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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Hassan, M.A. Qi Wei Songqing Chen |
| Copyright Year | 2015 |
| Description | Author affiliation: NetApp Inc., Wichita, KS, USA (Hassan, M.A.) || Dept. of Comput. Sci., George Mason Univ., Fairfax, VA, USA (Qi Wei; Songqing Chen) |
| Abstract | As mobile devices are battery powered and have less computing resources, plenty of research has been conducted on how to efficiently offload computing-intensive tasks in a mobile application to more powerful counterpart. However, prior research either implicitly assumes that the computing-intensive tasks are known in advance or the application developers will make special notations about them. In this paper, we design a framework Elicit to efficiently identify the computation-intensive tasks in mobile applications for offloading. Furthermore, we also consider the response time savings dynamically when deciding whether to offload a task based on the runtime system resources. A prototype of Elicit is built based on the Dalvik VM. Our evaluation with some popular Android applications from Google Play shows that Elicit can efficiently find an application's computing-intensive task and save response time and energy consumption when these tasks are offloaded. |
| Starting Page | 12 |
| Ending Page | 22 |
| File Size | 367865 |
| Page Count | 11 |
| File Format | |
| e-ISBN | 9781467378918 |
| DOI | 10.1109/NAS.2015.7255215 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-08-06 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Support vector machines Training Performance gain Mobile handsets Mobile applications Servers Time factors |
| Content Type | Text |
| Resource Type | Article |
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