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Bio-inspired Service Provisioning Scheme for Fog-based Industrial Internet of Things
Department of IT Convergence Engineering, Kumoh National Institute of Technology, Gumi, 39177, South Korea.ORCID iD: 0000-0002-3022-6110
Number of Authors: 42019 (English)In: 2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), Institute of Electrical and Electronics Engineers (IEEE) , 2019, Vol. 2019-September, p. 1661-1664Conference paper, Published paper (Refereed)
Abstract [en]

This paper proposes a bio-inspired service provisioning scheme for fog-based industrial Internet of Things (IIoT). We use wild-goats algorithm to address the adaptive fog service provisioning problem. Specifically, the master node is configured to monitor the network condition of all fog nodes inside of its domain. Then, the master node will distribute a service to the most suitable fog node based on network latency, computation cost, and storage cost. Therefore, the service can be accomplished in a real-time. The proposed method also considers a probability of node failure during the service provisioning process due to the harsh condition of IIoT environment. The results show that the proposed scheme can achieve low latency compared to the traditional architectures. The results also show that the node failure can escalate the latency of fog-based IIoT network. Thus, the adaptive service provisioning scheme is essential to maintain the network performance of fog-based IIoT.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2019. Vol. 2019-September, p. 1661-1664
Series
IEEE International Conference on Emerging Technologies and Factory Automation, ETFA, ISSN 1946-0740 ; 2019-September
National Category
Communication Systems
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kth:diva-302289DOI: 10.1109/etfa.2019.8869402Scopus ID: 2-s2.0-85074196165OAI: oai:DiVA.org:kth-302289DiVA, id: diva2:1595814
Conference
24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), 10 September 2019 through 13 September 2019
Note

QC 20211103

Part of proceedings: ISBN 978-172810303-7

Available from: 2021-09-20 Created: 2021-09-20 Last updated: 2022-06-25Bibliographically approved

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Ramli, Muhammad Rusyadi

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CiteExportLink to record
Permanent link

Direct link
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