System and method for performing dynamic orchestration of rules in a big data environment

• US 10,545,973 B2
• Filed: 07/28/2016
• Issued: 01/28/2020
• Est. Priority Date: 07/28/2016
• Status: Active Grant

• Current Assignee: Wipro Limited
• Original Assignee: Wipro Limited
• Inventors: Shah, Vikas
• Primary Examiner(s): Bibbee, Jared M
• Application Number:
  US15/222,776
• Publication Number:
  US 20180032565A1
• Time in Patent Office: 1,279 Days
• CPC Class Codes: G06F 16/2465 Query processing support for facilitating data mining operations in structured databases

Abstract

The present disclosure relates to a method and system for performing dynamic orchestration of rules. The system monitors activities performed by entity in the big data environment to detect events. The events are associated with product/service. Further, the system determines scenario by analyzing data pertaining to the product or the service. The scenario comprises one or more scenario categories. Further, the scenario is correlated with the events based on the one or more scenario categories. The correlation is further validated by the system based on dimensions. Further, the system derives one or more rules for each of the correlation of the scenario and the events upon validation. The system may further apply an operational constraints and migration controls to the one or more rules to perform dynamic orchestration. Thus, the system provides one-stop solution for deriving the rules based on context of the scenarios and migrating them to target systems.

Claims

1. A method for performing dynamic orchestration of rules in a big data environment, the method comprising:

monitoring, by a rule orchestration device, activities performed by an entity in the big data environment to detect one or more events, wherein the one or more events are associated with at least one of a product or a service;

determining, by the rule orchestration device, at least one scenario by analyzing data associated with consumer buying behavior and historical data of the at least one of the product and the service, wherein the at least one scenario comprises one or more scenario categories, wherein the one or more scenario categories are determined based on a utilization map associated with the at least one of the product and the service or interrelationship among the product and the service;

correlating, by the rule orchestration device, the at least one scenario with the one or more events based on the one or more scenario categories;

validating, by the rule orchestration device, the correlation between the at least one scenario and the one or more events based on one or more dimensions, wherein the one or more dimensions indicate features of consumer buying behavior that affect the at least one scenario;

deriving, by the rule orchestration device, one or more rules and corresponding rule hierarchies for each of the correlation of the at least one scenario and the one or more events upon validation; and

applying, by the rule orchestration device, at least one of operational constraints and migration controls to the one or more rules to perform dynamic orchestration.

2. The method as claimed in claim 1, wherein the determining the at least one scenario further comprises:

receiving, by the rule orchestration device, one or more predefined scenarios from a scenario database;

comparing, by the rule orchestration device, the at least one scenario with the one or more predefined scenarios to determine whether the at least one scenario is preexisting in the scenario database; and

updating, by the rule orchestration device, the at least one scenario in the scenario database based on the comparing.

3. The method as claimed in claim 1, wherein the determining the at least one scenario further comprises validating the at least one scenario based on the one or more dimensions.

4. The method as claimed in claim 1 further comprises:

determining, by the rule orchestration device, whether the one or more dimensions are defined to correlate with the at least one scenario;

associating, by the rule orchestration device, the data pertaining to the at least one of the product and the service with big data query specification based on the determining; and

deriving, by the rule orchestration device, the one or more dimensions based on the association.

5. The method as claimed in claim 1, wherein the one or more dimensions comprises at least one of predefined technology dimensions, application dimensions, social dimensions, economic dimensions, geolocation dimensions and legal dimensions.

6. The method as claimed in claim 1, wherein the deriving the one or more rules further comprises:

determining, by the rule orchestration device, whether the one or more rules are predefined in a rule database;

identifying, by the rule orchestration device, a level of the one or more rules based on a rules hierarchy based on the determining, wherein the rules hierarchy is updated dynamically based on the data pertaining to the at least one of the product and the service; and

adding, by the rule orchestration device, the one or more rules to the rule database along with the level.

7. The method as claimed in claim 1 further comprises:

deriving, by the rule orchestration device, the migration controls to continuously migrate the one or more rules to one or more target systems; and

defining, by the rule orchestration device, the operational constraints in association with the migration controls.

