Dissemination of Internet of Things Streams in a Real-time Linked Dataspace

Yongrui Qin, Quan Z. Sheng, Edward Curry

Research output: Chapter in Book or Conference Publication/ProceedingChapterpeer-review

2 Citations (Scopus)

Abstract

The Internet of Things (IoT) envisions smart objects and intelligent systems collecting and sharing data on a global scale to enable smart environments. One challenging data management issue is how to disseminate data to relevant consumers efficiently. This chapter 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 collectors and disseminates matched data to relevant consumers based on user queries registered in the system. We design two new data structures to suit the needs of high-performance linked data stream dissemination in the following two scenarios: (1) stream dissemination in point-to-point systems; and (2) stream dissemination in wireless broadcast systems. The evaluation of the approaches using real-world datasets shows that they can disseminate linked data streams more efficiently than existing techniques.

Original languageEnglish
Title of host publicationReal-time Linked Dataspaces
Subtitle of host publicationEnabling Data Ecosystems for Intelligent Systems
PublisherSpringer International Publishing
Pages191-208
Number of pages18
ISBN (Electronic)9783030296650
ISBN (Print)9783030296643
DOIs
Publication statusPublished - 1 Jan 2019

Keywords

  • Dataspaces
  • Event matching
  • Event processing
  • Internet of Things
  • Linked data
  • Stream dissemination

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