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7 - Smartphone subsystems

from Part II - Energy management and conservation

Published online by Cambridge University Press:  05 August 2014

Sasu Tarkoma
Affiliation:
University of Helsinki
Matti Siekkinen
Affiliation:
Aalto University, Finland
Eemil Lagerspetz
Affiliation:
University of Helsinki
Yu Xiao
Affiliation:
Aalto University, Finland
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Summary

To develop energy-efficient techniques, the first step is to understand how energy is consumed on a mobile device. A mobile device consists of hardware components, such as microprocessors, wireless network interfaces, storage, cameras and a touchscreen, and software running on top of these hardware components. Lower-power serial buses facilitate the communication between the internal system components. These hardware components are the actual energy consumers.

Smartphone and mobile device power optimization happens on multiple levels:

  1. • Silicon-level, in which the transistor capacitance and the chip design affect the energy efficiency. Higher capacitance requires the transistors to do more work.

  2. • SoC-level, in which multiple power/voltage/clock domains can be used to support granular power management with the help of software. In addition, dynamic voltage and frequency scaling (DVFS) is used to dynamically adjust both the voltage and frequency to meet the given energy and performance level.

  3. • Software-level, in which various power managers monitor and control the energy and power settings. A high-level framework is needed to perform system-wide tuning and optimization.

There are several choices that contribute critically to the overall efficiency of a mobile device, for instance from an energy-consumption viewpoint. They are the SoC including the CPU, display technology, communications technology, and the OS. The system-level power management is coordinated by the OS. In this chapter, we survey these crucial components and examine their energy consumption.

Type
Chapter
Information
Smartphone Energy Consumption
Modeling and Optimization
, pp. 92 - 136
Publisher: Cambridge University Press
Print publication year: 2014

