Towards resource sharing in mobile device clouds: power balancing across mobile devices

MCC '13 Pub Date : 2013-08-16 DOI:10.1145/2491266.2491276
Abderrahmen Mtibaa, A. Fahim, Khaled A. Harras, M. Ammar
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引用次数: 118

Abstract

Despite the increased capabilities of mobile devices, mobile application resource requirements can often transcend what can be accomplished on a single device. This has been addressed through several proposals for efficient computation offloading from mobile devices to remote cloud resources or closely located computing resources known as cloudlets. In this paper we consider an environment in which computational offloading is performed among a set of mobile devices. We call this environment a Mobile Device Cloud (MDC). We are interested in MDCs where nodes are {\em highly collaborative}. We develop computational offloading schemes that {\em maximize the lifetime} of the ensemble of mobile devices where we consider the network to be alive as long as no device has depleted its battery. As a secondary contribution in this work, we develop and use an experimentation platform that allows us to evaluate a range of computational models and profiles derived from a realistic testbed. We use this platform as a first step in an evaluation exercise that demonstrates the effectiveness of our computation offloading algorithms in extending the lifetime of an MDC.
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移动设备云中的资源共享:跨移动设备的功率平衡
尽管移动设备的功能有所增加,但移动应用程序的资源需求往往超出了单个设备所能完成的任务。这个问题已经通过一些建议得到解决,这些建议将计算从移动设备高效地卸载到远程云资源或被称为cloudlets的位置较近的计算资源上。在本文中,我们考虑在一组移动设备之间执行计算卸载的环境。我们将这种环境称为移动设备云(MDC)。我们对节点高度协作的mdc感兴趣。我们开发了计算卸载方案,使移动设备集合的寿命最大化,我们认为只要没有设备耗尽其电池,网络就会存活。作为这项工作的次要贡献,我们开发并使用了一个实验平台,该平台允许我们评估一系列来自现实测试平台的计算模型和轮廓。我们使用这个平台作为评估练习的第一步,该练习演示了我们的计算卸载算法在延长MDC生命周期方面的有效性。
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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