Title :
Benchmarking leading-edge mobile devices for data-intensive distributed mobile cloud applications
Author :
Nayyab Zia Naqvi;Tim Vansteenkiste-Muylle;Yolande Berbers
Author_Institution :
iMinds-DistriNet, Department of Computer Science, KU Leuven, Belgium
fDate :
7/1/2015 12:00:00 AM
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.
Keywords :
"Mobile handsets","Cloud computing","Mobile communication","Benchmark testing","Performance evaluation","Face","Face recognition"
Conference_Titel :
Computers and Communication (ISCC), 2015 IEEE Symposium on
DOI :
10.1109/ISCC.2015.7405493