Moving Real-Time Linked Data Query Evaluation to the Client
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 time-sensitive 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.
KeywordsLinked data Linked data fragments sparql Continuous querying Real-time querying
The described research activities were funded by iMinds and Ghent University, the Institute for the Promotion of Innovation by Science and Technology in Flanders (IWT), the Fund for Scientific Research Flanders (FWO Flanders), and the European Union. Ruben Verborgh is a Postdoctoral Fellow of the Research Foundation Flanders.
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