Smartphone energy consumption: Modeling and optimization

Smartphone Energy Consumption: Modeling and Optimization

Volumn , Issue , 2014, Pages 1-336

  Tarkoma, Sasu ^a   Siekkinen, Matti ^b   Lagerspetz, Eemil ^c   Xiao, Yu ^c  

^a UNIVERSITY OF HELSINKI   (Finland)

^b AALTO UNIVERSITY   (Finland)

^c NONE

Author keywords

[No Author keywords available]

Indexed keywords

CURRICULA; EDUCATION; ELECTRIC BATTERIES; ENERGY EFFICIENCY; STUDENTS;

DESIGN AND IMPLEMENTATIONS; ENERGY EFFICIENT SYSTEMS; ENERGY OPTIMIZATION; EXPERIMENTAL SYSTEM; HARDWARE AND SOFTWARE; LABORATORY COMPONENTS; MODELING AND OPTIMIZATION; PRACTICAL GUIDANCE;

ENERGY UTILIZATION;

EID: 84928149760     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1017/CBO9781107326279     Document Type: Book

References (273)

1. S. Albers, “Energy-efficient algorithms,” Commun. ACM, vol. 53, no. 5, pp. 86-96, May 2010.
2. A. Rahmati, A. Qian, and L. Zhong, “Understanding human-battery interaction on mobile phones,” in Proc. 9th Int. Conf. on Human Computer Interaction with Mobile Devices and Services. New York, NY, USA: ACM, 2007, pp. 265-272. [Online]. Available: http://doi. acm.org/10.1145/1377999.1378017
3. C. H. K. van Berkel, “Multi-core for mobile phones,” in Proc. Conf. Design, Automation and Test in Europe (DATE’09), 2009, pp. 1260-1265.
4. Y. Neuvo, “Cellular phones as embedded systems,” in IEEE Int. Solid-State Circuits Conf. (ISSCC), 2004, pp. 32-37.
5. A. Pathak, Y. C. Hu, and M. Zhang, “Where is the energy spent inside my app?: fine grained energy accounting on smartphones with eProf,” in Proc. 7th ACM European Conf. On Computer Systems. New York, NY, USA: ACM, 2012, pp. 29-42. [Online]. Available: http://doi.acm.org/10.1145/2168836.2168841
6. J. Kurtto, “Mapping and improving the energy efficiency of the Nokia N900,” Master’s thesis, Department of Computer Science, University of Helsinki, 2011.
7. S. Madhavapeddy and B. Carlson, OMAP 3 Architecture from Texas Instruments opens new horizons for mobile Internet devices, Texas Instruments, 2008, Whitepaper.
8. D. Linden and T. B. Reddy, Handbook of Batteries. 3rd ed. McGraw-Hill Professional, 2001.
9. K. Pentikousis, “In search of energy-efficient mobile networking,” IEEE Communications Magazine, vol. 48, no. 1, pp. 95-103, 2010.
10. Hewlett-Packard, Intel, Microsoft, Phoenix, “The ACPI specification: revision 5.0,” 2011. [Online]. Available: www.acpi.info/spec.htm
11. S. Lee, J. Kim, J. Lee, and B. Cho, “State-of-charge and capacity estimation of lithium-ion battery using a new open-circuit voltage versus state-of-charge,” J. Of Power Sources, vol. 185, no. 2, pp. 1367-1373, 2008.
12. O. Erdinc, B. Vural, and M. Uzunoglu, “A dynamic lithium-ion battery model considering the effects of temperature and capacity fading,” in Proc. 2009 Int. Conf. Clean Electrical Power, 2009, pp. 383-386.
13. D. Linden and T. B. Reddy, Handbook of Batteries. 3rd ed. McGraw-Hill Professional, 2001
14. N. S. Kim, T. Austin, D. Blaauw, T. Mudge, K. Flautner, J. S. Hu, M. J. Irwin, M. Kan-demir, and V. Narayanan, “Leakage current: Moore’s law meets static power,” Computer, vol. 36, no. 12, pp. 68-75, Dec. 2003. [Online]. Available: http://dx.doi.org/10.1109/MC. 2003.1250885
15. 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/10.1145/1289927.1289945
16. F. Yao, A. Demers, and S. Shenker, “A scheduling model for reduced CPU energy,” in Proc. 36th Ann. Symp. On Foundations of Computer Science, ser. FOCS’95. Washington, DC, USA: IEEE Computer Society, 1995, pp. 374-. [Online]. Available: http://dl.acm.org/citation.cfm? id=795662.796264
17. S. Zhuravlev, J. Saez, S. Blagodurov, A. Fedorova, and M. Prieto, “Survey of energy-cognizant scheduling techniques,” IEEE Trans. Parallel Distrib. Syst., vol. 24, no. 7, pp. 1447-1464, 2013.
18. F. I. Kushnirskii and M. E. Primak, “Regression with nonnegative coefficients,” in Cybernetics and Systems Analysis, vol. 9, no. 1, 1973.
19. R. H. Shumway and D. Stoffer, “Time series analysis and its applications: With r examples,” in Springer Texts in Statistics, 2006, pp. 85-154.
20. H. Chen, T. N. Cong, W. Yang, C. Tan, Y. Li, and Y. Ding, “Progress in electrical energy storage system: A critical review,” Progress in Natural Science, vol. 19, no. 3, pp. 291-312, Mar. 2009. [Online]. Available: http://dx.doi.org/10.1016Zj.pnsc.2008.07.014
21. D. Linden and T. B. Reddy, Handbook of Batteries. 3rd ed. McGraw-Hill Professional
22. F. Hoffart, “Extend battery life with proper charging, discharging,” EE Times Asia, Jun. 2008. [Online], Available: 2
23. P. Rong and M. Pedram, “An analytical model for predicting the remaining battery capacity of lithium-ion batteries,” IEEE Trans. Very Large Scale Integr. (VLSI) Syst., vol. 14, no. 5, pp. 441-451, 2006.
24. M. Jongerden and B. Haverkort, “Battery modeling,” Tech. Rep. TR-CTI, January 2008. [Online]. Available: http://doc.utwente.nl/64556/
25. M. Coleman, W. Hurley, and C. K. Lee, “An improved battery characterization method using a two-pulse load test,” IEEE Trans. Energy Convers., vol. 23, no. 2, pp. 708-713, 2008.
26. D. Liu, J. Pang, J. Zhou, Y. Peng, and M. Pecht, “Prognostics for state of health estimation of lithium-ion batteries based on combination gaussian process functional regression,” Microelectronics Reliability, vol. 53, no. 6, pp. 832-839, 2013. [Online]. Available: http://www.sciencedirect.com/science/article/pii/S0026271413000747
27. M. Dong and L. Zhong, “Self-constructive high-rate system energy modeling for battery-powered mobile systems,” in Proc. 9th Int. Conf. Mobile Systems, Applications, and Services. New York, NY, USA: ACM, 2011, pp. 335-348.
28. M. Yu and J. Qian, How to Use BQ27505 in a Smart Phone System, Texas Instruments, Aug. 2009, Application Report.
29. W. Jung, C. Kang, C. Yoon, D. Kim, and H. Cha, “Devscope: a nonintrusive and online power analysis tool for smartphone hardware components,” in Proc. 8th IEEE/ACM/IFIP Int. Conf. Hardware/Software Codesign and System Synthesis. New York, NY, USA: ACM, 2012, pp. 353-362. [Online]. Available: http://doi.acm.org/10.1145/2380445.2380502
30. F. Xu, Y. Liu, Q. Li, and Y. Zhang, V-edge: fast self-constructive power modeling of smartphones based on battery voltage dynamics in Proc. 10th USENIX Conf. Networked Systems Design and Implementation. Berkeley, CA, USA: USENIX Association, 2013, pp. 43-56.
31. C. Simpson, Battery Charging, National Semiconductor, 2011, Literature Number: SNVA557.
32. D. Ferreira, A. K. Dey, and V. Kostakos, “Understanding human-smartphone concerns: A study of battery life,” in Pervasive, 2011.
33. O. Erdinc, B. Vural, and M. Uzunoglu, “A dynamic lithium-ion battery model considering the effects of temperature and capacity fading,” in 2009 Int. Conf. On Clean Electrical Power 2009, pp. 383-386.
34. C. Zhang, J. Jiang, W. Zhang, and S. M. Sharkh, “Estimation of state of charge of lithium-ion batteries used in HEV using robust extended kalman filtering,” Energies, vol. 5, no. 4, pp. 1098-1115, 2012.
35. S. Lee, J. Kim, J. Lee, and B. Cho, “State-of-charge and capacity estimation of lithium-ion battery using a new open-circuit voltage versus state-of-charge,” Journal of Power Sources, vol. 185, no. 2, pp. 1367-1373, 2008.
36. B. Xiao, Y. Shi, and L. He, “A universal state-of-charge algorithm for batteries,” in Proc. 47th Design Automation Conf. New York, NY, USA: ACM, 2010, pp. 687-692. [Online]. Available: http://doi.acm.org/10.1145/1837274.1837449
