TY - JOUR
T1 - Survey of real-time processing technologies of IoT data streams
AU - Yasumoto, Keiichi
AU - Yamaguchi, Hirozumi
AU - Shigeno, Hiroshi
N1 - Publisher Copyright:
© 2016 Information Processing Society of Japan.
Copyright:
Copyright 2018 Elsevier B.V., All rights reserved.
PY - 2016/3/15
Y1 - 2016/3/15
N2 - 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.
AB - 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.
KW - Content curation
KW - Data stream
KW - Distributed processing
KW - IoT
KW - On-line learning
KW - Real-time processing
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U2 - 10.2197/ipsjjip.24.195
DO - 10.2197/ipsjjip.24.195
M3 - Article
AN - SCOPUS:84961193629
SN - 0387-5806
VL - 24
SP - 195
EP - 202
JO - Journal of information processing
JF - Journal of information processing
IS - 2
ER -