eTime:云与移动设备之间的高能效传输

Peng Shu, Fangming Liu, Hai Jin, Min Chen, Feng Wen, Yupeng Qu, Bo Li
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引用次数: 163

摘要

移动云计算有望扩展资源受限的移动设备的功能,它正在作为一种新的计算范式出现,并催生了一系列令人兴奋的应用程序。在这种新模式下,云和移动设备之间的高效数据传输变得至关重要。然而,由于一些不可控因素,特别是无线连接的不稳定性和间歇性、通信带宽的波动以及用户的移动性,这是非常不可靠和不可预测的。因此,这给移动设备的能源消耗带来了沉重的负担。我们的实验证实,在“不良”连接期间消耗的能量要多得多。受预取友好或延迟容忍应用程序调度数据传输可行性的启发,本文提出了一种基于Lyapunov优化的云和移动设备之间的新型节能数据传输策略eTime。它积极地、自适应地抓住良好连接的时间来预取频繁使用的数据,同时在连接差的情况下延迟容忍延迟的数据。为了应对无线连接的随机性和不可预测性,eTime仅依靠当前状态信息来做出全局能量延迟权衡决策。我们对跟踪驱动仿真和现实世界实现的评估表明,eTime可以应用于各种流行的应用,同时实现20%-35%的节能。
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eTime: Energy-efficient transmission between cloud and mobile devices
Mobile cloud computing, promising to extend the capabilities of resource-constrained mobile devices, is emerging as a new computing paradigm which has fostered a wide range of exciting applications. In this new paradigm, efficient data transmission between the cloud and mobile devices becomes essential. This, however, is highly unreliable and unpredictable due to several uncontrollable factors, particularly the instability and intermittency of wireless connections, fluctuation of communication bandwidth, and user mobility. Consequently, this puts a heavy burden on the energy consumption of mobile devices. Confirmed by our experiments, significantly more energy is consumed during “bad” connectivity. Inspired by the feasibility to schedule data transmissions for prefetching-friendly or delay-tolerant applications, in this paper, we present eTime, a novel Energy-efficient data Transmission strategy between cloud and Mobile dEvices, based on Lyapunov optimization. It aggressively and adaptively seizes the timing of good connectivity to prefetch frequently used data while deferring delay-tolerant data in bad connectivity. To cope with the randomness and unpredictability of wireless connectivity, eTime only relies on the current status information to make a global energy-delay tradeoff decision. Our evaluations from both trace-driven simulation and realworld implementation show that eTime can be applied to various popular applications while achieving 20%-35% energy saving.
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