NDLI: Benchmarking leading-edge mobile devices for data-intensive distributed mobile cloud applications

Content Provider	IEEE Xplore Digital Library
Author	Naqvi, Nayyab Zia Vansteenkiste-Muylle, Tim Berbers, Yolande
Copyright Year	2015
Description	Author affiliation: iMinds-DistriNet, Department of Computer Science, KU Leuven, Belgium (Naqvi, Nayyab Zia; Vansteenkiste-Muylle, Tim; Berbers, Yolande)
Abstract	Mobile Cloud Computing (MCC) addresses the resource limitations of the mobile devices, but with a hidden cost depending on the requirements of the mobile applications. In this work, we investigate the proclaimed benefits of MCC for smart phones when thin clients are used to access remote cloud services, especially for applications that capitalize on the data generated from the mobile device. The added value of MCC can be hampered if the power of today's leading-edge mobile technology is not estimated. The opportunistic use of cloud is inevitable for the maximum benefit of the devices. Our experiments show that many resource and performance trade-offs exist and the current deployment schemes for these kind of applications are rough around the edges. There is a need for an automated deployment decision support for mobile applications to exploit the benefits of the cloud as well as the power of today's high-end mobile devices.
Starting Page	50
Ending Page	57
File Size	389686
Page Count	8
File Format	PDF
e-ISBN	9781467371940
DOI	10.1109/ISCC.2015.7405493
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-07-06
Publisher Place	Cyprus
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Mobile handsets Cloud computing Mobile communication Benchmark testing Performance evaluation Face Face recognition face recognition Mobile cloud computing benchmarking mobile computing
Content Type	Text
Resource Type	Article

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