Abstract
Software energy profilers are the tools to measure the energy consumption of mobile devices, applications running on those devices, and various hardware components. They adopt different modeling and measurement techniques. In this article, we aim to review a wide range of such energy profilers for mobile devices. First, we introduce the terminologies and describe the power modeling and measurement methodologies applied in model-based energy profiling. Next, we classify the profilers according to their implementation and deployment strategies, and compare the profiling capabilities and performance between different types. Finally, we point out their limitations and the corresponding challenges.
- Android. 2014a. Android Power Profiles. Retrieved February 20, 2014, from https://source.android.com/devices/tech/power.html.Google Scholar
- Android. 2014b. Battery Historian. Retrieved January 7, 2015, from https://developer.android.com/about/versions/android-5.0.html.Google Scholar
- Android. 2014c. Hierarchy Viewer: Debugging and Profiling UIs. Retrieved November 20, 2014, from http://developer.android.com/tools/help/hierarchy-viewer.html.Google Scholar
- Android. 2015. Android WifiManager.WifiLock. Retrieved April 30, 2015, from http://developer.android.com/reference/android/net/wifi/WifiManager.WifiLock.html.Google Scholar
- Kumaripaba Athukorala, Eemil Lagerspetz, Maria von Kügelgen, Antti Jylhä, Adam J. Oliner, Sasu Tarkoma, and Giulio Jacucci. 2014. How Carat affects user behavior: Implications for mobile battery awareness applications. In Proceedings of the 32nd Annual ACM Conference on Human Factors in Computing Systems (CHI’14). ACM, New York, NY, 1029--1038. Google ScholarDigital Library
- Niranjan Balasubramanian, Aruna Balasubramanian, and Arun Venkataramani. 2009. Energy consumption in mobile phones: A measurement study and implications for network applications. In Proceedings of the 9th ACM SIGCOMM Conference on Internet Measurement Conference (IMC’09). ACM, New York, NY, 280--293. Google ScholarDigital Library
- Abhijeet Banerjee, Lee Kee Chong, Sudipta Chattopadhyay, and Abhik Roychoudhury. 2014. Detecting energy bugs and hotspots in mobile apps. In Proceedings of the 22nd ACM SIGSOFT International Symposium on Foundations of Software Engineering (FSE’14). ACM, New York, NY, 588--598. Google ScholarDigital Library
- Anthony Barré, Frédéric Suard, Mathias Gérard, and Delphine Riu. 2014. A real-time data-driven method for battery health prognostics in electric vehicle use. In Proceedings of the 2nd European Conference of the Prognostics and Health Management Society 2014 (PHMCE’14). 1--8.Google Scholar
- Frank Bellosa. 2000. The benefits of event: Driven energy accounting in power-sensitive systems. In Proceedings of the 9th ACM SIGOPS European Workshop: Beyond the PC—New Challenges for the Operating System. ACM, New York, NY, 37--42. Google ScholarDigital Library
- W. Lloyd Bircher and Lizy K. John. 2007. Complete system power estimation: A trickle-down approach based on performance events. In Proceedings of the IEEE International Symposium on Performance Analysis of Systems Software (ISPASS’07). IEEE, Los Alamitos, CA, 158--168.Google Scholar
- Niels Brouwers, Marco Zuniga, and Koen Langendoen. 2014. NEAT: A novel energy analysis toolkit for free-roaming smartphones. In Proceedings of the 12th ACM Conference on Embedded Network Sensor Systems (SenSys’14). ACM, New York, NY, 16--30. Google ScholarDigital Library
