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Battery-Aware Multimedia Coding Optimization by Dynamic Frequency Scaling

机译:通过动态频率缩放优化电池感知的多媒体编码

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Nowadays, multimedia application and video streaming have gained a great popularity because of the boasting development on mobile hardware, and battery driven devices have emerged with a tremendous speed. Due to the important issue of battery efficiency on mobile devices, many optimization algorithms have being proposed toward various of battery powered platforms and scenarios. Most of the provided solutions choose to aim at the minimization of energy usage under a given task scheduling by adjusting parameters reside in the processes of different schemes. However, the battery discharging characteristics and its instant output pattern are still ignored if the optimization is done only from high level adjustment. In this paper, we propose a battery-aware optimization framework toward the H.264 video coding by applying dynamic frequency scaling on hardware platform. The CPU frequency can be dynamically adjusted according to the instant status of battery in order to maximize the number of the coding frame. Experimental results indicate the efficiency and effectiveness of the proposed optimization framework.
机译:如今,由于移动硬件的蓬勃发展,多媒体应用程序和视频流已获得了极大的普及,并且电池驱动的设备以惊人的速度出现。由于移动设备上电池效率的重要问题,针对各种电池供电的平台和方案提出了许多优化算法。提供的大多数解决方案都选择通过调整驻留在不同方案过程中的参数来在给定的任务调度下将能耗最小化。但是,如果仅通过高电平调整进行优化,则仍会忽略电池放电特性及其即时输出模式。在本文中,我们通过在硬件平台上应用动态频率缩放,针对H.264视频编码提出了一种电池感知的优化框架。可以根据电池的即时状态动态调整CPU频率,以使编码帧的数量最大化。实验结果表明了所提出的优化框架的效率和有效性。

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