User Presence Prediction Driven Device Management

Patent metadata

Field	Value
Publication number	US-2020183747-A1
Application number	US-201916724875-A
Country	US
Kind code	A1
Filing date	Dec 23, 2019
Priority date	Feb 19, 2016
Publication date	Jun 11, 2020
Grant date	—

Abstract

Pooling computing resources based on inferences about a plurality of hardware devices. The method includes identifying inference information about the plurality of devices. The method further includes based on the inference information optimizing resource usage of the plurality of hardware devices.

First claim

1 - 20 . (canceled)

21 . A method of managing a computing resource of a computing device of a user who has access to one or more additional computing devices, the method comprising:
receiving, at the computing device of the user, a request to consume a hardware resource from the computing device for execution of a task; and in response to receiving the request,
determining, based on a usage model of the user, that the user is to lose access to functionality of the hardware resource of the computing device after a period of time, the usage model containing records of one or more usage patterns of the computing device by the user; and
in response to determining that the user is to lose access to the functionality of the hardware resource of the computing device after the preset period of time,
prioritizing execution of the task at the computing device over other tasks executed at the computing device before access to the functionality of the hardware resource of the computing device is lost;
preventing additional tasks that would use the hardware resources of the computing device from being assigned to the computing device; and
disabling the hardware resource of the computing device after the period of time expires.

22 . The method of claim 21 , further comprising:
identifying, based on the usage model of the user, another computing device of the user that is accessible to the user; and offloading, from the computing device, the execution of the task to the another computing device.

23 . The method of claim 21 , further comprising:
identifying, based on the usage model of the user, another period of time after which the user has access to another computing device of the user; determining whether the identified another period of time is within a predetermined threshold; and in response to determining that the identified another period of time is within the predetermined threshold,
preventing execution of the task at the computing device; and
upon elapse of the identified another period of time, offloading, from the computing device, the execution of the task to the another computing device.

24 . The method of claim 21 wherein the hardware resource includes one or more of processor cycles, network bandwidths, memory capacity, or storage capacity.

25 . The method of claim 21 wherein the usage patterns include records individually containing data representing a time, a location, and one or more activities performed at the time and location by the computing device and the another computing device.

26 . The method of claim 21 wherein the one or more usage patterns include records individually containing data representing multiple usage patterns of the user, and wherein identifying the another period of time includes selecting one of the multiple usage patterns based on a time or location at which the request is received.

27 . The method of claim 21 , further comprising:
in response to determining that the user is to lose access to the functionality of the hardware resource of the computing device after the preset period of time,
determining, based on the usage model, whether the computing device and the another computing device are proximate to each other such that the user has access to both the computing device and the another computing device; and
in response to determining that the computing device and the another computing device are proximate to each other such that the user has access to both the computing device and the another computing device, executing the task using the hardware resource from both the computing device and the another computing device.

28 . A server for managing a hardware resource of a computing device of a user, the server comprising:
a processor; and a memory operatively coupled to the processor, the memory having instructions executable by the processor to cause the server to:
upon receiving a request to consume the hardware resource from the computing device for execution of a task,
determine, based on a usage model of the user, that the user is to lose access to functionality of the hardware resource of the computing device after a period of time, the usage model containing records of one or more usage patterns of the computing device by the user; and
in response to determining that the user is to lose access to the functionality of the hardware resource of the computing device after the preset period of time,
prioritize execution of the task at the computing device over other tasks executed at the computing device before access to the functionality of the hardware resource of the computing device is lost; and
disable the hardware resource of the computing device after the period of time expires.

29 . The server of claim 28 wherein the hardware resource includes one or more of processor cycles, network bandwidths, memory capacity, or storage capacity.

30 . The server of claim 28 wherein the usage patterns include records individually containing data representing a time, a location, and one or more activities performed at the time and location by the computing device.

31 . The server of claim 28 wherein the memory includes additional instructions executable by the processor to cause the server to identify, based on the usage model of the user, another computing device of the user that is accessible to the user and offload, from the computing device, the execution of the task to the another computing device.

32 . The server of claim 31 wherein the one or more usage patterns include records individually containing data representing multiple usage patterns of the user, and wherein to determine whether the user has access to the another computing device includes to select one of the multiple usage patterns based on a time or location at which the request is received and utilize the selected one of the multiple usage patterns to determine whether the user has access to the another computing device.

33 . The server of claim 28 wherein the memory includes additional instructions executable by the processor to cause the server to:
determine, based on the usage model of the user, whether the user is to lose access to the another computing device after a preset period of time; and
in response to determining that the user is to lose access to the another computing device after the preset period of time, instruct the another computing device to prevent additional tasks being offloaded to the second computing device.

34 . The server of claim 28 wherein the memory includes additional instructions executable by the processor to cause the server to:
determine, based on the usage model, whether the computing device and the another computing device are proximate to each other such that the user has access to both the computing device and the another computing device; and
in response to determining that the computing device and the another computing device are proximate to each other such that the user has access to both the computing device and the another computing device, execute the task using the hardware resource from both the computing device and the another computing device.

35 . A method of managing a hardware resource of first and second computing devices of a user, the method comprising:
receiving, at the first computing device of the user, a request to consume the hardware resource from the first computing device for execution of a task; and in response to receiving the request,
determining, based on a usage model of the user, whether the user has access to the second computing device within a predetermined time t

Assignees

• Microsoft Technology Licensing Llc

Inventors

• Kishan Arun U
• Wilson Emily Nicole
• Soliman Mohammed Nashaat
• Maisuria Paresh
• Weinberg Shira
• Virdi Gurpreet
• Brown Jared

Classifications

• G06N7/01

  Probabilistic graphical models, e.g. probabilistic networks · CPC title

• G06F9/5027 Primary

  the resource being a machine, e.g. CPUs, Servers, Terminals · CPC title

• Y02D10/00

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

• G06F9/46

  Multiprogramming arrangements · CPC title

• G06F9/5088

  involving task migration · CPC title