Fine-grain Computation Offloading Considering Application Components’ Sequencing

Razie Roostaei, Marzieh Sheikhi, Z. Movahedi
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引用次数: 1

Abstract

Nowadays, the usage of mobile devices is increasing in human’s life. But these devices have some constraints such as limited storage, low battery lifetime, and weak computation capacity. To deal with these limitations, mobile devices offload their heavy applications to the cloud by using mobile cloud computing technology. Because of the network conditions, offloading may impose delay and energy costs on mobile devices. Thus, it is a tradeoff between local and remote execution. Further, offloading some components of the application may be cost-effective than the whole one. In this paper, we propose a fine-grain computation offloading scheme considering application components’ sequencing. The proposed scheme turns the exponential complexity of the decision algorithm into the polynomial. The simulation and evaluation results demonstrate that the offloading efficiency improves thanks to reducing the decision overhead.
考虑应用组件排序的细粒度计算卸载
如今,移动设备在人们生活中的使用越来越多。但这些设备有一些限制,如有限的存储,电池寿命短,计算能力弱。为了解决这些限制,移动设备通过使用移动云计算技术将其繁重的应用程序卸载到云中。由于网络条件的原因,卸载可能会对移动设备造成延迟和能源成本。因此,这是本地执行和远程执行之间的权衡。此外,卸载应用程序的某些组件可能比卸载整个组件更具成本效益。本文提出了一种考虑应用组件排序的细粒度计算卸载方案。该方案将决策算法的指数复杂度转化为多项式复杂度。仿真和评估结果表明,由于减少了决策开销,卸载效率得到了提高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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