37. H. He, R. Xiong, and J. Fan, “Evaluation of lithium-ion battery equivalent circuit models for state of charge estimation by an experimental approach,” Energies, vol. 4, no. 4, pp. 582-598, 2011. [Online]. Available: www.mdpi.com/1996-1073/4/4/582
38. S. Wen, “Design Fuel Gauging for Multicell Li-Ion Battery Pack (Part 2),” EE Times Asia, Mar. 2008. [Online]. Available: www.eetasia.com/articleLogin.do?artId=8800508929
39. S. Pang, J. Farrell, J. Du, and M. Barth, “Battery state-of-charge estimation,” in American Control Conf., vol. 2, 2001, pp. 1644-1649.
40. L. Zhang, B. Tiwana, Z. Qian, Z. Wang, R. P. Dick, Z. M. Mao, and L. Yang, “Accurate online power estimation and automatic battery behavior based power model generation for smartphones,” in Proc. Eighth IEEE/ACM/IFIP Int. Conf. On Hardware/Software Codesign and System Synthesis. New York, NY, USA: ACM, 2010, pp. 105-114.
41. A. Carroll and G. Heiser, “The systems hacker’s guide to the galaxy: energy usage in a modern smartphone,” in Proc. 4th Asia-Pacific Workshop on Systems. New York, NY, USA: ACM, 2013, pp. 5:1-5:7. [Online]. Available: http://doi.acm.org/10.1145/2500727.2500734
42. A. Carroll and G. Heiser, “An analysis of power consumption in a smartphone,” in Proc. 2010 USENIX Ann. Technical Conf. Berkeley, CA, USA: USENIX Association, 2010. [Online]. Available: http://dl.acm.org/citation.cfm?id=1855840.1855861
43. A. Pathak, Y. C. Hu, and M. Zhang, “Where is the energy spent inside my app? Fine grained energy accounting on smartphones with eProf,” in EuroSys, 2012.
44. G. Creus and M. Kuulusa, “Optimizing mobile software with built-in power profiling,” in Mobile Phone Programming, F. H. Fitzek and F. Reichert, Eds. Springer Netherlands, 2007, pp. 449-462. [Online], Available: http://dx.doi.org/10.1007/978-l-4020-5969-8_25
45. W. Jung, C. Kang, C. Yoon, D. Kim, and H. Cha, “Devscope: a nonintrusive and online power analysis tool for smartphone hardware components,” in Proc. 8th IEEE/ACM/IFIP Int. Conf. On Hardware/Software Codesign and System Synthesis. New York, NY, USA: ACM, 2012, pp. 353-362. [Online]. Available: http://doi.acm.org/10.1145/2380445.2380502
46. M. Dong and L. Zhong, “Self-constructive high-rate system energy modeling for battery-powered mobile systems,” in Proc. 9th Int. Conf. On Mobile Systems, Applications, and Services. New York, NY, USA: ACM, 2011, pp. 335-348.
47. F. Xu, Y. Liu, Q. Li, and Y. Zhang, “V-edge: fast self-constructive power modeling of smartphones based on battery voltage dynamics,” in Proc. 10th USENIX Conf. On Networked Systems Design and Implementation. Berkeley, CA, USA: USENIX Association, 2013, pp. 43-56.
48. A. Rice and S. Hay, “Decomposing power measurements for mobile devices,” in Proc. 2010 IEEE Int. Conference on Pervasive Computing and Communications (PerCom), 2010, pp. 70-78.
49. N. Banerjee, A. Rahmati, M. D. Corner, S. Rollins, and L. Zhong, “Users and batteries: Interactions and adaptive energy management in mobile systems,” in UbiComp 2007: Ubiquitous Computing, ser. Lecture Notes in Computer Science
50. J. Krumm, G. D. Abowd, A. Senevi-ratne, and T. Strang, Eds. Springer Berlin Heidelberg, 2007, vol. 4717, pp. 217-234. [Online], Available: http://dx.doi.org/10.1007/978-3-540-74853-3.13
51. A. Rahmati and L. Zhong, “Human-battery interaction on mobile phones,” Pervasive and Mobile Computing, vol. 5, no. 5, pp. 465-477, 2009. [Online]. Available: www. sciencedirect.com/science/article/pii/S1574119208000746
52. M. V. J. Heikkinen, J. K. Nurminen, T. Smura, and H. Hammainen, “Energy efficiency of mobile handsets: Measuring user attitudes and behavior,” Telemat. Inf., vol. 29, no. 4, pp. 387-399, Nov. 2012. [Online]. Available: http://dx.doi.org/10.1016fj.tele.2012.01.005
53. D. Ferreira, E. Ferreira, J. Goncalves, V. Kostakos, and A. K. Dey, “Revisiting human-battery interaction with an interactive battery interface,” in Proc. Of Ubicomp 2013. ACM, 2013.
54. E. A. Oliver and S. Keshav, “An empirical approach to smartphone energy level prediction,” in Proc. 13th Int. Conf. On Ubiquitous Computing. New York, NY, USA: ACM, 2011, pp. 345-354. [Online]. Available: http://doi.acm.org/10.1145/2030112.2030159
55. D. Ferreira, A. Dey, and V. Kostakos, “Understanding human-smartphone concerns: A study of battery life,” in Pervasive Computing
56. J. Hightower, and E. Huang, Eds. Springer Berlin Heidelberg, 2011, vol. 6696, pp. 19-33. [Online], Available: http://dx.doi.Org/10.1007/978-3-642-21726-5.2
57. A. Shye, B. Scholbrock, and G. Memik, “Into the wild: studying real user activity patterns to guide power optimizations for mobile architectures,” in Proc. 42nd Annual IEEE/ACM Int. Symp. On Microarchitecture. New York, NY, USA: ACM, 2009, pp. 168-178. [Online]. Available: http://doi.acm.org/10.1145/1669112.1669135
58. N. Vallina-Rodriguez, P. Hui, J. Crowcroft, and A. Rice, “Exhausting battery statistics: understanding the energy demands on mobile handsets,” in Proc. 2nd ACM SIGCOMM Workshop on Networking, Systems, and Applications on Mobile Handhelds. New York, NY, USA: ACM, 2010, pp. 9-14. [Online]. Available: http://doi.acm.org/10.1145/1851322. 1851327
59. A. Rahmati, A. Qian, and L. Zhong, “Understanding human-battery interaction on mobile phones,” in Proc. 9th Int. Conf. On Human Computer Interaction with Mobile Devices and Services. New York, NY, USA: ACM, 2007, pp. 265-272. [Online]. Available: http://doi. acm. Org/10.1145/1377999.1378017
60. N. Ravi, J. Scott, L. Han, and L. Iftode, “Context-aware battery management for mobile phones,” in Proc. 2008 6th Annual IEEE Int. Conf. On Pervasive Computing and Communications. Washington, DC, USA: IEEE Computer Society, 2008, pp. 224-233. [Online]. Available: http://portal.acm.org/citation.cfm?id=1371610.1372956
61. K. Athukorala, E. Lagerspetz, M. von Khgelgen, A. Jylha, A. J. Oliner, G. Jacucci, and S. Tarkoma, “How Carat affects user behavior: Implications for mobile battery awareness applications,” in CHI’14: Proc. SIGCHI Conf. On Human Factors in Computing Systems. New York, NY, USA: ACM, 2014.
62. C. Shen, “Energy profiling of hardware subsystems and user settings on Android,” Master’s thesis, Department of Computer Science, University of Helsinki, Helsinki, Finland, May 2013. [Online]. Available: http://hdl.handle.net/10138/39542
63. M. Dong and L. Zhong, “Self-constructive high-rate system energy modeling for battery-powered mobile systems,” in Proc. 9th Int. Con. On Mobile Systems, Applications, and Services. New York, NY, USA: ACM, 2011, pp. 335-348.
64. L. Zhang, B. Tiwana, Z. Qian, Z. Wang, R. P. Dick, Z. M. Mao, and L. Yang, “Accurate online power estimation and automatic battery behavior based power model generation for smartphones,” in Proc. 8th IEEE/ACM/IFIP Int. Conf. On Hardware/Software Codesign and System Synthesis. New York, NY, USA: ACM, 2010, pp. 105-114.
65. 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/10.1145/1966445.1966460
66. J. Flinn and M. Satyanarayanan, “Energy-aware adaptation for mobile applications,” SIGOPS Oper. Syst. Rev., vol. 33, no. 5, pp. 48-63, Dec. 1999. [Online]. Available: http://doi.acm. Org/10.1145/319344.319155
67. J. Flinn and M. Satyanarayanan, “Powerscope: A tool for profiling the energy usage of mobile applications,” in Proc. 2nd IEEE Workshop on Mobile Computer Systems and Applications. Washington, DC, USA: IEEE Computer Society, 1999. [Online]. Availablhttp://dl.acm.org/citation.cfm?id=520551.837522
