Incentive-based app execution

• US 9,760,401 B2
• Filed: 11/14/2015
• Issued: 09/12/2017
• Est. Priority Date: 02/24/2014
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Inventors: Burger, Douglas C., Massey, Daniel Lee, De Smet, Bart J. F., Aguera y Arcas, Blaise Hilary
• Primary Examiner(s): Siddiqui, Kashif
• Application Number:
  US14/941,576
• Publication Number:
  US 20160147567A1
• Time in Patent Office: 668 Days
• CPC Class Codes: G06F 21/123 by using dedicated hardware, e.g. dongles, smart cards, cryptographic processors, global positioning systems [GPS] devices
• CPC Class Codes: G06F 21/62 Protecting access to data via a platform, e.g. using keys or access control rules
• CPC Class Codes: G06F 9/445 Program loading or initiating bootstrapping G06F9/4401; security arrangements for program loading or initiating G06F21/57
• CPC Class Codes: G06F 9/4881 Scheduling strategies for dispatcher, e.g. round robin, multi-level priority queues

Abstract

Systems and methods of a personal daemon, executing as a background process on a mobile computing device, for providing personal assistant to an associated user is presented. Also executing on the mobile computing device is a scheduling manager. The personal daemon executes one or more personal assistance actions on behalf of the associated user. The scheduling manager responds to events in support of the personal daemon. More particularly, in response to receiving an event the scheduling manager determines a set of apps that are responsive to the received event and from that set of apps, identifies at least a first subset of apps for execution on the mobile computing device. The scheduling manager receives feedback information regarding the usefulness of the executed apps of the first subset of apps and updates the associated score of each of the apps of the first subset of apps.

Claims

1. A mobile computing device configured to provide personal assistance to an associated user, the computing device comprising a processor and a memory, wherein the processor executes instructions to provide personal assistant to the associated user in conjunction with additional components, the additional components comprising:

a scheduling manager, wherein in execution on the mobile computing device, the scheduling manager is configured to;

receive notice of an event;

determine a set of apps that are responsive to the event;

determine a first subset of apps of the determined set of apps according to a score associated with each of the apps of the set of apps, wherein the first subset of apps includes apps with an associated score that meets or exceeds a predetermined threshold; and

execute the apps of the first subset of apps on the mobile computing device.

2. The computing device of claim 1, wherein the scheduling manager is further configured to:

obtain feedback information regarding the usefulness of the executed apps of the first subset of apps; and

update the associated score of each of the apps of the first subset of apps.

3. The computing device of claim 1, wherein the scheduling manager is further configure to:

determine a second subset of apps of the determined set of apps according to the score associated with each of the apps of the set of apps, wherein the second subset of apps includes apps with an associated score that meets or exceeds a second predetermined threshold;

cause the execution of the apps of the second subset of apps on one or more remote computing devices;

obtain feedback information regarding the usefulness of the executed apps of the second subset of apps; and

update the associated score of each of the apps of the second subset of apps.

4. The computing device of claim 3, wherein at least one of the one or more remote computing devices is a sibling device executing a personal daemon associated with the associated user.

5. The computing device of claim 3, wherein determining the first subset of apps according to a score associated with each of the apps of the set of apps comprises determining a first subset of apps according to a score associated with each of the apps of the set of apps for a set of current contextual factors.

6. The computing device of claim 5, wherein determining the second subset of apps according to a score associated with each of the apps of the set of apps comprises determining a second subset of apps according to a score associated with each of the apps of the set of apps for the set of current contextual factors.

7. The computing device of claim 6, wherein the set of current contextual factors includes any one or more of the current processing capacity of the mobile computing device, the current processing capacity comprising one or more of the processing load of the mobile computing device, the processing capabilities of the mobile computing device, the current capacity of the mobile computing device'"'"'s power supply, the availability and bandwidth of network connectivity, and availability of data or resources.

8. The computing device of claim 4 further comprising a machine learning engine configured to:

obtain the feedback information regarding the usefulness of the executed apps of the first subset of apps; and

update the scores of the associated score of each of the apps of the first subset of apps according to the obtained feedback and the set of current contextual factors.

