Present day portable devices such as laptops, smartphones, etc., offer their users fastest processors, advanced operating systems, and numerous applications. However, a large section of the users are critical to the available battery capacity and its lifetime. This is because performance of the battery and its lifetime as perceived by the users are quite subjective in nature. It depends directly on user satisfactions, which are usually expressed in terms of words. So, in this paper, we propose a user-satisfaction-aware energy management approach, called “perceptual computer power management approach (Per-C PMA),” based on the technique of perceptual computing. At the heart of our technique is the perceptual computer that processes the linguistic input of the users to aid in the selection of a suitable processor frequency, which plays a significant role in the overall energy consumption of the systems. The Per-C PMA minimizes the energy consumption, while still keeping the user satisfied with the perceived system performance. The Per-C PMA achieves 1) reductions of 42.26% and 10.84% in power consumption, and 2) improvements in the overall satisfaction ratings of 16% and 10%, when compared to other existing power-saving schemes such as ON-DEMAND and human and application-driven frequency scaling for processor power efficiency, respectively. Per-C PMA is the first such application of Per-C on any hardware platform. It is implemented as Ubuntu scripts for end users and can be downloaded from: http://sau.ac.in/∼cilab/. We have also provided the MATLAB files so that interested researchers can use it in their research. For the ease of the users, the Ubuntu scripts and the MATLAB codes are given in the graphical user interface mode; a demo video on how to use the software is also provided on the webpage.

中文翻译：

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基于感知计算的移动设备用户满意度感知电源管理

当今的便携式设备，例如笔记本电脑、智能手机等，为用户提供最快的处理器、先进的操作系统和众多应用程序。然而，很大一部分用户对可用电池容量及其寿命至关重要。这是因为用户感知的电池性能及其寿命本质上是非常主观的。它直接取决于用户的满意度，通常用文字来表示。因此，在本文中，我们提出了一种基于感知计算技术的用户满意度感知能源管理方法，称为“感知计算机电源管理方法（Per-C PMA）”。我们技术的核心是感知计算机，它处理用户的语言输入以帮助选择合适的处理器频率，这在系统的整体能耗中起着重要作用。Per-C PMA 最大限度地减少了能源消耗，同时仍然让用户对感知的系统性能感到满意。Per-C PMA 实现 1) 功耗降低 42.26% 和 10.84%，以及 2) 与其他现有节电方案（如 ON-DEMAND 和分别针对处理器功率效率进行人工和应用驱动的频率缩放。Per-C PMA 是 Per-C 在任何硬件平台上的第一个此类应用程序。它是作为面向最终用户的 Ubuntu 脚本实现的，可以从以下网址下载：http://sau.ac.in/∼cilab/。我们还提供了 MATLAB 文件，以便感兴趣的研究人员可以在他们的研究中使用它。为方便用户，Ubuntu脚本和MATLAB代码以图形用户界面模式给出；网页上还提供了有关如何使用该软件的演示视频。