- Martin Burtscher, Ivan Zecena, and Ziliang Zong. 2014. Measuring GPU power with the K20 built-in sensor. In Proceedings of the Workshop on General Purpose Processing Using GPUs (GPGPU-7). ACM, New York, NY, Article No. 28. Google ScholarCross Ref
- Min Chen and Gabriel A. Rincon-Mora. 2006. Accurate electrical battery model capable of predicting runtime and I-V performance. IEEE Transactions on Energy Conversion 21, 2, 504--511.Google ScholarCross Ref
- Xiang Chen, Yiran Chen, Zhan Ma, and Felix C. A. Fernandes. 2013. How is energy consumed in smartphone display applications? In Proceedings of the 14th Workshop on Mobile Computing Systems and Applications (HotMobile’13). ACM, New York, NY, Article No. 3. Google ScholarDigital Library
- Xiang Chen, Jian Zheng, Yiran Chen, Mengying Zhao, and Chun Jason Xue. 2012. Quality-retaining OLED dynamic voltage scaling for video streaming applications on mobile devices. In Proceedings of the 49th Annual Design Automation Conference (DAC’12). ACM, New York, NY, 1000--1005. Google ScholarDigital Library
- Gilberto Contreras and Margaret Martonosi. 2005. Power prediction for Intel XScale processors using performance monitoring unit events. In Proceedings of the International Symposium on Low Power Electronics and Design (ISLPED’05). ACM, New York, NY, 221--226. Google ScholarDigital Library
- Gerard Bosch Creus and Mika Kuulusa. 2007. Optimizing mobile software with built-in power profiling. In Mobile Phone Programming, Frank H. P. Fitzek and Frank Reichert (Eds.). Springer, Netherlands, 449--462.Google Scholar
- Eduardo Cuervo, Aruna Balasubramanian, Dae-Ki Cho, Alec Wolman, Stefan Saroiu, Ranveer Chandra, and Paramvir Bahl. 2010. MAUI: Making smartphones last longer with code offload. In Proceedings of the 8th International Conference on Mobile Systems, Applications, and Services (MobiSys’10). ACM, New York, NY, 49--62. Google ScholarDigital Library
- Ning Ding, Daniel Wagner, Xiaomeng Chen, Abhinav Pathak, Y. Charlie Hu, and Andrew Rice. 2013. Characterizing and modeling the impact of wireless signal strength on smartphone battery drain. In Proceedings of the ACM SIGMETRICS/International Conference on Measurement and Modeling of Computer Systems (SIGMETRICS’13). ACM, New York, NY, 29--40. Google ScholarDigital Library
- Tahir Diop, Natalie Enright Jerger, and Jason Anderson. 2014. Power modeling for heterogeneous processors. In Proceedings of the Workshop on General Purpose Processing Using GPUs (GPGPU-7). ACM, New York, NY, Article No. 90. Google ScholarCross Ref
- Mian Dong, Yung-Seok Kevin Choi, and Lin Zhong. 2009. Power modeling of graphical user interfaces on OLED displays. In Proceedings of the 46th Annual Design Automation Conference (DAC’09). ACM, New York, NY, 652--657. Google ScholarDigital Library
- Mian Dong and Lin Zhong. 2011. Self-constructive high-rate system energy modeling for battery-powered mobile systems. In Proceedings of the 9th International Conference on Mobile Systems, Applications, and Services. ACM, New York, NY, 335--348. Google ScholarDigital Library
- Mian Dong and Lin Zhong. 2012. Power modeling and optimization for OLED displays. IEEE Transactions on Mobile Computing 11, 9, 1587--1599. Google ScholarDigital Library
- Hossein Falaki, Ratul Mahajan, Srikanth Kandula, Dimitrios Lymberopoulos, Ramesh Govindan, and Deborah Estrin. 2010. Diversity in smartphone usage. In Proceedings of the 8th International Conference on Mobile Systems, Applications, and Services (MobiSys’10). ACM, New York, NY, 179--194. Google ScholarDigital Library