9. A computing device implemented method for providing personal assistance to an associated user, the method comprising each of the following as implemented on a mobile computing device:

executing a scheduling manager on the mobile computing device, wherein the scheduling manager responds to one or more events, and in response to receiving an event, the scheduling manager is configure to;

determine a set of apps that are responsive to the received event;

determine a first subset of apps of the determined set of apps according to a score associated with each of the apps of the set of apps, wherein the first subset of apps includes apps with an associated score that meets or exceeds a predetermined threshold; and

execute the apps of the first subset of apps on the mobile computing device.

10. The computing device implemented method of claim 9, wherein the scheduling manager is further configured to:

obtain feedback information regarding the usefulness of the executed apps of the first subset of apps; and

update the associated score of each of the apps of the first subset of apps according to the obtained feedback regarding the usefulness of the executed apps of the first subset of apps.

11. The computing device implemented method of claim 9, wherein the scheduling manager is further configure to:

determine a second subset of apps of the determined set of apps according to the score associated with each of the apps of the set of apps, wherein the second subset of apps includes apps with an associated score that meets or exceeds a second predetermined threshold;

cause the execution of the apps of the second subset of apps on one or more remote computing devices;

obtain feedback information regarding the usefulness of the executed apps of the second subset of apps; and

update the associated score of each of the apps of the second subset of apps according to the obtained feedback information regarding the usefulness of the executed apps of the second subset of apps.

12. The computing device implemented method of claim 11, wherein:

determining the first subset of apps according to a score associated with each of the apps of the set of apps comprises determining a first subset of apps according to a score associated with each of the apps of the set of apps for a set of current contextual factors; and

determining the second subset of apps according to a score associated with each of the apps of the set of apps comprising determining a second subset of apps according to a score associated with each of the apps of the set of apps for the set of current contextual factors.

13. The computing device implemented method of claim 12, wherein the set of current contextual factors includes one or more of the current processing capacity of the mobile computing device, the current processing capacity comprising one or more of the processing load of the mobile computing device, the processing capabilities of the mobile computing device, the current capacity of the mobile computing device'"'"'s power supply, the availability and bandwidth of network connectivity, and availability of data or resources.

14. The computing device implemented method of claim 12, wherein the set of current contextual factors includes one or more of the current time of day, the current day of week, the current day of year, and whether the current day is a holiday or in a holiday season.

15. A computer readable medium bearing computer executable instructions which, when executed on a mobile computing device having at least a processor and a memory, carry out a method for providing personal assistance to a user, the method comprising:

executing a scheduling manager on the mobile computing device, wherein the scheduling manager responds to one or more events in support of the personal daemon, and in response to receiving an event, the scheduling manager is configure to;

determine a set of apps that are responsive to the received event;

determine a first subset of apps of the determined set of apps according to a score associated with each of the apps of the set of apps in view of a set of current contextual factors, wherein the first subset of apps includes apps with an associated score that meets or exceeds a predetermined threshold; and

execute the apps of the first subset of apps on the mobile computing device.

16. The computer readable medium of claim 15, wherein the scheduling manager is further configured to:

determine a second subset of apps of the determined first subset of apps according to the score associated with each of the apps of the set of apps in view of the set of current contextual factors, wherein the second subset of apps includes apps with an associated score that meets or exceeds a second predetermined threshold; and

cause the execution of the apps of the second subset of apps on one or more remote computing devices, wherein at least one of the one or more remote computing devices is a sibling device executing a personal daemon associated with the associated user.

17. The computer readable medium of claim 16, wherein the scheduling manager is further configured to:

obtain feedback information regarding the usefulness of the executed apps of the first subset of apps and the second subset of apps; and

update the associated score of each of the apps of the first subset of apps and the second subset of apps.

18. The computer readable medium of claim 17, wherein the method further comprises:

executing a machine learning engine on the mobile computing device, wherein the machine learning engine is configured to;

obtain the feedback information regarding the usefulness of the executed apps of the first subset of apps and the second subset of apps; and

update the scores of the associated score of each of the apps of the first subset of apps and second subset of apps according to the obtained feedback and the set of current contextual factors.