Research and Application of Complex Event Processing Method Based on RDF Stream

The development of Semantic Web technology has produced massive resource description framework (RDF) data, most of which are collected from the Internet of Things in the form of streams and analyzed in real time. How to reason and query RDF streams, and to mine valuable information from the streams for decision-making has become a hot research topic. Complex event processing (CEP) can perform real-time analysis of event streams, but the processed data usually lacks semantic information, is not suitable for semantic interoperability between multi-source heterogeneous data, and cannot combine data streams with domain ontology. In order to solve the above problems, CEPR, a complex event processing method based on RDF flow, is proposed. CEPR is based on answer set programming ASP, using LARS that extends ASP, combining Datalog and relational algebra, to implement RDF flow inference and query on the Flink platform. Use the PHM 2010 tool wear data set to evaluate the performance of CEPR, and compare CEPR with C-SPARQL and Strider. Experiments show that CEPR has a greater advantage in query latency.