- Jason Flinn and Mahadev Satyanarayanan. 1999. PowerScope: A tool for profiling the energy usage of mobile applications. In Proceedings of the 2nd IEEE Workshop on Mobile Computer Systems and Applications. IEEE, Los Alamitos, CA. Google ScholarDigital Library
- Andres Garcia-Saavedra, Pablo Serrano, Albert Banchs, and Giuseppe Bianchi. 2012. Energy consumption anatomy of 802.11 devices and its implication on modeling and design. In Proceedings of the 8th International Conference on Emerging Networking Experiments and Technologies (CoNEXT’12). ACM, New York, NY, 169--180. Google ScholarDigital Library
- Trevor Hastie, Robert Tibshirani, and Jerome Friedman. 2001. The Elements of Statistical Learning. Springer, New York, NY.Google Scholar
- Sunpyo Hong and Hyesoon Kim. 2010. An integrated GPU power and performance model. In Proceedings of the 37th Annual International Symposium on Computer Architecture (ISCA’10). ACM, New York, NY, 280--289. Google ScholarDigital Library
- Mohammad A. Hoque, M. Siekkinen, and Jukka K. Nurminen. 2014a. Energy efficient multimedia streaming to mobile devices: A survey. IEEE Communications Surveys Tutorials 16, 1, 579--597.Google ScholarCross Ref
- Mohammad A. Hoque, M. Siekkinen, Jukka K. Nurminen, and M. Aalto. 2013a. Dissecting mobile video services: An energy consumption perspective. In Proceedings of the 2013 IEEE 14th International Symposium and Workshops on a World of Wireless, Mobile, and Multimedia Networks (WoWMoM’13), IEEE, Los Alamitos, CA, 1--11.Google Scholar
- Mohammad A. Hoque, Matti Siekkinen, and Jukka K. Nurminen. 2013b. Using crowd-sourced viewing statistics to save energy in wireless video streaming. In Proceedings of the 19th Annual International Conference on Mobile Computing and Networking. ACM, New York, NY, 377--388. Google ScholarDigital Library
- Mohammad A. Hoque, Matti Siekkinen, Jukka K. Nurminen, Sasu Tarkoma, and Mika Aalto. 2014b. Saving energy in mobile devices for on-demand multimedia streaming—a cross-layer approach. ACM Transactions on Multimedia Computing, Communications, and Applications 10, 3, Article No. 25. Google ScholarDigital Library
- Mohammad A. Hoque and Sasu Tarkoma. 2015. Sudden drop in the battery level? Understanding smartphone state of charge anomaly. In Proceedings of the Workshop on Power-Aware Computing and Systems (HotPower’15). ACM, New York, NY, 26--30. Google ScholarDigital Library
- Junxian Huang, Feng Qian, Alexandre Gerber, Z. Morley Mao, Subhabrata Sen, and Oliver Spatscheck. 2012. A close examination of performance and power characteristics of 4G LTE networks. In Proceedings of the 10th International Conference on Mobile Systems, Applications, and Services (MobiSys’12). ACM, New York, NY, 225--238. Google ScholarDigital Library
- Anders R. Jensen, Mads Lauridsen, Preben Mogensen, Troels B. Srensen, and Per Jensen. 2012. LTE UE power consumption model: For system level energy and performance optimization. In Proceedings of the 2012 IEEE Vehicular Technology Conference (VTC Fall’12). IEEE, Los Alamitos, CA, 1--5.Google ScholarCross Ref
- Wonwoo Jung, Yohan Chon, Dongwon Kim, and Hojung Cha. 2014. Powerlet: An active battery interface for smartphones. In Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp’14). ACM, New York, NY, 45--56. Google ScholarDigital Library
