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EFFORT: Energy efficient framework for offload communication in mobile cloud computing

机译:努力:移动云计算中卸载通信的节能框架

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摘要

There is an abundant expansion in the race of technology, specifically in the production of data, because of the smart devices, such as mobile phones, smart cards, sensors, and Internet of Things (IoT). Smart phones and devices have undergone an enormous evolution in a way that they can be used. More and more new applications, such as face recognition, augmented reality, online interactive gaming, and natural language processing are emerging and attracting the users. Such applications are generally data intensive or compute intensive, which demands high resource and energy consumption. Mobile devices are known for the resource scarcity, having limited computational power and battery life. The tension between compute/data intensive application and resource constrained mobile devices hinders the successful adaption of emerging paradigms. In the said perspective, the objective of this article is to study the role of computation offloading in mobile cloud computing to supplement mobile platforms ability in executing complex applications. This article proposes a systematic approach (EFFORT) for offload communication in the cloud. The proposed approach provides a promising solution to partially solve energy consumption issue for communication-intensive applications in a smartphone. The experimental study shows that our proposed approach outperforms its counterparts in terms of energy consumption and fast processing of smartphone devices. The battery consumption was reduced to 19% and the data usage was reduced to 16%.
机译:在技​​术的比赛中,有一个丰富的扩展,特别是在数据的生产中,因为智能设备,如手机,智能卡,传感器和物联网(物联网)。智能手机和设备在可以使用它们的方式经历了巨大的演变。越来越多的新应用程序,例如面部识别,增强现实,在线交互游戏以及自然语言处理正在出现并吸引用户。这些应用通常是数据密集或计算密集型,这需要高资源和能源消耗。可用于资源稀缺,具有有限的计算能力和电池寿命。计算/数据密集型应用和资源受限移动设备之间的紧张阻碍了新兴范式的成功适应。在上述的角度来看,本文的目的是研究计算卸载在移动云计算中的作用,以补充移动平台在执行复杂应用程序中的能力。本文提出了一种系统的方法(努力)在云中卸载通信。该方法提供了有希望的解决方案,可以部分解决智能手机中的通信密集型应用程序的能耗问题。实验研究表明,我们所提出的方法在能耗和快速加工方面优于智能手机设备的快速处理。电池消耗降至19%,数据使用减少到16%。

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