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System Support for Distributed Information Change Monitoring

System Support for Distributed Information Change Monitoring
分布式信息变更监控的系统支持
批准号:
9988452
负责人:
Ling Liu
金额:
$28.0万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2000
资助国家:
美国
项目状态:
已结题
起止时间:
2000-07-01 至 2003-12-31

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中文摘要
翻译
该项目调查的设计和实施问题,在大型分布式网络,如互联网和万维网的信息变化的监测。 目标之一是开发有效的和可扩展的策略,技术和系统支持的分布式控制大量的信息变化监测请求。 需要解决的研究问题包括以下几个方面。 哪些软件技术和工具能够提取、集成和查询半结构化或非结构化数据上的数据流? 哪种分布式触发器和数据处理技术在存在数百万信息更改监控请求的情况下最具可扩展性且最有效? 在运行时环境(如Internet)中,变更监视器如何适应广泛的系统参数变化? 随着信息源的数量达到数百万,它们如何扩大规模? 关键系统组件包括变化检测算法(例如,用于网页的树比较)、触发器和查询分组、索引和高速缓存以及并行处理。 将通过因特网上的模拟和测量来实施和评价适当的组成部分。 这些实验将强调互联网规模的信息变化监测系统的效率和可扩展性。 研究结果将有助于系统和中间件软件支持的工程,实施和评估,以支持分布式触发器和查询的可扩展和高效处理,以及有效检测和通知信息更改。
英文摘要
The project investigates the design and implementation issues in the mointoring of information changes in large distributed networks such as the Internet and World Wide Web. One of the objectives is to develop efficient and scalable strategies, techniques, and systems support for distributed control of large numbers of information change monitoring requests. Research questions to be addressed include the following. What software techniques and tools are able to extract, integrate, and query streams of data over semi-structured or unstructured data? Which distributed trigger and data processing techniques are most scalable and yet efficient in the presence of millions of information change monitoring requests? How do change monitors adapt to wide system parameter variations in runtime environments such as the Internet? How do they scale up as the number of information sources reach millions? Critical system components include change detection algorithms (e.g., tree comparison for web pages), trigger and query grouping, indexing, and caching, as well as parallel processing. Appropriate components will be implemented and evaluated through simulation and measurements on the Internet. These experiments will emphasize the efficiency and scalability of Internet-scale information change monitoring systems. The research results will aid in the engineering, implementation and evaluation of systems and middleware software support for scalable and efficient processing of distributed triggers and queries, as well as effective detection and notification of information changes.
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