A Review on mobile application energy profiling: Taxonomy, state-of-the-art, and open research issues, Journal of Network and Computer Applications, vol.58, pp.42-59, 2015. ,
DOI : 10.1016/j.jnca.2015.09.002
A Computing Profiling Procedure for Mobile Developers to Estimate Energy Cost, Proceedings of the 18th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems, MSWiM '15, pp.301-305, 2015. ,
DOI : 10.1145/1878961.1878982
, ARM Inc. Technologies ? big.LITTLE ? Arm Developer
Detecting energy bugs and hotspots in mobile apps, Proceedings of the 22nd ACM SIGSOFT International Symposium on Foundations of Software Engineering, FSE 2014, pp.588-598, 2014. ,
DOI : 10.1145/2635868.2635871
Seeing the Unseen: Revealing Mobile Malware Hidden Communications via Energy Consumption and Artificial Intelligence, IEEE Transactions on Information Forensics and Security, vol.11, issue.4, pp.799-810, 2016. ,
DOI : 10.1109/TIFS.2015.2510825
URL : https://hal.archives-ouvertes.fr/hal-01247495
GreenOracle, Proceedings of the 13th International Workshop on Mining Software Repositories, MSR '16, pp.49-60, 2016. ,
DOI : 10.1145/1878961.1878982
PETrA: A Software-Based Tool for Estimating the Energy Profile of Android Applications, 2017 IEEE/ACM 39th International Conference on Software Engineering Companion (ICSE-C), pp.3-6, 2017. ,
DOI : 10.1109/ICSE-C.2017.18
Software-based energy profiling of Android apps: Simple, efficient and reliable? In SANER 2017 -24th IEEE Int, Conf. Softw. Anal. Evol. Reengineering, vol.15, pp.103-114, 2017. ,
Modular Modelling of an Embedded Mobile CPU-GPU Chip for Feature Estimation, Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics, 2017. ,
DOI : 10.5220/0006470803380345
URL : https://hal.archives-ouvertes.fr/hal-01770233
, Proc. 14th Int. Conf. Informatics Control, pp.338-345
Self-constructive high-rate system energy modeling for battery-powered mobile systems, Proceedings of the 9th international conference on Mobile systems, applications, and services, MobiSys '11, 2011. ,
DOI : 10.1145/1999995.2000027
Measuring Power Values ? Android Open Source Project, 2017. ,
PowerTutor, 2011. ,
Understanding Application-Battery Interactions on Smartphones: A Large-Scale Empirical Study, IEEE Access, vol.5, pp.13387-13400, 2017. ,
DOI : 10.1109/ACCESS.2017.2728620
, Modeling, Profiling, and Debugging the Energy Consumption of Mobile Devices, 2015.
, ACM Comput. Surv, vol.48, issue.3, pp.1-40
Energy-Efficient Resource Utilization for Heterogeneous Embedded Computing Systems, IEEE Transactions on Computers, vol.66, issue.9, pp.1518-1531, 2017. ,
DOI : 10.1109/TC.2017.2693186
DevScope, Proceedings of the eighth IEEE/ACM/IFIP international conference on Hardware/software codesign and system synthesis, CODES+ISSS '12, p.353, 2012. ,
DOI : 10.1145/2380445.2380502
Accurate Prediction of Available Battery Time for Mobile Applications, ACM Transactions on Embedded Computing Systems, vol.15, issue.3, pp.1-17, 2016. ,
DOI : 10.1145/1982185.1982327
FEPMA: Fine-Grained Event- Driven Power Meter for Android Smartphones Based on Device Driver Layer Event Monitoring, Des. Autom. Test Eur. Conf. Exhib, pp.1-6, 2014. ,
Accurate GPU power estimation for mobile device power profiling, 2013. ,
, Conf. Consum. Electron, pp.183-184
Enhancing online power estimation accuracy for smartphones, IEEE Transactions on Consumer Electronics, vol.58, issue.2, pp.333-339, 2012. ,
DOI : 10.1109/TCE.2012.6227431
A Novel GPU Power Model for Accurate Smartphone Power Breakdown, ETRI Journal, vol.37, issue.1, pp.157-164, 2015. ,
DOI : 10.1145/1966445.1966460
Empowering developers to estimate app energy consumption, Proceedings of the 18th annual international conference on Mobile computing and networking, Mobicom '12, p.317, 2012. ,
DOI : 10.1145/2348543.2348583
Where is the energy spent inside my app?, Proceedings of the 7th ACM european conference on Computer Systems, EuroSys '12, pp.29-42, 2012. ,
DOI : 10.1145/2168836.2168841
, Qualcomm Innovation Center, I. Trepn Profiler -Android Apps on Google Play
Utilizationbased power consumption profiling in smartphones, Proc. 2016 2nd Int. Conf. Contemp. Comput. Informatics , IC3I 2016, pp.881-886, 2016. ,
Into the wild, Proceedings of the 42nd Annual IEEE/ACM International Symposium on Microarchitecture, Micro-42, pp.168-178, 2009. ,
DOI : 10.1145/1669112.1669135
Accurate and Stable Run-Time Power Modeling for Mobile and Embedded CPUs, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, vol.36, issue.1, pp.106-119, 2017. ,
DOI : 10.1109/TCAD.2016.2562920
Time series prediction based on narx neural networks: An advanced approach, Proc. 2009 Int. Conf, pp.1275-1279, 2009. ,
V-edge: fast self-constructive power modeling of smartphones based on battery voltage dynamics, nsdi'13 Proc. 10th USENIX Conf. Networked Syst. Des. Implement, pp.43-55, 2013. ,
Accurate power modeling of modern mobile application processors, Journal of Systems Architecture, vol.81, pp.17-31, 2017. ,
DOI : 10.1016/j.sysarc.2017.10.001
Accurate online power estimation and automatic battery behavior based power model generation for smartphones, Proceedings of the eighth IEEE/ACM/IFIP international conference on Hardware/software codesign and system synthesis, CODES/ISSS '10, p.105, 2010. ,
DOI : 10.1145/1878961.1878982