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Task offloading engine for heterogeneous mobile Clouds

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Sulaiman_2016_Task_offloading_MobiCASE_AAM.pdf (222.2Kb)
Date
01/12/2016
Author
Sulaiman, Dawand Jalil
Barker, Adam David
Keywords
Mobile Clouds
Task offloading
Heterogeneity
QA75 Electronic computers. Computer science
QA76 Computer software
TA Engineering (General). Civil engineering (General)
NDAS
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Abstract
The limitations in computational resources and battery power of mobile devices led to the concept of offloading compute-intensive tasks to powerful devices. We have developed a framework to offload tasks from a mobile device to other nearby heterogeneous devices. It contains an offloading engine to selectively choose the target devices for the execution of the offloaded tasks to address optimal scheduling across devices with diverse capabilities. Our initial conducted runtime measurements show the feasibility of this concept. As preliminary results, we show that offloading compute intensive tasks from a device with less computational capability to a set of nearby more powerful devices can reduce the overall computational time by approximately 50%.
Citation
Sulaiman , D J & Barker , A D 2016 , Task offloading engine for heterogeneous mobile Clouds . in Proceedings of The 8th EAI International Conference on Mobile Computing, Applications and Services . ACM , 8th EAI International Conference on Mobile Computing, Applications and Services , Cambridge , United Kingdom , 30/11/16 . https://doi.org/10.4108/eai.30-11-2016.2267048
 
conference
 
Publication
Proceedings of The 8th EAI International Conference on Mobile Computing, Applications and Services
DOI
https://doi.org/10.4108/eai.30-11-2016.2267048
Type
Conference item
Rights
© 2016, EAI. 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 www.eudl.eu / http://dx.doi.org/10.4108/eai.30-11-2016.2267048
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  • University of St Andrews Research
URI
http://hdl.handle.net/10023/10292

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