Predicate Priority Based Event Matching Algorithm in Publish/Subscribe System

M. Xu, Pin Lv, Haibo Wang
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引用次数: 2

Abstract

The large distributed interactive simulation system which based on the publish/subscribe model has considerable data, it needs to disseminate accurate data to the interested users quickly, so improving the match efficient is a very important method to solve this problem. Based on the study and comparison of current matching algorithm, we have proposed a predicate priority based event matching algorithm(hereinafter referred to as PPEM). Performance analysis and detailed experimentations are carried out to verify the effectiveness of PPEM. When the number of subscriptions is 10000, the average time of matching one event is only 22.6ms and when we change the type of data distribution or increase the number of event attribute, the average matching time of PPEM is almost unchangeable comparing with bucket and multi-dimension algorithms. All the results show that PPEM achieves high matching efficiency and also has good scalability and robustness.
发布/订阅系统中基于谓词优先级的事件匹配算法
基于发布/订阅模式的大型分布式交互仿真系统拥有大量的数据,需要将准确的数据快速传播给感兴趣的用户,因此提高匹配效率是解决这一问题的重要方法。在研究和比较现有匹配算法的基础上,我们提出了一种基于谓词优先级的事件匹配算法(以下简称PPEM)。通过性能分析和详细的实验验证了PPEM的有效性。当订阅数为10000时,匹配一个事件的平均时间仅为22.6ms,当我们改变数据分布类型或增加事件属性的数量时,与桶算法和多维算法相比,PPEM的平均匹配时间几乎不变。结果表明,该算法不仅具有较高的匹配效率,而且具有良好的可扩展性和鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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