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Erschienen in: Cluster Computing 1/2018

22.05.2017

Industrial Internet of things over tactile Internet in the context of intelligent manufacturing

Erschienen in: Cluster Computing | Ausgabe 1/2018

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Abstract

With the rapid advance of wireless technologies and its related domains, numerous emerging solutions and applications of industrial wireless systems have been developed, such as industrial Internet of things (2IoT), industrial wireless sensor networks, big data, cloud computing and augmented reality. The present development of communication in industrial environments drives the need for ubiquitous access to distributed resources and services that are connected to things, devices, and systems. However, given the fact that most industrial wireless sensor devices are resource constrained and operate on batteries, the communication overhead is therefore important issues for 2IoT’s design. In the context of intelligent manufacture, all kinds of intelligent equipment (e.g., industrial robots, industrial control system, industrial machine tools and test equipment) supported by wired or wireless networks are widely adopted, and both real-time, delayed signals and system security coexist. In order to efficiently manage these wireless devices in a unified manner, the intelligent manufacture authorities should be able to provide a network infrastructure supporting various 2IoT applications and services. This paper presents an overview of 2IoT’s network infrastructure and describe the information interaction among different devices. Then, a tactile Internet 2IoT architecture is proposed to manage physical devices and provide an interface for information exchange. Finally, the paper is discussed the prominent problems and possible solutions for tactile Internet 2IoT. This work will open a new research direction of 2IoT, and accelerate the implementation of intelligent manufacturing technical architecture.

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Metadaten
Titel
Industrial Internet of things over tactile Internet in the context of intelligent manufacturing
Publikationsdatum
22.05.2017
Erschienen in
Cluster Computing / Ausgabe 1/2018
Print ISSN: 1386-7857
Elektronische ISSN: 1573-7543
DOI
https://doi.org/10.1007/s10586-017-0925-1

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