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Application-Specific Performance-Aware Energy Optimization on Android Mobile Devices

机译:Android移动设备上针对特定应用的性能感知能源优化

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Energy management is a key issue for mobile devices. On current Android devices, power management relies heavily on OS modules known as governors. These modules are created for various hardware components, including the CPU, to support DVFS. They implement algorithms that attempt to balance performance and power consumption. In this paper we make the observation that the existing governors are (1) general-purpose by nature (2) focused on power reduction and (3) are not energy-optimal for many applications. We thus establish the need for an application-specific approach that could overcome these drawbacks and provide higher energy efficiency for suitable applications. We also show that existing methods manage power and performance in an independent and isolated fashion and that co-ordinated control of multiple components can save more energy. In addition, we note that on mobile devices, energy savings cannot be achieved at the expense of performance. Consequently, we propose a solution that minimizes energy consumption of specific applications while maintaining a user-specified performance target. Our solution consists of two stages: (1) offline profiling and (2) online controlling. Utilizing the offline profiling data of the target application, our control theory based online controller dynamically selects the optimal system configuration (in this paper, combination of CPU frequency and memory bandwidth) for the application, while it is running. Our energy management solution is tested on a Nexus 6 smartphone with 6 real-world applications. We achieve 4 - 31% better energy than default governors with a worst case performance loss of
机译:能源管理是移动设备的关键问题。在当前的Android设备上,电源管理严重依赖于称为调速器的OS模块。这些模块是为各种硬件组件(包括CPU)创建的,以支持DVFS。他们实现了试图平衡性能和功耗的算法。在本文中,我们发现现有的调速器是(1)本质上是通用的(2)专注于降低功率,并且(3)在许多应用中不是能源最优的。因此,我们建立了一种针对特定应用的方法的需求,该方法可以克服这些缺点并为合适的应用提供更高的能源效率。我们还表明,现有方法以独立和隔离的方式管理电源和性能,并且对多个组件的协调控制可以节省更多能量。此外,我们注意到,在移动设备上,无法以性能为代价实现节能。因此,我们提出了一种解决方案,可在保持用户指定的性能目标的同时将特定应用的能耗降至最低。我们的解决方案包括两个阶段:(1)离线分析和(2)在线控制。利用目标应用程序的离线分析数据,我们基于控制理论的在线控制器在运行时动态地为应用程序选择最佳的系统配置(本文中,CPU频率和内存带宽的组合)。我们的能源管理解决方案已在具有6种实际应用的Nexus 6智能手机上经过测试。与默认的调速器相比,我们可节省4-31%的能源,而最坏情况下的性能损失为

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