Model Driven Diagnostics System and Methods Thereof

• US 20090150724A1
• Filed: 11/12/2008
• Published: 06/11/2009
• Est. Priority Date: 11/15/2007
• Status: Active Grant

• Current Assignee: EdgeVerve Systems Ltd. (Infosys Limited)
• Original Assignee: Infosys Technologies Limited (Infosys Limited)
• Inventors: VIVIANO, Tom, PRAMIDI, Sailaja, NATARAJAN, Swaminathan
• Granted Patent: US 8,086,897 B2
• Time in Patent Office: Days
• US Class Current: 714/37
• CPC Class Codes: H04L 41/0631 using root cause analysis; using analysis of correlation between notifications, alarms or events based on decision criteria, e.g. hierarchy, tree or time analysis
• CPC Class Codes: H04L 41/0663 Performing the actions predefined by failover planning, e.g. switching to standby network elements
• CPC Class Codes: H04L 41/16 using machine learning or artificial intelligence

Abstract

A method to perform a diagnostic test in an integrated support platform having a plurality of services is disclosed. The method includes a process of building at least one or more knowledge model for each of the plurality of services in the integrated support platform. The process of building the knowledge model includes determining one or more failure(s) of each component and at least one associated symptom to identify the one or more failures and constructing a framework for the diagnostic test associated to the one or more failures. The framework comprising the diagnostic test may be created by at least one of an execution plan based on the most efficient path for determining the failure. The method further includes performing the diagnostic test for resolving one or more failures of each component by using the framework based on the built knowledge model for the plurality of services.

Claims

1. A method of performing a diagnostics in an integrated support platform having a plurality of services, the method comprising:

building at least one or more knowledge model for each of the plurality of services in the integrated support platform by determining one or more components related to the plurality of services, wherein building the at least one knowledge model comprising;

determining one or more failures of each component and at least one associated symptom to identify the one or more failures;

constructing a framework for the diagnostics associated to the one or more failures by creating at least one execution plan based on a most efficient path for determining the one or more failures; and

performing the diagnostics for resolving one or more failures of each component by using the framework based on the built knowledge model for the plurality of services.

2. The method of claim 1, wherein the integrated support platform includes at least one of a customer support platform or a network support platform or both.

3. The method as recited in claim 2, wherein the customer support platform includes at least one of a trouble ticketing or a self care or a help desk or a customer relationship management (CRM) or combinations thereof.

4. The method as recited in claim 2, wherein the network support platform includes at least one of a network monitoring or an alarm collection and correlation or a network trouble reporting or a network performance monitoring or combinations thereof.

5. The method of claim 1, wherein the plurality of services includes at least one of a Digital Subscriber Line (DSL) service or a broadband service or an Internet Protocol (IP) TV service or a Voice over IP (VoIP) service or a wireless service or a cable service or an Internet Protocol (IP) Multimedia Subsystem (IMS) or combinations thereof.

6. The method of claim 1, wherein performing the diagnostics in the integrated support platform further includes a plurality of products for each of the plurality of services.

7. The method of claim 1, wherein the execution plan includes at least one of a trouble shooting workflow or a customer symptom validation or a resource state validation or combinations thereof.

8. The method of claim 1, wherein the one or more failures include at least one of a resource failure or a service failure or both.

9. The method of claim 8, wherein the service failures is identified based on a scenario describing a specific service feature used by the customer.

10. The method as recited in claim 8, wherein the resource failures from a network is correlated to the service failures of the customer, wherein correlation between the service failures and the resource failures includes one or more problems sensed from the customer in form of the plurality of symptoms.

11. The method of claim 1, wherein the diagnostics for resolving one or more failures using the knowledge model for the plurality of problems sensed from the customer are arranged optimally for resolving the failures.

12. The method of claim 1, wherein determining at least one or more failures of each component to build the knowledge model includes at least one of the failures derived from knowledge of one or more experts in a domain or from an actual failures captured earlier in the similar services or both.

