论高保证科学工作流程

M. Vouk, Pierre Mouallem
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引用次数: 5

摘要

科学工作流管理系统(S-WFMS),如开普勒,已被证明是解决科学问题的重要工具。有趣的是,S-WFMS的容错和故障恢复仍然是一个开放的话题。它通常涉及经典的容错机制,例如可选版本和带有重新运行的回滚,依赖于子组件和较低层(如调度器、网格和云资源)或底层操作系统提供的容错功能。当底层发生故障时,工作流系统将其视为流程中失败的步骤,但通常没有额外的细节。这限制了S-WFMS从故障中恢复的能力。我们描述了一个轻量级的端到端S-WFMS容错框架,用于处理一些现实生活中的科学工作流中出现的故障模式。讨论了该框架的功能和局限性,并利用仿真对其进行了评估。结果表明,该方案大大提高了工作流的可靠性和执行时间的稳定性。
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On High-Assurance Scientific Workflows
Scientific Workflow Management Systems (S-WFMS), such as Kepler, have proven to be an important tools in scientific problem solving. Interestingly, S-WFMS fault-tolerance and failure recovery is still an open topic. It often involves classic fault-tolerance mechanisms, such as alternative versions and rollback with re-runs, reliance on the fault-tolerance capabilities provided by subcomponents and lower layers such as schedulers, Grid and cloud resources, or the underlying operating systems. When failures occur at the underlying layers, a workflow system sees this as failed steps in the process, but frequently without additional detail. This limits S-WFMS' ability to recover from failures. We describe a light weight end-to-end S-WFMS fault-tolerance framework, developed to handle failure patterns that occur in some real-life scientific workflows. Capabilities and limitations of the framework are discussed and assessed using simulations. The results show that the solution considerably increase workflow reliability and execution time stability.
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