KEMB: A Keyword-Based XML Message Broker

KEMB: A Keyword-Based XML Message Broker
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KEMB:基于关键字的 XML 消息代理

DOI:
10.1109/tkde.2010.159
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发表时间:
2011-07
影响因子:
8.9
通讯作者:
Lizhu Zhou
Lizhu Zhou
中科院分区:
计算机科学2区
文献类型:
--
作者:
Guoliang Li;Jianhua Feng;Jianyong Wang;Lizhu Zhou

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研究了用户订阅关键字查询模板的XML消息代理问题,提出了一种基于关键字的XML消息代理(KEMB)。与传统的基于路径表达式的XML消息代理不同,KEMB以关键字查询的形式存储了大量的用户配置文件,这些配置文件捕获了用户/应用程序的数据需求,而不是路径表达式,如XPath/XQuery表达式。KEMB带来了新的挑战:1)如何有效地识别XML数据流中关键字查询的相关答案;2)如何高效地回答大量并发的关键字查询。我们采用紧凑的最低共同祖先(CLCA)来有效地识别相关答案。我们设计了一种基于自动机的方法来处理大量的查询,并设计了一种有效的优化策略来提高性能和可扩展性。我们已经在各种数据集上实施并评估了KEMB。实验结果表明,KEMB具有较高的性能和很好的可扩展性。
This paper studies the problem of XML message brokering with user subscribed profiles of keyword queries and presents a KEyword-based XML Message Broker (KEMB) to address this problem. In contrast to traditional-path-expressions-based XML message brokers, KEMB stores a large number of user profiles, in the form of keyword queries, which capture the data requirement of users/applications, as opposed to path expressions, such as XPath/XQuery expressions. KEMB brings new challenges: 1) how to effectively identify relevant answers of keyword queries in XML data streams; and 2) how to efficiently answer large numbers of concurrent keyword queries. We adopt compact lowest common ancestors (CLCAs) to effectively identify relevant answers. We devise an automaton-based method to process large numbers of queries and devise an effective optimization strategy to enhance performance and scalability. We have implemented and evaluated KEMB on various data sets. The experimental results show that KEMB achieves high performance and scales very well.
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