CI-ADDO-NEW: Storage System Trace Collection

“这项奖励是根据2009年美国复苏和再投资法案（公法111-5）资助的。”存储系统研究人员通常使用来自各种来源的I/O轨迹来驱动他们的分析和研究。然而，这些I/O跟踪无法充分捕捉到I/O对应用程序性能的影响。此外，它们不能与整个系统的其他部分（无论是应用程序、系统还是处理器）进行扩展。因此，很难重放跟踪以便在存储系统评估中使用。这尤其成问题，因为许多现存的公开可用的I/O跟踪都相当陈旧。该项目的重点是为存储研究社区提供一组跟踪，以便对存储技术进行准确的重播和评估。跟踪将来自存储系统层次结构中不同级别的实际系统，包括网络层、文件系统和低级磁盘。这些跟踪包括存储社区中目前不存在的跟踪，如iSCSI跟踪、虚拟机跟踪和MS Exchange跟踪。该项目还将提供一组工具，用于跟踪依赖于应用程序的I/O、重放跟踪和分析。工具和收集到的痕迹将通过公共资源作为社区资源提供。这个项目更广泛的影响包括提供工具和跟踪，可以帮助存储系统研究人员开发新的I/O系统技术。由于存储系统对当前的基于信息的经济至关重要，因此理解I/O系统行为的进展应该是非常有益的。它也应该对国家利益的数据密集型应用有用，如基因组计划、天气模拟和数字图书馆。

"This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5)."Storage system researchers have typically used I/O traces from various sources to drive their analysis and research. However, these I/O traces fail to adequately capture the effect of I/O on application performance. Moreover, they do not scale with other parts of the overall system whether it be application, systems, or processor. As a result, it is difficult to replay the trace for use in storage systems evaluation. This is particularly problematic since many of the extant publicly available I/O traces are quite old.The focus of the project is to provide to the storage research community a set of traces that will allow for accurate replay and evaluation of storage technologies. The traces will be from real systems at different levels of the storage system hierarchy including network layer, file system, and low-level disk. These include traces that do not currently exist in the storage community such as iSCSI traces, virtual machine traces, and MS Exchange traces. The project will also provide a set of tools for tracing application dependent I/O, replaying traces, and analysis. The tools and collected traces will be made available as a community resource through publicly available sources.The broader impacts of this project include providing tools and traces that can assist storage system researchers in developing new I/O system technologies. Since storage systems are critical to the current information-based economy, advances in understanding I/O system behavior should be highly beneficial. It should also be useful to data-intensive applications of national interest such as the genome project, weather simulation, and digital libraries.