skip to main content
article

Algorithmic problems in power management

Published:01 June 2005Publication History
Skip Abstract Section

Abstract

We survey recent research that has appeared in the theoretical computer science literature on algorithmic problems related to power management. We will try to highlight some open problem that we feel are interesting. This survey places more concentration on lines of research of the authors: managing power using the techniques of speed scaling and power-down which are also currently the dominant techniques in practice.

References

  1. http://www-bsac.eecs.berkeley.edu/archive/users/warneke-brett/SmartDust/.Google ScholarGoogle Scholar
  2. http://www.microsoft.com/windows2000/techenthusiast/features/standby 1127.asp.Google ScholarGoogle Scholar
  3. http://www2.parc.com/spl/projects/cosense/csp/ slides/Srivastava.pdf.Google ScholarGoogle Scholar
  4. http://www.rockwellscientific.com/hidra/.Google ScholarGoogle Scholar
  5. J. Augustine, S. Irani, K. Pruhs, and P. Uthaisombut. unpublished manuscript.Google ScholarGoogle Scholar
  6. John Augustine, Sandy Irani, and Chaitanya Swamy. Optimal power-down strategies. In Foundations of Computer Science, 2004. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. N. Bansal, T. Kimbrel, and K. Pruhs. Dynamic speed scaling to manage energy and temperature. In IEEE Symposium on Foundations of Computer Science, 2004. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. N. Bansal and K. Pruhs. Speed scaling to manage temperature. In Symposium on Theoretical Aspects of Computer Science, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Shekhar Borkar. Design challenges of technology scaling. IEEE Micro, 19(4):23--29, 1999. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Stephen Boyd and Lieven Vandenberghe. Convex Optimization. Cambridge University Press, 2004. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. David M. Brooks, Pradip Bose, Stanley E. Schuster, Hans Jacobson, Prabhakar N. Kudva, Alper Buyuktosunoglu, John-David Wellman, Victor Zyuban, Manish Gupta, and Peter W. Cook. Power-aware microarchitecture: Design and modeling challenges for next-generation microprocessors. IEEE Micro, 20(6):26--44, 2000. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Giorgio Buttazzo. Hard Real-Time Computing Systems. Kluwer, 1997. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Anantha Chandrakasan, Rex Min, Manish Bhardwaj, Seong-Hwan Cho, and Alice Wang. Power aware wireless microsensor systems. In European Solid-State Circuits Conference, 2002.Google ScholarGoogle ScholarCross RefCross Ref
  14. Carla Schlatter Ellis. The case for higher-level power management. In IEEE Workshop on Hot Topics in Operating Systems, 1999. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. C. Guo, L. C. Zhong, and J. M. Rabaey. Low power distributed mac for ad hoc sensor radio networks. In Proceedings of IEEE GlobeCom, 2001.Google ScholarGoogle Scholar
  16. S. Irani, R. K. Gupta, and S. Shukla. Algorithms for Power Savings. In ACM/SIAM Symposium on Discrete Algorithms, 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. S. Irani, R. Gupta, and S. Shukla. Competitive analysis of dynamic power management strategies for systems with multiple power savings states. In IEEE Conference on Design, Automation and Test in Europe, 2002. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. S. Irani and A. Karlin. Online computation. In Dorit Hochbaum, editor, Approximations for NP-Hard Problems. PWS Publishing Co., 1995. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Sandy Irani, Sandeep Shukla, and Rajesh Gupta. 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 ScholarGoogle ScholarDigital LibraryDigital Library
  20. R. Jejurikar and R. Gupta. Procrastination scheduling for fixed priority real-time systems. In Proc. of ACM SIGPLAN/SIGBED Conference on Languages, Compilers, and Tools for Embedded Systems, 2004. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. R. Jejurikar, C. Pereira, and R. Gupta. Leakage aware energy efficient task scheduling in embedded real-time systems. In Proceedings of the Design Automation Conference, 2004.Google ScholarGoogle Scholar
