DocumentCode :
3751319
Title :
The Cloudlet Accelerator: Bringing Mobile-Cloud Face Recognition into Real-Time
Author :
Nathaniel Powers;Alexander Alling;Kiara Osolinsky;Tolga Soyata;Meng Zhu;Haoliang Wang;He Ba;Wendi Heinzelman;Jiye Shi;Minseok Kwon
Author_Institution :
Dept. of ECE, U. of Rochester, Rochester, NY, USA
fYear :
2015
Firstpage :
1
Lastpage :
7
Abstract :
A mobile-cloud architecture provides a practical platform for performing face recognition on a mobile device. However, using a mobile-cloud architecture to perform real-time face recognition presents several challenges including resource limitations and long network delays. In this paper, we determine three approaches for accelerating the execution of the face recognition application by utilizing an intermediate device called a cloudlet. We study in detail one of these approaches, using the cloudlet to perform pre-processing, and quantify the maximum attainable acceleration. Our experimental results show up to a 128x improvement in response time when appropriate cloudlet hardware is used.
Keywords :
"Cloud computing","Face","Mobile handsets","Face recognition","Databases","Servers","Performance evaluation"
Publisher :
ieee
Conference_Titel :
Globecom Workshops (GC Wkshps), 2015 IEEE
Type :
conf
DOI :
10.1109/GLOCOMW.2015.7414055
Filename :
7414055
Link To Document :
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