Online algorithms for maximizing weighted throughput of unit jobs with temperature constraints

Abstract

We consider a temperature-aware online deadline scheduling model. The objective is to schedule a number of unit jobs, with release dates, deadlines, weights and heat contributions, to maximize the weighted throughput subject to a temperature threshold. We first give an optimally competitive randomized algorithm. Then we give a constant competitive randomized algorithm that allows a tradeoff between the maximum heat contribution of jobs and the competitiveness. Finally we consider the multiple processor case and give several tight upper and lower bounds.

This is a preview of subscription content, access via your institution.

Fig. 1

References

  1. Albers S (2010) Energy efficient algorithms. Commun ACM 53(5):86–96

    MathSciNet  Article  Google Scholar 

  2. Andelman N, Mansour Y, Zhu A (2003) Competitive queueing policies for QoS switches. In: Proceedings of 14th ACM-SIAM symposium on discrete algorithms, pp 761–770

    Google Scholar 

  3. Awerbuch B, Bartal Y, Fiat A, Rosen A (1994) Competitive non-preemptive call control. In: Proceedings of 5th ACM-SIAM symposium on discrete algorithms, pp 312–320

    Google Scholar 

  4. Bansal N, Kimbrel T, Pruhs K (2007) Dynamic speed scaling to manage energy and temperature. J ACM 54:1

    MathSciNet  MATH  Article  Google Scholar 

  5. Birks M, Fung SPY (2010) Temperature aware online scheduling with a low cooling factor. In: Proceedings of 7th annual conference on theory and applications of models of computation. Lecture notes in computer science, vol 6106, pp 105–116

    Google Scholar 

  6. Borodin A, Ran E-Y (1998) Online computation and competitive analysis. Cambridge University Press, New York

    MATH  Google Scholar 

  7. Chin FYL, Chrobak M, Fung SPY, Jawor W, Sgall J, Tichý T (2006) Online competitive algorithms for maximizing weighted throughput of unit jobs. J Discrete Algorithms 4(2):255–276

    MathSciNet  MATH  Article  Google Scholar 

  8. Chin FYL, Fung SPY (2003) Online scheduling with partial job values: Does timesharing or randomization help? Algorithmica 37(3):149–164

    MathSciNet  MATH  Article  Google Scholar 

  9. Chrobak M, Dürr C, Hurand M, Robert J (2008) Algorithms for temperature-aware task scheduling in microprocessor systems. In: Proceedings of 4th international conference on algorithmic aspects in information and management, pp 120–130

    Google Scholar 

  10. Coskun A, Rosing T, Whisnant K (2007) Temperature aware task scheduling in MPSoCs. In: Proc conference on design, automation and test in Europe, pp 1659–1664

    Google Scholar 

  11. Devadas V, Li F, Aydin H (2010) Competitive analysis of online real-time scheduling algorithms under hard energy constraint. Real-Time Syst 46:88–120

    MATH  Article  Google Scholar 

  12. Englert M, Westermann M (2007) Considering suppressed packets improves buffer management in QoS switches. In: Proceedings of 18th ACM-SIAM symposium on discrete algorithms, pp 209–218

    Google Scholar 

  13. Goldwasser MH (2010) A survey of buffer management policies for packet switches. SIGACT News 45(1):100–128

    Article  Google Scholar 

  14. Pruhs K, Uthaisombut P, Woeginger G (2008) Getting the best response for your erg. ACM Trans Algorithms 4:3

    MathSciNet  Article  Google Scholar 

  15. Yang J, Zhou X, Chrobak M, Zhango Y, Jin L (2008) Dynamic thermal management through task scheduling. In: IEEE international symposium on performance analysis of systems and software, pp 191–201

    Google Scholar 

  16. Yao AC-C (1977) Probabilistic computations: Toward a unified measure of complexity. In: Proceedings of 18th IEEE symposium on foundations of computer science, pp 222–227

    Google Scholar 

Download references

Acknowledgements

We thank the anonymous reviewers for their useful comments, and Kirk Pruhs for useful discussions.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Stanley P. Y. Fung.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Birks, M., Cole, D., Fung, S.P.Y. et al. Online algorithms for maximizing weighted throughput of unit jobs with temperature constraints. J Comb Optim 26, 237–250 (2013). https://doi.org/10.1007/s10878-012-9543-2

Download citation

Keywords

  • Online algorithms
  • Scheduling
  • Competitive analysis
  • Temperature
  • Resource augmentation