Methods and systems for regulating resource usage

• US 8,271,651 B1
• Filed: 12/31/2003
• Issued: 09/18/2012
• Est. Priority Date: 12/31/2003
• Status: Expired due to Fees

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Lawrence, Stephen R., Ionescu, Mihai Florin, Wang, Niniane
• Primary Examiner(s): Lin, Kenny
• Assistant Examiner(s): Sciacca, Scott M
• Application Number:
  US10/750,128
• Time in Patent Office: 3,184 Days
• Field of Search: 709201-203, 709/205, 709/225, 709/228, 710/58, 710/267, 712/220, 712/228, 712/229, 718/102, 718/104
• US Class Current: 709/226
• CPC Class Codes: G06F 9/505 considering the load
• CPC Class Codes: H04L 67/303 Terminal profiles
• CPC Class Codes: H04L 67/61 taking into account QoS or priority requirements

Abstract

Methods and systems for regulating resource usage of an application are disclosed. A method of regulating usage of an application is disclosed that comprises receiving an operating parameter of a client device, assigning a value to a usage variable associated with the operating parameter of the client device, and correlating by an application a resource usage level of the application with the usage variable.

Claims

1. A method comprising:

receiving, by an application executed by an operating system, a plurality of operating parameters having values describing a plurality of different types of resources of a client device;

determining a value representing an estimate of current load on the client device based at least in part on a combination of the plurality of operating parameter values describing the plurality of different types of resources of the client device;

assigning the value representing the estimate of current load on the client device to a usage variable; and

correlating by the application a level of throttling of the application with the usage variable, the correlating comprising;

examining a representation of a mapping of estimates of load on the client device to levels of throttling, wherein each tuple in the mapping maps a particular estimate of load on the client device to a particular level of throttling;

identifying a tuple of the mapping for which the particular value of the estimate of load on the client device matches the estimate of current load on the client device; and

the application modifying its own execution to throttle its usage to the level of throttling specified by the identified tuple.

2. The method of claim 1, wherein the application modifying its own execution comprises the application suspending one or more operations when the value assigned to the usage variable exceeds a threshold.

3. The method of claim 1, wherein the application modifying its own execution comprises the application performing an activity affecting the usage variable within a threshold time of the usage variable indicating that the client device is performing an existing activity.

4. The method of claim 1, wherein the application modifying its own execution comprises the application adjusting a rate of operation based at least in part on the value assigned to the usage variable.

5. The method of claim 1, wherein the application modifying its own execution comprises the application adjusting a sequence of operations based at least in part on the value assigned to the usage variable.

6. The method of claim 1, wherein the application modifying its own execution comprises the application adjusting an active feature based at least in part on the value assigned to the usage variable.

7. The method of claim 1, wherein the client device comprises a client processor and a client memory storage device.

8. The method of claim 7, wherein receiving the plurality of operating parameters comprises receiving at least one of the plurality of operating parameters during an initial load of the client processor.

9. The method of claim 7, further comprising writing to a non-transitory computer readable storage medium of the client memory storage device.

10. The method of claim 7, wherein the plurality of operating parameters comprise a first parameter and a second parameter, the first parameter comprising a speed of the client processor and the second parameter comprising a capacity of the client memory storage device.

11. The method of claim 1, wherein receiving the plurality of operating parameters comprises monitoring at least one of the plurality of the operating parameters.

12. The method of claim 1, further comprising monitoring a period of inactivity of the client device.

13. The method of claim 1, wherein receiving the plurality of operating parameters comprises receiving at least one of the plurality of operating parameters during a predetermined time interval.

14. The method of claim 13, wherein at least one of the plurality of operating parameters comprises a client processor load.

15. The method of claim 1, wherein the usage variable is a quantitative performance measure of the client device.

16. The method of claim 1, wherein the usage variable is a qualitative performance measure of the client device.

17. The method of claim 1, wherein the application modifying its own execution further comprises the application throttling back its usage of the client device.

18. The method of claim 1, wherein the application dynamically modifies its own execution based on dynamic changes to the value assigned to the usage variable.

19. The method of claim 1, wherein the application modifying its own execution further comprises the application pausing between execution of resource-intensive calculations.

20. The method of claim 1, wherein a resource used by the application is memory and wherein the application modifying its own execution further comprises the application dynamically scaling back its memory usage based on dynamic changes to the value assigned to the usage variable.

21. The method of claim 1, wherein a resource used by the application is network bandwidth and wherein the application modifying its own execution further comprises the application throttling-back usage of network bandwidth based on dynamic changes to the value assigned to the usage variable.

