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Accurate online power estimation and automatic battery behavior based power model generation for smartphones

Published:24 October 2010Publication History

ABSTRACT

This paper describes PowerBooter, an automated power model construction technique that uses built-in battery voltage sensors and knowledge of battery discharge behavior to monitor power consumption while explicitly controlling the power management and activity states of individual components. It requires no external measurement equipment. We also describe PowerTutor, a component power management and activity state introspection based tool that uses the model generated by PowerBooter for online power estimation. PowerBooter is intended to make it quick and easy for application developers and end users to generate power models for new smartphone variants, which each have different power consumption properties and therefore require different power models. PowerTutor is intended to ease the design and selection of power efficient software for embedded systems. Combined, PowerBooter and PowerTutor have the goal of opening power modeling and analysis for more smartphone variants and their users.

References

  1. T. Cignetti, K. Komarov, and C. Ellis, Energy estimation tools for the Palm," in Proc. of the ACM Modeling, Analysis and Simulation of Wireless and Mobile Systems, 2000, pp. 96--103. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. A. Shye, B. Scholbrock, and G. Memik, Into the wild: studing real user activity patterns to guide power optimizations for mobile architectures," in Proc. Int. Symp. Microarchitecture, 2009, pp. 168--178. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. R. Joseph and M. Martonosi, Run-time power estimation in high-performance microprocessors," in Proc. Int. Symp. Low Power Electronics & Design, Aug. 2001, pp. 135--140. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. C. Isci and M. Martonosi, Runtime power monitoring in high-end processors: Methodology and empirical data," in Proc. Int. Symp. Microarchitecture, Dec. 2003, pp. 93--104. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. F. Bellosa, The benefits of event-driven energy accounting in power-sensitive systems," in Proc. Special Interest Group on Operating Systems European Wkshp., 2006, pp. 37--42. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. G. Contreras, et al., XTREM: a power simulator for the Intel XScale," in Proc. Conf. Languages, Compilers, and Tools for Embedded Systems, June 2004, pp. 115--125. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. J. Flinn and M. Satyanarayanan, PowerScope: a tool for profiling the energy usage of mobile applications," in Proc. Wkshp. on Mobile Computer Systems and Applications, 1999, p. 2. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. M. Dong and L. Zhong, Sesame: A self-constructive virtual power meter for battery-powered mobile systems," Tech. Rep., 2010.Google ScholarGoogle Scholar
  9. S. Gurun and C. Krintz, A run-time, feedback-based energy estimation model for embedded devices," in Proc. Int. Conf. Hardware/Software Codesign and System Synthesis, Oct. 2006, pp. 28--33. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Monsoon power monitor," http://www.msoon.com/LabEquipment/PowerMonitor/.Google ScholarGoogle Scholar
  11. MSM7000 chipset," http://www.qualcomm.com/products services/chipsets/index.html.Google ScholarGoogle Scholar
  12. Android SDK reference," http://developer.android.com/reference/packages.html.Google ScholarGoogle Scholar
  13. H. Holma and A. Toskala, HSDPA/HSUPA for UMTS: High Speed Radio Access for Mobile Communications. John Wiley & Sons, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. HTC Magic specification," http://www.htc.com/www/product/magic/overview.html.Google ScholarGoogle Scholar
  15. Environment working group data," http://www.ewg.org/cellphoneradiation/Get-a-Safer-Phone?&allavailable=1&order=sar.Google ScholarGoogle Scholar
  16. D. Linden and T. B. Reddy, Handbook of Batteries. MacGraw-Hill, 2002.Google ScholarGoogle Scholar
  17. Battery and energy characteristics," http://www.mpoweruk.com/performance.htm.Google ScholarGoogle Scholar
  18. PowerTutor," http://powertutor.org.Google ScholarGoogle Scholar

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      cover image ACM Conferences
      CODES/ISSS '10: Proceedings of the eighth IEEE/ACM/IFIP international conference on Hardware/software codesign and system synthesis
      October 2010
      348 pages
      ISBN:9781605589053
      DOI:10.1145/1878961

      Copyright © 2010 ACM

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      Publication History

      • Published: 24 October 2010

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