Expert system adapted data network guidance engine

• US 6,745,172 B1
• Filed: 07/19/2001
• Issued: 06/01/2004
• Est. Priority Date: 07/19/2000
• Status: Active Grant

• Current Assignee: NetCracker Technology Corporation (NEC Corporation)
• Original Assignee: WhisperWire, Inc. (Convergys Corporation)
• Inventors: Erickson, Charles R., Gheith, Ahmed, Mancisidor, Rod, Norris, Rob
• Primary Examiner(s): Davis, George B.
• Application Number:
  US09/909,240
• Time in Patent Office: 1,048 Days
• Field of Search: 706/60
• US Class Current: 706/60
• CPC Class Codes: H04L 41/0883 Semiautomatic configuration, e.g. proposals from system
• CPC Class Codes: H04L 41/145 involving simulating, designing, planning or modelling of a network
• CPC Class Codes: H04L 41/16 using machine learning or artificial intelligence

Abstract

An expert system adapted data network guidance engine. The invention allows an agent to interact with a customer and to provide selection and recommendation of data network products and/or services for the customer. The invention allows for the use of agents of varying skill levels, including relatively low skill level, without suffering deleterious performance. The data network guidance engine is operable to perform generation and selection of configurations that are generated using various heuristics. If desired, numerous iterations are performed within each of the heuristic operations. The data network guidance engine is operable to select recommended configurations from among a number of potential options. In addition, compatible configurations may also be identified. The data network guidance engine is one of the underlying engines within the expert system that allows the agent to provide real time interaction with a customer and to provide a real time recommended solution to that customer.

Claims

1. An expert system adapted data network guidance engine, comprising:

a data network comprising a plurality of nodes;

the expert system adapted data network guidance engine employs a plurality of heuristics to generate a plurality of data network configurations based on the plurality of nodes within the data network;

the expert system adapted data network guidance engine transforms at least one data network configuration within the plurality of data network configurations into at least one transformed data network configuration; and

the expert system adapted data network guidance engine selects a recommended data network solution from among the plurality of network configurations and the at least one transformed data network configuration.

2. The expert system adapted data network guidance engine of claim 1, wherein the expert system adapted data network guidance engine provides the recommended data network solution to an agent using a graphical user interface.

3. The expert system adapted data network guidance engine of claim 2, wherein the expert system adapted data network guidance engine provides the recommended data network solution to the agent using the graphical user interface.

4. The expert system adapted data network guidance engine of claim 1, wherein the expert system adapted data network guidance engine generates a plurality of initial configurations;

the expert system adapted data network guidance engine applies the plurality of heuristics to the initial configuration within the plurality of initial configurations to generate the plurality of data network configurations; and

the expert system adapted data network guidance engine selectively applies the plurality of heuristics to the initial configuration.

5. The expert system adapted data network guidance engine of claim 1, wherein the plurality of heuristics comprises at least one of a distance tree heuristic, a maximal flow heuristic, a mesh of needs heuristic, a hub and spoke heuristic, a partitioned cluster heuristic, a gravity tree heuristic, and a hub mesh heuristic.

6. The expert system adapted data network guidance engine of claim 5, wherein the expert system adapted data network guidance engine performs an iteration when employing the plurality of heuristics to generate the plurality of data network configurations based on the plurality of nodes within the data network;

and

the iteration generates one data network configuration within the plurality of data network configurations.

7. The expert system adapted data network guidance engine of claim 1, wherein the expert system adapted data network guidance engine employs neural network processing to select a heuristic from the plurality of heuristics, the selected heuristic having a higher chance of success than the remaining heuristics within the plurality of heuristics.

8. The expert system adapted data network guidance engine of claim 1, wherein the expert system adapted data network guidance engine employs a mutation heuristic.

9. A data network guidance engine method used within an expert system, comprising:

rating a first plurality of traits that are used to characterize a first data network configuration;

rating a second plurality of traits that are used to characterize a second data network configuration;

increasing a trait within at least one of the first plurality of traits and the second plurality of traits, the increased trait is used to generate a modified data network configuration from at least one of the first data network configuration and the second data network configuration; and

selecting a recommended data network configuration from among the first data network configuration, the second data network configuration, and the modified data network configuration.

10. The method of claim 9, further comprising performing a capacity transformation to at least one of the first data network configuration, the second data network configuration, and the modified data network configuration.

11. The method of claim 10, wherein the capacity transformation comprises increasing a bandwidth capacity of a link that needs an increased capacity within at least one of the first data network configuration, the second data network configuration, and the modified data network configuration.

12. The method of claim 9, further comprising performing a topological transformation to at least one of the first data network configuration, the second data network configuration, and the modified data network configuration.

13. The method of claim 12, wherein the topological transformation comprises adding a link to at least one of the first data network configuration, the second data network configuration, and the modified data network configuration.

14. A data network guidance engine method used within an expert system, comprising:

obtaining a list of sites to be interconnected;

obtaining bandwidth requirements between a pair of sites within the list of sites;

obtaining information on a customer'"'"'s relative importance of a plurality of selected parameters;

creating a plurality of viable initial data network configurations;

selecting at least one viable initial data network configuration from the plurality of viable initial data network configurations;

generating a plurality of data network configuration solutions;

rating each of the plurality of data network configuration solutions; and

identifying a recommended data network solution from among the plurality of data network configuration solutions based on the ratings of the plurality of data network configuration solutions.

15. The method of claim 14, wherein the generating a plurality of data network configuration solutions further comprises transforming the at least one selected viable initial data network.

16. The method of claim 15, further comprising transforming the at least one selected viable initial data network configuration a number of times until a plurality of sufficient data network configurations are identified.

17. The method of claim 15, further comprising transforming the at least one selected viable initial data network configuration a number of times within a predetermined amount of time.

18. The method of claim 14, further comprising presenting the recommended data network solution to an agent using a graphical user interface.

19. The method of claim 18, further comprising presenting at least one additional recommended data network solution to an agent using a graphical user interface.

20. The method of claim 14, wherein the plurality of selected parameters that comprises at least one of a cost, a latency, a bandwidth fulfillment, a reliability, and a security.