Reducing System Level Power Consumption for Mobile and Embedded Platforms

  • Ripal Nathuji
  • Karsten Schwan
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3432)


The power consumption of peripheral devices is a significant portion of the overall energy usage of a mobile platform. To take advantage of idle times, most devices offer the ability to transition into low power states. However, the amount of energy saved by utilizing these sleep states depends on the lengths and number of idle periods experienced by the device. This paper describes a new process scheduling algorithm which accumulates device usage information in the form of device windows to make power a first class resource: it attempts to increase the burstiness of both device accesses and idle periods, and it provides enhanced behavior for timeout-based sleep mechanisms. An initial implementation based on the default Linux scheduler demonstrates the algorithm’s and approach’s ability to reduce the average power consumption of devices by increasing device sleep times and reducing transition overheads.


Schedule Algorithm Idle Time Sleep Mode Idle Period Device Access 
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.
    Kravets, R., Krishnan, P.: Application-Driven Power Management for Mobile Communication. In: Proceedings of the Fourth ACM International Conference on Mobile Computing and Networking (MOBICOM), pp. 263–277 (1998)Google Scholar
  2. 2.
    Lu, Y., Chung, E., Simunic, T., Benini, L., Micheli, G.: Quantitative Comparison of Power Management Algorithms. In: Design Automation and Test in Europe, pp. 20–26 (2000)Google Scholar
  3. 3.
    Ellis, C.: The Case for Higher-Level Power Management. In: Proceedings of the Seventh IEEE Workshop on Hot Topics in Operating Systems, HotOS-VII (1999)Google Scholar
  4. 4.
    Lu, Y., Benini, L., Micheli, G.: Operating System Directed Power Reduction. In: International Symposium on Low Power Electronics and Design, pp. 37–42 (2000)Google Scholar
  5. 5.
    Weiser, M., Welch, B., Demers, A., Shenker, S.: Scheduling for Reduced CPU Energy. In: Proceedings of the First Symposium on Operating Systems Design and Implementation, pp. 13–23 (1994)Google Scholar
  6. 6.
    Swaminathan, V., Chakrabarty, K.: Real-time task scheduling for energy-aware embedded systems. In: Proceedings of Real-time Systems and Symposium (Workin-Progress Session) (2000)Google Scholar
  7. 7.
    Swaminathan, V., Schweizer, C., Chakrabarty, K., Patel, A.: Experiences in Implementing an Energy-Driven Task Scheduler in RT-Linux. In: Proceedings of the Real-time and Embedded Technology and Applications Symposium, pp. 229–239 (2002)Google Scholar
  8. 8.
    Chou, P., Liu, J., Li, D., Bagherzadeh, N.: IMPACCT:Methodology and Tools for Power-Aware Embedded Systems. Kluwer Design Automation of Embedded Systems (2002)Google Scholar
  9. 9.
    Poellabauer, C., Schwan, K.: Power-Aware Video Decoding using Real-Time Event Handlers. In: Proceedings of the 5th International Workshop on Wireless Mobile Multimedia, WoWMoM (2002)Google Scholar
  10. 10.
    AbouGhazaleh, N., Mosse, D., Childers, B., Melhem, R., Craven, M.: Collaborative Operating System and Compiler Power Management for Real-Time Applications. In: Proceedings of the IEEE Real-Time and Embedded Technology and Applications Symposium, RTAS (2003)Google Scholar
  11. 11.
    Zeng, H., Fan, X., Ellis, C., Lebeck, A., Vahdat, A.: ECOSystem: Managing Energy as a First Class Operating System Resource. In: Proceedings of the Tenth International Conference on Architectural Support for Programming Languages and Operating Systems, ASPLOS X (2002)Google Scholar
  12. 12.
    Zeng, H., Ellis, C., Lebeck, A., Vahdat, A.: Currentcy: A Unifying Abstraction for Expressing Energy Management Policies. In: Proceedings of USENIX, pp. 43–56 (2003)Google Scholar
  13. 13.
    Bellosa, F.: The Benefits of Event-Driven Energy Accounting in Power-Sensitive Systems. In: Proceedings of the 9th ACM SIGOPS European Workshop (2000)Google Scholar
  14. 14.
    Shih, E., Bahl, P., Sinclair, M.: Wake on Wireless: An Event Driven Energy Saving Strategy for Battery Operated Devices. In: Proceedings of ACM MobiCom, pp. 160–171 (2002)Google Scholar
  15. 15.
    Krashinsky, R., Balakrishnan, H.: Minimizing Energy for Wireless Web Access with Bounded Slowdown. In: Proceedings of ACM MOBICOM, pp. 119–130 (2002)Google Scholar
  16. 16.
    Weissel, A., Beutel, B., Bellosa, F.: Cooperative I/O-A Novel IO Semantics for Energy-Aware Applications. In: Proceedings of the Fifth Symposium on Operating Systems Design and Implementation, OSDI (2002)Google Scholar
  17. 17.
    Swaminathan, V., Chakrabarty, K., Iyengar, S.: Dynamic I/O Power Management for Hard Real-time Systems. In: Proceedings of International Symposium on Hardware/Software Codesign, pp. 237–243 (2001)Google Scholar
  18. 18.
    Lu, Y., Benini, L., Micheli, G.: Low-Power Task Scheduling for Multiple Devices. In: 8th International Workshop on Hardware/Software Codesign, pp. 39–43 (2000)Google Scholar
  19. 19.
    Lu, Y., Benini, L., Micheli, G.: Power-Aware Operating Systems for Interactive Systems. In: IEEE Transactions on Very Large Scale Integration Systems, pp. 119–134 (2002)Google Scholar
  20. 20.
    Squillante, M., Lazowska, E.: Using Processor-Cache Affinity Information in Shared-Memory Multiprocessor Scheduling. IEEE Transactions on Parallel and Distributed Systems 4, 131–143 (1993)CrossRefGoogle Scholar
  21. 21.
    Havinga, P., Smit, G.: Energy-Efficient Wireless Networking for Multimedia Applications. Journal on Wireless Communications and Mobile Computing (2001)Google Scholar
  22. 22.
    Poellabauer, C., Schwan, K.: Energy-Aware Traffic Shaping for Wireless Real-Time Applications. In: Proceedings of the Real-Time and Embedded Technology and Applications Symposium (2004)Google Scholar
  23. 23.
    Poellabauer, C., Schwan, K.: Energy-Aware Media Transcoding in Wireless Systems. In: Proceedings of the Second IEEE International Conference on Pervasive Computing and Communications, PerCom 2004 (2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Ripal Nathuji
    • 1
  • Karsten Schwan
    • 1
  1. 1.College of ComputingGeorgia Institute of TechnologyAtlantaUSA

Personalised recommendations