面向EAI的基于内容的pub/sub系统中的扩展事件匹配方法

Gang Xu, W. Xu, Tao Huang
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引用次数: 4

摘要

基于内容的发布/订阅为信息生产者和消费者提供了方便的抽象,通过集成多个分布式独立应用程序系统来支持大规模的系统设计和发展。与传统的基于地址的单播或多播不同,其核心问题是如何通过事件内容上的谓词来匹配事件。在现有的匹配方法中,匹配谓词是由非语义约束的合取和析取组成的。但是,在企业应用程序集成的上下文中,尽管它们可以通过内容匹配事件,但是这种传统的匹配谓词在处理复杂的事件匹配(例如“一对多”和“多对一”匹配)时表达能力不够。因此,需要对传统的匹配方法进行扩展,以解决复杂的匹配问题。在分析企业应用集成中的信息匹配模式的基础上,提出了三种匹配模型,将这种简单的匹配方法扩展到多语义匹配方法,并进一步引入时间约束变量。多语义匹配方法允许根据不同的语义使用不同的操作;时间约束变量支持在时间序列中处理多个离散事件。然后,我们将OBDD图扩展为层次彩色OBDD图,并证明了变换的等价性。在扩展OBDD图的基础上,提出并分析了复合匹配算法。实验结果表明,该算法是有效的。
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An extended event matching approach in content-based pub/sub systems for EAI
Content-based publish/subscribe offers a convenient abstraction for information producers and consumers, supporting a large-scale system design and evolution by integrating several distributed independent application systems. Unlike in the traditional address-based unicast or multicast, its core problem is how to match events by predicates on the content of events. In existing matching approaches, matching predicates are composed by the conjunction and disjunction of non-semantic constraints. But, in context of enterprise application integration, although they can match events by their contents, this traditional matching predicates are not expressive enough in manipulating the complex event matching, such as the "one-to-many" and "many-to-one" matching. Therefore, traditional matching approaches should be extended to solve the complex matching problems. After analyzing information matching patterns in enterprise application integration, we propose three matching models, extend this simple matching approach to the multi-semantic matching approach and further introduce the temporal constraint variable. The multi-semantic matching approach allows using different operations in accordance with different semantics; the temporal constraint variable supports processing several discrete events in temporal sequences. Then, we extend OBDD graphs into hierarchy coloured OBDD graphs and prove the equivalence of the transformation. Based on the extended OBDD graphs, the composite matching algorithm is presented and analysed. By experiments, we show the proposed algorithm is efficient.
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