松耦合科学工作流中动态任务触发的权衡研究
Exploring Trade-offs in Dynamic Task Triggering for Loosely Coupled Scientific Workflows
摘要：
为了实现近时间的见解，科学工作流程往往是以灵活和动态的方式组织。数据驱动的任务触发已经被探索为支持基于数据发展的工作流的一种方式。然而，这种任务的动态触发所引入的开销是一个研究不足的主题。本文讨论了动态任务触发器的不同方面。特别是，我们探索不同的方式来构建一个数据驱动的动态工作流，然后评估这样的设计决策所引入的开销。我们评估工作流与不同的数据大小，有趣的数据，时间数据分布的百分比，和触发的任务数。最后，我们根据对评估结果的分析，为希望构建数据驱动的科学工作流程的用户提供建议。
英文摘要：
In order to achieve near-time insights, scientific workflows tend to be organized in a flexible and dynamic way. Data-driven triggering of tasks has been explored as a way to support workflows that evolve based on the data. However, the overhead introduced by such dynamic triggering of tasks is an under-studied topic. This paper discusses different facets of dynamic task triggers. Particularly, we explore different ways of constructing a data-driven dynamic workflow and then evaluate the overheads introduced by such design decisions. We evaluate workflows with varying data size, percentage of interesting data, temporal data distribution, and number of tasks triggered. Finally, we provide advice based upon analysis of the evaluation results for users looking to construct data-driven scientific workflows.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