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References

[1] J. L., Hennessy and D. A., Patterson, Computer Architecture: A Quantitative Approach, 3rd ed. San Francisco, CA, USA: Morgan Kaufmann Publishers Inc., 2003.Google Scholar
[2] ARM Infocenter Website, Nov. 2013. [Online] Available at: http://infocenter.arm.com
[3] D., Lewis, Fundamentals of Embedded Software with the ARM Cortex-M3. Pearson Education, 2012. [Online]. Available: http://books.google.fi/books?id=iaIvAAAAQBAJGoogle Scholar
[4] A., Edelsten, “TEGRA: Attacking Mobile Entertainment with Sword and SHIELD,” July 2013, SIGGRAPH 2013 Tech Talk. [Online]. Available: www.nvidia.com/object/ siggraph2013-tech-talks.htmlGoogle Scholar
[5] Nvidia, “Tegra 4 Family GPU Architecture,” Feb. 2013, Whitepaper V1.0. [Online]. Available: www.nvidia.com/docs/IO/116757/Tegra_4_GPU_Whitepaper_FINALv2.pdf
[6] G. A., Paleologo, L., Benini, A., Bogliolo, and G. De, Micheli, “Policy optimization for dynamic power management,” in Proc. 35th Annu. Design Automation Conf. New York, NY, USA: ACM, 1998, pp. 182-187. [Online]. Available: http://doi.acm.org/10.1145/277044.277094Google Scholar
[7] L., Benini, A., Bogliolo, and G. D., Micheli, “A survey of design techniques for system-level dynamic power management,” IEEE Trans. Very Large Scale Integ. (VLSI) Syst., vol. 8, no. 3, pp. [299-316, Jun. 2000.Google Scholar
[8] I., Hong, G., Qu, M., Potkonjak, and M. B., Srivastava, “Synthesis techniques for low-power hard real-time systems on variable voltage processors,” in RTSS, 1998, pp. 178-187.Google Scholar
[9] E., Bini, G., Buttazzo, and G., Lipari, “Minimizing CPU energy in real-time systems with discrete speed management,” ACM Trans. Embed. Comput. Syst., vol. 8, no. 4, pp. 31:1-31:23, Jul. 2009.Google Scholar
[10] D. C., Snowdon, S. M., Petters, and G., Heiser, “Accurate on-line prediction of processor and memory energy usage under voltage scaling,” in Proc. 7th ACM & IEEE Int. Conf. on Embedded Software. New York, NY, USA: ACM, 2007, pp. 84-93. [Online]. Available: http://doi.acm.org/10.1145/1289927.1289945Google Scholar
[11] A., Musah and A., Dykstra, Power-Management Techniques for OMAP 35x Applications Processors, Texas Instruments, Aug. 2008, Whitepaper.Google Scholar
[12] G., Kornaros and D., Pnevmatikatos, “A survey and taxonomy of on-chip monitoring of multicore systems-on-chip,” ACM Trans. Des. Autom. Electron. Syst., vol. 18, no. 2, pp. 17:1–17:38, Apr. 2013. [Online]. Available: http://doi.acm.org/http://dx.doi.org/10.1145/2442087.2442088Google Scholar
[13] Hewlett-Packard, Intel, Microsoft, Phoenix, and Toshiba, “The ACPI specification: revision 5.0,” 2011. [Online]. Available: www.acpi.info/spec.htm
[14] J., Kurtto, “Mapping and improving the energy efficiency of the Nokia N900,” Master's thesis, Department of Computer Science, University of Helsinki, 2011.Google Scholar
[15] Y., Zhang, X., Wang, X., Liu, Y., Liu, L., Zhuang, and F., Zhao, “Towards better CPU power management on multicore smartphones,” in Proc. ofthe Workshop on Power-Aware Computing and Systems, ser. HotPower '13. New York, NY, USA: ACM, 2013, pp. 11:1–11:5. [Online]. Available: http://doi.acm.org/10.1145/2525526.2525849Google Scholar
[16] V., Pallipadi and A., Starikovskiy, “The ondemand governor: past, present and future,” in Proc. Linux Symp., vol. 2, pp. 223-238, 2006.Google Scholar
[17] P., Greenhalgh, big.LITTLE Processing with ARM Cortex-A15 & Cortex-A7: Improving Energy Efficiency in High-Performance Mobile Platforms, Sept. 2011. [Online]. Available: www.arm.com/files/downloads/big_LITTLE_Fin al_Final.pdfGoogle Scholar
[18] M., Kim and S. W., Chung, “Accurate GPU power estimation for mobile device power profiling,” in 2013 IEEE Int. Conf. on Consumer Electronics (ICCE), 2013.Google Scholar
[19] Qualcomm, “Snapdragon S4 Processors: System on Chip Solutions for a New Mobile Age,” Oct. 2011.
