Skip to main content

Speed Scaling with a Solar Cell

  • Conference paper
Algorithmic Aspects in Information and Management (AAIM 2008)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 5034))

Included in the following conference series:

Abstract

We consider the speed scaling problem of scheduling a collection of tasks with release times, deadlines, and sizes so as to minimize the energy recharge rate. This is the first theoretical investigation of speed scaling for devices with a regenerative energy source. We show that the problem can be expressed as a polynomial sized convex program. We that using the KKT conditions, one can obtain an efficient algorithm to verify the optimality of a schedule. We show that the energy optimal YDS schedule, is 2-approximate with respect to the recharge rate. We show that the online algorithm BKP is O(1)-competitive with respect to recharge rate.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. http://www.eetimes.com/story/OEG20020405S0015

  2. Albers, S., Fujiwara, H.: Energy-efficient algorithms for flow time minimization. In: Durand, B., Thomas, W. (eds.) STACS 2006. LNCS, vol. 3884, pp. 621–623. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  3. Albers, S., Müller, F., Schmelzer, S.: Speed scaling on parallel processors. In: Proc. ACM Symposium on Parallel Algorithms and Architectures (SPAA), pp. 289–298 (2007)

    Google Scholar 

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

    Google Scholar 

  5. Bansal, N., Bunde, D., Chan, H.-L., Pruhs, K.: Average rate speed scaling. In: LATIN 2008 (to appear, 2008)

    Google Scholar 

  6. Bansal, N., Chan, H.-L., Pruhs, K., Rogozhnikov-Katz, D.: Improved bounds for speed scaling in devices obeying the cube-root rule. In: IBM Research Technical Report

    Google Scholar 

  7. Bansal, N., Pruhs, K.: Speed scaling to manage temperature. In: Diekert, V., Durand, B. (eds.) STACS 2005. LNCS, vol. 3404, pp. 460–471. Springer, Heidelberg (2005)

    Google Scholar 

  8. Bansal, N., Pruhs, K., Stein, C.: Speed scaling for weighted flow time. In: SODA 2007: Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms, pp. 805–813 (2007)

    Google Scholar 

  9. Boyd, S., Vandenberghe, L.: Convex Optimization. Cambridge University Press, Cambridge (2004)

    MATH  Google Scholar 

  10. Brooks, D.M., Bose, P., Schuster, S.E., Jacobson, H., Kudva, P.N., Buyuktosunoglu, A., Wellman, J.-D., Zyuban, V., Gupta, M., Cook, P.W.: Power-aware microarchitecture: Design and modeling challenges for next-generation microprocessors. IEEE Micro. 20(6), 26–44 (2000)

    Article  Google Scholar 

  11. Chan, H.-L., Chan, W.-T., Lam, T.-W., Lee, L.-K., Mak, K.-S., Wong, P.W.H.: Energy efficient online deadline scheduling. In: SODA 2007: Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms, pp. 795–804 (2007)

    Google Scholar 

  12. Irani, S., Shukla, S., Gupta, R.: Online strategies for dynamic power management in systems with multiple power saving states. Trans. on Embedded Computing Sys (2003); Special Issue on Power Aware Embedded Computing

    Google Scholar 

  13. Kwon, W.-C., Kim, T.: Optimal voltage allocation techniques for dynamically variable voltage processors. In: Proc. ACM-IEEE Design Automation Conf., pp. 125–130 (2003)

    Google Scholar 

  14. Li, M., Liu, B.J., Yao, F.F.: Min-energy voltage allocation for tree-structured tasks. Journal of Combinatorial Optimization 11(3), 305–319 (2006)

    Article  MATH  MathSciNet  Google Scholar 

  15. Li, M., Yao, F.F.: An efficient algorithm for computing optimal discrete voltage schedules. SIAM J. on Computing 35, 658–671 (2005)

    Article  MathSciNet  Google Scholar 

  16. Yao, F., Demers, A., Shenker, S.: A scheduling model for reduced CPU energy. In: Proc. IEEE Symp. Foundations of Computer Science, pp. 374–382 (1995)

    Google Scholar 

  17. Yun, H.S., Kim, J.: On energy-optimal voltage scheduling for fixed priority hard real-time systems. ACM Trans. on Embedded Computing Systems 2(3), 393–430 (2003)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Rudolf Fleischer Jinhui Xu

Rights and permissions

Reprints and permissions

Copyright information

© 2008 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Bansal, N., Chan, HL., Pruhs, K. (2008). Speed Scaling with a Solar Cell. In: Fleischer, R., Xu, J. (eds) Algorithmic Aspects in Information and Management. AAIM 2008. Lecture Notes in Computer Science, vol 5034. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68880-8_4

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-68880-8_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-68865-5

  • Online ISBN: 978-3-540-68880-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics