Camera Networks Dimensioning and Scheduling with Quasi Worst-Case Transmission Time

Authors Viktor Edpalm, Alexandre Martins, Karl-Erik Årzén, Martina Maggio

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Author Details

Viktor Edpalm
  • Axis Communications, Lund, Sweden
Alexandre Martins
  • Axis Communications and Department of Automatic Control, Lund University, Lund, Sweden
Karl-Erik Årzén
  • Department of Automatic Control, Lund University, Sweden
Martina Maggio
  • Department of Automatic Control, Lund University, Sweden

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Viktor Edpalm, Alexandre Martins, Karl-Erik Årzén, and Martina Maggio. Camera Networks Dimensioning and Scheduling with Quasi Worst-Case Transmission Time. In 30th Euromicro Conference on Real-Time Systems (ECRTS 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 106, pp. 17:1-17:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)


This paper describes a method to compute frame size estimates to be used in quasi Worst-Case Transmission Times (qWCTT) for cameras that transmit frames over IP-based communication networks. The precise determination of qWCTT allows us to model the network access scheduling problem as a multiframe problem and to re-use theoretical results for network scheduling. The paper presents a set of experiments, conducted in an industrial testbed, that validate the qWCTT estimation. We believe that a more precise estimation will lead to savings for network infrastructure and to better network utilization.

Subject Classification

ACM Subject Classification
  • Computer systems organization → Embedded systems
  • Computer systems organization → Real-time systems
  • Networks → Network components
  • worst-case transmission time
  • H.264
  • bandwidth estimation
  • video compression
  • network access scheduling
  • multiframe model
  • camera network


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