mdh.sePublications
Change search
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
Learning the Parameters of Periodic Traffic based on Network Measurements
TTTech Computertechnik AG, Austria.
TTTech Computertechnik AG, Austria.
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0003-4157-3537
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0001-5269-3900
2015 (English)In: Measurements & Networking M&N 2015, 2015, p. 100-115Conference paper, Published paper (Refereed)
Abstract [en]

The configuration of real-time networks is one of the most challenging demands of the Real-Time Internet-of-Things trend, where the network has to be deterministic and yet flexible enough to adapt to changes through its life-cycle. To achieve this we have outlined an approach that learns the necessary configuration parameters from network measurements, that way providing a continuous configuration service for the network. First, the network is monitored to obtain traffic measurements. Then traffic parameters are derived from those measurements. Finally, a new time-triggered schedule is produced with which the network will be reconfigured. In this paper we propose an analysis based on measurements to obtain the specific traffic parameters and we evaluate it through network simulations. The results show that the configuration parameters can be learned from the measurements with enough accuracy and that those measurements can be easily obtained through network monitoring.

Place, publisher, year, edition, pages
2015. p. 100-115
National Category
Computer Systems
Identifiers
URN: urn:nbn:se:mdh:diva-29670DOI: 10.1109/IWMN.2015.7322981ISI: 000380404300018Scopus ID: 2-s2.0-84966340207ISBN: 978-1-4799-1860-7 (print)OAI: oai:DiVA.org:mdh-29670DiVA, id: diva2:876080
Conference
Measurements & Networking M&N 2015, 12-13 Oct 2015, Coimbra, Portugal
Projects
RetNet - The European Industrial Doctorate Programme on Future Real-Time NetworksAvailable from: 2015-12-02 Created: 2015-11-26 Last updated: 2017-12-22Bibliographically approved
In thesis
1. A Configuration Agent for Real-Time Networks
Open this publication in new window or tab >>A Configuration Agent for Real-Time Networks
2017 (English)Licentiate thesis, comprehensive summary (Other academic)
Place, publisher, year, edition, pages
Västerås: Mälardalen University, 2017
Series
Mälardalen University Press Licentiate Theses, ISSN 1651-9256 ; 265
National Category
Embedded Systems
Research subject
Computer Science
Identifiers
urn:nbn:se:mdh:diva-37117 (URN)978-91-7485-354-4 (ISBN)
Presentation
2017-11-17, Kappa, Mälardalens högskola, Västerås, 13:15 (English)
Opponent
Supervisors
Available from: 2017-10-23 Created: 2017-10-20 Last updated: 2017-11-01Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records BETA

Dobrin, RaduPunnekkat, Sasikumar

Search in DiVA

By author/editor
Dobrin, RaduPunnekkat, Sasikumar
By organisation
Embedded Systems
Computer Systems

Search outside of DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 29 hits
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