68. J. L. Hennessy and D. A. Patterson, Computer Architecture: A Quantitative Approach, 3rd ed. San Francisco, CA, USA: Morgan Kaufmann Publishers Inc., 2003.
69. D. Lewis, Fundamentals of Embedded Software with the ARM Cortex-M3. Pearson Education, 2012. [Online]. Available: http://books.google.fi/books?id=iaIvAAAAQBAJ
70. 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.html
71. 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
72. 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. 277094
73. L. Benini, A. Bogliolo, and G. D. Micheli, “A survey of design techniques for system-level dynamic power management,” IEEETrans. Very Large Scale Integ. (VLSI) Syst., vol. 8, no. 3, pp. 299-316, Jun. 2000.
74. 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.
75. 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. 31:131:23, Jul. 2009.
76. 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/10.1145/1289927.1289945
77. A. Musah and A. Dykstra, Power-Management Techniques for OMAP35x Applications Processors, Texas Instruments, Aug. 2008, Whitepaper.
78. 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/10.1145/2442087.2442088
79. J. Kurtto, “Mapping and improving the energy efficiency of the Nokia N900,” Master’s thesis, Department of Computer Science, University of Helsinki, 2011.
80. Y. Zhang, X. Wang, X. Liu, Y. Liu, L. Zhuang, and F. Zhao, “Towards better CPU power management on multicore smartphones,” in Proc. Of the 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/10.1145/2525526.2525849
81. V. Pallipadi and A. Starikovskiy, “The ondemand governor: past, present and future,” in Proc. Linux Symp., vol. 2, pp. 223-238, 2006.
82. P. Greenhalgh, big.LITTLE Processing with ARM Cortex-A15 & Cortex-A7: Improving Energy Efficiency in High-Performance Mobile Platforms, Sept. 2011. [Online]. Available: www.aim.com/flles/downloads/big_LITTLE_FinaLFinal.pdf
83. 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.
84. 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/10.1145/1816038.1815998
85. K. Pulli, J. Vaarala, V. Miettinen, T. Aarnio, and K. Roimela, Mobile 3D Graphics: With OpenGL ES andM3G. San Francisco, CA, USA: Morgan Kaufmann Publishers Inc., 2007.
86. 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=956417.956567
87. 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
88. 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. 2000004
89. 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/10.1145/2348543.2348583
90. 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/10.1145/2444776.2444781
91. 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/10.1145/2517351.2517364
92. J. F. Kurose and K. W. Ross, Computer Networking: A Top-Down Approach, 6th ed. USA: Addison-Wesley Publishing Company, 2012.
93. 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/10.1145/1966445.1966460
94. 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/10.1145/1108956.1108957
95. D. Halperin, B. Greenstein, A. Sheth, and D. Wetherall, “Demystifying 802.11n power consumption,” 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= 1924920.1924928
96. 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. 2348585
97. 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
98. 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.
99. 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.
100. 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.
101. 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 Communications and Networking Conf. Workshops (WCNCW), 2012 IEEE, 2012, pp. 232-237.
102. 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.
103. 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.
104. 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/10.1145/2504730.2504764
105. N. Balasubramanian, A. Balasubramanian, and A. Venkataramani, “Energy consumption in mobile phones: A measurement study and implications for network applications,” in IMC, 2009.
106. M. Poikselk, H. Holma, J. Hongisto, J. Kallio, and A. Toskala, Voice over LTE (VoLTE), 1st ed. John Wiley and Sons, Inc, 2012.
107. 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.pdf
108. 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/10.1145/2370216.2370218
109. 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/10.1145/2189750.2150979
110. 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.
111. S. Tarkoma and E. Lagerspetz, “Arching over the mobile computing chasm: Platforms and runtimes,” Computer, vol. 44, no. 4, pp. 22-28, Apr. 2011. [Online]. Available: http://dx. doi.org/10.1109/MC.2010.272
112. R. Berjon, S. Faulkner, T. Leithead, E. D. Navara, E. O’Connor, S. Pfeiffer, and I. Hickson, “HTML5: A vocabulary and associated APIs, for HTML and XHTML,” W3C, Tech. Rep., Aug. 2013, Candidate recommendation. [Online]. Available: www.w3.org/TR/html5/
113. O. Halvorsen and D. Clarke, Power Management. Apress, 2011. [Online]. Available: http://dx.doi.org/10.1007/978-1-4302-3537-8.10
114. A. Kostiainen and M. Lamouri, W3C Battery Status API, Apr. 2013, W3C Editor’s Draft April 19, 2013.
115. A. Pathak, A. Jindal, Y. C. Hu, and S. Midkiff, “What is keeping my phone awake? Characterizing and detecting no-sleep energy bugs in smartphone apps,” Mobisys, 2012.
116. P. Vekris, R. Jhala, S. Lerner, and Y. Agarwal, “Towards verifying Android apps for the absence of no-sleep energy bugs,” in Proc. 2012 USENIX Conf. On Power-Aware Computing and Systems, ser. HotPower’12. Berkeley, CA, USA: USENIX Association, 2012. [Online]. Available: http://dl.acm.org/citation.cfm?id=2387869.2387872
117. 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. 277094
118. N. Vallina-Rodriguez and J. Crowcroft, “Energy management techniques in modern mobile handsets,” IEEE Communications Surveys Tutorials, vol. 15, no. 1, pp. 179-198, 2013.
119. J. Flinn and M. Satyanarayanan, “Energy-aware adaptation for mobile applications,” SIGOPS Oper. Syst. Rev., vol. 33, no. 5, pp. 48-63, Dec. 1999. [Online]. Available: http://doi.acm.org/10.1145/319344.319155
120. J. Flinn and M. Satyanarayanan, “Powerscope: A tool for profiling the energy usage of mobile applications,” in Proc. 2nd IEEE Workshop on Mobile Computer Systems and Applications. Washington, DC, USA: IEEE Computer Society, 1999. [Online]. Available: http://dl.acm.org/citation.cfm?id=520551.837522
121. H. Zeng, C. S. Ellis, A. R. Lebeck, and A. Vahdat, “Ecosystem: managing energy as a first class operating system resource,” SIGOPS Oper. Syst. Rev., vol. 36, no. 5, pp. 123-132, Oct. 2002. [Online]. Available: http://doi.acm.org/10.1145/635508.605411
122. A. Roy, S. M. Rumble, R. Stutsman, P. Levis, D. Mazieres, and N. Zeldovich, “Energy management in mobile devices with the Cinder operating system,” in Proc. 6th Conf. On Computer Systems. New York, NY, USA: ACM, 2011, pp. 139-152. [Online]. Available: http://doi.acm.org/10.1145/1966445.1966459
123. A. J. Issott, Common Design Patterns for Symbian OS: The Foundations of Smartphone Software. Wiley Publishing, 2008.
124. J. Sales, Symbian OS Internals: Real-time Kernel Programming. Wiley Publishing, December 2005.
125. G. Creus and M. Kuulusa, “Optimizing mobile software with built-in power profiling,” in Mobile Phone Programming, F. H. Fitzek and F. Reichert, Eds. Springer Netherlands, 2007, pp. 44SM62. [Online], Available: http://dx.doi.org/10.1007/978-l-4020-5969-8_25
126. 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/10.1145/1966445.1966460
