首页> 外文会议>2013 18th Asia and South Pacific Design Automation Conference >Online estimation of the remaining energy capacity in mobile systems considering system-wide power consumption and battery characteristics
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Online estimation of the remaining energy capacity in mobile systems considering system-wide power consumption and battery characteristics

机译:考虑系统范围的功耗和电池特性,在线估算移动系统中的剩余能量

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Emerging mobile systems integrate a lot of functionality into a small form factor with a small energy source in the form of rechargeable battery. This situation necessitates accurate estimation of the remaining energy in the battery such that user applications can be judicious on how they consume this scarce and precious resource. This paper thus focuses on estimating the remaining battery energy in Android OS-based mobile systems. This paper proposes to instrument the Android kernel in order to collect and report accurate subsystem activity values based on real-time profiling of the running applications. The activity information along with offline-constructed, regression-based power macro models for major subsystems in the smartphone yield the power dissipation estimate for the whole system. Next, while accounting for the rate-capacity effect in batteries, the total power dissipation data is translated into the battery's energy depletion rate, and subsequently, used to compute the battery's remaining lifetime based on its current state of charge information. Finally, this paper describes a novel application design framework, which considers the batterys state-of-charge (SOC), batterys energy depletion rate, and service quality of the target application. The benefits of the design framework are illustrated by examining an archetypical case, involving the design space exploration and optimization of a GPS-based application in an Android OS.
机译:新兴的移动系统将许多功能集成到了小巧的外形中,并采用了可充电电池形式的小型能源。这种情况需要准确估计电池中的剩余能量,以便用户应用程序可以明智地了解他们如何消耗这种稀缺和宝贵的资源。因此,本文着重于估计基于Android OS的移动系统中的剩余电池电量。本文提议对Android内核进行检测,以便基于正在运行的应用程序的实时性能分析来收集和报告准确的子系统活动值。活动信息以及针对智能手机中主要子系统的离线构造的,基于回归的功率宏模型可得出整个系统的功耗估算。接下来,在考虑电池中的速率-容量效应的同时,将总功耗数据转换为电池的能量消耗率,然后根据其当前的充电状态信息将其用于计算电池的剩余寿命。最后,本文描述了一种新颖的应用程序设计框架,该框架考虑了电池的荷电状态(SOC),电池能量消耗率以及目标应用程序的服务质量。通过检查一个典型案例来说明设计框架的好处,其中涉及设计空间探索和对Android OS中基于GPS的应用程序的优化。

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