- Wonwoo Jung, Chulkoo Kang, Chanmin Yoon, Donwon Kim, and Hojung Cha. 2012. DevScope: A nonintrusive and online power analysis tool for smartphone hardware components. In Proceedings of the 8th IEEE/ACM/IFIP International Conference on Hardware/Software Codesign and System Synthesis. ACM, New York, NY, 353--362. Google ScholarDigital Library
- Jim Keniston, Prasanna S. Panchamukhi, and Masami Hiramatsu. 2011. Kernel Probes. Technical Report. Retrieved October 27, 2014, from https://www.kernel.org/doc/Documentation/kprobes.txt.Google Scholar
- Eamonn Keogh, Jessica Lin, and Ada Fu. 2005. HOT SAX: Efficiently finding the most unusual time series subsequence. In Proceedings of the 5th IEEE International Conference on Data Mining (ICDM’05). IEEE, Los Alamitos, CA, 226--233. Google ScholarDigital Library
- Mikkel Baun Kjaergaard and Henrik Blunck. 2012. Unsupervised power profiling for mobile devices. In Mobile and Ubiquitous Systems: Computing, Networking, and Services. Lecture Notes of the Institute for Computer Sciences, Social Informatics, and Telecommunications Engineering, Vol. 104. Springer, 138--149.Google Scholar
- Mads Lauridsen, Preben Mogensen, and Laurent Noel. 2013. Empirical LTE smartphone power model with DRX operation for system level simulations. In Proceedings of the 2013 IEEE 78th Vehicular Technology Conference (VTC Fall’13). 1--6.Google ScholarCross Ref
- Jingwen Leng, Tayler Hetherington, Ahmed ElTantawy, Syed Gilani, Nam Sung Kim, Tor M. Aamodt, and Vijay Janapa Reddi. 2013. GPUWattch: Enabling energy optimizations in GPGPUs. SIGARCH Computer Architecture News 41, 3, 487--498. Google ScholarDigital Library
- Tao Li and Lizy Kurian John. 2003. Run-time modeling and estimation of operating system power consumption. In Proceedings of the 2003 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems (SIGMETRICS’03). ACM, New York, NY, 160--171. Google ScholarDigital Library
- Xiaohan Ma, Mian Dong, Lin Zhong, and Zhigang Deng. 2009. Statistical power consumption analysis and modeling for GPU-based computing. In Proceedings of the ACM SOSP Workshop on Power Aware Computing and Systems (HotPower’09). ACM, New York, NY.Google Scholar
- Xiao Ma, Peng Huang, Xinxin Jin, Pei Wang, Soyeon Park, Dongcai Shen, Yuanyuan Zhou, Lawrence K. Saul, and Geoffrey M. Voelker. 2013. eDoctor: Automatically diagnosing abnormal battery drain issues on smartphones. In Proceedings of the 10th USENIX Conference on Networked Systems Design and Implementation. 57--70. Google ScholarDigital Library
- Aravind Machiry, Rohan Tahiliani, and Mayur Naik. 2013. Dynodroid: An input generation system for Android apps. In Proceedings of the 2013 9th Joint Meeting on Foundations of Software Engineering (ESEC/FSE’13). ACM, New York, NY, 224--234. Google ScholarDigital Library
- Frank Maker, Rajeevan Amirtharajah, and Venkatesh Akella. 2013. Update rate tradeoffs for improving online power modeling in smartphones. In Proceedings of the 2013 IEEE International Symposium on Low Power Electronics and Design (ISLPED’13). IEEE, Los Alamitos, CA, 114--119. Google ScholarDigital Library
- Maxim. 2014a. MAX17047/MAX17050, ModelGauge m3 Fuel Gauge. Technical Report. Retrieved November 9, 2015, from http://datasheets.maximintegrated.com/en/ds/MAX17047-MAX17050.pdf.Google Scholar
- Maxim. 2014b. MAX17048/MAX17049, Micropower 1-Cell/2-Cell Li+ ModelGauge ICs. Technical Report. Retrieved November 9, 2015, from http://datasheets.maximintegrated.com/en/ds/MAX17048-MAX17049.pdf.Google Scholar