22. The method of claim 1, wherein the representation of the mapping comprises a table having a column representing the usage variable and a column representing the resource usage level of the application and each tuple in the mapping corresponds to a row in the table.

23. The method of claim 1, wherein there are a plurality of usage variables and wherein the correlating comprises the application modifying its own execution based at least in part on changes to values assigned to the plurality of usage variables.

24. The method of claim 1, wherein the application modifying its own execution comprises the application combining an activity performed by the application with another activity performed on the client device, the combining reducing resources of the client device consumed by the combined activities.

25. The method of claim 24, wherein the combined activities are disk activities.

26. A non-transitory computer readable storage medium comprising instructions, that, when executed, cause an application to perform steps comprising:

receiving, by an application executed by an operating system, a plurality of operating parameters having values describing a plurality of different types of resources of a client device;

determining a value representing an estimate of current load on the client device based at least in part on a combination of the plurality of operating parameter values describing the plurality of different types of resources of the client device;

assigning the value representing the estimate of current load on the client device to a usage variable; and

correlating by the application a level of throttling of the application with the usage variable, the correlating comprising;

examining a representation of a mapping of estimates of load on the client device to levels of throttling, wherein each tuple in the mapping maps a particular value estimate of load on the client device to a particular level of throttling;

identifying a tuple of the mapping for which the particular value of the estimate of load on the client device matches the estimate of current load on the client device; and

the application modifying its own execution to throttle its usage to the level of throttling specified by the identified tuple.

27. The non-transitory computer readable storage medium of claim 26, wherein the application modifying its own execution comprises the application suspending one or more operations when the value assigned to the usage variable exceeds a threshold.

28. The non-transitory computer readable storage medium of claim 26, wherein the application modifying its own execution comprises the application performing an activity affecting the usage variable within a threshold time of the usage variable indicating that the client device is performing an existing activity.

29. The non-transitory computer readable storage medium of claim 26, wherein the application modifying its own execution comprises the application adjusting a rate of operation based at least in part on the value assigned to the usage variable.

30. The non-transitory computer readable storage medium of claim 26, wherein the application modifying its own execution comprises the application adjusting a sequence of operations based at least in part on the value assigned to the usage variable.

31. The non-transitory computer readable storage medium of claim 26, wherein the application modifying its own execution comprises the application adjusting an active feature based at least in part on the value assigned to the usage variable.

32. The non-transitory computer readable storage medium of claim 26, wherein the client device comprises a client processor and a client memory storage device.

33. The non-transitory computer readable storage medium of claim 32, wherein receiving the plurality of operating parameters comprises receiving at least one of the plurality of operating parameters during an initial load of the client processor.

34. The non-transitory computer readable storage medium of claim 32, wherein receiving the plurality of operating parameters comprises receiving at least one of the plurality of operating parameters during a predetermined time interval.

35. The non-transitory computer readable storage medium of claim 34, wherein at least one of the plurality of operating parameters comprises a client processor load.

36. The non-transitory computer readable storage medium of claim 32, further comprising instructions, that, when executed, cause the application to perform the step of writing to a non-transitory computer readable storage medium of the client memory storage device.

37. The non-transitory computer readable storage medium of claim 32, wherein the plurality of operating parameters comprise a first parameter and a second parameter, the first parameter comprising a speed of the client processor and the second parameter comprising a capacity of the client memory storage device.

38. The non-transitory computer readable storage medium of claim 26, further comprising instructions, that, when executed, cause the application to perform the step of monitoring a period of inactivity of the client device.

39. The non-transitory computer readable storage medium of claim 26, wherein receiving the plurality of operating parameters comprises monitoring at least one of the plurality of operating parameters.

40. The non-transitory computer readable storage medium of claim 26, wherein the representation of the mapping comprises a table having a column representing the usage variable and a column representing the resource usage level of the application and each tuple in the mapping corresponds to a row in the table.

41. A method comprising:

receiving, by an application executed by an operating system, a plurality of operating parameters having values describing a plurality of different types of resources of a client device;

determining a value representing an estimate of current load on the client device based at least in part on a combination of the plurality of operating parameter values;

examining a representation of a mapping comprising tuples, each tuple specifying a mapping from an estimate of load on the client device to a level of throttling, wherein the estimate of load specified in a tuple is based on a usage of a particular combination of resources of the client device;

identifying a tuple, in the representation of the mapping, for which the particular value of the estimate of load on the client device specified in the tuple matches the value representing the estimate of current load on the client device; and

modifying, by the application, execution of the application to throttle its usage to the level of throttling specified by the identified tuple.