On Power and Energy Consumption Modeling for Smart Mobile Devices

In nowadays life, mobile phones are becoming a cheaper and smaller alternative to laptops for simple, everyday tasks. They experienced an astonishing growth in functionalities and, because of their constant presence in our life, mobile phones became fundamental for the interaction with information coming from the environment. Nevertheless, their resources are limited, both in terms of performance and power, and their availability can greatly vary over time. Especially when dealing with power consumption, mobile devices cannot disregard environment conditions and user habits. Both internal and external conditions are rapidly changing and may influence the response of the entire system, e.g., switching between network types may causes an unpredictable power consumption. In order to puzzle out all these issues, we regard the definition of a power/energy model for mobile devices as a first mandatory step. In literature, several attempts to do so are present, basing their approaches on techniques coming from different computer science fields. They differ in the way they consider hardware components, in the operating system they are suitable for and in the scope of their tests and experiments. Within this paper, we categorize techniques presented in the major works in the field, in order to be able to compare different methods, highlight open issues and give suggestions on future works.

[1]  Lei Liu,et al.  VirusMeter: Preventing Your Cellphone from Spies , 2009, RAID.

[2]  James Won-Ki Hong,et al.  Usage pattern analysis of smartphones , 2011, 2011 13th Asia-Pacific Network Operations and Management Symposium.

[3]  Gokhan Memik,et al.  Into the wild: Studying real user activity patterns to guide power optimizations for mobile architectures , 2009, 2009 42nd Annual IEEE/ACM International Symposium on Microarchitecture (MICRO).

[4]  Xia Zhao,et al.  A system context-aware approach for battery lifetime prediction in smart phones , 2011, SAC '11.

[5]  Konstantina Papagiannaki,et al.  Catnap: exploiting high bandwidth wireless interfaces to save energy for mobile devices , 2010, MobiSys '10.

[6]  Deborah Estrin,et al.  A first look at traffic on smartphones , 2010, IMC '10.

[7]  Narseo Vallina-Rodriguez,et al.  Energy Management Techniques in Modern Mobile Handsets , 2013, IEEE Communications Surveys & Tutorials.

[8]  Liviu Iftode,et al.  Context-aware Battery Management for Mobile Phones , 2008, 2008 Sixth Annual IEEE International Conference on Pervasive Computing and Communications (PerCom).

[9]  Matti Siekkinen,et al.  A System-Level Model for Runtime Power Estimation on Mobile Devices , 2010, 2010 IEEE/ACM Int'l Conference on Green Computing and Communications & Int'l Conference on Cyber, Physical and Social Computing.

[10]  Cecilia Mascolo The Power of Mobile Computing in a Social Era , 2010, IEEE Internet Computing.

[11]  Hyungshin Kim,et al.  Smart phone power model generation using use pattern analysis , 2012, 2012 IEEE International Conference on Consumer Electronics (ICCE).

[12]  Narseo Vallina-Rodriguez,et al.  Exhausting battery statistics: understanding the energy demands on mobile handsets , 2010, MobiHeld '10.

[13]  Mikkel Baun Kjærgaard,et al.  Unsupervised Power Profiling for Mobile Devices , 2011, MobiQuitous.

[14]  Philip Levis,et al.  Energy management in mobile devices with the cinder operating system , 2011, EuroSys '11.

[15]  Gernot Heiser,et al.  An Analysis of Power Consumption in a Smartphone , 2010, USENIX Annual Technical Conference.

[16]  Marco D. Santambrogio,et al.  A Framework for Thermal and Performance Management , 2012, MAD.

[17]  Matti Siekkinen,et al.  Practical power modeling of data transmission over 802.11g for wireless applications , 2010, e-Energy.

[18]  Arun Venkataramani,et al.  Energy consumption in mobile phones: a measurement study and implications for network applications , 2009, IMC '09.

[19]  Simon Hay,et al.  Decomposing power measurements for mobile devices , 2010, 2010 IEEE International Conference on Pervasive Computing and Communications (PerCom).

[20]  Chandra Krintz,et al.  A run-time, feedback-based energy estimation model For embedded devices , 2006, Proceedings of the 4th International Conference on Hardware/Software Codesign and System Synthesis (CODES+ISSS '06).

[21]  James Won-Ki Hong,et al.  Personalized Battery Lifetime Prediction for Mobile Devices based on Usage Patterns , 2011, J. Comput. Sci. Eng..

[22]  Lin Zhong,et al.  Self-constructive high-rate system energy modeling for battery-powered mobile systems , 2011, MobiSys '11.

[23]  Paramvir Bahl,et al.  Fine-grained power modeling for smartphones using system call tracing , 2011, EuroSys '11.

[24]  A. Agarwal,et al.  Control-theoretical CPU allocation : Design and Implementation with Feedback Control , 2011 .

[25]  Henry Hoffmann,et al.  Power Optimization in Embedded Systems via Feedback Control of Resource Allocation , 2013, IEEE Transactions on Control Systems Technology.

[26]  Mahadev Satyanarayanan,et al.  Managing battery lifetime with energy-aware adaptation , 2004, TOCS.

[27]  Douglas C. Schmidt,et al.  Analyzing Mobile Application Software Power Consumption via Model-driven Engineering , 2011, PECCS.

[28]  Jason Flinn,et al.  Ghosts in the machine: interfaces for better power management , 2004, MobiSys '04.

[29]  Deborah Estrin,et al.  Diversity in smartphone usage , 2010, MobiSys '10.

[30]  Narseo Vallina-Rodriguez,et al.  ErdOS: achieving energy savings in mobile OS , 2011, MobiArch '11.

[31]  Chandra Krintz,et al.  Online Prediction of Battery Lifetime for Embedded and Mobile Devices , 2003, PACS.

[32]  Lei Yang,et al.  Accurate online power estimation and automatic battery behavior based power model generation for smartphones , 2010, 2010 IEEE/ACM/IFIP International Conference on Hardware/Software Codesign and System Synthesis (CODES+ISSS).