RT-CASEs: Container-Based Virtualization for Temporally Separated Mixed-Criticality Task Sets

Authors Marcello Cinque , Raffaele Della Corte, Antonio Eliso, Antonio Pecchia



PDF
Thumbnail PDF

File

LIPIcs.ECRTS.2019.5.pdf
  • Filesize: 1.41 MB
  • 22 pages

Document Identifiers

Author Details

Marcello Cinque
  • Federico II University of Naples, Italy
Raffaele Della Corte
  • Federico II University of Naples, Italy
Antonio Eliso
  • Federico II University of Naples, Italy
Antonio Pecchia
  • Federico II University of Naples, Italy

Acknowledgements

We are thankful to the anonymous reviewers of the ECRTS program committee for the valuable comments, which allowed us to improve the paper and provided useful guidance to better target our future research efforts on rt-cases.

Cite AsGet BibTex

Marcello Cinque, Raffaele Della Corte, Antonio Eliso, and Antonio Pecchia. RT-CASEs: Container-Based Virtualization for Temporally Separated Mixed-Criticality Task Sets. In 31st Euromicro Conference on Real-Time Systems (ECRTS 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 133, pp. 5:1-5:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)
https://doi.org/10.4230/LIPIcs.ECRTS.2019.5

Abstract

This paper presents the notion of real-time containers, or rt-cases, conceived as the convergence of container-based virtualization technologies, such as Docker, and hard real-time operating systems. The idea is to allow critical containers, characterized by stringent timeliness and reliability requirements, to cohabit with traditional non real-time containers on the same hardware. The approach allows to keep the advantages of real-time virtualization, largely adopted in the industry, while reducing its inherent scalability limitation when to be applied to large-scale mixed-criticality systems or severely constrained hardware environments. The paper provides a reference architecture scheme for implementing the real-time container concept on top of a Linux kernel patched with a hard real-time co-kernel, and it discusses a possible solution, based on execution time monitoring, to achieve temporal separation of fixed-priority hard real-time periodic tasks running within containers with different criticality levels. The solution has been implemented using Docker over a Linux kernel patched with RTAI. Experimental results on real machinery show how the implemented solution is able to achieve temporal separation on a variety of random task sets, despite the presence of faulty tasks within a container that systematically exceed their worst case execution time.

Subject Classification

ACM Subject Classification
  • Software and its engineering → Real-time systems software
Keywords
  • Containers
  • mixed-criticality
  • temporal separation
  • monitoring

