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Erschienen in: The Journal of Supercomputing 12/2018

04.05.2018

IoT service classification and clustering for integration of IoT service platforms

verfasst von: Daewon Lee, HwaMin Lee

Erschienen in: The Journal of Supercomputing | Ausgabe 12/2018

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Abstract

With the rapid development of sensors, wireless communication, and cloud computing, information technology today focuses on service environments created by the Internet of Things (IoT). IoT technologies have become widely used in various contexts including smart homes, building management, surveillance services, and smart farms. Some IoT applications such as Siri are popular in everyday life. IoT requires communication and interaction between various devices and services. To solve the various complex problems associated with IoT services, earlier research focused on IoT service platforms such as gateways and mobile edge computing services. However, the similarities and reusabilities of IoT services have received little attention. In this paper, we develop an IoT service classification and clustering system. We classify the operation of an IoT service into four steps that differ in their characteristics. Based on this classification, we extend the classic EM (expectation–maximization) algorithm to cluster IoT services in terms of their similarities. To validate our proposed classification and clustering system, we divide over 100 commercial IoT services into five clusters, showing that such services are well clustered by similarity and purpose.

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Metadaten
Titel
IoT service classification and clustering for integration of IoT service platforms
verfasst von
Daewon Lee
HwaMin Lee
Publikationsdatum
04.05.2018
Verlag
Springer US
Erschienen in
The Journal of Supercomputing / Ausgabe 12/2018
Print ISSN: 0920-8542
Elektronische ISSN: 1573-0484
DOI
https://doi.org/10.1007/s11227-018-2288-7

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