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MAMoC-Android : Multisite Adaptive Computation Offloading for Android applications

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MAMoC_Android_Final_Version.pdf (335.0Kb)
Date
13/05/2019
Author
Sulaiman, Dawand Jalil
Barker, Adam David
Keywords
Mobile Clouds
Multisite offloading
Adaptive offloading
Android apps
Android offloading
QA75 Electronic computers. Computer science
T Technology
Computer Science Applications
NDAS
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Abstract
Computational offloading has been widely used to improve the performance of mobile applications and conserve the energy of mobile devices. Prior studies have primarily focused on a form of offloading where only a single server is considered as the offloading site. However, mobile devices now have access to a range of nearby mobile and fixed devices and multiple cloud providers. This paper proposes a method for multisite computation offloading in dynamic mobile cloud environments, in order to save energy and improve application execution time. Our proposed dynamic offloading decision algorithm takes into consideration the offloading score and records of past offloading executions to select the best candidate(s) for offloading. Multisite offloading execution achieves a greater reduction with respect to the completion time and energy consumption of mobiles when compared to local execution or a single-site offloading execution on a public cloud instance.
Citation
Sulaiman , D J & Barker , A D 2019 , MAMoC-Android : Multisite Adaptive Computation Offloading for Android applications . in 2019 7th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud) . IEEE Computer Society , pp. 68-75 , 2019 7th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering , San Fransisco , United States , 4/04/19 . https://doi.org/10.1109/MobileCloud.2019.00017
 
conference
 
Publication
2019 7th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud)
DOI
https://doi.org/10.1109/MobileCloud.2019.00017
Type
Conference item
Rights
© 2019, IEEE. This work has been made available online in accordance with the publisher’s policies. This is the author created, accepted version manuscript following peer review and may differ slightly from the final published version. The final published version of this work is available at https://doi.org/10.1109/MobileCloud.2019.00017
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  • University of St Andrews Research
URI
http://hdl.handle.net/10023/17842

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