Survey of real-time processing technologies of IoT data streams

Keiichi Yasumoto, Hirozumi Yamaguchi, Hiroshi Shigeno

Research output: Contribution to journalArticle

48 Citations (Scopus)

Abstract

Recently, Internet of Things (IoT) has been attracting attention due to its economical impact and high expectations for drastically changing our modern societies. Worldwide by 2022, over 50 billion IoT devices including sensors and actuators are predicted to be installed in machines, humans, vehicles, buildings, and environments. Demand is also huge for the real-time utilization of IoT data streams instead of the current off-line analysis/utilization of stored big data. The real-time utilization of massive IoT data streams suggests a paradigm shift to new horizontal and distributed architecture because existing cloud-based centralized architecture will cause large delays for providing service and waste many resources on the cloud and on networks. Content curation, which is the intelligent compilation of valuable content from IoT data streams, is another key to fully utilize and penetrate IoT technologies. In this pa- per, we survey the emerging technologies toward the real-time utilization of IoT data streams in terms of networking, processing, and content curation and clarify the open issues. Then we propose a new framework for IoT data streams called the Information Flow of Things (IFoT) that processes, analyzes, and curates massive IoT streams in real-time based on distributed processing among IoT devices.

Original languageEnglish
Pages (from-to)195-202
Number of pages8
JournalJournal of Information Processing
Volume24
Issue number2
DOIs
Publication statusPublished - 2016 Mar 15

Keywords

  • Content curation
  • Data stream
  • Distributed processing
  • IoT
  • On-line learning
  • Real-time processing

ASJC Scopus subject areas

  • Computer Science(all)

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