Please use this identifier to cite or link to this item: https://doi.org/10.1145/1247480.1247562
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dc.titleEfficient xml data dissemination with piggybacking
dc.contributor.authorChan, C.Y.
dc.contributor.authorNi, Y.
dc.date.accessioned2013-07-04T08:04:55Z
dc.date.available2013-07-04T08:04:55Z
dc.date.issued2007
dc.identifier.citationChan, C.Y.,Ni, Y. (2007). Efficient xml data dissemination with piggybacking. Proceedings of the ACM SIGMOD International Conference on Management of Data : 737-748. ScholarBank@NUS Repository. <a href="https://doi.org/10.1145/1247480.1247562" target="_blank">https://doi.org/10.1145/1247480.1247562</a>
dc.identifier.isbn1595936866
dc.identifier.issn07308078
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/40464
dc.description.abstractContent-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 optimizations 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 subscriptions. The effectiveness of both these techniques are, however, limited to locally improving the performance of individual routers. In this paper, we propose a novel and holistic 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 experimental results demonstrate that our piggyback optimization achieves significant performance improvement under various conditions. Copyright 2007 ACM.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1145/1247480.1247562
dc.sourceScopus
dc.subjectAnnotation
dc.subjectData dissemination
dc.subjectPiggybacking
dc.subjectPub/sub system
dc.subjectXML
dc.subjectXPath
dc.typeConference Paper
dc.contributor.departmentCOMPUTER SCIENCE
dc.description.doi10.1145/1247480.1247562
dc.description.sourcetitleProceedings of the ACM SIGMOD International Conference on Management of Data
dc.description.page737-748
dc.identifier.isiutNOT_IN_WOS
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