基于Bloom过滤器的XML包过滤数百万个路径查询

Xueqing Gong, Ying Yan, Weining Qian, Aoying Zhou
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引用次数: 62

摘要

XML数据的过滤是许多复杂应用程序的基础。为了解决这个问题,已经提出了许多算法。一个重要的挑战是路径查询的数量非常大。有必要采用一种表示路径查询的有效数据结构。另一个挑战是,这些路径查询通常随时间而变化。路径查询的维护决定了过滤系统的灵活性和容量。本文介绍了一种新的XML数据过滤近似方法,该方法使用Bloom过滤器表示路径查询。该方法可以高效地存储数以百万计的路径查询,同时易于处理这些路径查询的变化。为了提高过滤性能,我们引入了一种新的数据结构,前缀过滤器,以减少候选路径的数量。实验表明,基于Bloom过滤器的路由表构建方法比基于自动机的路由表构建方法耗时更短。在使用数百万个路径查询过滤相对深度较小的XML数据包时,我们的方法具有良好的性能,并且具有可接受的误报。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Bloom filter-based XML packets filtering for millions of path queries
The filtering of XML data is the basis of many complex applications. Lots of algorithms have been proposed to solve this problem. One important challenge is that the number of path queries is huge. It is necessary to take an efficient data structure representing path queries. Another challenge is that these path queries usually vary with time. The maintenance of path queries determines the flexibility and capacity of a filtering system. In this paper, we introduce a novel approximate method for XML data filtering, which uses Bloom filters representing path queries. In this method, millions of path queries can be stored efficiently At the same time, it is easy to deal with the change of these path queries. To improve the filtering performance, we introduce a new data structure, Prefix Filters, to decrease the number of candidate paths. Experiments show that our Bloom filter-based method takes less time to build routing table than automaton-based method. And our method has a good performance with acceptable false positive when filtering XML packets of relatively small depth with millions of path queries.
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