Real-Time Systems

, Volume 46, Issue 2, pp 160–188 | Cite as

Schedulability analysis in hard real-time systems under thermal constraints

Article

Abstract

In this paper, we study thermal-constrained hard real-time systems, where real-time guarantees must be met without exceeding safe temperature levels within the processor. Dynamic speed scaling is one of the major techniques to manage power so as to maintain safe temperature levels. As example, we adopt a reactive speed control technique in our work. We design an extended busy-period analysis methodology to perform schedulability analysis for general task arrivals under reactive speed control with First-In-First-Out (FIFO), Static-Priority (SP), and Earliest-Deadline-First (EDF) scheduling. As a special case, we obtain a closed-form formula for the worst-case response time of jobs under the leaky-bucket task arrival model. Our data show how reactive speed control can decrease the worst-case response time of tasks in comparison with any constant-speed scheme.

Keywords

Thermal Dynamic speed scaling Real-time Scheduling Schedulability analysis 

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References

  1. Advanced configuration and power interface specification (2010) http://www.acpi.info/spec.htm. The last access time is July 2010
  2. Semiconductor Industry Association (2005) 2005 international technology roadmap for semiconductors. http://public.itrs.net. The last access time is July 2010
  3. Bansal N, Kimbrel T, Pruhs K (2005) Dynamic speed scaling to manage energy and temperature. In: IEEE symposium on foundations of computer science Google Scholar
  4. Bansal N, Pruhs K (2005) Speed scaling to manage temperature. In: Symposium on theoretical aspects of computer science Google Scholar
  5. Brooks D, Martonosi M (2001) Dynamic thermal management for high-performance microprocessors. In: The 7th international symposium on high-performance computer architecture, pp 171–182 Google Scholar
  6. Chantem T, Dick RP, Hu XS (2008) Temperature-aware scheduling and assignment for hard real-time applications on MPSoCs. In: Design, automation and test in Europe Google Scholar
  7. Chen J-J, Hung C-M, Kuo T-W (2007) On the minimization of the instantaneous temperature for periodic real-time tasks. In: IEEE real-time and embedded technology and applications symposium Google Scholar
  8. Cohen A, Finkelstein L, Mendelson A, Ronen R, Rudoy D (2003) On estimating optimal performance of CPU dynamic thermal management. In: Computer architecture letters Google Scholar
  9. Cohen A, Finkelstein L, Mendelson A, Ronen R, Rudoy D (2006) On estimating optimal performance of CPU dynamic thermal management. In: Computer architecture letters Google Scholar
  10. Dhodapkar A, Lim CH, Cai G, Daasch WR (2000) TEMPEST: a thermal enabled multi-model power/performance estimator. In: Workshop on power-aware computer systems, ASPLOS-IX Google Scholar
  11. Ferreira AP, Oh J, Moss D (2006) Toward thermal-aware load-distribution for real-time server. In: IEEE real-time systems symposium work-in-progress session Google Scholar
  12. Gochman S, Mendelson A, Naveh A, Rotem E (2006) Introduction to Intel Core Duo processor architecture. Intel Technol J 10(2):89–97 Google Scholar
  13. Liu J (2000) Real-time systems. Prentice Hall, New York Google Scholar
  14. Rabaey JM, Chandrakasan A, Nikolic B (2002) Digital integrated circuits, 2nd edn. Prentice Hall, New York Google Scholar
  15. Rao R, Vrudhula S, Chakrabarti C, Chang N (2006) An optimal analytical solution for processor speed control with thermal constraints. In: International symposium on low power electronics and design. ACM Press, New York Google Scholar
  16. Rotem E, Naveh A, Moffie M, Mendelson A (2004) Analysis of thermal monitor features of the Intel Pentium M processor. In: Workshop on temperature-aware computer systems Google Scholar
  17. Sanchez H, Kuttanna B, Olson T, Alexander M, Gerosa G, Philip R, Alvarez J (1997) Thermal management system for high performance powerpc microprocessors. In: IEEE international computer conference Google Scholar
  18. Skadron K, Stan M, Huang W, Velusamy S, Sankaranarayanan K, Tarjan D (2003) Temperature-aware microarchitecture: extended discussion and results. Technical report CS-2003-08, Department of Computer Science, University of Virginia Google Scholar
  19. Srinivasan J, Adve SV (2003) Predictive dynamic thermal management for multimedia applications. In: International conference on supercomputing Google Scholar
  20. Tiwari V, Singh D, Rajgopal S, Mehta G, Patel R, Baez F (1998) Reducing power in high-performance microprocessors. In: Design automation conference, pp 732–737 Google Scholar
  21. Wang S, Bettati R (2006) Delay analysis in temperature-constrained hard real-time systems with general task arrivals. In: IEEE real-time systems symposium Google Scholar
  22. Wang S, Bettati R (2008) Reactive speed control in temperature-constrained real-time systems. Real-Time Syst J 39(1–3), 658–671 Google Scholar
  23. Wu J, Liu J, Zhao W (2005) On schedulability bounds of static priority schedulers. In: IEEE real-time and embedded technology and applications symposium Google Scholar
  24. Xu R, Zhu D, Rusu C, Melhem R, Moss D (2005) Energy efficient policies for embedded clusters. In: ACM SIGPLAN/SIGBED conference on languages, compilers, and tools for embedded systems Google Scholar
  25. Zhang S, Chatha KS (2007) Approximation algorithm for the temperature-aware scheduling problem. In: IEEE/ACM international conference on computer-aided design Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Shengquan Wang
    • 1
  • Youngwoo Ahn
    • 2
  • Riccardo Bettati
    • 2
  1. 1.Department of Computer and Information ScienceUniversity of Michigan-DearbornDearbornUSA
  2. 2.Department of Computer Science and EngineeringTexas A&M UniversityCollege StationUSA

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