Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • 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
Adaptive congestion control in cognitive industrial wireless sensor networks
KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0001-6737-0266
KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0001-9810-3478
2015 (English)In: Proceeding - 2015 IEEE International Conference on Industrial Informatics, INDIN 2015, IEEE conference proceedings, 2015, 900-907 p.Conference paper, Published paper (Refereed)
Resource type
Text
Abstract [en]

Strict quality of service requirements of industrial applications, challenged by harsh environments and huge interference especially in multi-vendor sites, demand incorporation of cognition in industrial wireless sensor networks (IWSNs). In this paper, a distributed protocol of light complexity for congestion regulation in cognitive IWSNs is proposed to improve the channel utilization while ensuring predetermined performance for specific devices, called primary devices. By sensing the congestion level of a channel with local measurements, a novel congestion control protocol is proposed by which every device decides whether it should continue operating on the channel, or vacate it in case of saturation. Such a protocol dynamically changes the congestion level based on variations of non-stationary wireless environment as well as traffic demands of the devices. The proposed protocol is implemented on STM32W108 chips that offer IEEE 802.15.4 standard communications. Experimental results confirm substantial performance enhancement compared to the original standard, while imposing almost no signaling/computational overhead. In particular, channel utilization is increased by 56% with fairness and delay guarantees. The presented results provide useful insights on low-complexity adaptive congestion control mechanism in IWSNs.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2015. 900-907 p.
Keyword [en]
channel utilization, cognitive industrial wireless sensor networks, Congestion control, CSMA, Adaptive control systems, Carrier sense multiple access, Complex networks, Congestion control (communication), Information science, Quality of service, Standards, Adaptive congestion control, Congestion control protocols, Distributed protocols, IEEE 802.15.4 standards, Industrial wireless sensor networks, Industrial wireless sensor networks (IWSNs), Performance enhancements, Wireless sensor networks
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-181145DOI: 10.1109/INDIN.2015.7281855ISI: 000380453900131Scopus ID: 2-s2.0-84949483454ISBN: 9781479966493 (print)OAI: oai:DiVA.org:kth-181145DiVA: diva2:904313
Conference
13th International Conference on Industrial Informatics, INDIN 2015, 22 July 2015 through 24 July 2015
Note

QC 20160218

Available from: 2016-02-18 Created: 2016-01-29 Last updated: 2016-09-05Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full textScopus

Search in DiVA

By author/editor
Shokri-Ghadikolaei, HosseinFischione, Carlo
By organisation
Automatic ControlACCESS Linnaeus Centre
Electrical Engineering, Electronic Engineering, Information Engineering

Search outside of DiVA

GoogleGoogle Scholar

Altmetric score

Total: 45 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • 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