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Evaluation of the impact of Cloud Database services on Industrial IoT Applications
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2020 (English)In: Proceedings, Institute of Electrical and Electronics Engineers Inc. , 2020Conference paper, Published paper (Refereed)
Abstract [en]

The Internet of Things applied to Industry (IIoT) is one of the pillars of Industry 4.0. The connection to Internet of all the industrial devices, and the storage (sharing) of enormous amount of data inside Cloud database, enable the development of analysis algorithms for the delivery of new "high value" services. However, the industrial market may require response with short predictable latency (real-time response) even for supervision and optimization functions. Often today, the estimation of the latency of new services is not taken into account. For all these reasons, this work introduces an experimental measurement procedure for investigating the impact of Cloud database services on the communication delay from the production line to the Cloud and the way back (feedback). In this paper, a use case demonstrates the feasibility of the proposed test methodology. In details, the considered use case is a predictive maintenance system with Siemens S7 industrial automation controller sending data to a Cloudant database inside the IBM Bluemix platform. The use case results show that the IIoT solutions based on Cloud database services can be easily evaluated, compared (and optimized) thanks to the proposed approach. © 2020 IEEE.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc. , 2020.
Keywords [en]
Automation Networks, Cloud computing, Distributed measurement systems, Industry 4.0, Node-RED, Database systems, Digital storage, Storage as a service (STaaS), Analysis algorithms, Communication delays, Industrial automation, Industrial devices, Industrial markets, Measurement procedures, Optimization function, Real time response, Industrial internet of things (IIoT)
Identifiers
URN: urn:nbn:se:miun:diva-41512DOI: 10.1109/I2MTC43012.2020.9129080ISI: 000581255700001Scopus ID: 2-s2.0-85088284579ISBN: 9781728144603 (print)OAI: oai:DiVA.org:miun-41512DiVA, id: diva2:1536296
Conference
I2MTC 2020 - International Instrumentation and Measurement Technology Conference
Available from: 2021-03-10 Created: 2021-03-10 Last updated: 2025-09-25Bibliographically approved

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Sisinni, Emiliano

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf