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Automated Selection of Offloadable Tasks for Mobile Computation Offloading in Edge Computing

Abstract : Mobile computation offloading has recently attracted much interest and first offloading solutions have been developed. However, the relevant technical challenge of how to automatically determine offloadable sections of Android applications has not been adequately investigated so far. This paper proposes an innovative task selection algorithm that can parse an Android application autonomously and classify all the methods based on their offloadability by adopting a fine grained and multi-steps analyzer. The reported experimental results show the effectiveness of our solution when applied to the top 25 most downloaded Android apps on the Google Play store, by showing its accuracy in identifying off loadable methods and demonstrating the potential benefits of automated mobile computation offloading.
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https://hal-upec-upem.archives-ouvertes.fr/hal-01672750
Contributor : Langar Rami <>
Submitted on : Wednesday, December 27, 2017 - 12:25:33 AM
Last modification on : Sunday, May 17, 2020 - 2:11:31 AM

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Alessandro Zanni, Se-Young Yu, Paolo Bellavista, Rami Langar, Stefano Secci. Automated Selection of Offloadable Tasks for Mobile Computation Offloading in Edge Computing. 13th International Conference on Network and Service Management - CNSM 2017, Nov 2017, Tokyo, Japan. pp.1-5, ⟨10.23919/CNSM.2017.8256026⟩. ⟨hal-01672750⟩

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