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.
CITATION STYLE
Taelman, R., Verborgh, R., Colpaert, P., & Mannens, E. (2016). Moving real-time linked data query evaluation to the client. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9989 LNCS, pp. 3–7). Springer Verlag. https://doi.org/10.1007/978-3-319-47602-5_1
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