
Moving real-time linked data query evaluation to the client
- Author
- Ruben Taelman (UGent) , Ruben Verborgh (UGent) , Pieter Colpaert (UGent) and Erik Mannens (UGent)
- Organization
- Abstract
- Traditional RDF stream processing engines work completely server-side, which contributes to a high server cost. For allowing a large number of concurrent clients to do continuous querying, we extend the low-cost Triple Pattern Fragments (TPF) interface with support for timesensitive queries. In this poster, we give the overview of a client-side rdf stream processing engine on top of tpf. Our experiments show that our solution significantly lowers the server load while increasing the load on the clients. Preliminary results indicate that our solution moves the complexity of continuously evaluating real-time queries from the server to the client, which makes real-time querying much more scalable for a large amount of concurrent clients when compared to the alternatives.
- Keywords
- Linked data, Linked data fragments, SPARQL, Continuous querying, Real-time querying
Downloads
-
2016 - Ruben Taelman et al. - Moving Real-Time Linked Data Query Evaluation to the Client.pdf
- full text
- |
- open access
- |
- |
- 483.86 KB
Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-8503520
- MLA
- Taelman, Ruben, et al. “Moving Real-Time Linked Data Query Evaluation to the Client.” Lecture Notes in Computer Science, vol. 9989, Springer Nature, 2016, pp. 3–7, doi:10.1007/978-3-319-47602-5_1.
- APA
- Taelman, R., Verborgh, R., Colpaert, P., & Mannens, E. (2016). Moving real-time linked data query evaluation to the client. Lecture Notes in Computer Science, 9989, 3–7. https://doi.org/10.1007/978-3-319-47602-5_1
- Chicago author-date
- Taelman, Ruben, Ruben Verborgh, Pieter Colpaert, and Erik Mannens. 2016. “Moving Real-Time Linked Data Query Evaluation to the Client.” In Lecture Notes in Computer Science, 9989:3–7. Springer Nature. https://doi.org/10.1007/978-3-319-47602-5_1.
- Chicago author-date (all authors)
- Taelman, Ruben, Ruben Verborgh, Pieter Colpaert, and Erik Mannens. 2016. “Moving Real-Time Linked Data Query Evaluation to the Client.” In Lecture Notes in Computer Science, 9989:3–7. Springer Nature. doi:10.1007/978-3-319-47602-5_1.
- Vancouver
- 1.Taelman R, Verborgh R, Colpaert P, Mannens E. Moving real-time linked data query evaluation to the client. In: Lecture Notes in Computer Science. Springer Nature; 2016. p. 3–7.
- IEEE
- [1]R. Taelman, R. Verborgh, P. Colpaert, and E. Mannens, “Moving real-time linked data query evaluation to the client,” in Lecture Notes in Computer Science, Heraklion, Greece, 2016, vol. 9989, pp. 3–7.
@inproceedings{8503520, abstract = {{Traditional RDF stream processing engines work completely server-side, which contributes to a high server cost. For allowing a large number of concurrent clients to do continuous querying, we extend the low-cost Triple Pattern Fragments (TPF) interface with support for timesensitive queries. In this poster, we give the overview of a client-side rdf stream processing engine on top of tpf. Our experiments show that our solution significantly lowers the server load while increasing the load on the clients. Preliminary results indicate that our solution moves the complexity of continuously evaluating real-time queries from the server to the client, which makes real-time querying much more scalable for a large amount of concurrent clients when compared to the alternatives.}}, author = {{Taelman, Ruben and Verborgh, Ruben and Colpaert, Pieter and Mannens, Erik}}, booktitle = {{Lecture Notes in Computer Science}}, isbn = {{978-3-319-47601-8}}, issn = {{0302-9743}}, keywords = {{Linked data,Linked data fragments,SPARQL,Continuous querying,Real-time querying}}, language = {{eng}}, location = {{Heraklion, Greece}}, pages = {{3--7}}, publisher = {{Springer Nature}}, title = {{Moving real-time linked data query evaluation to the client}}, url = {{http://doi.org/10.1007/978-3-319-47602-5_1}}, volume = {{9989}}, year = {{2016}}, }
- Altmetric
- View in Altmetric
- Web of Science
- Times cited: