A. Raja-wasim-ahmad, S. Gani, F. Hamid, M. Xia, and . Shiraz, A Review on mobile application energy profiling: Taxonomy, state-of-the-art, and open research issues, J. Netw. Comput. Appl, vol.58, pp.42-59, 2015.

A. Shaiful, A. Chowdhury, and . Hindle, GreenOracle: Estimating Software Energy Consumption with Energy Measurement Corpora, Proc. 13th, 2016.

. Int, . Work, and . Min, Softw. Repos.-MSR '16, pp.49-60

D. Di-nucci, F. Palomba, A. Prota, A. Panichella, A. Zaidman et al., PETrA: A Software-Based Tool for Estimating the Energy Profile of Android Applications, IEEE/ACM 39th Int. Conf. Softw. Eng. Companion. IEEE, 2017.

D. Di-nucci, F. Palomba, A. Prota, A. Panichella, A. Zaidman et al., Software-based energy profiling of Android apps: Simple, efficient and reliable, SANER 2017-24th IEEE Int, vol.15, pp.103-114, 2017.

O. Djedidi, M. A. Djeziri, K. Nacer, A. M'sirdi, and . Naamane, Modular Modelling of an Embedded Mobile CPU-GPU Chip for Feature Estimation, Proc. 14th Int. Conf. Informatics Control, vol.1, pp.338-345, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01770233

O. Djedidi, . Mohand-arab-djeziri, K. Nacer, A. Sirdi, and . Naamane, A Novel Easy-to-Construct Power Model for Embedded and Mobile System, Proc. 15th Int. Conf. Informatics Control. Autom. Robot. (ICINCO 2018), vol.1, pp.541-545, 2018.

M. Mohammad-ashraful-hoque, . Siekkinen, Y. Kashif-nizam-khan, S. Xiao, and . Tarkoma, Modeling, Profiling, and Debugging the Energy Consumption of Mobile Devices, ACM Comput. Surv, vol.48, pp.1-40, 2015.

K. Kim, D. Shin, Q. Xie, Y. Wang, M. Pedram et al., FEPMA: Fine-Grained Event-Driven Power Meter for Android Smartphones Based on Device Driver Layer Event Monitoring, 2014.

. T. Autom and . Eur, Conf. Exhib. IEEE Conference Publications

E. Ying-dar-lin, Y. Rattagan, L. P. Lai, Y. Chang, . Chien-yo et al., Calibrating parameters and formulas for process-level energy consumption profiling in smartphones, J. Netw. Comput. Appl, vol.44, pp.106-119, 2014.

R. Mittal, A. Kansal, and R. Chandra, Empowering developers to estimate app energy consumption, Proc. 18th Annu. Int. Conf. Mob. Comput. Netw.-Mobicom '12, 2012.

E. Rattagan, T. H. Edward, Y. D. Chu, Y. Lin, and . Lai, Semi-online power estimation for smartphone hardware components, 10th IEEE Int. Symp. Ind. Embed. Syst. SIES 2015-Proc. IEEE, pp.174-177, 2015.

R. Narendra-kumar-shukla, S. Pila, and . Rawat, Utilizationbased power consumption profiling in smartphones, Proc. 2016 2nd Int. Conf. Contemp. Comput. Informatics, IC3I 2016, pp.881-886, 2016.

M. J. Walker, S. Diestelhorst, A. Hansson, A. K. Das, S. Yang et al., Accurate and Stable Run-Time Power Modeling for Mobile and Embedded CPUs, IEEE Trans. Comput. Des. Integr. Circuits Syst, vol.36, issue.1, pp.106-119, 2017.

H. Xie, H. Tang, and Y. Liao, Time series prediction based on narx neural networks: An advanced approach, Proc. 2009 Int. Conf, vol.3, pp.1275-1279, 2009.

L. Zhang, B. Tiwana, Z. Qian, Z. Wang, R. P. Dick et al., Accurate online power estimation and automatic battery behavior based power model generation for smartphones, Proc. eighth IEEE/ACM/IFIP Int. Conf. Hardware/software codesign Syst. Synth.CODES/ISSS '10, p.105, 2010.