Metrics

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

References

  1. L. Abeni and G. Buttazzo. Integrating multimedia applications in hard real-time systems. In Proceedings 19th IEEE Real-Time Systems Symposium (Cat. No.98CB36279), pages 4-13, December 1998. URL: http://dx.doi.org/10.1109/REAL.1998.739726.
  2. N.C. Audsley. Optimal Priority Assignment And Feasibility Of Static Priority Tasks With Arbitrary Start Times. Technical report YCS 164, 1991. Google Scholar
  3. Paul Barham, Boris Dragovic, Keir Fraser, Steven Hand, Tim Harris, Alex Ho, Rolf Neugebauer, Ian Pratt, and Andrew Warfield. Xen and the Art of Virtualization. In Proceedings of the Nineteenth ACM Symposium on Operating Systems Principles, SOSP '03, pages 164-177, New York, NY, USA, 2003. ACM. URL: http://dx.doi.org/10.1145/945445.945462.
  4. Alan Burns and Robert I. Davis. Mixed Criticality Systems - A review. Tech Rep of the University of York, 2018. URL: https://www-users.cs.york.ac.uk/burns/review.pdf.
  5. Maxime Chéramy, Pierre-Emmanuel Hladik, and Anne-Marie Déplanche. SimSo: A Simulation Tool to Evaluate Real-Time Multiprocessor Scheduling Algorithms. In Proc. of the 5th International Workshop on Analysis Tools and Methodologies for Embedded and Real-time Systems, WATERS, 2014. Google Scholar
  6. M. Cinque and D. Cotroneo. Towards Lightweight Temporal and Fault Isolation in Mixed-Criticality Systems with Real-Time Containers. In 2018 48th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSN-W), pages 59-60, June 2018. URL: http://dx.doi.org/10.1109/DSN-W.2018.00029.
  7. M. Cinque and G. De Tommasi. Work-in-Progress: Real-Time Containers for Large-Scale Mixed-Criticality Systems. In 2017 IEEE Real-Time Systems Symposium (RTSS), pages 369-371, December 2017. URL: http://dx.doi.org/10.1109/RTSS.2017.00046.
  8. N. T. Dantam, D. M. Lofaro, A. Hereid, P. Y. Oh, A. D. Ames, and M. Stilman. The Ach Library: A New Framework for Real-Time Communication. IEEE Robotics Automation Magazine, 22(1):76-85, March 2015. URL: http://dx.doi.org/10.1109/MRA.2014.2356937.
  9. Z. Deng and J. W. . Liu. Scheduling real-time applications in an open environment. In Proceedings Real-Time Systems Symposium, pages 308-319, December 1997. URL: http://dx.doi.org/10.1109/REAL.1997.641292.
  10. P. Emberson, R. Stafford, and R.I. Davis. Techniques For The Synthesis Of Multiprocessor Tasksets. In WATERS workshop at the Euromicro Conference on Real-Time Systems, pages 6-11, July 2010. Google Scholar
  11. G. Farrall, C. Stellwag, J. Diemer, and R. Ernst. Hardware and software support for mixed-criticality multicore systems. In Proc. of the Conference on Design, Automation and Test in Europe, WICERT, DATE, 2013. Google Scholar
  12. G. Garre, D. Mundo, M. Gubitosa, and A. Toso. Real-Time and Real-Fast Performance of General-Purpose and Real-Time Operating Systems in Multithreaded Physical Simulation of Complex Mechanical Systems. Mathematical Problems in Engineering, Article ID 945850, 2014. URL: http://dx.doi.org/10.1155/2014/945850.
  13. M. Joseph and P. Pandya. Finding Response Times in a Real-Time System. The Computer Journal, 29(5):390-395, January 1986. URL: http://dx.doi.org/10.1093/comjnl/29.5.390.
  14. R. Kaiser. The PikeOS concept history and design. Technical Report, SYSGO, 2007. Google Scholar
  15. K. Lakshmanan, D. d. Niz, R. Rajkumar, and G. Moreno. Resource Allocation in Distributed Mixed-Criticality Cyber-Physical Systems. In 2010 IEEE 30th International Conference on Distributed Computing Systems, pages 169-178, June 2010. URL: http://dx.doi.org/10.1109/ICDCS.2010.91.
  16. Juri Lelli, Claudio Scordino, Luca Abeni, and Dario Faggioli. Deadline scheduling in the Linux kernel. Software: Practice and Experience, 46(6):821-839, 2016. URL: http://dx.doi.org/10.1002/spe.2335.
  17. G. Lipari and S. Baruah. A hierarchical extension to the constant bandwidth server framework. In Proceedings Seventh IEEE Real-Time Technology and Applications Symposium, pages 26-35, May 2001. URL: http://dx.doi.org/10.1109/RTTAS.2001.929863.
  18. C. Mao, M. Huang, S. Padhy, S. Wang, W. Chung, Y. Chung, and C. Hsu. Minimizing Latency of Real-Time Container Cloud for Software Radio Access Networks. In 2015 IEEE 7th International Conference on Cloud Computing Technology and Science (CloudCom), pages 611-616, November 2015. URL: http://dx.doi.org/10.1109/CloudCom.2015.67.
  19. Philip Masek, Magnus Thulin, Hugo Sica de Andrade, Christian Berger, and Ola Benderius. Systematic Evaluation of Sandboxed Software Deployment for Real-time Software on the Example of a Self-Driving Heavy Vehicle. CoRR, abs/1608.06759, 2016. URL: http://arxiv.org/abs/1608.06759.
  20. Miguel Masmano, Ismael Ripoll, Alfons Crespo, and J Metge. Xtratum: a hypervisor for safety critical embedded systems. In 11th Real-Time Linux Workshop, pages 263-272. Citeseer, 2009. Google Scholar
  21. M. S. Mollison, J. P. Erickson, J. H. Anderson, S. K. Baruah, and J. A. Scoredos. Mixed-Criticality Real-Time Scheduling for Multicore Systems. 10th IEEE International Conference on Computer and Information Technology, Bradford, pp. 1864-1871, 2010. Google Scholar
  22. R. Santos, S. Venkataraman, A. Das, and A. Kumar. Criticality-aware scrubbing mechanism for SRAM-based FPGAs. Technical report, Nanyang Technological University, Singapore, 2014. Google Scholar
  23. Brinkley Sprunt, Lui Sha, and John Lehoczky. Aperiodic task scheduling for Hard-Real-Time systems. Real-Time Systems, 1(1):27-60, June 1989. URL: http://dx.doi.org/10.1007/BF02341920.
  24. X. Wang, Z. Li, and W. M. Wonham. Optimal Priority-Free Conditionally-Preemptive Real-Time Scheduling of Periodic Tasks Based on DES Supervisory Control. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 47(7):1082-1098, July 2017. URL: http://dx.doi.org/10.1109/TSMC.2016.2531681.
  25. WindRiver. VxWorks Virtualization Profile. http://www.windriver.com/products/vxworks/technology-profiles/#virtualization. [Online; accessed 15-Jan-2019].
  26. A. Winter, P. Makijarvi, S. Simrock, J.A. Snipes, A. Wallander, and L. Zabeo. Towards the conceptual design of the ITER real-time plasma control system. Fusion Engineering and Design, 89(3):267-272, 2014. URL: http://dx.doi.org/10.1016/j.fusengdes.2014.02.064.
  27. S. Xi, C. Li, C. Lu, C. D. Gill, M. Xu, L. T. X. Phan, I. Lee, and O. Sokolsky. RT-Open Stack: CPU Resource Management for Real-Time Cloud Computing. In 2015 IEEE 8th International Conference on Cloud Computing, pages 179-186, June 2015. URL: http://dx.doi.org/10.1109/CLOUD.2015.33.
  28. S. Xi, M. Xu, C. Lu, L. T. X. Phan, C. Gill, O. Sokolsky, and I. Lee. Real-time multi-core virtual machine scheduling in Xen. In 2014 International Conference on Embedded Software (EMSOFT), pages 1-10, October 2014. URL: http://dx.doi.org/10.1145/2656045.2656061.
  29. Sisu Xi, Justin Wilson, Chenyang Lu, and Christopher Gill. RT-Xen: Towards Real-time Hypervisor Scheduling in Xen. In Proceedings of the Ninth ACM International Conference on Embedded Software, EMSOFT '11, pages 39-48, New York, NY, USA, 2011. ACM. URL: http://dx.doi.org/10.1145/2038642.2038651.
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