  22. J. M. Kahn, R. H. Katz, and K. S. J. Pister. Next century challenges: mobile networking for smart dust. In Proceedings of the 5th annual ACM/IEEE international conference on Mobile computing and networking, pages 271--278, 1999. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. Bala Kalyanasundaram and Kirk Pruhs. Speed is as powerful as clairvoyance. J. ACM, 47(4):617--643, 2000. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. A Karlin, M. Manasse, L. McGeoch, and S. Owicki. Randomized competitive algorithms for nonuniform problems. In ACM-SIAM Symposium on Discrete Algorithms, pages 301--309, 1990. Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. W. Kwon and T. Kim. Optimal voltage allocation techniques for dynamically variable voltage processors. In Design Automation, 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. Minming Li, Becky Jie Liu, and Frances F. Yao. Min-energy voltage allocation for tree-structured tasks. In International Computing and Combinatorics Conference, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. John Markov. http://www.iht.com/articles/520233.html.Google ScholarGoogle Scholar
  28. Trevor Mudge. Power: A first-class architectural design constraint. Computer, 34(4):52--58, 2001. Google ScholarGoogle ScholarDigital LibraryDigital Library
  29. Kirk Pruhs, Jiri Sgall, and Eric Torng. Online scheduling. In Handbook on Scheduling. CRC Press, 2004.Google ScholarGoogle Scholar
  30. Kirk Pruhs, Patchrawat Uthaisombut, and Gerhard Woeginger. Getting the best response for your erg. In Scandanavian Workshop on Algorithms and Theory, 2004.Google ScholarGoogle ScholarCross RefCross Ref
  31. D. Ramanathan, S. Irani, and R. K. Gupta. Latency Effects of System Level Power Management Algorithms. In IEEE International Conference on Computer-Aided Design, 2000. Google ScholarGoogle ScholarDigital LibraryDigital Library
  32. D. Ramanathan, S. Irani, and R. Gupta. An Analysis of System Level Power Management Algorithms and their effects on Latency. IEEE Trans. on Computer Aided Design, 21(3), march 2002.Google ScholarGoogle Scholar
  33. Jerry E. Sergent and Al Krum. Thermal Management Handbook. McGraw-Hill, 1998.Google ScholarGoogle Scholar
  34. Kevin Skadron, Mircea R. Stan, Wei Huang, Sivakumar Velusamy, Karthik Sankaranarayanan, and David Tarjan. Temperature-aware microarchitecture. In International Symposium on Computer Architecture, pages 2--13, 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library
  35. Donald R. Smith. Variational Methods in Optimization. Prentice-Hall, 1974.Google ScholarGoogle Scholar
  36. Vivek Tiwari, Deo Singh, Suresh Rajgopal, Gaurav Mehta, Rakesh Patel, and Franklin Baez. Reducing power in high-performance microprocessors. In Design Automation Conference, pages 732--737, 1998. Google ScholarGoogle ScholarDigital LibraryDigital Library
  37. F. Yao, A. Demers, and S. Shenker. A scheduling model for reduced cpu energy. In IEEE Symposium on Foundations of Computer Science, page 374, 1995. Google ScholarGoogle ScholarDigital LibraryDigital Library
  38. Wei Ye, John Heidemann, and Deborah Estrin. An energy-efficient mac protocol for wireless sensor networks. In Proceedings 21st International Annual Joint Conference of the IEEE Computer and Communications Societies, 2002.Google ScholarGoogle Scholar
  39. H.S. Yun and J. Kim. On energy-optimal voltage scheduling for fixed priority hard real-time systems. ACM Transactions on Embedded Computing Systems, 2(3):393--430, 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library
  40. Technical specifications of hard drive IBM Travelstar VP 2.5inch, available at. http://www.storage.ibm.com/storage/oem/data/travvp.htm, 1996.Google ScholarGoogle Scholar

Index Terms

  1. Algorithmic problems in power management

      Recommendations

      Comments

      Login options

      Check if you have access through your login credentials or your institution to get full access on this article.

      Sign in

      Full Access

      • Published in

        cover image ACM SIGACT News
        ACM SIGACT News  Volume 36, Issue 2
        June 2005
        101 pages
        ISSN:0163-5700
        DOI:10.1145/1067309
        Issue’s Table of Contents

        Copyright © 2005 Authors

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 1 June 2005

        Check for updates

        Qualifiers

        • article

      PDF Format

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader