Methods, systems, articles of manufacture, and apparatus to dynamically schedule a wake pattern in a computing system

Patent metadata

Field	Value
Publication number	US-12346191-B2
Application number	US-202017928595-A
Country	US
Kind code	B2
Filing date	Jun 26, 2020
Priority date	Jun 26, 2020
Publication date	Jul 1, 2025
Grant date	Jul 1, 2025

Abstract

Methods, apparatus, systems and articles of manufacture are disclosed to dynamically schedule a wake pattern in a computing system. An example apparatus includes a device state controller to determine contexts of a device based on sensor measurements collected at a first time, an associator to associate a state of an operating system with the contexts of the device, the state obtained at a second time after the first time, a training controller to generate a prediction model based on the association, the prediction model to predict a third time when the state of the operating system will be active based on the contexts, and a schedule controller to reduce power consumption of the device by triggering a wake event before the third time, the wake event to prepare the device for exiting an inactive state.

First claim

What is claimed is:

1. An apparatus comprising:
at least one memory;
machine readable instructions; and
at least one processor circuit to be programmed by the machine readable instructions to:
generate a first histogram corresponding to a frequency of at least one context of a device based on first sensor measurements collected over a time period;
generate a second histogram corresponding to a frequency of a state of an operating system over the time period;
generate a third histogram corresponding to an association of (a) the frequency of the at least one context of the device and (b) the frequency of the state of the operating system over the time period; and
generate a prediction model based on the association, the prediction model to predict times when the state of the operating system will be one of in an active state or an inactive state based on the at least one context, the prediction model to cause transmission of a wake event trigger to the device based on the predicted times corresponding to the active state.

2. The apparatus of claim 1 , wherein one or more of the at least one processor circuit is to determine activity of a user of the device based on at least one of a lid mode of the device, a location of the device, or a motion of the device.

3. The apparatus of claim 1 , wherein one or more of the at least one processor circuit is to store the at least one context for a maximum predictable time.

4. The apparatus of claim 3 , wherein one or more of the at least one processor circuit is to determine the maximum predictable time based on a duration between (a) a user action and (b) a time corresponding to activation of the operating system.

5. The apparatus of claim 1 , wherein one or more of the at least one processor circuit is to query a standby management system for the state of the operating system in response to obtaining the at least one context.

6. At least one non-transitory machine-readable storage medium comprising machine-readable instructions to cause at least one processor circuit to at least:
generate a first histogram corresponding to a frequency of at least one context of a device based on first sensor measurements collected over a time period;
generate a second histogram corresponding to a frequency of a state of an operating system over the time period;
generate a third histogram corresponding to an association of (a) the frequency of the at least one context of the device and (b) the frequency of the state of the operating system over the time period; and
generate a prediction model based on the association, the prediction model to predict times when the state of the operating system will be one of in an active state or an inactive state based on the at least one context, the prediction model to cause transmission of a wake event trigger to the device based on the predicted times corresponding to the active state.

7. The at least one non-transitory machine-readable storage medium of claim 6 , wherein the machine-readable instructions are to cause one or more of the at least one processor circuit to determine activity of a user of the device based on at least one of a lid mode of the device, a location of the device, or a motion of the device.

8. The at least one non-transitory machine-readable storage medium of claim 6 , wherein the machine-readable instructions are to cause one or more of the at least one processor circuit to store the at least one context for a maximum predictable time.

9. The at least one non-transitory machine-readable storage medium of claim 8 , wherein the machine-readable instructions are to cause one or more of the at least one processor circuit to determine the maximum predictable time based on a duration between (a) a user action and (b) a time corresponding to activation of the operating system.

10. The at least one non-transitory machine-readable storage medium of claim 6 , wherein the machine-readable instructions are to cause one or more of the at least one processor circuit to query a standby management system for the state of the operating system in response to obtaining the at least one context.

11. A method comprising:
generating a first histogram corresponding to a frequency of at least one context of a device based on first sensor measurements collected over a time period;
generating a second histogram corresponding to a frequency of a state of an operating system over the time period;
generating a third histogram corresponding to an association of (a) the frequency of the at least one context of the device and (b) the frequency of the state of the operating system over the time period; and
generating, by at least one processor circuit programmed by at least one instruction, a prediction model based on the association, the prediction model to predict times when the state of the operating system will be one of in an active state or an inactive state based on the at least one context, the prediction model to cause transmission of a wake event trigger to the device based on the predicted times corresponding to the active state.

12. The method of claim 11 , further including determining activity of a user of the device based on at least one of a lid mode of the device, a location of the device, or a motion of the device.

13. The method of claim 11 , further including storing the at least one context for a predetermined period of time, the predetermined period of time corresponding to a maximum predictable time.

14. The method of claim 13 , further including determining the maximum predictable time based on a duration between (a) a user action and (b) a time corresponding to activation of the operating system.

15. The method of claim 11 , further including querying a standby management system for the state of the operating system in response to obtaining the at least one context, the query to occur at a predetermined period of time after the first time.

Assignees

• Intel Corp

Inventors

• Han Hemin
• Han Ke
• Ma Lili
• Lv Mengchun
• Sun Shouwei

Classifications

• G06F1/3231

  Monitoring the presence, absence or movement of users · CPC title

• Y02D10/00

  Energy efficient computing, e.g. low power processors, power management or thermal management · CPC title

• G06N20/00

  Machine learning · CPC title

• G06F18/25

  Fusion techniques · CPC title

• G06F18/26

  Discovering frequent patterns · CPC title