Energy-optimal mobile application execution: Taming resource-poor mobile devices with cloud clones

In this paper, we propose to leverage cloud computing to tame resource-poor mobile devices. Specifically, mobile applications can be executed in the mobile device (known as mobile execution) or offloaded to the cloud clone for execution (known as cloud execution), with an objective to conserve energ...

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Main Authors: Yonggang Wen, Weiwen Zhang, Haiyun Luo
Format: Conference Proceeding
Language:English
Subjects:
application offloading
Cloning
cloud computing
dynamic voltage scaling
mobile applications
Mobile communication
Transmission line matrix methods
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Weiwen Zhang
Haiyun Luo
description In this paper, we propose to leverage cloud computing to tame resource-poor mobile devices. Specifically, mobile applications can be executed in the mobile device (known as mobile execution) or offloaded to the cloud clone for execution (known as cloud execution), with an objective to conserve energy for mobile device. The energy-optimal execution policy is obtained by solving two constrained optimization problems, i.e., how to optimally configure the clock frequency to complete CPU cycles for mobile execution, and how to optimally schedule the data transmission for cloud execution in order to achieve the minimal energy within time delay. Closed-form solutions are obtained for both cases and applied to decide the optimal condition under whether the local execution or the remote execution is more energy-efficient for the mobile device. Moreover, numerical results illustrate that a significant amount of energy (e.g., up to 13 times for a typical mobile application profile) can be saved by optimally offloading the mobile application to the cloud clone.
doi_str_mv 10.1109/INFCOM.2012.6195685
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subjects application offloading
Cloning
cloud computing
dynamic voltage scaling
mobile applications
Mobile communication
Transmission line matrix methods
title Energy-optimal mobile application execution: Taming resource-poor mobile devices with cloud clones
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