Efficient XML Data Dissemination with Piggybacking

Content-based dissemination of XML data using the publish-subscribe paradigm is an effective means to deliver relevant data to interested data consumers. To meet the performance challenges of content-based filtering and routing, two key op-timizations have been developed: the use of efficient indexes to speed up subscription filtering, and the use of effective aggregation algorithms to reduce the number of subscrip-tions. The effectiveness of both these techniques are, how-ever, limited to locally improving the performance of indi-vidual routers. In this paper, we propose a novel and holis-tic optimization approach that allows a downstream router to leverage the subscription matchings done by upstream routers to reduce its own filtering work. This is achieved by piggybacking useful annotations to the XML document being forwarded. We explore several design options and tradeoffs of this novel optimization approach. Our experi-mental results demonstrate that our piggyback optimization achieves significant performance improvement under various conditions