Quality-Of-Control-Aware Scheduling of Communication in TSN-Based Fog Computing Platforms Using Constraint Programming

Authors Mohammadreza Barzegaran , Bahram Zarrin , Paul Pop



PDF
Thumbnail PDF

File

OASIcs.Fog-IoT.2020.3.pdf
  • Filesize: 1.01 MB
  • 9 pages

Document Identifiers

Author Details

Mohammadreza Barzegaran
  • DTU Compute, Technical University of Denmark, Kongens Lyngby, Denmark
Bahram Zarrin
  • DTU Compute, Technical University of Denmark, Kongens Lyngby, Denmark
Paul Pop
  • DTU Compute, Technical University of Denmark, Kongens Lyngby, Denmark

Cite AsGet BibTex

Mohammadreza Barzegaran, Bahram Zarrin, and Paul Pop. Quality-Of-Control-Aware Scheduling of Communication in TSN-Based Fog Computing Platforms Using Constraint Programming. In 2nd Workshop on Fog Computing and the IoT (Fog-IoT 2020). Open Access Series in Informatics (OASIcs), Volume 80, pp. 3:1-3:9, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)
https://doi.org/10.4230/OASIcs.Fog-IoT.2020.3

Abstract

In this paper we are interested in real-time control applications that are implemented using Fog Computing Platforms consisting of interconnected heterogeneous Fog Nodes (FNs). Similar to previous research and ongoing standardization efforts, we assume that the communication between FNs is achieved via IEEE 802.1 Time Sensitive Networking (TSN). We model the control applications as a set of real-time streams, and we assume that the messages are transmitted using time-sensitive traffic that is scheduled using the Gate Control Lists (GCLs) in TSN. Given a network topology and a set of control applications, we are interested to synthesize the GCLs for messages such that the quality-of-control of applications is maximized and the deadlines of real-time messages are satisfied. We have proposed a Constraint Programming-based solution to this problem, and evaluated it on several test cases.

Subject Classification

ACM Subject Classification
  • Networks → Traffic engineering algorithms
  • Computer systems organization → Embedded software
  • Theory of computation → Constraint and logic programming
Keywords
  • TSN
  • Fog Computing
  • Constraint Programming
  • Quality of Control

Metrics

  • Access Statistics
  • Total Accesses (updated on a weekly basis)
    0
    PDF Downloads

References

  1. M. Barzegran, A. Cervin, and P. Pop. Towards quality-of-control-aware scheduling of industrial applications on fog computing platforms. In Workshop on Fog Computing and the IoT, 2019. Google Scholar
  2. Edmund K Burke, Graham Kendall, et al. Search methodologies. Springer, 2005. Google Scholar
  3. A. Cervin, D. Henriksson, B. Lincoln, J. Eker, and K.-E. Årzén. How does control timing affect performance? analysis and simulation of timing using Jitterbug and TrueTime. IEEE Control Systems Magazine, 23(3):16-30, June 2003. Google Scholar
  4. A. Cervin, P. Pazzaglia, M. Barzegaran, and R. Mahfouzi. Using JitterTime to analyze transient performance in adaptive and reconfigurable control systems. In IEEE International Conference on Emerging Technologies and Factory Automation, pages 1025-1032, 2019. Google Scholar
  5. Silviu S Craciunas, Ramon Serna Oliver, Martin Chmelík, and Wilfried Steiner. Scheduling real-time communication in ieee 802.1 qbv time sensitive networks. In Proceedings of the 24th International Conference on Real-Time Networks and Systems, pages 183-192, 2016. Google Scholar
  6. Google. Google OR-Tools. https://developers.google.com/optimization, Accessed on Jan 2020. URL: https://developers.google.com/optimization.
  7. IEEE. Official Website of the 802.1 Time-Sensitive Networking Task Group, 2016 (accessed December. 12, 2018). URL: http://www.ieee802.org/1/pages/tsn.html.
  8. IEEE. 802.1Qbv - enhancments for scheduled traffic. https://www.ieee802.org/1/pages/802.1bv.html, 2016 Draft 3.1. URL: https://www.ieee802.org/1/pages/802.1bv.html.
  9. IEEE. 802.1ASrev - timing and synchronization for time-sensitive applications. http://www.ieee802.org/1/pages/802.1AS-rev.html, 2017. URL: http://www.ieee802.org/1/pages/802.1AS-rev.html.
  10. Rouhollah Mahfouzi, Amir Aminifar, Soheil Samii, Ahmed Rezine, Petru Eles, and Zebo Peng. Stability-aware integrated routing and scheduling for control applications in Ethernet networks. In Design, Automation & Test in Europe Conference, pages 682-687, 2018. Google Scholar
  11. Carla Mouradian, Diala Naboulsi, Sami Yangui, Roch H. Glitho, Monique J. Morrow, and Paul A. Polakos. A Comprehensive Survey on Fog Computing: State-of-the-Art and Research Challenges. IEEE Communications Surveys and Tutorials, 20(1):416-464, 2018. Google Scholar
  12. P. Pop, M. L. Raagaard, M. Gutierrez, and W. Steiner. Enabling fog computing for industrial automation through Time-Sensitive Networking (TSN). IEEE Communications Standards Magazine, 2(2):55-61, 2018. Google Scholar
  13. Paul Pop, Michael Lander Raagaard, Silviu S Craciunas, and Wilfried Steiner. Design optimisation of cyber-physical distributed systems using IEEE Time-Sensitive Networks. IET Cyber-Physical Systems: Theory & Applications, 1(1):86-94, 2016. Google Scholar
  14. Zhi Wen Wang and Hong Tao Sun. Control and scheduling co-design of networked control system: Overview and directions. In in Proceedings International Conference on Machine Learning and Cybernetics, volume 3, pages 816-824, 2012. Google Scholar
Questions / Remarks / Feedback
X

Feedback for Dagstuhl Publishing


Thanks for your feedback!

Feedback submitted

Could not send message

Please try again later or send an E-mail