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14 - Mobile cloud offloading

from Part III - Advanced energy optimization

Published online by Cambridge University Press:  05 August 2014

Sasu Tarkoma ,
Matti Siekkinen ,
Eemil Lagerspetz  and
Yu Xiao
Sasu Tarkoma
Affiliation:
University of Helsinki
Matti Siekkinen
Affiliation:
Aalto University, Finland
Eemil Lagerspetz
Affiliation:
University of Helsinki
Yu Xiao
Affiliation:
Aalto University, Finland
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Summary

A seemingly straightforward way to conserve the battery life of a mobile device is to migrate application execution partially to a cloud. This technique is called offloading or sometimes cyber foraging. Offloading computationally expensive processing from smartphones onto more powerful servers has been widely discussed in the literature. In this section, we introduce four frameworks (MAUI [1], Think Air [2], Cuckoo [3], and Clone Cloud [4]) that allow mobile applications to dynamically migrate part of their execution from the smartphone to the cloud. These frameworks have been developed to offload CPU-intensive tasks. We call it computation offloading. Note that most popular mobile applications also involve network communications, which in fact consume a significant part of the overall battery life. Hence, it is justified to ask: Can offloading techniques help save energy, if applied to such applications? To answer this question, we also discuss communication offloading, a technique that focuses on reducing communication costs through offloading.

Computation offloading

Offloading computationally expensive processing (such as speech recognition, face recognition, language translation, and 3D modeling) from smartphones onto more powerful servers has proved to be useful for improving performance and energy efficiency. Take face detection as an example: Simoens et al. [5] implemented a video-sharing application in which faces detected from the video captured by mobile devices were first blurred before the video was shared.

Type
Chapter
Information
Smartphone Energy Consumption
Modeling and Optimization
 , pp. 281 - 296
Publisher: Cambridge University Press
Print publication year: 2014

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References

[1] E., Cuervo, A., Balasubramanian, D.-k. Cho, A., Wolman, S., Saroiu, R., Chandra, and P., Bahl, “Maui: making smartphones last longer with code offload,” in Proc. 8th Int. Conf. on Mobile Systems, Applications, and Services (MobiSys'10). New York, NY, USA: ACM, 2010, pp. 49–62.Google Scholar
[2] S., Kosta, A., Aucinas, P., Hui, R., Mortier, and X., Zhang, “ThinkAir: Dynamic resource allocation and parallel execution in the cloud for mobile code offloading,” in Proc. IEEE INFOCOM, 2012, 2012, pp. 945–953.Google Scholar
[3] R., Kemp, N., Palmer, T., Kielmann, and H., Bal, “Cuckoo: A computation offloading frame¬work for smartphones,” in Proc. 2nd Int. ICST Conf. Mobile Computing, Applications, and Services, MobiCASE 2010, 2012.Google Scholar
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[5] P., Simoens, Y., Xiao, P., Pillai, Z., Chen, K., Ha, and M., Satyanarayanan, “Scalable crowd- sourcing of video from mobile devices,” in Proc. 11th Annu. Int. Conf. on Mobile Systems, Applications, and Services. New York, NY, USA: ACM, 2013, pp. 139–152. [Online]. Available: http://doi.acm.org/10.1145/2462456.2464440Google Scholar
[6] A., Saarinen, M., Siekkinen, Y., Xiao, J. K., Nurminen, M., Kemppainen, and P., Hui, “Can offloading save energy for popular apps?” in Proc. 7th ACM Int. Workshop on Mobility in the Evolving Internet Architecture. New York, NY, USA: ACM, 2012, pp. 3–10. [Online]. Available: http://doi.acm.org/10.1145/2348676.2348680Google Scholar
[7] A., Saarinen, M., Siekkinen, Y., Xiao, J. K., Nurminen, M., Kemppainen, and P., Hui, “Offload-able apps using SmartDiet: Towards an analysis toolkit for mobile application developers,” CoRR, vol. abs/1111.3806, 2011.Google Scholar
[8] Y., Xiao, Y., Cui, P., Savolainen, M., Siekkinen, A., Wang, L., Yang, A., Yla-Jaaski, and S., Tarkoma, “Modeling energy consumption of data transmission over Wi-Fi,” IEEE Trans. on Mobile Computing, vol. 99, no. PrePrints, 2013.Google Scholar
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[10] Y., Xiao, P., Simoens, P., Pillai, K., Ha, and M., Satyanarayanan, “Lowering the barriers to large-scale mobile crowdsensing,” in Proc. 14th Workshop on Mobile Computing Systems and Applications. New York, NY, USA: ACM, 2013, pp. 9:1–9:6. [Online]. Available: http: //doi. acm.org/10.1145/2444776.2444789Google Scholar

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