127. R. Fonseca, P. Dutta, P. Levis, and I. Stoica, “Quanto: tracking energy in networked embedded systems,” in Proc. 8th USENIX Conf. On Operating Systems Design and Implementation. Berkeley, CA, USA: USENIX Association, 2008, pp. 323-338. [Online]. Available: http://portal.acm.org/citation.cfm?id=1855741.1855764
128. G. Qu, N. Kawabe, K. Usami, and M. Potkonjak, “Function-level power estimation methodology for microprocessors,” in Proc. 37th Annu. Design Automation Conf. New York, NY, USA: ACM, 2000, pp. 810-813. [Online]. Available: http://doi.acm.org/10.1145/337292. 337786
129. J. Laurent, N. Julien, E. Senn, and E. Martin, “Functional level power analysis: an efficient approach for modeling the power consumption of complex processors,” in Proc. Conf. On Design, Automation and Test in Europe - Volume 1. Washington, DC, USA: IEEE Computer Society, 2004. [Online]. Available: http://portal.acm.org/citation.cfm?id=968878.968987
130. L. M. Feeney and M. Nilsson, “Investigating the energy consumption of a wireless network interface in an ad hoc networking environment,” in Proc. 12th Conf. On Computer Communications, vol. 3, 2001, pp. 1548-1557.
131. B. Wang and S. Singh, “Analysis of TCP’s computational energy cost for mobile computing,” SIGMETRICS Perform. Eval. Rev., vol. 31, pp. 296-297, June 2003. [Online]. Available:http://doi.acm.org/10.1145/885651.781065
132. N. Potlapally, S. Ravi, A. Raghunathan, and N. Jha, “A study of the energy consumption characteristics of cryptographic algorithms and security protocols,” IEEE Trans. On Mobile Computing, vol. 5, no. 2, pp. 128-143, February 2006.
133. T. K. Tan, A. Raghunathan, and N. K. Jha, “Energy macromodeling of embedded operating systems,” ACM Trans. Embed. Comput. Syst., vol. 4, pp. 231-254, February 2005. [Online]. Available: http://doi.acm.org/10.1145/1053271.1053281
134. T. Li and L. K. John, “Run-time modeling and estimation of operating system power consumption,” in Proc. 2003 ACM SIGMETRICS Int. Conf. On Measurement and Modeling of Computer Systems. New York, NY, USA: ACM, 2003, pp. 160-171. [Online]. Available: http://doi. acm.org/10.1145/781027.781048
135. J. Flinn and M. Satyanarayanan, “Powerscope: A tool for profiling the energy usage of mobile applications,” in Proc. 2nd IEEE Workshop on Mobile Computer Systems and Applications. Washington, DC, USA: IEEE Computer Society, 1999. [Online]. Available: http://dl.acm. Org/citation.cfm?id=520551.837522
136. L. Zhang, B. Tiwana, Z. Qian, Z. Wang, R. P. Dick, Z. M. Mao, and L. Yang, “Accurate online power estimation and automatic battery behavior based power model generation for smartphones,” in Proc. 8th IEEE/ACM/IFIP Int. Conf. On Hardware/Software Codesign and System Synthesis. New York, NY, USA: ACM, 2010, pp. 105-114.
137. M. Dong and L. Zhong, “Self-constructive high-rate system energy modeling for battery-powered mobile systems,” in Proc. 9th Int. Conf. On Mobile Systems, Applications, and Services. New York, NY, USA: ACM, 2011, pp. 335-348. [Online]. Available: http://doi. acm. Org/10.1145/1999995.2000027
138. Y. Xiao, R. Bhaumik, Z. Yang, M. Siekkinen, P. Savolainen, and A. Yla-Jaaski, “A system-level model for runtime power estimation on mobile devices,” in Green Computing and Communications (GreenCom), 2010 IEEE/ACM Int. Conf. On Cyber, Physical and Social Computing (CPSCom), 2010, pp. 27-34.
139. C. Lawson and R. Hanson, Solving Least Squares Problems. Prentice-Hall, 1974.
140. 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/10.1145/1289927.1289945
141. X. Lu, T. Fernaine, and Y. Wang “Modelling power consumption of aH.263 video encoder,” in Proc. 2004 Int. Symp. On Circuits and Systems, vol. 2, May 2004, pp. 77-80.
142. F. Qian, Z. Wang, A. Gerber, Z. Mao, S. Sen, and O. Spatscheck, “Profiling resource usage for mobile applications: A cross-layer approach,” in Proc. 9th Int. Conf. On Mobile Systems, Applications, and Services. New York, NY, USA: ACM, June 2011, pp. 321-334. [Online]. Available: http://doi.acm.org/10.1145/1999995.2000026
143. K.-c. Lan and J. Heidemann, “A measurement study of correlations of internet flow characteristics,” Comput. Netw., vol. 50, no. 1, pp. 46-62, 2006.
144. 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. On Mobile Computing, vol. 99, PrePrints, 2013.
145. 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 MICRO-36. 2003, pp. 93-104.
146. R. Azimi, M. Stumm, and R. W. Wisniewski, “Online performance analysis by statistical sampling of microprocessor performance counters,” in Proc. 19th Annu. Int. Conf. On Supercomputing. New York, NY, USA: ACM, 2005, pp. 101-110. [Online]. Available: http://doi.acm.org/10.1145/1088149.1088163
147. A. Pathak, Y. C. Hu, and M. Zhang, “Where is the energy spent inside my app? Fine grained energy accounting on smartphones with eProf,” in Proc. 7th ACM European Conf. On Computer Systems. New York, NY, USA: ACM, 2012, pp. 29-42. [Online]. Available: http://doi.acm.org/10.1145/2168836.2168841
148. S. L. Graham, P. B. Kessler, and M. K. Mckusick, “Gprof: A call graph execution profiler,” SIGPLANNot., vol. 17, no. 6, pp. 120-126, Jun. 1982. [Online]. Available: http://doi.acm. Org/10.1145/872726.806987
149. A. Carroll and G. Heiser, “An analysis of power consumption in a smartphone,” in Proc. 2010 USENIXAnnu. Tech. Conf. Berkeley, CA, USA: USENIX Association, 2010. [Online]. Available: http://dl.acm.org/citation.cfm?id=1855840.1855861
150. J. Flinn and M. Satyanarayanan, “Powerscope: A tool for profiling the energy usage of mobile applications,” in Proc. 2nd IEEE Workshop on Mobile Computer Systems and Applications. Washington, DC, USA: IEEE Computer Society, 1999. [Online]. Available: http://dl.acm.org/citation.cfm?id=520551.837522
151. F. Bellosa, “The benefits of event-driven energy accounting in power-sensitive systems,” in Proc. 9th Workshop on ACM SIGOPS European Workshop: Beyond the PC: New Challenges for the Operating System. New York, NY, USA: ACM, 2000, pp. 37-42. [Online]. Available: http://doi.acm.org/10.1145/566726.566736
152. G. Creus and M. Kuulusa, “Optimizing mobile software with built-in power profiling,” in Mobile Phone Programming, F. H. Fitzek and F. Reichert, Eds. Netherlands: Springer, 2007, pp. 449-462. [Online]. Available: http://dx.doi.org/10.1007/978-1-4020-5969-8_25
153. A. Shye, B. Scholbrock, and G. Memik, “Into the wild: studying real user activity patterns to guide power optimizations for mobile architectures,” in Proc. 42nd Annual IEEE/ACM Int. Symp. On Microarchitecture. New York, NY, USA: ACM, 2009, pp. 168-178. [Online]. Available: http://doi.acm.org/10.1145/1669112.1669135
154. L. Zhang, B. Tiwana, Z. Qian, Z. Wang, R. P. Dick, Z. M. Mao, and L. Yang, “Accurate online power estimation and automatic battery behavior based power model generation for smartphones,” in Proc. 8th IEEE/ACM/IFIP Int. Conf. On Hardware/Software Codesign and System Synthesis. New York, NY, USA: ACM, 2010, pp. 105-114.
155. M. Dong and L. Zhong, “Self-constructive high-rate system energy modeling for battery-powered mobile systems,” in Proc. 9th Int. Conf. On Mobile Systems, Applications, and Services. New York, NY, USA: ACM, 2011, pp. 335-348.
156. W. Jung, C. Kang, C. Yoon, D. Kim, and H. Cha, “DevScope: a nonintrusive and online power analysis tool for smartphone hardware components,” in Proc. 8th IEEE/ACM/IFIP Int. Conf. On Hardware/Software Codesign and System Synthesis. New York, NY, USA: ACM, 2012, pp. 353-362. [Online]. Available: http://doi.acm.org/10.1145/2380445.2380502
