Abstract
Mobile Cloud Computing (MCC) combines mobile computing and cloud computing aiming to aid performance of mobile devices. The idea is simple: thin devices offload heavy methods to resource-rich servers in the clouds. We believe that in the near future MCC will adopt more advanced offloading techniques. In particular, in this paper we envision a scenario where offloading frameworks will have to deal with GPU code offloading. Amazon already offers instances with Graphics Processing Units (GPU), which can be used for this purpose. We propose and implement MCC-Adviser, a simulation tool that can predict the performance of GPUs with different number of cores using Stochastic Petri Nets. We tested MCC-Adviser in a case study with one of the expensive Amazon GPU instances. The simulations showed that it is possible to minimize costs, while satisfying user's quality of service requirements, by utilizing less powerful instances.
Original language | English |
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Title of host publication | Proceedings - IEEE 7th International Conference on Cloud Computing Technology and Science, CloudCom 2015 |
Number of pages | 4 |
Publisher | IEEE |
Publication date | 1 Feb 2016 |
Pages | 471-474 |
Article number | 7396196 |
ISBN (Print) | 9781467395601 |
DOIs | |
Publication status | Published - 1 Feb 2016 |
Externally published | Yes |
Event | 7th IEEE International Conference on Cloud Computing Technology and Science, CloudCom 2015 - Vancouver, Canada Duration: 30 Nov 2015 → 3 Dec 2015 |
Conference
Conference | 7th IEEE International Conference on Cloud Computing Technology and Science, CloudCom 2015 |
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Country/Territory | Canada |
City | Vancouver |
Period | 30/11/2015 → 03/12/2015 |
Sponsor | Cloud Computing Association, et al., IEEE Cloud Computing, IEEE Computer Society, IEEE Technical Committee on Scalable Computing (TCSC), IEEE Vancouver Section |
Keywords
- Graphic Processing Unit
- Mobile Cloud Computing
- Stochastic Petri Nets