D. Chaffey, Mobile marketing statistics 2016, 2016.

X. Ma, Characterizing the Performance and Power Consumption of 3D Mobile Games, Computer, vol.46, issue.4, pp.76-82, 2013.
DOI : 10.1109/MC.2012.190

Y. Mao, J. Zhang, and K. B. Letaief, Dynamic Computation Offloading for Mobile-Edge Computing With Energy Harvesting Devices, IEEE Journal on Selected Areas in Communications, vol.34, issue.12, pp.3590-3605, 2016.
DOI : 10.1109/JSAC.2016.2611964

URL : http://arxiv.org/pdf/1605.05488

R. Kemp, Cuckoo: A Computation Offloading Framework for Smartphones, Mobile Computing, Applications, and Services, pp.59-79
DOI : 10.1109/MPRV.2005.9

E. Cuervo, MAUI, Proceedings of the 8th international conference on Mobile systems, applications, and services, MobiSys '10, 2010.
DOI : 10.1145/1814433.1814441

A. Pamboris, Mobile Code Offloading for Multiple Resources, 2014.

M. Etsi, Mobile-Edge Computing, 2014.

B. Chun, CloneCloud, Proceedings of the sixth conference on Computer systems, EuroSys '11, 2011.
DOI : 10.1145/1966445.1966473

C. Shi, COSMOS, Proceedings of the 15th ACM international symposium on Mobile ad hoc networking and computing, MobiHoc '14, 2014.
DOI : 10.1145/2632951.2632958

S. Kosta, ThinkAir: Dynamic resource allocation and parallel execution in the cloud for mobile code offloading, 2012 Proceedings IEEE INFOCOM
DOI : 10.1109/INFCOM.2012.6195845

J. L. Neto, D. F. Macedo, and J. M. Nogueira, Location aware decision engine to offload mobile computation to the cloud, NOMS 2016, 2016 IEEE/IFIP Network Operations and Management Symposium, 2016.
DOI : 10.1109/NOMS.2016.7502856

T. Verbelen, P. Simoens, F. D. Turck, and B. Dhoedt, AIOLOS: Middleware for improving mobile application performance through cyber foraging, Journal of Systems and Software, vol.85, issue.11, pp.2629-2639, 2012.
DOI : 10.1016/j.jss.2012.06.011

R. Esteves, M. Mccool, and C. Lemieux, Real options for mobile communication management, 2011 IEEE GLOBECOM Workshops (GC Wkshps)
DOI : 10.1109/GLOCOMW.2011.6162380

M. Kristensen, Scavenger: Transparent development of efficient cyber foraging applications, 2010 IEEE International Conference on Pervasive Computing and Communications (PerCom), 2010.
DOI : 10.1109/PERCOM.2010.5466972

A. Pathak, Y. C. Hu, and M. Zhang, Where is the energy spent inside my app?, Proceedings of the 7th ACM european conference on Computer Systems, EuroSys '12
DOI : 10.1145/2168836.2168841

S. Hao, Estimating mobile application energy consumption using program analysis, 2013 35th International Conference on Software Engineering (ICSE)
DOI : 10.1109/ICSE.2013.6606555

URL : http://www-bcf.usc.edu/%7Ehalfond/papers/hao13icse.pdf

L. Zhang, 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
DOI : 10.1145/1878961.1878982

A. P. Miettinen and J. K. Nurminen, Energy Efficiency of Mobile Clients in Cloud Computing, USENIX HotCloud, 2010.

R. Vallée-rai, Soot -a Java Bytecode Optimization Framework

. Fig, 18. Power consumption experimental distribution for different traffic loads and network interfaces

P. Hudak, Conception, evolution, and application of functional programming languages, ACM Computing Surveys, vol.21, issue.3, pp.359-411, 1989.
DOI : 10.1145/72551.72554

H. Akima, A New Method of Interpolation and Smooth Curve Fitting Based on Local Procedures, Journal of the ACM, vol.17, issue.4, pp.589-602, 1970.
DOI : 10.1145/321607.321609

G. Wolberg and I. Alfy, Monotonic cubic spline interpolation, Computer Graphics International, 1999.

J. Leskovec and R. Sosi?, SNAP, ACM Transactions on Intelligent Systems and Technology, vol.8, issue.1, 2016.
DOI : 10.1145/2556195.2556243

H. Jiang, Understanding bufferbloat in cellular networks, Proceedings of the 2012 ACM SIGCOMM workshop on Cellular networks: operations, challenges, and future design, CellNet '12
DOI : 10.1145/2342468.2342470

S. Secci, P. Raad, and P. Gallard, Linking Virtual Machine Mobility to User Mobility, IEEE Transactions on Network and Service Management, vol.13, issue.4, pp.927-940, 2016.
DOI : 10.1109/TNSM.2016.2592241

URL : https://hal.archives-ouvertes.fr/hal-01345678

T. J. Mccabe, A Complexity Measure, IEEE Transactions on Software Engineering, vol.2, issue.4, pp.308-320, 1976.
DOI : 10.1109/TSE.1976.233837

M. Shepperd, A critique of cyclomatic complexity as a software metric, Software Engineering Journal, vol.3, issue.2, pp.30-36, 1988.
DOI : 10.1049/sej.1988.0003

V. Paxson and M. Allman, Computing TCP's Retransmission Timer, RFC Editor, 2000.
DOI : 10.17487/rfc6298

URL : http://ietfreport.isoc.org/cgi-bin/id2pdf?f1=draft-paxson-tcp-rto-00.txt

L. Corral, A method for characterizing energy consumption in Android smartphones, 2013 2nd International Workshop on Green and Sustainable Software (GREENS)
DOI : 10.1109/GREENS.2013.6606420

A. Zanni, Automated selection of offloadable tasks for mobile computation offloading in edge computing, 2017 13th International Conference on Network and Service Management (CNSM)
DOI : 10.23919/CNSM.2017.8256026

URL : https://hal.archives-ouvertes.fr/hal-01672750

P. Mach and Z. Becvar, Mobile Edge Computing: A Survey on Architecture and Computation Offloading, IEEE Communications Surveys & Tutorials, vol.19, issue.3, pp.1628-1656, 2017.
DOI : 10.1109/COMST.2017.2682318

C. Wang, Computation Offloading and Resource Allocation in Wireless Cellular Networks With Mobile Edge Computing, IEEE Transactions on Wireless Communications, vol.16, issue.8, pp.4924-4938, 2017.
DOI : 10.1109/TWC.2017.2703901

C. Wang, F. R. Yu, C. Liang, Q. Chen, and L. Tang, Joint Computation Offloading and Interference Management in Wireless Cellular Networks with Mobile Edge Computing, IEEE Transactions on Vehicular Technology, vol.66, issue.8, pp.7432-7445, 2017.
DOI : 10.1109/TVT.2017.2672701

F. Wang, J. Xu, X. Wang, C. , and S. , Joint offloading and computing optimization in wireless powered mobile-edge computing systems, 2017.

T. Q. Dinh, Offloading in Mobile Edge Computing: Task Allocation and Computational Frequency Scaling, IEEE Trans. on Communications, vol.65, issue.8, pp.3571-3584, 2017.

Z. Chen, An empirical study of latency in an emerging class of edge computing applications for wearable cognitive assistance, Proceedings of the Second ACM/IEEE Symposium on Edge Computing , SEC '17
DOI : 10.1007/978-3-319-10590-1_53