157. F. Xu, Y. Liu, Q. Li, and Y. Zhang, “V-edge: fast self-constructive power modeling of smartphones based on battery voltage dynamics,” in Proc. 10th USENIX Conf. On Networked Systems Design and Implementation. Berkeley, CA, USA: USENIX Association, 2013, pp. 43-56.
158. C. Yoon, D. Kim, W. Jung, C. Kang, and H. Cha, “AppScope: Application energy metering framework for Android smartphones using kernel activity monitoring,” in Proc. 2012 USENIXAnnu. Tech. Conf. ser. USENIX ATC’12. Berkeley, CA, USA: USENIX Association, 2012, pp. 36-36. [Online]. Available: http://dl.acm.org/citation.cfm?id=2342821. 2342857
159. M. Kjrgaard and H. Blunck, “Unsupervised power profiling for mobile devices,” in Mobile and Ubiquitous Systems: Computing, Networking, and Services, ser. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, A. Puiatti and T. Gu, Eds., vol. 104. Berlin, Heidelberg: Springer, 2012, pp. 138-149. [Online], Available: http://dx.doi.org/10.1007/978-3-642-30973-l_12
160. A. Schulman, T. Schmid, P. Dutta, and N. Spring, Demo: Phone Power Monitoring withBat-tOr, 2011, ACM Mobicom 2011. [Online]. Available: www.stanford.edu/~aschulm/battor. html
161. S. Agarwal, R. Mahajan, A. Zheng, and V. Bahl, “Diagnosing mobile applications in the wild,” in Proc. 9th ACM SIGCOMM Workshop on Hot Topics in Networks. New York, NY, USA: ACM, 2010, pp. 22:1-22:6. [Online]. Available: http://doi.acm.org/10.1145/1868447. 1868469
162. A. Pathak, Y. C. Hu, and M. Zhang, “Where is the energy spent inside my app?: fine grained energy accounting on smartphones with eProf,” in Proc. 7th ACM European Conf. On Computer Systems. New York, NY, USA: ACM, 2012, pp. 29-42. [Online]. Available: http://doi.acm.org/10.1145/2168836.2168841
163. A. J. Oliner, A. P. Iyer, I. Stoica, E. Lagerspetz, and S. Tarkoma, “Carat: Collaborative energy diagnosis for mobile devices,” in Proc. 11th ACM Conf. On Embedded Networked Sensor Systems. New York, NY, USA: ACM, 2013, pp. 10:1-10:14. [Online]. Available: http://doi.acm.org/10.1145/2517351.2517354
164. 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/10.1145/2504730.2504764
165. J. Flinn and M. Satyanarayanan, “Energy-aware adaptation for mobile applications,” SIGOPS Oper. Syst. Rev., vol. 33, no. 5, pp. 48-63, Dec. 1999. [Online]. Available: http://doi.acm.org/10.1145/319344.319155
166. 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/10.1145/1966445.1966460
167. G. Creus and M. Kuulusa, “Optimizing mobile software with built-in power profiling,” in Mobile Phone Programming
168. F. H. Fitzek and F. Reichert, Eds. Netherlands: Springer, 2007, pp. 449-162. [Online], Available: http://dx.doi.org/10.1007/978-l-4020-5969-8_25
169. X. Ma, P. Huang, X. Jin, P. Wang, S. Park, D. Shen, Y. Zhou, L. K. Saul, and G. M. Voelker, “eDoctor: automatically diagnosing abnormal battery drain issues on smartphones,” in Proc. 10th USENIX Conf. On Networked Systems Design and Implementation. Berkeley, CA, USA: USENIX Association, 2013, pp. 57-70. [Online]. Available: http://dl.acm.org/citation.cfm? id=2482626.2482634
170. A. Pathak, Y. C. Hu, and M. Zhang, “Bootstrapping energy debugging on smartphones: A first look at energy bugs in mobile devices,” in HotNets, 2011.
171. A. Pathak, Y. C. Hu, and M. Zhang, “Where is the energy spent inside my app?: fine grained energy accounting on smartphones with eProf,” in Proc. 7th ACM European Conf. On Computer Systems. New York, NY, USA: ACM, 2012, pp. 29-42. [Online]. Available: http://doi.acm.org/10.1145/2168836.2168841
172. Y. Xiao, Y. Cui, P. Savolainen, M. Siekkinen, A. Wang, L. Yang, A. Yla-Jaaski, andS. Tarkoma, “Modeling energy consumption of data transmission over Wi-Fi,” IEEE Trans. On Mobile Computing, vol. 99, no. PrePrints, 2013.
173. M. Hoque, M. Siekkinen, and J. K. Nurminen, “TCP receive buffer aware wireless multimedia streaming - an energy efficient approach,” in Proc. 23rd ACM Workshop on Network and Operating Systems Support for Digital Audio and Video.ACM, 2013, pp. 13-18.
174. I. Kelenyi, A. Ludanyi, and J. Nurminen, “Using home routers as proxies for energy-efficient BiTtorrent downloads to mobile phones,” IEEE Commun. Mag. vol. 49, no. 6, pp. 142-147, 2011.
175. F. R. Dogar, P. Steenkiste, and K. Papagiannaki, “Catnap: exploiting high bandwidth wireless interfaces to save energy for mobile devices,” in Proc. 8th Int. Conf. On Mobile Systems, Applications, and Services. New York, NY, USA: ACM, 2010, pp. 107-122[Online]. Available: http://doi.acm.org/10.1145/1814433.1814446
176. N. Cardwell, S. Savage, and T. Anderson, “Modeling TCP latency,” in INFOCOM 2000. Proc. 19th Annual Joint Conf. Of the IEEE Computer and Communications Societies, vol. 3, 2000, pp. 1742-1751.
177. J. Nurminen, “Parallel connections and their effect on the battery consumption of a mobile phone,” in 2010 7th IEEE Consumer Communications and Networking Conf. (CCNC)
178. Qualcomm, “Managing Background Data Traffic in Mobile Devices,” January 2012. [Online]. Available: www.qualcomm.com/media/documents/managing-background-data- traffic-mobile-devices
179. E. Estep, “Mobile HTML5: Efficiency and Performance of WebSockets and Server-Sent Events,” Master’s thesis, Dept. Of Computer Science and Engineering, Aalto University, School of ScienceHelsinki, Finland, Jun. 2013. [Online]. Available: http://nordsecmob.aalto. fi/en/publications/theses2013/thesis_estep
180. I. Leontiadis, C. Efstratiou, M. Picone, and C. Mascolo, “Don’t kill my ads!: balancing privacy in an ad-supported mobile application market,” in Proc. 12th Workshop on Mobile Computing Systems and Applications.ACM, 2012, pp. 2:1-2:6.
181. N. Vallina-Rodriguez, J. Shah, A. Finamore, Y. Grunenberger, K. Papagiannaki, H. Haddadi, and J. Crowcroft, “Breaking for commercials: characterizing mobile advertising,” in Proc. 2012 ACM Conf. On Internet Measurement. New York, NY, USA: ACM, 2012, pp. 343-356. [Online]. Available: http://doi.acm.org/10.1145/2398776.2398812
182. P. Mohan, S. Nath, and O. Riva, “Prefetching mobile ads: can advertising systems afford it?” in Proc. 8th ACM European Conf. On Computer Systems. New York, NY, USA: ACM, 2013, pp. 267-280. [Online]. Available: http://doi.acm.org/10.1145/2465351.2465378
183. A. Chakraborty, V. Navda, V. N. Padmanabhan, and R. Ramjee, “Coordinating cellular background transfers using LoadSense,” in Proc. 19th Annu. Int. Con. On Mobile Computing and Networking. New York, NY, USA: ACM, 2013, pp. 63-74.
184. A. Schulman, V. Navda, R. Ramjee, N. Spring, P. Deshpande, C. Grunewald, K. Jain, and V. N. Padmanabhan, “Bartendr: a practical approach to energy-aware cellular data scheduling,” in Proc. 16th Annu. Int. Conf. On Mobile Computing and Networking. New York, NY, USA: ACM, 2010, pp. 85-96. [Online]. Available: http://doi.acm.org/10.1145/1859995.1860006
185. Y. Xiao, P. Hui, P. Savolainen, and A. Yla-Jaäski, “CasCap: cloud-assisted context-aware power management for mobile devices,” in Proc. 2nd Int. Workshop on Mobile Cloud Computing and Services. New York, NY, USA: ACM, 2011, pp. 13-18. [Online]. Available: http://doi.acm.org/10.1145/1999732.1999736
186. Y. He and R. Yuan, “A novel scheduled power saving mechanism for 802.11 wireless lans,” IEEE Trans. On Mobile Computing, vol. 8, no. 10, pp. 1368-1383, 2009.