- John C. McCullough, Yuvraj Agarwal, Jaideep Chandrashekar, Sathyanarayan Kuppuswamy, Alex C. Snoeren, and Rajesh K. Gupta. 2011. Evaluating the effectiveness of model-based power characterization. In Proceedings of the 2011 USENIX Annual Technical Conference (USENIXATC’11). 12. Google ScholarDigital Library
- Microsoft. 2010. Nokia Energy Profiler. Retrieved December 15, 2014, from http://developer.nokia.com/community/discussion/showthread.php/160912-Nokia-Energy-Profiler/page8.Google Scholar
- Monsoon. 2014. Power Monitor. Retrieved November 9, 2015, from https://www.msoon.com/LabEquipment/PowerMonitor/.Google Scholar
- Hitoshi Nagasaka, Naoya Maruyama, Akira Nukada, Toshio Endo, and Satoshi Matsuoka. 2010. Statistical power modeling of GPU kernels using performance counters. In Proceedings of the International Conference on Green Computing (GREENCOMP’10). IEEE, Los Alamitoa, CA, 115--122. Google ScholarDigital Library
- Adam J. Oliner, Anand P. Iyer, Ion Stoica, Eemil Lagerspetz, and Sasu Tarkoma. 2013. Carat: Collaborative energy diagnosis for mobile devices. In Proceedings of the 11th ACM Conference on Embedded Networked Sensor Systems. ACM, New York, NY, Article No. 10. Google ScholarDigital Library
- OpenBinder. 2005. Binder Overview. Retrieved November 9, 2015, from http://www.angryredplanet.com/ hackbod/openbinder/docs/html/BinderOverview.html.Google Scholar
- Abhinav Pathak, Y. Charlie Hu, and Ming Zhang. 2011. Bootstrapping energy debugging on smartphones: A first look at energy bugs in mobile devices. In Proceedings of the 10th ACM Workshop on Hot Topics in Networks (HotNets-X). ACM, New York, NY, Article No. 5. Google ScholarDigital Library
- Abhinav Pathak, Y. Charlie Hu, and Ming Zhang. 2012. Where is the energy spent inside my app? Fine grained energy accounting on smartphones with Eprof. In Proceedings of the 7th ACM European Conference on Computer Systems. ACM, New York, NY, 29--42. Google ScholarDigital Library
- Abhinav Pathak, Y. Charlie Hu, Ming Zhang, Paramvir Bahl, and Yi-Min Wang. 2011. Fine-grained power modeling for smartphones using system call tracing. In Proceedings of the 6th Conference on Computer Systems. ACM, New York, NY, 153--168. Google ScholarDigital Library
- Ge Peng, Gang Zhou, David T. Nguyen, and Xin Qi. 2015. All or none? The dilemma of handling WiFi broadcast traffic in smartphone suspend mode. In Proceedings of the 2015 IEEE INFOCOM (INFOCOM’15). IEEE, Los Alamitos, CA, 9.Google ScholarCross Ref
- PowerTutor. 2009. PowerTutor: A Power Monitor for Android-Based Mobile Platforms. Retrieved November 9, 2015, from http://ziyang.eecs.umich.edu/projects/powertutor/documentation.html.Google Scholar
- Feng Qian, Zhaoguang Wang, Alexandre Gerber, Zhuoqing Mao, Subhabrata Sen, and Oliver Spatscheck. 2011. Profiling resource usage for mobile applications: A cross-layer approach. In Proceedings of the 9th International Conference on Mobile Systems, Applications, and Services (MobiSys’11). ACM, New York, NY, 321--334. Google ScholarDigital Library
- Qualcomm. 2014a. MDP Power Rail. (2014). Retrieved November 15, 2014, from https://developer.qualcomm.com/forum/qdn-forums/increase-app-performance/trepn-profiler/27700.Google Scholar
- Qualcomm. 2014b. Trepn Profiler. Retrieved June 11, 2014, from https://developer.qualcomm.com/trepn-profiler.Google Scholar
- Swaminathan Vasanth Rajaraman, Matti Siekkinen, and Mohammad Hoque. 2014. Energy consumption anatomy of live video streaming from a smartphone. In Proceedings of the 25th IEEE International Symposium on Personal, Indoor, and Mobile Radio Communications. (PIMRC’14). IEEE, Los Alamitos, CA.Google ScholarCross Ref
