Drop计算中移动云的设备到设备协作

Radu-Corneliu Marin, Alexandru Gherghina-Pestrea, Alexandru Florin Robert Timisica, Radu-Ioan Ciobanu, C. Dobre
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引用次数: 6

摘要

如今存在的大量移动设备已经导致移动云计算朝着使数据和计算更接近节点的方向发展。这首先以雾和边缘计算的形式表现出来,其中在网络边缘添加了额外的通信和处理层。然而,物联网的快速普及显示出这种模式的局限性,因此现在的焦点转向了下一层:由移动设备本身组成的自组织网络。基于该模型的一个范例是Drop Computing,其中需要进行一些计算的节点首先尝试通过使用近距离通信(如Wi-Fi Direct或蓝牙)的邻居设备的帮助来处理它们,然后它们才尝试联系雾/边缘节点或云本身。在本文中,我们提出了一个在Android上实现Drop Computing的设备到设备层。在此实现的基础上,我们提出了一个应用程序,该应用程序通过使用HYCCUPS和Google Nearby框架的近距离通信,在邻近节点的帮助下,使用ffmpeg从多张照片创建视频拼贴。通过在4个Android设备上的实验,我们发现我们的实现可以大幅降低每台设备的CPU使用率,从而提高Android用户的整体体验质量。此外,由于节点需要执行的计算更少,CPU内核在更高频率上花费的时间更少,因此降低了总电池消耗。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Device to Device Collaboration for Mobile Clouds in Drop Computing
The large number of mobile devices existing nowadays has led to the evolution of mobile cloud computing towards bringing data and computations closer to the nodes. This has manifested first in the shape of fog and edge computing, where an additional communication and processing layer is added at the edge of the network. However, the fast adoption of the Internet of Things has shown the limitations of even this model, so the focus now is moving towards another layer that is one level below: the ad hoc network composed of the mobile devices themselves. One paradigm based on this model is Drop Computing, where nodes that need to do some computations first attempt to process them through the help of neighbor devices using close-range communication (such as Wi-Fi Direct or Bluetooth), and only then do they attempt to contact the fog/edge nodes or the cloud itself. In this paper, we propose an Android implementation of the device-to-device layer of Drop Computing. On top of this implementation, we present an application that creates a video collage from multiple photos using ffmpeg with the help of neighboring nodes through close-range communication using the HYCCUPS and Google Nearby frameworks. Through experiments on four Android devices, we show that our implementation can drastically decrease CPU usage per device, which in turn increases the overall quality of experience for Android users. Furthermore, the total battery consumption is lowered, since nodes have less computations to perform and the CPU cores spend less time in higher frequencies.
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