Reliability Comparison of Schedulability Test in Ubiquitous Computing

  • Fei Teng
  • Lei Yu
  • Frédéric Magoulès
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6905)


The development of ubiquitous intelligent has increased the real-time requirements for computing system. If one real-time computation does not complete before its deadline, it is as worse as that the computation is never executed at all. Ineffective computation not only wastes computational resources, but also might bring system overload and collapse. Hence, a schedulability test is necessary to ensure the stability of ubiquitous system. The schedulability test is concerned with determining whether a set of tasks is schedulable on a cluster. Although a number of schedulability tests have been developed, they can not be compared due to distinct test principles. In this paper, we propose a reliability indicator, through which the probability that a random task set succeeds in schedulability test can be evaluated. The larger the probability is, the better the test is. The reliability of two sufficient deadline monotonic tests are compared, and the comparison result is further validated by detailed experiments. Both analysis and experimental results show that the performance discrepancy of schedulability test is determined by a prerequisite pattern. Since this pattern can be deduce by reliability indicator, it may help system designers choose a good schedulability test in advance.


Ubiquitous Computing Schedulability Test Relative Deadline Aperiodic Task Task Utilization 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Nguyen, T.-M.-H., Magoulès, F.: Autonomic data management system in grid environment. Journal of Algorithms and Computational Technologies 3, 155–178 (2009)CrossRefGoogle Scholar
  2. 2.
    Yu, L., Magoulès, F.: Service scheduling and rescheduling in an applications integration framework. Advances in Engineering Software 40(9), 941–946 (2009)CrossRefzbMATHGoogle Scholar
  3. 3.
    Masrur, A., Chakraborty, S., Färber, G.: Constant-time admission control for deadline monotonic tasks. In: Proceedings of the Conference on Design, Automation and Test in Europe (DATE), pp. 220–225 (2010)Google Scholar
  4. 4.
    Liu, C.L., Layland, J.W.: Scheduling algorithms for multiprogramming in a hard-real-time environment. Journal of the Association for Computing Machinery 20(1), 46–61 (1973)MathSciNetCrossRefzbMATHGoogle Scholar
  5. 5.
    Peng, D.-T., Shin, K.G.: A new performance measure for scheduling independent real-time tasks. Journal of Parallel Distributed Computing 19, 11–26 (1993)MathSciNetCrossRefzbMATHGoogle Scholar
  6. 6.
    Bini, E., Buttazzo, G.C., Buttazzo, G.: Rate monotonic analysis: The hyperbolic bound. IEEE Transactions on Computers 52(7), 933–942 (2003)CrossRefGoogle Scholar
  7. 7.
    Abdelzaher, T.F., Sharma, V., Lu, C.: A utilization bound for aperiodic tasks and priority driven scheduling. IEEE Transactions on Computers 53(3), 334–350 (2004)CrossRefGoogle Scholar
  8. 8.
    Leung, J.Y.T., Whitehead, J.: On the complexity of fixed-priority scheduling of periodic, real-time tasks. Performance Evaluation 2, 237–250 (1982)MathSciNetCrossRefzbMATHGoogle Scholar
  9. 9.
    Buttazzo, G.C.: Rate monotonic vs. edf: judgment day. Real-Time Systems 29, 5–26 (2005)CrossRefzbMATHGoogle Scholar
  10. 10.
    Joseph, M., Pandya, P.K.: Finding response times in a real-time system. The Computer Journal 29, 390–395 (1986)MathSciNetCrossRefGoogle Scholar
  11. 11.
    Audsley, N., Burns, A., Richardson, M., Tindell, K., Wellings, A.J.: Applying new scheduling theory to static priority pre-emptive scheduling. Software Engineering Journal 8, 284–292 (1993)CrossRefGoogle Scholar
  12. 12.
    Lehoczky, J.P.: Fixed priority scheduling of periodic task sets with arbitrary deadlines. In: Proceedings of the 11th Real-Time Systems Symposium, pp. 201–209 (1990)Google Scholar
  13. 13.
    Sjodin, M., Hansson, H.: Improved response-time analysis calculations. In: Proceedings of IEEE Real-Time Systems Symposium, pp. 399–408 (1998)Google Scholar
  14. 14.
    Abdelzaher, T.F., Lu, C.: Schedulability analysis and utilization bounds for highly scalable real-time service. In: Proceedings of IEEE Real Time Technology and Applications Symposium, pp. 15–25 (2001)Google Scholar
  15. 15.
    Chen, D., Mok, A.K., Kuo, T.-W.: Utilization bound revisited. IEEE Transactions on Computers 52, 351–361 (2003)CrossRefGoogle Scholar
  16. 16.
    Bini, E., Buttazzo, G.C.: Schedulability analysis of periodic fixed priority systems. IEEE Transactions on Computers 53(11), 1462–1473 (2004)CrossRefGoogle Scholar
  17. 17.
    Fisher, N., Baruah, S.K.: A fully polynomial-time approximation scheme for feasibility analysis in static-priority systems with bounded relative deadlines. Journal of Embedded Computing 2(3-4), 291–299 (2006)Google Scholar
  18. 18.
    Teng, F., Yu, L., Magoules, F.: SimMapReduce: a simulator for modeling MapReduce framework. In: Proceedings of International Conference on Multimedia and Ubiquitous Engineering, Loutraki, Greece, pp. 277–282 (June 2011)Google Scholar
  19. 19.
    Bini, E., Buttazzo, G.C.: Measuring the performance of schedulability tests. Real-Time Systems 30(1-2), 129–154 (2005)CrossRefzbMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Fei Teng
    • 1
  • Lei Yu
    • 2
  • Frédéric Magoulès
    • 1
  1. 1.Ecole Centrale ParisChatenay-MalabryFrance
  2. 2.Ecole Centrale de PekinBeihang UniversityBeijingChina

Personalised recommendations