- Santhosh Kumar Rethinagiri, Oscar Palomar, Rabie Ben Atitallah, Smail Niar, Osman Unsal, and Adrian Cristal Kestelman. 2014. System-level power estimation tool for embedded processor based platforms. In Proceedings of the 6th Workshop on Rapid Simulation and Performance Evaluation: Methods and Tools (RAPIDO’14). ACM, New York, NY, Article No. 5. Google ScholarDigital Library
- Seyed Mohammad Rezvanizaniani, Zongchang Liu, Yan Chen, and Jay Lee. 2014. Review and recent advances in battery health monitoring and prognostics technologies for electric vehicle (EV) safety and mobility. Journal of Power Sources 256, 110--124.Google ScholarCross Ref
- Thorsten Schreiber. 2011. Android Binder: Android Interprocess Communication. Retrieved November 9, 2015, from https://www.nds.rub.de/media/attachments/files/2011/10/main.pdf.Google Scholar
- Aaron Schulman, Thomas Schmid, Prabal Dutta, and Neil Spring. 2011. Demo: Phone Power Monitoring with BattOr. Retrieved November 9, 2015, from http://www.web.stanford.edu/∼aschulm/docs/mobicom11-phone-powermonitor-demo.pdf.Google Scholar
- Donghwa Shin, Kitae Kim, Naehyuck Chang, Woojoo Lee, Yanzhi Wang, Qing Xie, and Massoud Pedram. 2013. Online estimation of the remaining energy capacity in mobile systems considering system-wide power consumption and battery characteristics. In Proceedings of the 2013 18th Asia and South Pacific Design Automation Conference (ASP-DAC’13). IEEE, Los Alamitos, CA, 59--64.Google Scholar
- Alex Shye, Benjamin Scholbrock, and Gokhan Memik. 2009. Into the wild: Studying real user activity patterns to guide power optimizations for mobile architectures. In Proceedings of the 42nd Annual IEEE/ACM International Symposium on Microarchitecture. ACM, New York, NY, 168--178. Google ScholarDigital Library
- Matti Siekkinen, Mohammad A. Hoque, Jukka K. Nurminen, and Mika Aalto. 2013. Streaming over 3G and LTE: How to save smartphone energy in radio access network-friendly way. In Proceedings of the 5th ACM Workshop on Mobile Video (MoVid’13). ACM, New York, NY. Google ScholarDigital Library
- Karan Singh, Major Bhadauria, and Sally A. McKee. 2009. Real time power estimation and thread scheduling via performance counters. SIGARCH Computer Architecture News 37, 2, 46--55. Google ScholarDigital Library
- Lindsay I. Smith. 2002. A Tutorial on Principle Components Analysis. Retrieved November 9, 2015, from http://www.cs.otago.ac.nz/cosc453/student_tutorials/principal_components.pdf.Google Scholar
- Texas Instruments. 1999. Understanding Data Converters. Technical Report. Retrieved November 9, 2015, from http://www.ti.com/lit/an/slaa013/slaa013.pdf.Google Scholar
- Kuen Hung Tsoi and Wayne Luk. 2011. Power profiling and optimization for heterogeneous multi-core systems. SIGARCH Computer Architecture News 39, 4, 8--13. Google ScholarDigital Library
- Bogdan Marius Tudor and Yong Meng Teo. 2013. On understanding the energy consumption of arm-based multicore servers. SIGMETRICS Performance Evaluation Review 41, 1, 267--278. Google ScholarDigital Library
- Narseo Vallina-Rodriguez, Andrius Auçinas, Mario Almeida, Yan Grunenberger, Konstantina Papagiannaki, and Jon Crowcroft. 2013. RILAnalyzer: A comprehensive 3G monitor on your phone. In Proceedings of the 2013 Internet Measurement Conference (IMC’13). ACM, New York, NY, 257--264. Google ScholarDigital Library
