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|Abstract=Client-side query processing techniques that rely on the materialization of fragments of the original RDF dataset provide a promising solution for Web query processing. However, because of unexpected data transfers, the traditional optimize-then-execute paradigm, used by exist- ing approaches, is not always applicable in this context, i.e., performance of client-side execution plans can be negatively affected by live conditions where rate at which data arrive from sources change. We tackle adaptivity for client-side query processing, and present a network of Linked Data Eddies that is able to adjust query execution schedulers to data avail- ability and runtime conditions. Experimental studies suggest that the network of Linked Data Eddies outperforms static Web query schedulers in scenarios with unpredictable transfer delays and data distributions. | |Abstract=Client-side query processing techniques that rely on the materialization of fragments of the original RDF dataset provide a promising solution for Web query processing. However, because of unexpected data transfers, the traditional optimize-then-execute paradigm, used by exist- ing approaches, is not always applicable in this context, i.e., performance of client-side execution plans can be negatively affected by live conditions where rate at which data arrive from sources change. We tackle adaptivity for client-side query processing, and present a network of Linked Data Eddies that is able to adjust query execution schedulers to data avail- ability and runtime conditions. Experimental studies suggest that the network of Linked Data Eddies outperforms static Web query schedulers in scenarios with unpredictable transfer delays and data distributions. | ||
| − | |Forschungsgruppe=Wissensmanagement | + | |Download=Datei:Acosta vidal iswc2015.pdf |
| + | |Link=http://link.springer.com/chapter/10.1007/978-3-319-25007-6_7#page-1 | ||
| + | |Forschungsgruppe=Web Science und Wissensmanagement | ||
}} | }} | ||
Version vom 29. Oktober 2015, 14:45 Uhr
Networks of Linked Data Eddies: An Adaptive Web Query Processing Engine for RDF Data
Networks of Linked Data Eddies: An Adaptive Web Query Processing Engine for RDF Data
Published: 2015
Oktober
Buchtitel: The Semantic Web – ISWC 2015
Verlag: Springer
Organisation: International Semantic Web Conference
Referierte Veröffentlichung
BibTeX
Kurzfassung
Client-side query processing techniques that rely on the materialization of fragments of the original RDF dataset provide a promising solution for Web query processing. However, because of unexpected data transfers, the traditional optimize-then-execute paradigm, used by exist- ing approaches, is not always applicable in this context, i.e., performance of client-side execution plans can be negatively affected by live conditions where rate at which data arrive from sources change. We tackle adaptivity for client-side query processing, and present a network of Linked Data Eddies that is able to adjust query execution schedulers to data avail- ability and runtime conditions. Experimental studies suggest that the network of Linked Data Eddies outperforms static Web query schedulers in scenarios with unpredictable transfer delays and data distributions.
Download: Media:Datei:Acosta vidal iswc2015.pdf
Weitere Informationen unter: Link
Web Science und Wissensmanagement