187. E. Rozner, V. Navda, R. Ramjee, and S. Rayanchu, “NAPman: network-assisted power management for wifi devices,” in Proc. 8th Int. Conf. On Mobile Systems, Applications, and Services. New York, NY, USA: ACM, 2010, pp. 91-106. [Online]. Available: http://doi.acm.org/10.1145/1814433.1814445
188. J. Manweiler and R. Roy Choudhury, “Avoiding the rush hours: Wifi energy management via traffic isolation,” in Proc. 9th Int. Conf. On Mobile Systems, Applications, and Services. New York, NY, USA: ACM, 2011, pp. 253-266. [Online]. Available: http://doi.acm.org/10.1145/1999995.2000020
189. H. Wu, K. Tan, J. Liu, and Y. Zhang, “Footprint: cellular assisted Wi-Fi AP discovery on mobile phones for energy saving,” in Proc. 4th ACM Int. Workshop on Experimental Evaluation and Characterization. New York, NY, USA: ACM, 2009, pp. 67-76.
190. K.-H. Kim, A. Min, D. Gupta, P. Mohapatra, and J. Singh, “Improving energy efficiency of Wi-Fi sensing on smartphones,” in Proc. IEEEINFOCOM, 2011, pp. 2930-2938.
191. R. Zhou, Y. Xiong, G. Xing, L. Sun, and J. Ma, “Zifi: wireless lan discovery viaZigBee interference signatures,” in Proc. 16th Annu. Int. Conf. On Mobile Computing and Networking. New York, NY, USA: ACM, 2010, pp. 49-60.
192. G. Ananthanarayanan and I. Stoica, “Blue-fi: enhancing Wi-Fi performance using Bluetooth signals,” in Proc. 7th Int. Conf. On Mobile Systems, Applications, and Services. New York, NY, USA: ACM, 2009, pp. 249-262.
193. E. Shih, P. Bahl, and M. J. Sinclair, “Wake on wireless: an event driven energy saving strategy for battery operated devices,” in Proc. 8th Annu. Int. Conf. On Mobile Computing and Networking. New York, NY, USA: ACM, 2002, pp. 160-171.
194. Y. Agarwal, R. Chandra, A. Wolman, P. Bahl, K. Chin, and R. Gupta, “Wireless wakeups revisited: energy management for VoIP over Wi-Fi smartphones,” in Proc. 5th Int. Conf. On Mobile Systems, Applications and Services. New York, NY, USA: ACM, 2007, pp. 179-191.
195. T. Pering, Y. Agarwal, R. Gupta, and R. Want, “Coolspots: reducing the power consumption of wireless mobile devices with multiple radio interfaces,” in MobiSys’06: Proc. 4th Int. Conf. On Mobile Systems, Applications and Services. New York, NY, USA: ACM, 2006, pp. 220-232.
196. A. Rahmati and L. Zhong, “Context-for-wireless: context-sensitive energy-efficient wireless data transfer,” in Proc. 5th Int. Conf. On Mobile Systems, Applications and Services. New York, NY, USA: ACM, 2007, pp. 165-178.
197. T. Jin, G. Noubir, and B. Sheng, “Wizi-cloud: Application-transparent dual ZigBee-WiFi radios for low power internet access,” in Proceedings IEEE INFOCOM, 2011, pp. 1593-1601.
198. A. Y. Ding, P. Hui, M. Kojo, and S. Tarkoma, “Enabling energy-aware mobile data offloading for smartphones through vertical collaboration,” in Proc. 2012 ACM Conf. On CoNEXT Student Workshop, ser. CoNEXT Student’12. New York, NY, USA: ACM, 2012, pp. 27-28. [Online]. Available: http://doi.acm.org/10.1145/2413247.2413264
199. S. Liu and A. Striegel, “Casting doubts on the viability of wifi offloading,” in Proc. 2012 ACM SIGCOMM Workshop on Cellular Networks: Operations, Challenges, and Future Design, ser. CellNet’12. New York, NY, USA: ACM, 2012, pp. 25-30. [Online]. Available: http://doi.acm.org/10.1145/2342468.2342475
200. N. Ristanovic, J.-Y. Le Boudec, A. Chaintreau, and V. Erramilli, “Energy efficient offloading of 3G networks,” in Proc. 2011 IEEE 8th Int. Conf. On Mobile Ad-Hoc and Sensor Systems, ser. MASS’11. Washington, DC, USA: IEEE Computer Society, 2011, pp. 202-211. [Online]. Available: http://dx.doi.org/10.1109/MASS.2011.27
201. B. Han, P. Hui, and A. Srinivasan, “Mobile data offloading in metropolitan area networks,” SIGMOBILEMob. Comput. Commun. Rev., vol. 14, no. 4, pp. 28-30, Nov. 2010. [Online]. Available: http://doi.acm.org/10.1145/1942268.1942279
202. A. Aijaz, H. Aghvami, and M. Amani, “A survey on mobile data offloading: technical and business perspectives,” IEEE Wireless Communications, vol. 20, no. 2, pp. 104-112, 2013.
203. J. Korhonen, T. Savolainen, A. Ding, and M. Kojo, “Toward network controlled IP traffic offloading,” IEEE Commun. Mag., vol. 51, no. 3, pp. 96-102, 2013.
204. A. Balasubramanian, R. Mahajan, and A. Venkataramani, “Augmenting mobile 3G using wifi,” in Proc. 8th Int. Conf. On Mobile Systems, Applications, and Services, ser. MobiSys’10. New York, NY, USA: ACM, 2010, pp. 209-222. [Online]. Available: http://doi.acm.org/10.1145/1814433.1814456
205. K. Lee, J. Lee, Y. Yi, I. Rhee, and S. Chong, “Mobile data offloading: How much can wifi deliver?” in Proc. 6th Int. Conf., ser. Co-NEXT’ 10. New York, NY, USA: ACM, 2010, pp. 26:1-26:12. [Online]. Available: http://doi.acm.org/10.1145/1921168.1921203
206. X. Hou, P. Deshpande, and S. Das, “Moving bits from 3G to metro-scale wifi for vehicular network access: An integrated transport layer solution,” in 2011 19th IEEE Int. Conf. On Network Protocols (ICNP), 2011, pp. 353-362.
207. S. Dimatteo, P. Hui, B. Han, and V. Li, “Cellular traffic offloading through wifi networks,” in 2011 IEEE 8th Int. Conf. On Mobile Adhoc and Sensor Systems (MASS), 2011, pp. 192-201.
208. P. Bahl and V. Padmanabhan, “Radar: an in-building rf-based user location and tracking system,” in INFOCOM 2000. Proc. 19th Annu. Joint Conf. Of the IEEE Computer and Communications Societies, vol. 2, 2000, pp. 775-784.
209. V. Brik, A. Mishra, and S. Banerjee, “Eliminating handoff latencies in 802.11 WLANs using multiple radios: Applications, experience, and evaluation,” in Proc. 5th ACM SIGCOMM Conf. On Internet Measurement, ser. IMC’05. Berkeley, CA, USA: USENIX Association, 2005, pp. 27-27. [Online]. Available: http://dl.acm.org/citation.cfm?id=1251086. 1251113
210. I. Ramani and S. Savage, “Syncscan: practical fast handoff for 802.11 infrastructure networks,” in INFOCOM 2005. Proc. 24th Annu. Joint Conf. Of the IEEE Computer and Communications Societies, vol. 1, 2005, pp. 675-684 vol. 1.
211. R. Chakravorty, P. Vidales, K. Subramanian, I. Pratt, and J. Crowcroft, “Performance issues with vertical handovers - experiences from GPRS cellular and WLAN hot-spots integration,” in Proc. 2nd IEEE Int. Conf. On Pervasive Computing and Communications (PerCom’04), ser. PERCOM’04. Washington, DC, USA: IEEE Computer Society, 2004, pp. 155-. [Online]. Available: http://dl.acm.org/citation.cfm?id=977406.978694
212. M. Shin, A. Mishra, and W. A. Arbaugh, “Improving the latency of 802.11 hand-offs using neighbor graphs,” in Proc. 2nd Int. Conf. On Mobile Systems, Applications, and Services, ser. MobiSys’04. New York, NY, USA: ACM, 2004, pp. 70-83. [Online]. Available: http://doi.acm.org/10.1145/990064.990076
213. P. Deshpande, A. Kashyap, C. Sung, and S. R. Das, “Predictive methods for improved vehicular wifi access,” in Proc. 7th Int. Conf. On Mobile Systems, Applications, and Services, ser. MobiSys’09. New York, NY, USA: ACM, 2009, pp. 263-276. [Online]. Available: http://doi.acm.org/10.1145/1555816.1555843
214. A. J. Nicholson and B. D. Noble, “Breadcrumbs: Forecasting mobile connectivity,” in Proc. 14th ACM Int. Conf. On Mobile Computing and Networking, ser. MobiCom’08. New York, NY, USA: ACM, 2008, pp. 46-57. [Online]. Available: http://doi.acm.org/10.1145/1409944. 1409952
215. A. J. Nicholson, Y. Chawathe, M. Y. Chen, B. D. Noble, and D. Wetherall, “Improved access point selection,” in Proc. 4th Int. Conf. On Mobile Systems, Applications and Services, ser. MobiSys’06. New York, NY, USA: ACM, 2006, pp. 233-245. [Online]. Available: http://doi.acm.org/10.1145/1134680.1134705
