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

随着移动的设备获得了新的能力，它们的能量需求也增加了。十年前，用户可能每周都要给他们的移动的设备充电一次;现在每天都要充电已经很常见了。这种增加的能量需求部分地是由于移动终端执行恒定轮询以确定是否已经接收到输入（诸如手势、电子邮件消息或蜂窝呼叫）。即使当设备空闲并且在用户的口袋中时，轮询也会不断唤醒CPU并防止其进入低功耗、节能状态。由于输入设备在接收输入时传统上是“静音”的，因此这种能量效率低的“拉动”模型是必要的。因此，为了确保输入被迅速处理，CPU被迫每秒多次查询每个输入设备，以确定该设备是否正在保持输入。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。这一进步使我们能够研究另一种“推”模型，该模型在没有输入的情况下使CPU休眠，只有在实际接收到输入时才唤醒CPU。因此，当移动终端闲置在用户的口袋中时，CPU不再需要消耗功率。此外，较新的移动的设备具有多个CPU核心，其中一些是较慢的、较低功耗的核心，当CPU休眠时，这些核心唤醒得更快。我们可以将输入引导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。这种布局有两个好处。首先，可以忽略一些输入，并且如果可以在较低功率核上处理和丢弃输入，则不需要唤醒较高功率消耗核。第二，如果输入必须由应用程序处理，则可以预热较高功率的内核，同时收集有关输入的信息并将其暂存到较低功率的内核上的应用程序。为了实现这种推送模型，事件处理的控制点将从应用程序转移到内核。这种新的布局将需要1）开发用于事件调度的内核例程，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进程的调度。我们将首先为图形用户界面接收的输入开发一个推模型，然后将其扩展到通用系统I/O，如传感器和GPS信号。我们计划修改Android运行时（ART），使其与推送模型一起工作，以便分析实际应用程序，以确定我们提出的模型可以节省多少电量，并可能减少延迟。我们的研究应该具有理想的更广泛的影响，既减少了移动的设备需要充电的频率，又通过减少移动的设备消耗的能量来减少它们对环境的影响。另一个更广泛的影响是，所提出的技术应该适用于蜂窝和Wi-Fi处理应用程序以及台式计算机。

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.