CISE Research Instrumentation: Semantics-based Prefetching for Mobile Computing

CISE Research Instrumentation：用于移动计算的基于语义的预取

• 批准号: 9529304
• 负责人: Gail Kaiser
• 金额: $ 4.67万
• 依托单位: Columbia University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1996
• 资助国家: 美国
• 起止时间: 1996-02-15 至 1997-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9529304&HistoricalAwards=false
• 关键词: CISE; Research; Instrumentation; Semantics; based

CDA 95-29304 Kaiser, Gail E. Duchamp, Daniel J. Columbia University Semantics-based Prefetching for Mobile Computing This proposal investigates collaborative workflow environments, and previously constructed an infrastructure that assumes conventional high-speed networking. Professor Kaiser is developing new algorithms and techniques to support mobile hosts. The research addresses prefetching based on semantic information on what the user is likely to do next drawn from the workflow definition tailoring the specific environment instance, to permit low-bandwidth and temporarily detached operation by participants in collaborative enterprises. Professor Duchamp is developing operating system support for intelligently prefetching files from a file system or objects from an objectbase. The goal is to improve performance and automate cache loading prior to disconnecting from the network, via two types of prefetching: The first is performed by the file system, transparent to applications; the file system ``learns'' file access patterns and uses these patterns to prefetch if/when the patterns recur. The second type of prefetching is application-directed; applications with knowledge of their future data accesses can use a special interface to instruct the operating system what to prefetch. Professor Kaiser's workflow system is the major example application for this type of prefetching. Both the collaborative work and operating systems directions require mobile notebook computers for development, testing, and measurement of the prototype support.

CDA 95-29304 Kaiser，Gail E. 丹尼尔·杜尚 哥伦比亚大学 面向移动的计算的语义预取 该提案调查了协作工作流环境，并在此之前构建了一个假设传统高速网络的基础设施。 Kaiser教授正在开发新的算法和技术来支持移动的主机。 该研究解决了预取的语义信息的基础上，用户可能会做下一步从工作流定义裁剪特定的环境实例，允许低带宽和暂时分离的操作参与者在协作企业。 Duchamp教授正在开发操作系统支持，以智能地从文件系统预取文件或从对象库预取对象。 目标是通过两种类型的预取来提高性能并在断开网络之前自动加载缓存：第一种是由文件系统执行的，对应用程序透明;文件系统“学习”文件访问模式，并在模式重现时使用这些模式进行预取。 第二种类型的预取是面向应用程序的;知道其未来数据访问的应用程序可以使用特殊接口来指示操作系统预取什么。 Kaiser教授的工作流系统是这种类型的预取的主要示例应用程序。 协作工作和操作系统方向都需要移动的笔记本计算机来进行原型支持的开发、测试和测量。