Planning Mobile Cloud Infrastructures Using Stochastic Petri Nets and Graphic Processing Units

被引：16

作者：

Silva, Francisco Airton ^{[1
]}

Rodrigues, Matheus ^{[1
]}

Maciel, Paulo ^{[1
]}

Kosta, Sokol ^{[2
]}

Mei, Alessandro ^{[2
]}

机构：

[1] Univ Fed Pernambuco, Informat Ctr, Recife, PE, Brazil

[2] Univ Roma La Sapienza, Dept Comp Sci, Rome, Italy

来源：

2015 IEEE 7TH INTERNATIONAL CONFERENCE ON CLOUD COMPUTING TECHNOLOGY AND SCIENCE (CLOUDCOM) | 2015年

关键词：

Stochastic Petri Nets; Mobile Cloud Computing; Graphic Processing Unit;

D O I：

10.1109/CloudCom.2015.46

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

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.

引用

页码：471 / 474

页数：4

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