13. The method of claim 1, further comprising the framework for associating at least one symptom to identify one or more failures includes knowledge derived out of at least one or more experts in a domain.

14. The method of claim 1, wherein the most efficient path for determining one or more failures includes at least one of a route defined from the expert(s) in the domain or through a process of continuous learning or combinations thereof.

15. The method as recited in claim 14, wherein the process of continuous learning includes at least one of knowledge captured about failures from the experts in the domain or from the experience of resolving the similar problems by a customer support representative (CSR) or from a prior use of similar diagnostics by the CSR in resolving the problem or combinations thereof.

16. The method as recited in claim 14, wherein the process of continuous learning further includes determining situational information of the network including at least one of a planned engineering maintenance work or a network migration or an early service failure about a new service rolled in the market or combinations thereof.

17. The method as recited in claim 14, wherein the process of determining the most efficient further includes determining a state of at least one of the products or the services or both.

18. The method as recited in claim 14, wherein the process of continuous learning further includes computing a historical result for a specific problem and associated diagnostics and resolution at periodic intervals to determine the most used diagnostics for resolving the failures sensed from the customer.

19. The method as recited in claim 18, wherein the historical results are used to identify and prioritize one or more diagnostics for resolving the failures sensed from the customer based on a resolution index assigned for each diagnostics.

20. The method as recited in claim 14, wherein the process of continuous learning further includes determining at least one of a cost of performing the diagnostics or an impact of the diagnostics on the network or a need for the diagnostics to interact with a manual process or an access privilege for performing the diagnostics or combinations thereof.

21. The method of claim 1, wherein constructing the framework for the diagnostics includes associating the resource failures of the network with the associated symptoms.

22. The method of claim 1, wherein determining at least one or more resource failures of each physical component related to the logical component and the associated symptoms to identify the resource failures is captured in the knowledge model.

23. The method of claim 1, further comprising enhancing the context of a ticket for the problem escalated from at least one of the customer or the network support platform or both using an information model, wherein the information model includes information gathered from a plurality of application source, wherein the plurality of application source comprises at least one of a customer relationship management (CRM) or a network inventory or an engineering application or a fault management or a performance management or a Service Level Agreement (SLA) management or a trouble management or combinations thereof.

24. A system for building a knowledge model to perform a diagnostics for a plurality of services, the system comprising:

one or more components configured for building the knowledge model related to each of the plurality of services;

a framework configured for the plurality of components associated to each of the plurality of services, to perform the diagnostics, wherein the framework comprising;

a failure module including at least one or more failures for each of the plurality of components;

a problem module including at least one or more problems associated to each of the failures;

a symptom module including at least one symptoms associated to each problems; and

a diagnostics module including at least one or more diagnostics to run for localizing each of one or more problems.

25. The system as recited in claim 24, wherein the components of the knowledge model includes at least one of a logical component or a physical component or both.

26. The system as recited in claim 24, wherein the failure module further includes at least one of a service failure module or a resource failure module or combinations thereof.

27. The system of claim 26, wherein the each of the plurality of failures in the logical component is associated to respective failures in the physical component.

28. The system of claim 24, further comprising a scenario module including at least one or more scenario associated to the problems.

29. A computer program product comprising a computer usable medium having a computer readable program code embodied therein for performing a diagnostics in an integrated support platform having a plurality of services, the method comprising:

program code adapted for building at least one knowledge model for each of the plurality of services in the integrated support platform, by determining one or more components related to the plurality of services, wherein program code adapted for building the at least one knowledge model comprising;

program code adapted for determining one or more failures of each component and at least one associated symptom to identify the one or more failures;

program code adapted for constructing a framework for the diagnostics associated to the one or more failures, by creating at least one execution plan based on the most efficient path for determining the one or more failures; and

program code adapted for performing the diagnostics for resolving one or more failures of each components by using the framework based on the built knowledge model for the plurality of services.