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Fine-grain Computation Offloading Considering Application Components’ Sequencing

机译:考虑应用组件测序的细粒计算卸载

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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.
机译:如今,移动设备的使用在人类的生活中正在增加。 但这些设备具有一些限制,例如有限的存储,低电量寿命和弱计算能力。 要处理这些限制,移动设备通过使用移动云计算技术将其沉重的应用程序卸载到云中。 由于网络条件,卸载可能会对移动设备施加延迟和能量成本。 因此,它是本地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整个成本高。 在本文中,我们提出了考虑应用组件的测序的细粒计算卸载方案。 该方案将决策算法的指数复杂性转变为多项式。 仿真和评估结果表明,由于减少决策开销,卸载效率提高。

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