Abstract :
The Internet of Things (IoT) envisions smart objects collecting and sharing data at a global scale via the Internet. One challenging issue is how to disseminate data to relevant data consumers efficiently. This article leverages semantic technologies, such as Linked Data, which can facilitate machine-to-machine communications to build an efficient stream dissemination system for Semantic IoT. The system integrates Linked Data streams generated from various data collectors and disseminates matched data to relevant data consumers based on user queries registered in the system. Here, the authors present a new data structure, TP-automata, designed to suit the high-performance needs of Linked Data stream dissemination. They evaluate the system using a real-world dataset generated in a Smart Building IoT Project. The proposed system can disseminate Linked Data streams at one million triples per second with 100,000 registered user queries, which is several orders of magnitude faster than existing techniques.
Keywords :
Internet of Things; automata theory; data acquisition; data structures; information dissemination; pattern matching; query processing; TP-automata; data collector; data structure; linked data stream dissemination; linked data stream integration; matched data dissemination; smart building IoT project; user queries; Computer networks; Cyber-physical systems; Internet of things; Resource description framework; Semantics; Social network services; CPSS; Internet/Web technologies; cyber-physical-social systems; linked data; query index; stream dissemination; stream processing;