[20] S., Hong and H., Kim, “An integrated GPU power and performance model,” SIGARCH Comput. Archit. News, vol. 38, no. 3, pp. 280–289, Jun. 2010. [Online]. Available: http: //doi.acm.org/10.1145/1816038.1815998Google Scholar
[21] K., Pulli, J., Vaarala, V., Miettinen, T., Aarnio, and K., Roimela, Mobile 3D Graphics: With OpenGL ES and M3G. San Francisco, CA, USA: Morgan Kaufmann Publishers Inc., 2007.Google Scholar
[22] C., Isci and M., Martonosi, “Runtime power monitoring in high-end processors: Methodology and empirical data,” in Proc. 36th Annu. IEEE/ACM Int. Symp. on Microarchitecture, ser. MICRO 36. Washington, DC, USA: IEEE Computer Society, 2003, pp. 93-. [Online]. Available: http://dl.acm.org/citation.cfm?id=956417.956567Google Scholar
[23] A., Carroll and G., Heiser, “An analysis of power consumption in a smartphone,” in Proc. 2010 USENIXAnnu. Technical Conf. Berkeley, CA, USA: USENIX Association, 2010. [Online]. Available: http://dl.acm.org/citation.cfm?id=1855840.1855861
[24] M., Dong and L., Zhong, “Chameleon: A color-adaptive web browser for mobile OLED displays,” in Proc. 9th Int. Conf. on Mobile Systems, Applications, and Services. New York, NY, USA: ACM, 2011, pp. 85-98. [Online]. Available: http://doi.acm.org/10.1145/1999995.2000004Google Scholar
[25] R., Mittal, A., Kansal, and R., Chandra, “Empowering developers to estimate app energy consumption,” in Proc. 18th Annu. Int. Conf. on Mobile Computing and Networking. New York, NY, USA: ACM, 2012, pp. 317-328. [Online]. Available: http://doi.acm.org/10.1145/2348543.2348583Google Scholar
[26] X., Chen, Y., Chen, Z., Ma, and F. C. A., Fernandes, “How is energy consumed in smartphone display applications?” in Proc. 14th Workshop on Mobile Computing Systems and Applications, ser. HotMobile '13. New York, NY, USA: ACM, 2013, pp. 3:1–3:6. [Online]. Available: http://doi.acm.org/10.1145/2444776.2444781Google Scholar
[27] H., Han, J., Yu, H., Zhu, Y., Chen, J., Yang, G., Xue, Y., Zhu, and M., Li, “E3: Energy-efficient engine for frame rate adaptation on smartphones,” in Proc. 11th ACM Conf. on Embedded Networked Sensor Systems. New York, NY, USA: ACM, 2013, pp. 15:1–15:14. [Online]. Available: http://doi.acm.org/10.1145/2517351.2517364Google Scholar
[28] “IEEE Standard for Information Technology - Telecommunications and Information Exchange Between Systems - Local and Metropolitan Area Networks-Specific Requirements - Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications,” IEEE Std 802.11-2007 (Revision of IEEE Std 802.11-1999), June 2007.
[29] J. F., Kurose and K. W., Ross, Computer Networking: A Top-Down Approach, 6th ed. USA: Addison-Wesley Publishing Company, 2012.Google Scholar
[30] A., Pathak, Y. C., Hu, M., Zhang, P., Bahl, and Y.-M., Wang, “Fine-grained power modeling for smartphones using system call tracing,” in Proc. 6th Conf. on Computer Systems. New York, NY, USA: ACM, 2011, pp. 153-168. [Online]. Available: http://doi.acm.org/10.1145/1966445.1966460Google Scholar
[31] V., Venkatachalam and M., Franz, “Power reduction techniques for microprocessor systems,” ACM Comput. Surv., vol. 37, pp. 195–237, September 2005. [Online]. Available: http://doi. acm.org/10.1145/1108956.1108957Google Scholar
[32] D., Halperin, B., Greenstein, A., Sheth, and D., Wetherall, “Demystifying 802.11n power con¬sumption,” in Proc. 2010 Int. Conf. on Power Aware Computing and Systems. Berkeley, CA, USA: USENIX Association, 2010. [Online]. Available: http://dl.acm.org/citation.cfm?id= 1924920.1924928Google Scholar
[33] C.-Y., Li, C., Peng, S., Lu, and X., Wang, “Energy-based rate adaptation for 802.11n,” in Proc. 18th Annu. Int. Conf. on Mobile Computing and Networking. New York, NY, USA: ACM, 2012, pp. 341–352. [Online]. Available: http://doi.acm.org/10.1145/2348543.2348585Google Scholar
[34] M. O., Khan, V., Dave, Y.-C., Chen, O., Jensen, L., Qiu, A., Bhartia, and S., Rallapalli, “Model-driven energy-aware rate adaptation,” in Proc. 14th ACM Int. Symp. on Mobile ad hoc Networking and Computing. New York, NY, USA: ACM, 2013, pp. 217–226. [Online]. Available: http://doi.acm.org/10.1145/2491288.2491300
