastructure
Monitoring
Prevention
Quality of service
Reliability
Software engineering
Software reliability
software verification
Statistical methods
Strategy
Studies
Temporal logic
Violations
Workflow
Workflow management
Workflow management software
Workflow software
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Summary:Due to the dynamic nature of the underlying high-performance infrastructures for scientific workflows such as grid and cloud computing, failures of timely completion of important scientific activities, namely, temporal violations, often take place. Unlike conventional exception handling on functional failures, nonfunctional QoS failures such as temporal violations cannot be passively recovered. They need to be proactively prevented through dynamically monitoring and adjusting the temporal consistency states of scientific workflows at runtime. However, current research on workflow temporal verification mainly focuses on runtime monitoring, while the adjusting strategy for temporal consistency states, namely, temporal adjustment, has so far not been thoroughly investigated. For this issue, two fundamental problems of temporal adjustment, namely, where and how, are systematically analyzed and addressed in this paper. Specifically, a novel minimum probability time redundancy-based necessary and sufficient adjustment point selection strategy is proposed to address the problem of where and an innovative genetic-algorithm-based effective and efficient local rescheduling strategy is proposed to tackle the problem of how. The results of large-scale simulation experiments with generic workflows and specific real-world applications demonstrate that our temporal adjustment strategy can remarkably prevent the violations of both local and global temporal constraints in scientific workflows.
ISSN:0098-5589
1939-3520
DOI:10.1109/TSE.2010.99