216. A. Aucinas, N. Vallina-Rodriguez, Y. Grunenberger, V. Erramilli, K. Papagiannaki, J. Crowcroft, and D. Wetherall, “Staying online while mobile: The hidden costs,” in Proc. 9th ACM Conf. On Emerging Networking Experiments and Technologies, ser. CoNEXT’ 13. New York, NY, USA: ACM, 2013, pp. 315-320.Online]. Available: http://doi.acm.org/10. 1145/2535372.2535408
217. P. Deshpande, X. Hou, and S. R. Das, “Performance comparison of 3G and metro-scale wifi for vehicular network access,” in Proc. 10th ACM SIGCOMM Conf. On Internet Measurement, ser. IMC’10. New York, NY, USA: ACM, 2010, pp301-307. [Online]. Available: http://doi.acm.org/10.1145/1879141.1879180
218. J. Eriksson, H. Balakrishnan, and S. Madden, “Cabernet: Vehicular content delivery using wifi,” in Proc. 14th ACM Int. Conf. On Mobile Computing and Networking, ser. MobiCom’08. New York, NY, USA: ACM, 2008, pp. 199-210. [Online]. Available: http://doi.acm.org/10.1145/1409944.1409968
219. J. Paek, J. Kim, and R. Govindan, “Energy-efficient rate-adaptive GPS-based positioning for smartphones,” in Proc. 8th Int. Conf. On Mobile Systems, Applications, and Services, ser. MobiSys’10. New York, NY, USA: ACM, 2010, pp. 299-314. [Online]. Available: http://doi.acm.org/10.1145/1814433.1814463
220. M. B. Kjrgaard, S. Bhattacharya, H. Blunck, and P. Nurmi, “Energy-efficient trajectory tracking for mobile devices,” in Proc. 9th Int. Conf. On Mobile Systems, Applications, and Services, ser. MobiSys’11. New York, NY, USA: ACM, 2011, pp. 307-320. [Online]. Available: http://doi.acm.org/10.1145/1999995.2000025
221. U. Shevade, Y.-C. Chen, L. Qiu, Y. Zhang, V. Chandar, M. K. Han, H. H. Song, and Y. Seung, “Enabling high-bandwidth vehicular content distribution,” in Proc. 6th Int. Conf., ser. Co-NEXT’10. New York, NY, USA: ACM, 2010, pp. 23:1-23:12. [Online]. Available: http://doi.acm.org/10.1145/1921168.1921199
222. B. Han, P. Hui, V. S. A. Kumar, M. V. Marathe, J. Shao, and A. Srinivasan, “Mobile data offloading through opportunistic communications and social participation,” IEEE Trans. On Mobile Computing, vol0 11, no. 5, pp. 821-834, May 2012. [Online]. Available: http://dx. doi.org/10.1109/TMC.2011.101
223. B. D. Higgins, J. Flinn, T. J. Giuli, B. Noble, C. Peplin, and D. Watson, “Informed mobile prefetching,” in Proc. 10th Int. Conf. On Mobile Systems, Applications, and Services, ser. MobiSys’12. New York, NY, USA: ACM, 2012, pp. 155-168. [Online]. Available: http://doi.acm.org/10.1145/2307636.2307651
224. L. Song, U. Deshpande, U. Kozat, D. Kotz, and R. Jain, “Predictability of WLAN mobility and its effects on bandwidth provisioning,” in INFOCOM 2006. Proc. 25th IEEE Int. Conf. On Computer Communications. Proc., 2006, pp. 1-13.
225. C. Rossi, N. Vallina-Rodriguez, V. Erramilli, Y. Grunenberger, L. Gyarmati, N. Laoutaris, R. Stanojevic, K. Papagiannaki, and P. Rodriguez, “3GOL: Power-boosting ADSL using 3G onloading,” in Proc. 9th ACM Conf. On Emerging Networking Experiments and Technologies, ser. CoNEXT’ 13. New York, NY, USA: ACM, 2013, pp. 187-198. [Online]. Available: http://doi.acm.org/10.1145/2535372.2535400
226. N. Vallina-Rodriguez, V. Erramilli, Y. Grunenberger, L. Gyarmati, N. Laoutaris, R. Stano-jevic, and K. Papagiannaki, “When David Helps Goliath: The Case for 3G Onloading,” in Proc. 11th ACM Workshop on Hot Topics in Networks, ser. HotNets-XI. New York, NY, USA: ACM, 2012, pp. 85-90. [Online]. Available: http://doi.acm.org/10.1145/2390231. 2390246
227. E. Cuervo, A. Balasubramanian, D.-k. Cho, A. Wolman, S. Saroiu, R. Chandra, and P. Bahl, “Maui: making smartphones last longer with code offload,” in Proc. 8th Int. Conf. On Mobile Systems, Applications, and Services (MobiSys’10). New York, NY, USA: ACM, 2010, pp. 49-62.
228. S. Kosta, A. Aucinas, P. Hui, R. Mortier, and X. Zhang, “ThinkAir: Dynamic resource allocation and parallel execution in the cloud for mobile code offloading,” in Proc. IEEE INFOCOM, 2012, 2012, pp. 945-953.
229. R. Kemp, N. Palmer, T. Kielmann, and H. Bal, “Cuckoo: A computation offloading framework for smartphones,” in Proc. 2nd Int. ICST Conf. Mobile Computing, Applications, and Services, MobiCASE 2010, 2012.
230. B.-G. Chun, S. Ihm, P. Maniatis, M. Naik, and A. Patti, “CloneCloud: elastic execution between mobile device and cloud,” in Proc. 6th Conf. On Computer Systems. New York, NY, USA: ACM, 2011, pp. 301-314.
231. P. Simoens, Y. Xiao, P. Pillai, Z. Chen, K. Ha, and M. Satyanarayanan, “Scalable crowdsourcing of video from mobile devices,” in Proc. 11th Annu. Int. Conf. On Mobile Systems, Applications, and Services. New York, NY, USA: ACM, 2013, pp. 139-152. [Online]. Available: http://doi.acm.org/10.1145/2462456.2464440
232. A. Saarinen, M. Siekkinen, Y. Xiao, J. K. Nurminen, M. Kemppainen, and P. Hui, “Can offloading save energy for popular apps?” in Proc. 7th ACM Int. Workshop on Mobility in the Evolving Internet Architecture. New York, NY, USA: ACM, 2012, pp. 3-10. [Online]. Available: http://doi.acm.org/10.1145/2348676.2348680
233. 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. On Mobile Computing, vol. 99, no. PrePrints, 2013.
234. M. Satyanarayanan, P. Bahl, R. Caceres, and N. Davies, “The case for VM-based cloudlets in mobile computing,” IEEE Pervasive Computing, vol. 8, no. 4, pp. 14-23, Oct. 2009. [Online]. Available: http://dx.doi.org/10.1109/MPRV.2009.82
235. Y. Xiao, P. Simoens, P. Pillai, K. Ha, and M. Satyanarayanan, “Lowering the barriers to large-scale mobile crowdsensing,” in Proc. 14th Workshop on Mobile Computing Systems and Applications. New York, NY, USA: ACM, 2013, pp. 9:1-9:6. [Online]. Available:http://doi.acm.org/10.1145/2444776.2444789
236. M. A. Hoque, M. Siekkinen, J. K. Nurminen, and M. Aalto, “Dissecting mobile video services: An energy consumption perspective,” in Proc. 14th IEEE Int. Sym. On a World of Wireless, Mobile and Multimedia Networks (WoWMoM), Jun. 2013.
237. T. Stockhammer, “Dynamic adaptive streaming over http: standards and design principles,” in Proc. 2nd Annu.ACM Conf. On Multimedia Systems. New York, NY, USA: ACM, 2011, pp. 133-144.
238. A. Finamore, M. Mellia, M. M. Munafo, R. Torres, and S. G. Rao, “YouTube everywhere: impact of device and infrastructure synergies on user experience,” in Proc. 2011 ACM SIG-COMM Conf. On Internet Measurement, ser. IMC’11. New York, NY, USA: ACM, 2011, pp. 345-360.
239. M. A. Hoque, M. Siekkinen, and J. K. Nurminen, “Using crowd-sourced viewing statistics to save energy in wireless video streaming,” in Proc. 19th Annu. Int. Conf. On Mobile Computing and Networking. New York, NY, USA: ACM, 2013, pp. 377-388. [Online]. Available: http://doi.acm.org/10.1145/2500423.2500427
240. M. Hoque, M. Siekkinen, and J. K. Nurminen, “TCP receive buffer aware wireless multimedia streaming - an energy efficient approach,” in Proc. 23rd ACM Workshop on Network and Operating Systems Support for Digital Audio and Video.ACM, 2013, pp. 13-18.
241. M. Hoque, M. Siekkinen, and J. Nurminen, “Energy efficient multimedia streaming to mobile devices: A survey,” IEEE Communications Surveys Tutorialsno. 99, pp. 1-19, 2012.
242. S. Mohapatra, R. Cornea, N. Dutt, A. Nicolau, and N. Venkatasubramanian, “Integrated power management for video streaming to mobile handheld devices,” in Proc. 11th ACM Int. Conf. On Multimedia. New York, NY, USA: ACM, 2003, pp. 582-591. [Online]. Available:http://doi.acm.org/10.1145/957013.957134
