III: Small: Reducing The Graphical User Interface's Consumption of Power on Mobile Devices

随着移动设备获得新功能，它们的能源需求也随之增加。十年前，用户可能需要每周给移动设备充电一次；现在，每天都要充电是很常见的。这种增加的能量需求部分是由于移动设备执行持续轮询以确定是否已经接收到诸如手势、电子邮件消息或蜂窝呼叫之类的输入。即使当设备处于空闲状态并且放在用户的口袋中时，轮询也会不断地唤醒CPU，防止其进入低功率、节能状态。由于输入设备在接收输入时传统上一直处于静音状态，因此有必要采用这种能源效率低下的“拉”模式。因此，为了确保迅速处理输入，CPU被迫每秒多次查询每个输入设备以确定该设备是否持有输入。最近的技术进步现在使输入设备能够在输入到达时立即通知CPU。这一改进使我们能够研究另一种“推”模式，该模式在没有输入时使CPU进入休眠状态，只有在实际收到输入时才唤醒CPU。因此，当移动设备闲置在用户的口袋中时，CPU不再需要消耗电能。此外，较新的移动设备有多个CPU核心，其中一些是速度较慢、功耗较低的核心，在CPU处于休眠状态时唤醒速度更快。我们可以将将输入定向到应用程序的软件放置在这些低功耗内核中的一个上，而将应用程序本身放置在速度更快、功耗更高的内核上。这种安置方式有两个好处。首先，可以忽略一些输入，如果输入可以在较低功率核心上处理和丢弃，则不需要唤醒较高功耗核心。其次，如果输入必须由应用程序处理，则可以预热较高功率核心，同时为较低功率核心上的应用程序收集和准备有关输入的信息。为了实现这种推送模式，事件处理的控制轨迹将从应用程序转移到内核。这种新的布局将需要1)开发用于事件分派的内核例程，2)开发允许进程调度器知道哪些进程是输入驱动的内核级显示服务器，以及3)修改进程调度器，以便它可以根据需要取消对输入驱动的进程的调度。我们将首先为图形用户界面接收的输入开发推送模型，然后将其扩展到传感器和GPS信号等通用系统I/O。我们计划修改Android运行时(ART)以使用推送模型，以便分析实际的应用程序，以确定使用我们建议的模型可以实现多少电力节约，并潜在地减少延迟。我们的研究应该会产生令人满意的更广泛的影响，既可以降低移动设备需要充电的频率，也可以通过减少移动设备的能耗来减少它们对环境的影响。另一个更广泛的影响是，拟议的技术应该适用于蜂窝和Wi-Fi处理应用程序，也适用于台式电脑。

Mobile devices have increased their energy demand as they have acquired new capabilities. A decade ago, users might have had to re-charge their mobile devices once a week; now it is common to have to re-charge them daily. This increased energy demand is in part due to the constant polling that a mobile device performs to determine whether an input, such as a gesture, an email message, or a cellular call, has been received. The polling, even when the device is idle and in the user's pocket, constantly rouses the CPU and prevents it from being put into low power, energy-conserving states. This energy inefficient 'pull' model has been necessitated by the fact that input devices traditionally have been 'mute' when they receive an input. Thus in order to ensure that an input is promptly processed, the CPU is forced to query each input device multiple times per second to determine if the device is holding an input. Recent technological advances now enable input devices to immediately notify the CPU when an input has arrived. This advance allows us to investigate an alternative 'push' model that puts the CPU to sleep while no inputs are present and awakens the CPU only when an input is actually received. Hence the CPU no longer needs to consume power while the mobile device sits idle in the user's pocket. Additionally, newer mobile devices have multiple CPU cores, some of which are slower, lower power consuming cores that awaken faster when the CPU has been asleep. We can place the software that directs inputs to apps on one of these lower power consuming cores and the apps themselves on the faster, higher power consuming cores. This placement has two benefits. First, some inputs can be ignored, and if an input can be handled and discarded on the lower power core, then the higher power consuming cores do not need to be awakened. Second, if the input must be handled by an app, the higher power core can be warmed up while information about the input is gathered and staged for the app on the lower power core.In order to realize this push model, the locus of control for event handling will move from the application into the kernel. This new placement will necessitate 1) the development of kernel routines for event dispatching, 2) the development of a kernel-level display server that allows the process scheduler to know which processes are input driven, and 3) the modification of the process scheduler so that it can de-schedule input-driven processes as needed. We will first develop a push model for inputs received by graphical user interfaces and then extend it to generic system I/O such as sensors and GPS signals. We plan to modify the Android runtime (ART) to work with the push model in order to profile actual apps to determine how much power savings, and potentially reduced latency, can be achieved with our proposed model. Our research should have the desirable broader impact of both reducing the frequency with which mobile devices need to be recharged and reducing the environmental impact of mobile devices by reducing the amount of energy they consume. Another broader impact is that the proposed techniques should work for cellular and Wi-Fi handling apps and for desktop computers as well.