8. A rule orchestration device for performing dynamic orchestration of rules in a big data environment, the rule orchestration device comprising:

a processor; and

a memory communicatively coupled to the processor, wherein the memory stores processor-executable instructions, which, on execution, causes the processor to;

monitor activities performed by an entity in the big data environment to detect one or more events, wherein the one or more events are associated with at least one of a product and a service;

determine at least one scenario by analyzing data associated with consumer buying behavior and historical data of the at least one of the product and the service, wherein the at least one scenario comprises one or more scenario categories, wherein the one or more scenario categories are determined based on a utilization map associated with the at least one of the product and the service or interrelationship among the product and the service;

correlate the at least one scenario with the one or more events based on the one or more scenario categories;

validate the correlation between the at least one scenario and the one or more events based on one or more dimensions, wherein the one or more dimensions indicate features of consumer buying behavior that affect the at least one scenario;

derive one or more rules and corresponding rule hierarchies for each of the correlation of the at least one scenario and the one or more events upon validation; and

apply at least one of operational constraints and migration controls to the one or more rules to perform dynamic orchestration.

9. The rule orchestration device as claimed in claim 8 determines the at least one scenario by further performing steps to:

receive one or more predefined scenarios from a scenario database;

compare the at least one scenario with the one or more predefined scenarios to determine whether the at least one scenario is preexisting in the scenario database; and

update the at least one scenario in the scenario database based on the comparing.

10. The rule orchestration device as claimed in claim 8 determines the at least one scenario by validating the at least one scenario based on the one or more dimensions.

11. The rule orchestration device as claimed in claim 8 further configured to:

determine whether the one or more dimensions are defined to correlate with the at least one scenario;

associate the data pertaining to the at least one of the product and the service with big data query specification based on the determining; and

derive the one or more dimensions based on the association.

12. The rule orchestration device as claimed in claim 8, wherein the one or more dimensions comprises at least one of predefined technology dimensions, application dimensions, social dimensions, economic dimensions, geolocation dimensions and legal dimensions.

13. The rule orchestration device as claimed in claim 8 derives the one or more rules by performing steps to:

determine whether the one or more rules are predefined in a rule database;

identify a level of the one or more rules based on a rules hierarchy based on the determining, wherein the rules hierarchy is updated dynamically based on the data pertaining to the at least one of the product and the service; and

add the one or more rules to the rule database along with the level.

14. The rule orchestration device as claimed in claim 8 further configured to:

derive the migration controls to continuously migrate the one or more rules to one or more target systems; and

define the operational constraints in association with the migration controls.

15. A non-transitory computer readable medium having stored thereon instructions for performing dynamic orchestration of rules in a big data environment comprising executable code which when executed by a processor, causes the processor to perform steps that comprise:

monitoring activities performed by an entity in the big data environment to detect one or more events, wherein the one or more events are associated with at least one of a product and a service;

determining at least one scenario by analyzing data associated with consumer buying behavior and historical data of the at least one of the product and the service, wherein the at least one scenario comprises one or more scenario categories, wherein the one or more scenario categories are determined based on a utilization map associated with the at least one of the product and the service or interrelationship among the product and the service;

correlating the at least one scenario with the one or more events based on the one or more scenario categories;

validating the correlation between the at least one scenario and the one or more events based on one or more dimensions, wherein the one or more dimensions indicate features of consumer buying behavior that affect the at least one scenario;

deriving one or more rules and corresponding rule hierarchies for each of the correlation of the at least one scenario and the one or more events upon validation; and

applying at least one of operational constraints or migration controls to the one or more rules to perform dynamic orchestration.

16. The medium as claimed in claim 15, wherein the instructions further cause the processor to determine the at least one scenario by:

receiving one or more predefined scenarios from a scenario database;

comparing the at least one scenario with the one or more predefined scenarios to determine whether the at least one scenario is preexisting in the scenario database; and

updating the at least one scenario in the scenario database based on the comparing.

17. The medium as claimed in claim 15, wherein the instructions further cause the processor to determine the at least one scenario by validating the at least one scenario based on the one or more dimensions.

18. The medium as claimed in claim 15, wherein the instructions further cause the processor to:

determine whether the one or more dimensions are defined to correlate with the at least one scenario;

associate the data pertaining to the at least one of the product and the service with big data query specification based on the determining; and

derive the one or more dimensions based on the association.

19. The medium as claimed in claim 15, wherein the instructions further cause the processor to derive the one or more rules by:

determining whether the one or more rules are predefined in a rule database;

identifying a level of the one or more rules based on a rules hierarchy based on the determining, wherein the rules hierarchy is updated dynamically based on the data pertaining to the at least one of the product and the service; and

adding the one or more rules to the rule database along with the level.