Collaborative mobile-to-mobile computation offloading

Abderrahmen Mtibaa, M. A. Snober, Antonio Carelli, R. Beraldi, H. Alnuweiri
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引用次数: 12

Abstract

It is common practice for mobile devices to offload computationally heavy tasks off to a cloud, which has greater computational resources. In this paper, we consider an environment in which computational offloading is made among collaborative mobile devices.We call such an environment a mobile device cloud (MDC). We highlight the gain in computation time and energy consumption that can be achieved by offloading tasks with given characteristics to nearby devices inside a mobile device cloud. We adopt an experimental approach to measure power consumption in mobile to mobile opportunistic offloading using MDCs. Then, we adopt a data driven approach to evaluate and assess various offloading algorithms in MDCs. We believe that MDCs are not replacing the Cloud, however they present an offloading opportunity for a set of tasks with given characteristics or simply a solution when the cloud is unacceptable or costly. The promise of this approach shown by evaluating these algorithms using real datasets that include contact traces and social information of mobile devices in a conference setting.
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协同移动到移动的计算卸载
对于移动设备来说,将计算量大的任务卸载到云上是一种常见的做法,因为云拥有更多的计算资源。在本文中,我们考虑了在协作移动设备之间进行计算卸载的环境。我们将这种环境称为移动设备云(MDC)。我们强调了通过将具有给定特征的任务卸载到移动设备云中的附近设备中可以实现的计算时间和能耗的增益。我们采用一种实验方法来测量使用mdc的移动设备到移动设备的机会性卸载的功耗。然后,我们采用数据驱动的方法来评估和评估mdc中的各种卸载算法。我们认为mdc不会取代云,但是它们为具有给定特征的一组任务提供了卸载机会,或者在云不可接受或成本高昂时提供了简单的解决方案。通过使用真实数据集(包括会议环境中移动设备的接触痕迹和社交信息)评估这些算法,这种方法的前景得到了体现。
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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