Application power usage
    1.
    发明授权

    公开(公告)号:US10281973B2

    公开(公告)日:2019-05-07

    申请号:US15171395

    申请日:2016-06-02

    Applicant: Apple Inc.

    Abstract: Systems and methods are disclosed for determining hours of utility of an application per amount of energy consumed by the application for a wide variety of device types. For each subsystem of a client device, a model of the subsystem is used to estimate a portion of the total energy consumed by the subsystem during a predetermined period of time. Energy consumed by a subsystem is apportioned to one or more applications or daemons that utilize the subsystem. Energy usage by a daemon is apportioned to one or more applications that the daemon performs work on behalf of. A large sample of application energy consumption information is gathered by an energy server and provided to an application information server that is accessible by developers. Thus, a developer can view energy consumption vs. application utility, by client device type and by subsystem for the client device type.

    LOGGING TECHNIQUES FOR THIRD PARTY APPLICATION DATA

    公开(公告)号:US20200379878A1

    公开(公告)日:2020-12-03

    申请号:US16671093

    申请日:2019-10-31

    Applicant: Apple Inc.

    Abstract: Embodiments of the present disclosure present devices, methods, and computer readable medium for techniques for measuring operational performance metrics, and presenting these metrics through an application programming interface (API) for developers to access for optimizing their applications. Exemplary metrics can include central processing unit or graphics processing unit time, foreground/background time, networking bytes (per application), location activity, display average picture luminance, cellular networking condition, peak memory, number of logical writes, launch and resume time, frame rates, and hang time. Regional markers can also be used to measure specific metrics for in application tasks. The techniques provide multiple user interfaces to help developers recognize the important metrics to optimize the performance of their applications. The data can be normalized over various different devices having different battery size, screen size, and processing requirements. The user interfaces can provide an intelligent method for visualizing performance changes for significant changes in application versions.

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