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.

Planning mobile cloud infrastructures using stochastic petri nets and graphic processing units / Silva, Francisco Airton; Rodrigues, Matheus; Maciel, Paulo; KOSTA, SOKOL; MEI, Alessandro. - STAMPA. - (2015), pp. 471-474. (Intervento presentato al convegno 7th IEEE International Conference on Cloud Computing Technology and Science, CloudCom 2015 tenutosi a Vancouver; Canada nel 2015) [10.1109/CloudCom.2015.46].

Planning mobile cloud infrastructures using stochastic petri nets and graphic processing units

KOSTA, SOKOL;MEI, Alessandro
2015

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.
2015
7th IEEE International Conference on Cloud Computing Technology and Science, CloudCom 2015
Graphic Processing Unit; Mobile Cloud Computing; Stochastic Petri Nets; Computer Networks and Communications; Computational Theory and Mathematics
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Planning mobile cloud infrastructures using stochastic petri nets and graphic processing units / Silva, Francisco Airton; Rodrigues, Matheus; Maciel, Paulo; KOSTA, SOKOL; MEI, Alessandro. - STAMPA. - (2015), pp. 471-474. (Intervento presentato al convegno 7th IEEE International Conference on Cloud Computing Technology and Science, CloudCom 2015 tenutosi a Vancouver; Canada nel 2015) [10.1109/CloudCom.2015.46].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/878092
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