243. Y. Li, M. Reisslein, and C. Chakrabarti, “Energy-efficient video transmission over a wireless link,” IEEE Transactions Veh. Technol., vol. 58, no. 3, pp. 1229-1244, 2009.
244. S. Madgwick, A. J. L. Harrison, and R. Vaidyanathan, “Estimation of IMU and MARG orientation using a gradient descent algorithm,” in 2011 IEEE Int. Conf. On Rehabilitation Robotics (ICORR), 2011, pp. 1-7.
245. D. Figo, P. C. Diniz, D. R. Ferreira, and J. a. M. Cardoso, “Preprocessing techniques for context recognition from accelerometer data,” Personal Ubiquitous Comput., vol. 14, no. 7, pp. 645-662, Oct. 2010. [Online]. Available: http://dx.doi.org/10.1007/s00779-010-0293-9
246. Z. Yan, V. Subbaraju, D. Chakraborty, A. Misra, and K. Aberer, “Energy-efficient continuous activity recognition on mobile phones: An activity-adaptive approach,” in Proc. 2012 16th Annu. Int. Symp. On Wearable Computers (ISWC), ser. ISWC’12. Washington, DC, USA: IEEE Computer Society, 2012, pp. 17-24. [Online]. Available: http://dx.doi.org/10.1109/ISWC.2012.23
247. H. Eren, S. Makinist, E. Akin, and A. Yilmaz, “Estimating driving behavior by a smartphone,” in 2012 IEEE Intelligent Vehicles Symp. (IV), 2012, pp. 234-239.
248. J. Paek, J. Kim, and R. Govindan, “Energy-efficient rate-adaptive GPS-based positioning for smartphones,” in Proc. 8th Int. Conf. On Mobile Systems, Applications, and Services, ser. MobiSys’10. New York, NY, USA: ACM, 2010, pp. 299-314. [Online]. Available: http://doi.acm.org/10.1145/1814433.1814463
249. M. B. Kjrgaard, S. Bhattacharya, H. Blunck, and P. Nurmi, “Energy-efficient trajectory tracking for mobile devices,” in Proc. 9th Int. Conf. On Mobile Systems, Applications, and Services, ser. MobiSys’11. New York, NY, USA: ACM, 2011, pp. 307-320. [Online]. Available: http://doi.acm.org/10.1145/1999995.2000025
250. H. Lu, W. Pan, N. D. Lane, T. Choudhury, and A. T. Campbell, “Soundsense: Scalable sound sensing for people-centric applications on mobile phones,” in Proc. 7th Int. Conf. On Mobile Systems, Applications, and Services, ser. MobiSys’09. New York, NY, USA: ACM, 2009, pp. 165-178. [Online]. Available: http://doi.acm.org/10.1145/1555816.1555834
251. G. Raffa, J. Lee, L. Nachman, and J. Song, “Don’t slow me down: Bringing energy efficiency to continuous gesture recognition,” in 2010 International Symp. On Wearable Computers (ISWC), 2010, pp. 1-8.
252. H. Lu, J. Yang, Z. Liu, N. D. Lane, T. Choudhury, and A. T. Campbell, “The Jigsaw continuous sensing engine for mobile phone applications,” in Proc. 8th ACM Conf. On Embedded Networked Sensor Systems, ser. SenSys’ 10. New York, NY, USA: ACM, 2010, pp. 71-84. [Online]. Available: http://doi.acm.org/10.1145/1869983.1869992
253. W. Stallings, Cryptography and Network Security: Principles and Practice, 5th ed. Upper Saddle River, NJ, USA: Prentice Hall Press, 2010.
254. N. Potlapally, S. Ravi, A. Raghunathan, and N. Jha, “A study of the energy consumption characteristics of cryptographic algorithms and security protocols,” IEEE Trans. On Mobile Computing, vol. 5, no. 2, pp. 128-143, 2006.
255. P. Miranda, M. Siekkinen, and H. Waris, “TLS and energy consumption on a mobile device: A measurement study,” in 2011 IEEE Symp. On Computers and Communications (ISCC), 2011, pp. 983-989.
256. A. S. Wander, N. Gura, H. Eberle, V. Gupta, and S. C. Shantz, “Energy analysis of public-key cryptography for wireless sensor networks,” in Proc. 3rd IEEE Int. Conf. On Pervasive Computing and Communications. Washington, DC, USA: IEEE Computer Society, 2005, pp. 324-328.
257. D. Linden and T. B. Reddy, Handbook of Batteries, 3rd ed. McGraw-Hill Professional, 2001.
258. P. Bruce, B. Scrosati, and J.-M. Tarascon, “Nanomaterials for rechargeable lithium batteries,” Angewandte Chemie International Edition, vol. 47, no. 16, pp. 2930-2946, 2008. [Online]. Available: http://dx.doi.org/10.1002/anie.200702505
259. C. K. Chan, H. Peng, G. Liu, K. McIlwrath, X. F. Zhang, R. A. Huggins, and Y. Cui, “High-performance lithium battery anodes using silicon nanowires,” Nature Nanotechnology, vol. 3, no. 1, pp. 31-35, 2007. [Online]. Available: www.nature.com/nnano/journal/v3/n1/full/nnano.2007.411.html
260. X. Zhao, C. M. Hayner, M. C. Kung, and H. H. Kung, “In-plane vacancy-enabled high-power sigraphene composite electrode for lithium-ion batteries,” Advanced Energy Materials, vol. 1, no. 6, pp. 1079-1084, 2011. [Online]. Available: http://dx.doi.org/10.1002/aenm. 201100426
261. S. W. Lee, N. Yabuuchi, B. M. Gallant, S. Chen, B. S. Kim, P. T. Hammond, and Y. Shao-Horn, “High-power lithium batteries from functionalized carbon-nanotube electrodes,” Nature Nanotechnology, vol. 5, no. 7, pp. 531-537, Jul.
262. J. H. Pikul, H. Gang Zhang, J. Cho, P. V. Braun, and W. P. King, “High-power lithium ion microbatteries from interdigitated three-dimensional bicontinuous nanoporous electrodes,” Nat. Commun., vol. 4, p. 1732, Apr. 2013, www.nature.com/ncomms/journal/v4/n4/suppinfo/ncomms2747_S 1.html
263. H. Zhu, Z. Jia, Y. Chen, N. Weadock, J. Wan, O. Vaaland, X. Han, T. Li, and L. Hu, “Tin anode for sodium-ion batteries using natural wood fiber as a mechanical buffer and electrolyte reservoir,” Nano Letters, vol. 13, no. 7, pp. 3093-3100, 2013. [Online]. Available: http://pubs.acs.org/doi/abs/10.1021/nl400998t
264. G. Girishkumar, B. McCloskey, A. C. Luntz, S. Swanson, and W. Wilcke, “Lithium-air battery: Promise and challenges,” The Journal of Physical Chemistry Letters, vol. 1, no. 14, pp. 2193-2203, 2010. [Online]. Available: http://pubs.acs.org/doi/abs/10.1021/jz1005384
265. J. Christensen, P. Albertus, R. S. Sanchez-Carrera, T. Lohmann, B. Kozinsky, R. Liedtke, J., “A Critical Review of Li/Air Batteries,” Journal of the Electrochemical Society, vol. 159, no. 2, pp. R1-R30, Jan. 2011. [Online]. Available: http://dx.doi.org/10.1149/2.086202jes
266. S. Chalasani and J. Conrad, “A survey of energy harvesting sources for embedded systems,” in 2008. IEEE Southeastcon, 2008, pp. 442-447.
267. T. Krupenkin and J. A. Taylor, “Reverse electrowetting as a new approach to high-power energy harvesting,” Nature Communications, vol. 2, no. 448, Aug. 2011. [Online]. Available: www.nature.com/ncomms/journal/v2/n8/full/ncomms1454.html
268. Y.-M. Lin, C. Dimitrakopoulos, K. A. Jenkins, D. B. Farmer, H.-Y. Chiu, A. Grill, and P. Avouris, “100-ghz transistors from wafer-scale epitaxial graphene,” Science, vol. 327, no. 5966, p. 662, 2010. [Online]. Available: www.sciencemag.org/content/327/5966/662. abstract
269. 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.html
270. C.-I. Badoi, N. Prasad, V. Croitoru, and R. Prasad, “5G based on cognitive radio,” Wirel. Pers. Commun., vol. 57, no. 3, pp. 441-464, Apr. 2011. [Online]. Available: http://dx.doi.org/10.1007/s11277-010-0082-9
271. S. Mohapatra, R. Cornea, N. Dutt, A. Nicolau, and N. Venkatasubramanian, “Integrated power management for video streaming to mobile handheld devices,” in Proc. 11th ACM Int. Conf. On Multimedia. New York, NY, USA: ACM, 2003, pp. 582-591.
272. B. -G. Chun, S. Ihm, P. Maniatis, M. Naik, and A. Patti, “CloneCloud: elastic execution between mobile device and cloud,” in Proc. 6th Conf. On Computer Systems. New York, NY, USA: ACM, 2011, pp. 301-314.
273. E. Cuervo, A. Balasubramanian, D.-k. Cho, A. Wolman, S. Saroiu, R. Chandra, and P. Bahl, “MAUI: making smartphones last longer with code offload,” in Proc. 8th Int. Conf. On Mobile Systems, Applications, and Services (MobiSys’10). New York, NY, USA: ACM, 2010, pp. 49-62.