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Mixed-Criticality Scheduling to Minimize Makespan

Authors Sanjoy Baruah, Arvind Easwaran, Zhishan Guo

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Keywords
  • Scheduling
  • Mixed criticality
  • Identical parallel machines
  • Makespan minimization
  • Approximation algorithm.

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Abstract

In the mixed-criticality job model, each job  is characterized by two execution time parameters, representing a smaller (less conservative) estimate and a larger (more conservative) estimate on its actual, unknown, execution time.  Each job is further classified as being either less critical or more critical.  The desired execution semantics are that all jobs should execute correctly provided all jobs complete upon being allowed to execute for up to the smaller of their execution time estimates, whereas if some jobs need to execute beyond their smaller execution time estimates (but not beyond their larger execution time estimates), then only the jobs classified as being more critical are required to execute  correctly.  The scheduling of collections of such mixed-criticality jobs upon identical multiprocessor platforms in order to minimize the makespan is considered here.

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Sanjoy Baruah, Arvind Easwaran, and Zhishan Guo. Mixed-Criticality Scheduling to Minimize Makespan. In 36th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2016). Leibniz International Proceedings in Informatics (LIPIcs), Volume 65, pp. 7:1-7:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016) https://doi.org/10.4230/LIPIcs.FSTTCS.2016.7

Author Details

Sanjoy Baruah
Arvind Easwaran
Zhishan Guo

References

  1. Sanjoy Baruah, Arvind Easwaran, and Zhishan Guo. MC-Fluid: simplified and optimally quantified. In Real-Time Systems Symposium (RTSS), 2015 IEEE, Dec 2015. Google Scholar
  2. Sanjoy K. Baruah, Liliana Cucu-Grosjean, Robert I. Davis, and Claire Maiza. Mixed Criticality on Multicore/Manycore Platforms (Dagstuhl Seminar 15121). Dagstuhl Reports, 5(3):84-142, 2015. URL: http://dx.doi.org/10.4230/DagRep.5.3.84.
  3. Alan Burns and Robert Davis. Mixed-criticality systems: A review. Available at http://www-users.cs.york.ac.uk/~burns/review.pdf, 2013.
  4. Chandra Chekuri and Sanjeev Khanna. On multi-dimensional packing problems. In Proceedings of the Tenth Annual ACM-SIAM Symposium on Discrete Algorithms, pages 185-194, January 1999. Google Scholar
  5. Chandra Chekuri and Sanjeev Khanna. On multidimensional packing problems. SIAM J. Comput., 33(4):837-851, 2004. URL: http://dx.doi.org/10.1137/S0097539799356265.
  6. Jr. E. Coffman and P. J. Denning. Operating Systems Theory. Prentice-Hall, Englewood Cliffs, NJ, 1973. Google Scholar
  7. Georgia Giannopoulou, Nikolay Stoimenov, Pengcheng Huang, and Lothar Thiele. Scheduling of mixed-criticality applications on resource-sharing multicore systems. In International Conference on Embedded Software (EMSOFT), pages 17:1-17:15, Montreal, Oct 2013. Google Scholar
  8. Lee Jaewoo, Kieu-My Phan, Xiaozhe Gu, Jiyeon Lee, A. Easwaran, Insik Shin, and Insup Lee. MC-Fluid: Fluid model-based mixed-criticality scheduling on multiprocessors. In Real-Time Systems Symposium (RTSS), 2014 IEEE, pages 41-52, Dec 2014. Google Scholar
  9. Jing Li, David Ferry, Shaurya Ahuja, Kunal Agrawal, Christopher Gill, and Chenyang Lu. Mixed-criticality federated scheduling for parallel real-time tasks. In Proceedings of the 22nd IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS), April 2016. Google Scholar
  10. R. McNaughton. Scheduling with deadlines and loss functions. Management Science, 6:1-12, 1959. Google Scholar
  11. Steve Vestal. Preemptive scheduling of multi-criticality systems with varying degrees of execution time assurance. In Proceedings of the Real-Time Systems Symposium, pages 239-243, Tucson, AZ, December 2007. IEEE Computer Society Press. Google Scholar
  12. Tjark Vredeveld. Vector scheduling problems. In Min-Yang Kao, editor, Encyclopedia of Algorithms. Springer, 2014. Google Scholar
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