SPARQL for Networks of Embedded Systems

D. Boldt, Henning Hasemann, Marcel Karnstedt, Alexander Kröller, Christian von der Weth


In the Internet of Things (IoT), small-scale embedded devices monitor and control real-world objects with different kinds of sensors and actuators. Often, devices communicate measurements and states using proprietary encodings, with the benefit of having all data stored in a central location, e.g., the Cloud. The drawbacks are that all data needs to be collected in advance, even if it is not used afterwards, and that nonstandard protocols make it hard to extend existing networks with new devices. In contrast, the Semantic Web (or Web of Data) represents the successful efforts towards linking and sharing data over the Web. The cornerstones of the Web of Data are RDF as data format and SPARQL as de-facto standard query language. Recent trends show the evolution of the integration of these two efforts into the Web of Things. We propose to elevate embedded devices to first-class citizens of the Web of Things by allowing storage and processing of RDF data. Our framework abstracts from individual deployments to represent them as common data sources in line with the ideas behind the Semantic Web. This includes the execution of SPARQL queries over the data from a pool of embedded devices and/or external data sources. Handling verbose RDF data and executing SPARQL queries in an embedded network pose major challenges to minimize the involved processing and communication cost. We therefore present an in-network query processor aiming to push processing steps onto devices. We demonstrate the practical application and the potential benefits of our framework in an evaluation using a real-world deployment and a range of SPARQL queries stemming from common use cases of the Web of Things.
Original languageEnglish
Title of host publication2015 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)
Number of pages8
Place of PublicationSingapore, Singapore
Publication date01.12.2015
Article number7396786
ISBN (Print)978-1-4673-9617-2
ISBN (Electronic) 978-1-4673-9618-9
Publication statusPublished - 01.12.2015
Event2015 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology Workshops - Singapore, Singapore
Duration: 06.12.201509.12.2015


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