Abstract
The limited battery life of the modern mobile devices is one of the key problems limiting their usage. The offloading of computation on cloud computing platforms can considerably extend the battery duration. However, it is really hard not only to evaluate the cases in which the offloading guarantees real advantages on the basis of the requirements of application in terms of data transfer, computing power needed, etc., but also to evaluate if user requirements (i.e. the costs of using the clouds, a determined QoS required, etc.) are satisfied. To this aim, in this work it is presented a framework for generating models for taking automatic decisions on the offloading of mobile applications using a genetic programming (GP) approach. The GP system is designed using a taxonomy of the properties useful to the offloading process concerning the user, the network, the data and the application. Finally, the fitness function adopted permits to give different weights to the four categories considered during the process of building the model.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Abowd, G.D., Dey, A.K.: Towards a Better Understanding of Context and Context-Awareness. In: Gellersen, H.-W. (ed.) HUC 1999. LNCS, vol. 1707, pp. 304–307. Springer, Heidelberg (1999)
Buyya, R., Yeo, C.S., Venugopal, S., Broberg, J., Brandic, I.: Cloud computing and emerging it platforms: Vision, hype, and reality for delivering computing as the 5th utility. Future Gener. Comput. Syst. 25(6), 599–616 (2009)
Flinn, J., Park, S., Satyanarayanan, M.: Balancing performance, energy, and quality in pervasive computing. In: ICDCS, pp. 217–226 (2002)
Folino, G., Pizzuti, C., Spezzano, G.: A scalable cellular implementation of parallel genetic programming. IEEE Transaction on Evolutionary Computation 7(1), 37–53 (2003)
Gu, X., Nahrstedt, K., Messer, A., Greenberg, I., Milojicic, D.S.: Adaptive offloading inference for delivering applications in pervasive computing environments. In: Proceedings of the First IEEE International Conference on Pervasive Computing and Communications (PerCom 2003), Fort Worth, Texas, USA, March 23-26, pp. 107–114 (2003)
Gurun, S., Krintz, C.: Addressing the energy crisis in mobile computing with developing power aware software. In: UCSB Technical Report. UCSB Computer Science Department (2003)
Kumar, K., Lu, Y.-H.: Cloud computing for mobile users: Can offloading computation save energy? IEEE Computer 43(4), 51–56 (2010)
Lee, K., Rhee, I., Lee, J., Chong, S., Yi, Y.: Mobile data offloading: how much can wifi deliver? In: CoNEXT 2010, Philadelphia, PA, USA, November 30 - December 03, p. 26. ACM (2010)
Liu, J., Kumar, K., Lu, Y.-H.: Tradeoff between energy savings and privacy protection in computation offloading. In: Proceedings of the 2010 International Symposium on Low Power Electronics and Design, Austin, Texas, USA, August 18- 20, pp. 213–218. ACM (2010)
Miettinen, A.P., Nurminen, J.K.: Energy efficiency of mobile clients in cloud computing. In: Proceedings of the 2nd USENIX Conference on Hot Topics in Cloud Computing, HotCloud 2010, USENIX Association, Berkeley (2010)
Namboodiri, V., Ghose, T.: To cloud or not to cloud: A mobile device perspective on energy consumption of applications. In: WOWMOM, pp. 1–9 (2012)
Ortiz, A., Ortega, J., Díaz, A.F., Prieto, A.: Modeling network behaviour by full-system simulation. JSW 2(2), 11–18 (2007)
Pathak, A., Hu, Y.C., Zhang, M., Bahl, P., Wang, Y.-M.: Enabling automatic offloading of resource-intensive smartphone applications. Technical report, Purdue University (2011)
Saarinen, A., Siekkinen, M., Xiao, Y., Nurminen, J.K., Kemppainen, M., Hui, P.: Offloadable apps using smartdiet: Towards an analysis toolkit for mobile application developers. CoRR, abs/1111.3806 (2011)
Wolski, R., Gurun, S., Krintz, C., Nurmi, D.: Using bandwidth data to make computation offloading decisions. In: 22nd IEEE International Symposium on Parallel and Distributed Processing, IPDPS 2008, Miami, Florida, USA, April 14-18, pp. 1–8. IEEE (2008)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Folino, G., Pisani, F.S. (2013). A Framework for Modeling Automatic Offloading of Mobile Applications Using Genetic Programming. In: Esparcia-Alcázar, A.I. (eds) Applications of Evolutionary Computation. EvoApplications 2013. Lecture Notes in Computer Science, vol 7835. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37192-9_7
Download citation
DOI: https://doi.org/10.1007/978-3-642-37192-9_7
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-37191-2
Online ISBN: 978-3-642-37192-9
eBook Packages: Computer ScienceComputer Science (R0)