- Narseo Vallina-Rodriguez and Jon Crowcroft. 2013. Energy management techniques in modern mobile handsets. IEEE Communications Surveys Tutorials 15, 1, 179--198.Google ScholarCross Ref
- Yu Xiao, Rijubrata Bhaumik, Zhirong Yang, Matti Siekkinen, Petri Savolainen, and Antti Yla-Jaaski. 2010. A system-level model for runtime power estimation on mobile devices. In Proceedings of the 2010 IEEE/ACM International Conference on Green Computing and Communications & International Conference on Cyber, Physical, and Social Computing (GREENCOM-CPSCOM’’10). IEEE, Los Alamitos, CA, 27--34. Google ScholarDigital Library
- Yu Xiao, Yong Cui, Petri Savolainen, Matti Siekkinen, An Wang, Liu Yang, Antti Yla-Jaaski, and Sasu Tarkoma. 2014. Modeling energy consumption of data transmission over Wi-Fi. IEEE Transactions on Mobile Computing 13, 8, 1760--1773.Google ScholarCross Ref
- Fengyuan Xu, Yunxin Liu, Qun Li, and Yongguang Zhang. 2013. V-edge: Fast self-constructive power modeling of smartphones based on battery voltage dynamics. In Proceedings of the 10th USENIX Conference on Networked Systems Design and Implementation (NSDI’13). 43--56. Google ScholarDigital Library
- Chanmin Yoon, Dongwon Kim, Wonwoo Jung, Chulkoo Kang, and Hojung Cha. 2012. AppScope: Application energy metering framework for Android smartphones using kernel activity monitoring. In Proceedings of the 2012 USENIX Annual Technical Conference (USENIX ATC’12). 36. Google ScholarDigital Library
- Lide Zhang, Birjodh Tiwana, Zhiyun Qian, Zhaoguang Wang, Robert P. Dick, Zhuoqing Morley Mao, and Lei Yang. 2010. Accurate online power estimation and automatic battery behavior based power model generation for smartphones. In Proceedings of the 8th IEEE/ACM/IFIP International Conference on Hardware/Software Codesign and System Synthesis. ACM, New York, NY, 105--114. Google ScholarDigital Library
- Yifan Zhang, Xudong Wang, Xuanzhe Liu, Yunxin Liu, Li Zhuang, and Feng Zhao. 2013. Towards better CPU power management on multicore smartphones. In Proceedings of the Workshop on Power-Aware Computing and Systems (HotPower’13). ACM, New York, NY, Article No. 11. Google ScholarDigital Library
Index Terms
- Modeling, Profiling, and Debugging the Energy Consumption of Mobile Devices
Recommendations
Energy profiling using IgProf
CCGRID '15: Proceedings of the 15th IEEE/ACM International Symposium on Cluster, Cloud, and Grid ComputingEnergy efficiency has become a primary concern for data centers in recent years. Understanding where the energy has been spent within a software is fundamental for energy-efficiency study as a whole. In this paper, we take the first step towards this ...
Profiling Software for Energy Consumption
GREENCOM '12: Proceedings of the 2012 IEEE International Conference on Green Computing and CommunicationsThe amount of energy consumed by computer systems can be lowered through the use of more efficient algorithms and software. Unfortunately, software developers lack the tools to pinpoint energy-hungry sections in their code and therefore have to rely on ...
Detect and optimize the energy consumption of mobile app through static analysis: an initial research
Internetware '12: Proceedings of the Fourth Asia-Pacific Symposium on InternetwareAlthough the market for smartphones is growing rapidly, their utility remains severely limited by the battery life. As such, much research effort has been made to understand the power consumption of the application running on mobile devices. However, ...
Comments