ADAPTIVE TERMINATION AND PRE-LAUNCHING POLICY FOR IMPROVING APPLICATION STARTUP TIME

• US 20120324481A1
• Filed: 06/16/2011
• Published: 12/20/2012
• Est. Priority Date: 06/16/2011
• Status: Abandoned Application

• Current Assignee: Samsung Electronics Co. Ltd.
• Original Assignee: Samsung Electronics Co. Ltd.
• Inventors: LAM, Ioi Kim, XIA, Bing
• Application Number:
  US13/161,703
• Publication Number:
  US 20120324481A1
• Time in Patent Office: Days
• US Class Current: 719/320
• CPC Class Codes: G06F 9/485 Task life-cycle, e.g. stopping, restarting, resuming execution G06F9/4881 takes precedence

Abstract

A method and device for adaptively determining processes to kill when a low memory situation is detected, and for adaptively determining processes to pre-launch, are disclosed. The method for determining processes to kill includes tracking statistics of application launching behaviors, predicting application behaviors under certain system states in accordance with the tracked statistics, detecting a certain system state, and, if the certain system state is detected, adaptively selecting an application loaded in a cache memory to kill in accordance with the predicted behaviors. The method of determining processes to pre-launch includes tracking statistics of application launching behaviors, predicting application behaviors under certain system states in accordance with the tracked statistics, detecting a certain system state, and, if the certain system state is detected, adaptively selecting and pre-launching an application by loading the selected application into cache memory in accordance with the predicted behaviors and the certain system state.

Claims

1. A method for adaptively determining processes to kill when a low memory situation is detected, the method comprising:

tracking statistics of application launching behaviors;

predicting application behaviors under certain system states in accordance with the tracked statistics;

detecting a certain system state; and

if the certain system state is detected, adaptively selecting an application loaded in a cache memory to kill in accordance with the predicted application behaviors and the certain system state.

2. The method of claim 1, wherein the application launching behaviors comprise a startup time of a cold launch of an application when not loaded in the cache memory.

3. The method of claim 2, further comprising, if the startup time of the cold launch of the application is relatively longer than a startup time of a cold launch of another application, reducing a probability of killing the application comprising the relatively longer startup time in comparison to a probability of killing the other application comprising the relatively shorter startup time.

4. The method of claim 3, wherein the application launching behaviors further comprise a startup time of a warm launch of an application loaded in a cache.

5. The method of claim 4, wherein the application launching behaviors further comprise a cold and warm startup time spread in accordance with a current system load.

6. The method of claim 5, further comprising, if the cold and warm startup time spread of the application is relatively longer than a cold and warm startup time spread of the other application, reducing a probability of killing the application comprising the relatively longer cold and warm startup time spread in comparison to a probability of killing the other application comprising the relatively shorter cold and warm startup time spread.

7. The method of claim 1, wherein the application launching behaviors comprise one or more of a cache memory usage of an application, a frequency of launching of the application, a time of day of a launch of the application, and a geolocation of a device launching the application.

8. The method of claim 7, wherein the predicting comprises determining a probability of the application being launched in a near future time based on one or more of the tracked frequency of the launch, time of day of the launch, and geolocation of the device.

9. The method of claim 8, further comprising, if the predicted probability of the application being launched in the near future is relatively higher than a predicted probability of another application being launched in the near future, reducing a probability of killing the application comprising the relatively higher predicted probability of being launched in the near future in comparison to a probability of killing the other application comprising the relatively lower predicted probability of being launched in the near future.

10. A portable digital device utilizing the method of claim 1.

11. A method for adaptively determining processes to pre-launch, the method comprising:

tracking statistics of application launching behaviors;

predicting application behaviors under certain system states in accordance with the tracked statistics;

detecting a certain system state; and

if the certain system state is detected, adaptively selecting an application to pre-launch and pre-launching the selected application by loading the selected application into a cache memory in accordance with the predicted behaviors and the certain system state.

12. The method of claim 11, wherein the application launching behaviors comprise a startup time of a cold launch of the selected application when not loaded in a cache.

13. The method of claim 12, further comprising, if the startup time of the cold launch of the selected application is relatively longer than a startup time of a cold launch of another application, increasing a probability of pre-launching the selected application comprising the relatively longer startup time in comparison to a probability of pre-launching the other application comprising the relatively shorter startup time.

14. The method of claim 13, wherein the application launching behaviors further comprise a startup time of a warm launch of an application loaded in the cache memory.

15. The method of claim 14, wherein the application launching behaviors further comprise a cold and warm startup time spread in accordance with a current system load.

16. The method of claim 15, further comprising, if the cold and warm startup time spread of the selected application is relatively longer than a cold and warm startup time spread of the other application, increasing a probability of pre-launching the selected application comprising the relatively longer cold and warm startup time spread in comparison to a probability of pre-launching the other application comprising the relatively shorter cold and warm startup time spread.

17. The method of claim 11, wherein the application launching behaviors comprise one or more of a cache memory usage of an application, a frequency of launching of the application, a time of day of a launch of the application, and a geolocation of a device launching the application.

18. The method of claim 17, wherein the predicting comprises determining a probability of the application being launched in a near future time based on one or more of the tracked frequency of the launch, time of day of the launch, and geolocation of the device.

19. The method of claim 18, further comprising, if the predicted probability of the application being launched in the near future is relatively higher than a predicted probability of another application being launched in the near future, increasing a probability of pre-launching the application comprising the relatively higher predicted probability of being launched in the near future in comparison to a probability of pre-launching the other application comprising the relatively lower predicted probability of being launched in the near future.

20. A portable digital device utilizing the method of claim 11.