Harnessing the Computing Continuum for Urgent Science
Harnessing the Computing Continuum for Urgent Science
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DOI：
10.1145/3439602.3439618
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发表时间：
2020-11
期刊：
影响因子：
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通讯作者：
Daniel Balouek-Thomert;I. Rodero;M. Parashar
中科院分区：
文献类型：
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作者：
Daniel Balouek-Thomert;I. Rodero;M. Parashar
紧急科学描述了时间关键的、数据驱动的科学工作流，这些工作流可以及时利用分布式数据源，以促进重要决策的制定。虽然我们生成数据的能力正在急剧扩大，但我们管理、分析这些数据并将其及时转化为知识的能力却没有跟上步伐。本文探讨了如何利用计算连续体，即边缘、核心和中间的资源，来支持紧迫的科学，并讨论了相关的研究挑战。使用早期地震预警(EEW)工作流，该工作流结合来自地理分布式地震仪和高精度GPS站的数据流来检测大型地面运动，作为驱动因素，我们提出了一个系统堆栈，该系统堆栈可以跨整个计算连续体的动态基础设施实现分布式分析的流体集成。
Urgent science describes time-critical, data-driven scientific work-flows that can leverage distributed data sources in a timely way to facilitate important decision making. While our capacity for generating data is expanding dramatically, our ability to manage, analyze, and transform this data into knowledge in a timely manner has not kept pace. This paper explores how the computing continuum, spanning resources at the edges, in the core, and in-between, can be harnessed to support urgent science and discusses associated research challenges. Using an Early Earthquake Warning (EEW) workflow, which combines data streams from geo-distributed seismometers and high-precision GPS stations to detect large ground motions, as a driver, we propose a system stack that can enable the fluid integration of distributed analytics across a dynamic infrastructure spanning the computing continuum.