[35] R., Friedman, A., Kogan, and Y., Krivolapov, “On power and throughput tradeoffs of Wi-Fi and Bluetooth in smartphones,” IEEE Trans. Mobile Computing, vol. 12, no. 7, pp. 1363–1376, 2013.Google Scholar
[36] C., Drula, C., Amza, F., Rousseau, and A., Duda, “Adaptive energy conserving algorithms for neighbor discovery in opportunistic Bluetooth networks,” IEEE J. Sel. Areas Commun., vol. 25, no. 1, pp. 96–107, Jan. 2007.Google Scholar
[37] J., Liu, C., Chen, and Y., Ma, “Modeling and performance analysis of device discovery in Bluetooth low energy networks,” in Global Communications Conference (GLOBECOM), 2012 IEEE, 2012, pp. 1538-1543.Google Scholar
[38] M., Siekkinen, M., Hiienkari, J., Nurminen, and J., Nieminen, “How low energy is Bluetooth low energy? Comparative measurements with ZigBee/802.15.4,” in Wireless Communica¬tions and Networking Conf. Workshops (WCNCW), 2012 IEEE, 2012, pp. 232–237.Google Scholar
[39] Y., Xiao, Y., Cui, P., Savolainen, M., Siekkinen, A., Wang, L., Yang, A. Yla-Jaaski, and S., Tarkoma, “Modeling energy consumption of data transmission over Wi-Fi,” IEEE Trans. Mobile Computing, vol. 99, no. PrePrints, 2013.Google Scholar
[40] “3GPP TS 25.331, Radio Resource Control (RRC); Protocol specification,” May 1999.
[41] “3GPP TS 36.331, E-UTRA; Radio Resource Control (RRC) Protocol Specification,” May 2008.
[42] F., Qian, Z. M., Mao, Z., Wang, S., Sen, A., Gerber, and O., Spatscheck, “Characterizing radio resource allocation for 3G networks,” in Proc. 10th Annu. Conf. on Internet Measurement. ACM, 2010, pp. 137–150.Google Scholar
[43] N., Vallina-Rodriguez, A., Aucinas, M., Almeida, Y., Grunenberger, K., Papagiannaki, and J., Crowcroft, “RILAnalyzer: A comprehensive 3G monitor on your phone,” in Proc. 2013 Conf. on Internet Measurement ser. IMC '13. New York, NY, USA: ACM, 2013, pp. 257–264. [Online]. Available: http://doi.acm.org/10.1145/2504730.2504764Google Scholar
[44] N., Balasubramanian, A., Balasubramanian, and A., Venkataramani, “Energy consumption in mobile phones: A measurement study and implications for network applications,” in IMC, 2009.Google Scholar
[45] “Docomo demands Google's help with signalling storm,” [Online]. Available: www.rethink-wireless.com/2012/01/30/docomo-demands-googles-signalling-storm.htm, Jan. 2012.
[46] GSM Association, “Fast dormancy best practices. version 1.0,” Jul. 2011. [Online]. Available: www.gsma.com/newsroom/wp-content/uploads/2013/08/TS18v1-0.pdf
[47] 3GPP, “3GPP specification TR 25.903: Continuous connectivity for packet data users,” www.3gpp.org/ftp/Specs/html-info/25903.htm, Nov. 2005.
[48] M., Poikselk, H., Holma, J., Hongisto, J., Kallio, and A., Toskala, Voice over LTE (VoLTE), 1st ed. John Wiley and Sons, Inc, 2012.Google Scholar
[49] A., Balasubramanian, A., LaMarca, and D., Wetherall, Efficiently Running Continuous Monitoring Applications on Mobile Devices using Sensor Hubs, Nov 2013, technical report. [Online]. Available: http://mobilehub.cs.washington.edu/papers/sensorhub.pdfGoogle Scholar
[50] M.-R., Ra, B., Priyantha, A., Kansal, and J., Liu, “Improving energy efficiency of personal sensing applications with heterogeneous multi-processors,” in Proc. 2012 ACM Conf. on Ubiquitous Computing. New York, NY, USA: ACM, 2012, pp. 1–10. [Online]. Available: http://doi.acm.org/10.1145/2370216.2370218Google Scholar
[51] F. X., Lin, Z., Wang, R., LiKamWa, and L., Zhong, “Reflex: Using low-power processors in smartphones without knowing them,” SIGARCH Comput. Archit. News, vol. 40, no. 1, pp. 13–24, Mar. 2012. [Online]. Available: http://doi.acm.org/10.1145/2189750.2150979Google Scholar
[52] R., LiKamWa, B., Priyantha, M., Philipose, L., Zhong, and P., Bahl, “Energy characterization and optimization of image sensing toward continuous mobile vision,” in Proc. 11th Annu. Int. Conf. on Mobile Systems, Applications, and Services, ser. MobiSys '13. ACM, 2013, pp. 69–82.Google Scholar

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