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Towards Complete Tracking of Provenance in Experimental Distributed Systems Research

机译:全面跟踪实验分布式系统研究中的来源

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摘要

Running experiments on modern systems like supercomputers, cloud infrastructures or P2P networks became very complex, both technically and methodologically. It is difficult to re-run an experiment or understand its results even with technical background on the technology and methods used. Storing the provenance of experimental data, i.e., storing information about how the results were produced, proved to be a powerful tool to address similar problems in computational natural sciences. In this paper, we (1) survey provenance collection in various domains of computer science, (2) introduce a new classification of provenance types, and (3) sketch a design of a provenance system inspired by this classification.
机译:在现代系统(例如超级计算机,云基础架构或P2P网络)上进行实验,无论从技术还是方法上都变得非常复杂。即使具有所使用技术和方法的技术背景,也很难重新运行实验或理解其结果。存储实验数据的来源,即存储有关如何产生结果的信息,被证明是解决计算自然科学中类似问题的有力工具。在本文中,我们(1)在计算机科学的各个领域中调查来源集合,(2)介绍一种新的来源类型分类,并且(3)绘制受此分类启发的来源系统设计。

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