Multi-mode device power-saving optimization
    1.
    发明授权
    Multi-mode device power-saving optimization 有权
    多模式设备省电优化

    公开(公告)号:US09244518B2

    公开(公告)日:2016-01-26

    申请号:US13721605

    申请日:2012-12-20

    申请人: XEROX Corporation

    IPC分类号: G06F1/32 G06F3/12

    摘要: Methods and systems input an energy consumption profile for each of a plurality of different sleep modes available for a device, and input a probability distribution of interjob times for the device. The methods and systems then compute the optimal time-out period for each sleep mode based on the energy consumption profile of each sleep mode and the probability distribution of interjob times. Further, such methods and systems monitor the usage of the device to determine the current interjob time, and switch between sleep modes to relatively lower power sleep modes as the current interjob time becomes larger.

    摘要翻译: 方法和系统为可用于设备的多个不同睡眠模式中的每一个输入能量消耗简档,并输入设备的间隔时间的概率分布。 然后,方法和系统基于每个睡眠模式的能量消耗曲线和间歇时间的概率分布来计算每个睡眠模式的最佳超时周期。 此外,这样的方法和系统监视设备的使用以确定当前的间隔时间,并且当当前间隔时间变大时,在休眠模式之间切换到相对较低的功率睡眠模式。

    MULTI-MODE DEVICE POWER-SAVING OPTIMIZATION
    2.
    发明申请
    MULTI-MODE DEVICE POWER-SAVING OPTIMIZATION 有权
    多模式设备省电优化

    公开(公告)号:US20140181552A1

    公开(公告)日:2014-06-26

    申请号:US13721605

    申请日:2012-12-20

    申请人: XEROX CORPORATION

    IPC分类号: G06F1/32

    摘要: Methods and systems input an energy consumption profile for each of a plurality of different sleep modes available for a device, and input a probability distribution of interjob times for the device. The methods and systems then compute the optimal time-out period for each sleep mode based on the energy consumption profile of each sleep mode and the probability distribution of interjob times. Further, such methods and systems monitor the usage of the device to determine the current interjob time, and switch between sleep modes to relatively lower power sleep modes as the current interjob time becomes larger.

    摘要翻译: 方法和系统为可用于设备的多个不同睡眠模式中的每一个输入能量消耗简档,并输入设备的间隔时间的概率分布。 然后,方法和系统基于每个睡眠模式的能量消耗曲线和间歇时间的概率分布来计算每个睡眠模式的最佳超时周期。 此外,这样的方法和系统监视设备的使用以确定当前的间隔时间,并且当当前间隔时间变大时,在休眠模式之间切换到相对较低的功率睡眠模式。