Resource Allocation for Cloud-Assisted Mobile Applications

M. Ferber, T. Rauber, M. Torres, T. Holvoet
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引用次数: 24

Abstract

Mobile devices such as netbooks, smartphones, and tablets have made computing ubiquitous. However, such battery powered devices often have limited computing power for the benefit of an extended runtime. Nevertheless, despite the reduced processing power, users expect to perform the same types of operations as they could do using their desktop or laptop computers. We address mobile devices's lack of computing power by leveraging cloud computing resources. We present a middleware that relocates computing-intensive parts of Java applications to cloud re-sources. Consequently, our middleware enables the execution of computing-intensive applications on mo-bile devices. We present a case study on which we adapt Sunflow, an open-source ray tracing application, to use our middleware and show the results obtained by deploying it on Amazon EC2. We show, via simulations, a cost analysis of using the different resource allocation strategies available on our solution.
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云辅助移动应用的资源分配
上网本、智能手机和平板电脑等移动设备使计算无处不在。然而,为了延长运行时间,这种电池供电的设备通常具有有限的计算能力。然而,尽管处理能力降低了,用户仍然希望执行与使用台式机或笔记本电脑相同类型的操作。我们通过利用云计算资源来解决移动设备缺乏计算能力的问题。我们提出了一种中间件,它可以将Java应用程序的计算密集型部分重新定位到云资源中。因此,我们的中间件支持在移动设备上执行计算密集型应用程序。我们给出了一个案例研究,在这个案例研究中,我们调整了Sunflow(一个开源光线跟踪应用程序)来使用我们的中间件,并展示了通过在Amazon EC2上部署它获得的结果。通过模拟,我们展示了在我们的解决方案中使用不同资源分配策略的成本分析。
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