Early profile pruning on XML-aware publish-subscribe systems

  • Authors:

  • Mirella M. Moro;Petko Bakalov;Vassilis J. Tsotras

  • Affiliations:

  • University of California, Riverside, CA;University of California, Riverside, CA;University of California, Riverside, CA

  • Venue:
  • VLDB '07 Proceedings of the 33rd international conference on Very large data bases
  • Year:
  • 2007

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Abstract

Publish-subscribe applications are an important class of content-based dissemination systems where the message transmission is defined by the message content, rather than its destination IP address. With the increasing use of XML as the standard format on many Internet-based applications, XML aware pub-sub applications become necessary. In such systems, the messages (generated by publishers) are encoded as XML documents, and the profiles (defined by subscribers) as XML query statements. As the number of documents and query requests grow, the performance and scalability of the matching phase (i.e. matching of queries to incoming documents) become vital. Current solutions have limited or no flexibility to prune out queries in advance. In this paper, we overcome such limitation by proposing a novel early pruning approach called Bounding-based XML Filtering or BoXFilter. The BoXFilter is based on a new tree-like indexing structure that organizes the queries based on their similarity and provides lower and upper bound estimations needed to prune queries not related to the incoming documents. Our experimental evaluation shows that the early profile pruning approach offers drastic performance improvements over the current state-of-the-art in XML filtering.