Granted Patent B2

US 12,321,779 · App. 17/654,855 · Granted Jun 3, 2025

Inventors: Asmahan Ali (Poughkeepsie, NY); Daniel De Souza Casali (Elmhurst, NY); Abhishek Jain (Baraut, IN); Sarbajit K. Rakshit (Kolkata, IN)

Assignee: International Business Machines Corporation

G06F9/4881G06F3/0613G06F3/0647G06F3/067

Abstract

Claims (59)

1. A computer-implemented method, comprising:

identifying a set of predicted contextual situations based on a set of data sources and a set of applications associated with a cloud server;

determining data relevant to a respective predicted contextual situation, the data including one or more data sets and one or more data sources;

generating a set of event scores by assigning the respective predicted contextual situation of the set of contextual situations with a respective event score;

identifying a contextual situation, from the set of predicted contextual situations, associated with at least a portion of data sets available for migration to the cloud server, the data sets being provided by the set of data sources, and wherein the contextual situation is associated with an event score;

identifying an application associated with the contextual situation;

determining bandwidths for one or more data sources associated with the portion of data sets associated with the contextual situation;

selecting one or more data sets for prioritization based on priority scores of respective data sets associated with the contextual situation, wherein the priority scores are based on the event score of the contextual situation, a relevancy of the respective data sets to the contextual situation, and the bandwidth for the one or more data sources; and

scheduling a job processing sequence of the selected one or more data sets based on the priority scores.

2. The method of claim 1 , wherein determining data relevant to the respective predicted contextual situation further comprises:

classifying the data based on a respective relevancy of the data to one or more predicted contextual situations.

3. The method of claim 2 , further comprising:

determining, for the respective predicted contextual situation, a predicted amount of context relevant data to migrate to the cloud server.

4. The method of claim 3 , wherein data relevant to the respective predicted contextual situation is associated with one or more data types, the method further comprising:

determining one or more data types to be processed together for the respective predicted contextual situation.

5. The method of claim 4 , wherein the job processing sequence of the selected one or more data sets is further scheduled, at least in part, based on the predicted amount of context relevant data associated with the contextual situation, the one or more data types to be processed together for the contextual situation, and the priority score of the one or more data sets.

6. The method of claim 1 , further comprising:

determining a set of use characteristics for the data sets based on the contextual situation and the application; and

wherein scheduling the job processing sequence is further based on the set of use characteristics.

7. A system, comprising:

one or more processors; and

a computer-readable storage medium, coupled to the one or more processors, storing program instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising:

identifying a set of predicted contextual situations based on a set of data sources and a set of applications associated with a cloud server;

determining data relevant to a respective predicted contextual situation, the data including one or more data sets and one or more data sources;

generating a set of event scores by assigning the respective predicted contextual situation of the set of contextual situations with a respective event score;

identifying a contextual situation, from the set of predicted contextual situations, associated with at least a portion of data sets available for migration to the cloud server, the data sets being provided by the set of data sources, and wherein the contextual situation is associated with an event score;

identifying an application associated with the contextual situation;

determining bandwidths for one or more data sources associated with the portion of data sets associated with the contextual situation;

selecting one or more data sets for prioritization based on priority scores of respective data sets associated with the contextual situation, wherein the priority scores are based on the event score of the contextual situation, a relevancy of the respective data sets to the contextual situation, and the bandwidth for the one or more data sources; and

scheduling a job processing sequence of the selected one or more data sets based on the priority scores.

8. The system of claim 7 , wherein determining data relevant to the respective predicted contextual situation further comprises:

classifying the data based on the relevancy of the data to one or more predicted contextual situations.

9. The system of claim 8 , wherein the operations further comprise:

determining, for the respective predicted contextual situation, a predicted amount of context relevant data to migrate to the cloud server.

10. The system of claim 9 , wherein data relevant to the respective predicted contextual situation is associated with one or more data types, the operations further comprise:

determining one or more data types to be processed together for the respective predicted contextual situation.

11. The system of claim 10 , wherein the job processing sequence of the selected one or more data sets is further scheduled, at least in part, based on the predicted amount of context relevant data associated with the contextual situation, the one or more data types to be processed together for the contextual situation, and the priority score of the one or more data sets.

12. The system of claim 7 , wherein the operations further comprise:

determining a set of use characteristics for the data sets based on the contextual situation and the application; and

wherein scheduling the job processing sequence is further based on the set of use characteristics.

13. A computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions being executable by one or more processors to cause the one or more processors to perform operations comprising:

identifying a set of predicted contextual situations based on a set of data sources and a set of applications associated with a cloud server;

determining data relevant to a respective predicted contextual situation, the data including one or more data sets and one or more data sources;

generating a set of event scores by assigning the respective predicted contextual situation of the set of contextual situations with a respective event score;

identifying a contextual situation associated with at least a portion of data sets available for migration to a cloud server, the data sets being provided by a set of data sources, and wherein the contextual situation is associated with an event score;

identifying an application associated with the contextual situation;

determining bandwidths for one or more data sources associated with the portion of data sets associated with the contextual situation;

selecting one or more data sets for prioritization based on priority scores of respective data sets associated with the contextual situation, wherein the priority scores are based on the event score of the contextual situation, a relevancy of the respective data sets to the contextual situation, and the bandwidth for the one or more data sources; and

scheduling a job processing sequence of the selected one or more data sets based on the priority scores.

14. The computer program product of claim 13 , wherein determining data relevant to the respective predicted contextual situation further comprises:

classifying the data based on the relevancy of the data to one or more predicted contextual situations.

15. The computer program product of claim 14 , wherein the operations further comprise:

determining, for the respective predicted contextual situation, a predicted amount of context relevant data to migrate to the cloud server.

16. The computer program product of claim 15 , wherein data relevant to the respective predicted contextual situation is associated with one or more data types, the operations further comprise:

determining one or more data types to be processed together for the respective predicted contextual situation; and

wherein the job processing sequence of the selected one or more data sets is further scheduled, at least in part, based on the predicted amount of context relevant data associated with the contextual situation, the one or more data types to be processed together for the contextual situation, and the priority score of the one or more data sets.

17. The computer program product of claim 13 , wherein the operations further comprise:

determining a set of use characteristics for the data sets based on the contextual situation and the application; and

wherein scheduling the job processing sequence is further based on the set of use characteristics.

Assignments (1)

Continuity (1)

References Cited (24)