DESC:USER DRIVEN SMARTPHONE SCHEDULING ENHANCEMENT FOR RUNNING DATA ANALYTICS APPLICATION ,CLAIMS:
1. A method comprising:
analyzing a usage pattern of computational resources (402, 406, 506, 508, 510, 512) by one or more applications (102, 104, 106) executing on a computing device (400);
estimating, based on the analysis and historical data (428), a prospective utilization of the computational resources (402, 406, 506, 508, 510, 512) by one or more foreground applications (102, 104);
determining whether the prospective utilization would result in starvation of the computational resources (402, 406, 506, 508, 510, 512) for executing a data analytics application (306) on the computing device (400); and
based on the determining, prompting a user of the computing device (400) to proactively control the execution of the one or more foreground applications (102, 104) executing on the computing device (400) for successful execution of the data analytics application (306).

2. The method as claimed in claim 1, wherein the method further comprising retrieving the historical data (428) of a user-specific usage pattern of the computational resources (402, 406, 506, 508, 510, 512) based on a plurality of context parameters, and wherein the plurality of context parameters comprises time of day, day of week, month, year, user’s locations, user’s network cell, user’s mobility and user’s network usage.

3. The method as claimed in claim 2, wherein the retrieving is performed at regular intervals.

4. The method as claimed in claim 1, wherein the method further comprising executing the data analytics application (306) on the computing device (400) at periodic time intervals, and wherein the data analytics application (306) is designated as a user preferred background application.

5. The method as claimed in claim 1, wherein the method further comprising prioritizing the user preferred background application in an operating system scheduler module (414) of the computing device (400).

6. The method as claimed in claim 1, wherein the prompting is performed when a conditional map is present between the prospective utilization of the computational resources (402, 406, 506, 508, 510, 512) by the one or more foreground applications (102, 104) and the starvation of the computational resources (402, 406, 506, 508, 510, 512) for execution of the data analytics application (306).

7. The method as claimed in claim 1, wherein the proactively control of execution comprises one of a remove, pause, and preempt execution of at least one of the one or more foreground applications (102, 104).

8. The method as claimed in claim 1, wherein the method comprising based on the determining, notifying the user about automatic preemption.

9. The method as claimed in claim 1, wherein the one or more applications (102, 104, 106) comprises foreground applications (102, 104) and background applications (106, 306).

10. A computing device (400) comprising:
a processor (402);
an analyzing module (420), coupled to the processor (402), to:
analyze a usage pattern of computational resources (402, 406, 506, 508, 510, 512) by one or more applications (102, 104, 106) executing on the computing device;
estimate, based on the analysis and historical data (428), a prospective utilization of the computational resources (402, 406, 506, 508, 510, 512) by one or more foreground applications (102, 104); and
a notifier module (422), coupled to the processor (402), to:
determine whether the prospective utilization would result in starvation of the computational resources (402, 406, 506, 508, 510, 512) for executing a data analytics application (306) on the computing device (400); and
based on the determining, prompt a user of the computing device (400) to proactively control the execution of the one or more foreground applications (102, 104) executing on the computing device (400) for executing the data analytics application (306).

11. The computing device (400) as claimed in claim 10, wherein notifier module (422) prompts the user when a conditional map is present between the prospective utilization of the computational resources (402, 406, 506, 508, 510, 512) by the one or more foreground applications (102, 104) and the starvation of the computational resources (402, 406, 506, 508, 510, 512) for execution of the data analytics application (306).

12. The computing device (400) as claimed in claim 10, wherein notifier module (422) notifies the user about automatic preemption based on the determining.

13. The computing device (400) as claimed in claim 10, wherein the computing device (400) further comprising a configuration module (418) to designate the data analytics application (306) as a user preferred background application.

14. The computing device (400) as claimed in claim 13, wherein the computing device (400) further comprising a scheduler enhancement module (424) to prioritize the user preferred background application in an operating system scheduler (414) of the computing device (400).

15. The computing device (400) as claimed in claim 10, wherein the computing device (400) further comprising a usage monitoring module (416) to retrieve the historical data (428) of a user-specific usage pattern of the computational resources (402, 406, 506, 508, 510, 512), at regular time intervals, based on a plurality of context parameters, and wherein the plurality of context parameters comprises time of day, day of week, month, year, user’s locations, user’s network cell, user’s mobility and user’s network usage.

16. The computing device (400) as claimed in claim 10, wherein the proactively control of execution comprises one of a remove, pause, and preempt execution of at least one of the one or more foreground applications (102, 204) executing on the computing device (400).

17. The computing device (400) as claimed in claim 10, wherein the one or more applications (102, 104, 106) comprises foreground applications (102, 104) and background applications (106, 306).