Method and apparatus for monitoring and controlling communications networks

• US 5,687,290 A
• Filed: 10/15/1996
• Issued: 11/11/1997
• Est. Priority Date: 09/20/1993
• Status: Expired due to Term

• Current Assignee: Computer Associates Think Inc. (Broadcom, Inc.)
• Original Assignee: Cabletron Systems Incorporated (Extreme Networks, Inc.)
• Inventors: Lewis, Lundy
• Primary Examiner(s): Downs, Robert W.
• Application Number:
  US08/722,580
• Time in Patent Office: 392 Days
• Field of Search: 395/183.02, 395/76, 395/51, 395/61, 395/900, 395/200.01
• US Class Current: 706/45
• CPC Class Codes: G06F 11/3485 for I/O devices
• CPC Class Codes: H04L 43/06 Generation of reports
• CPC Class Codes: H04L 43/062 related to network traffic
• CPC Class Codes: H04L 43/0882 Utilisation of link capacity
• CPC Class Codes: H04L 43/16 Threshold monitoring
• CPC Class Codes: Y10S 706/90 Fuzzy logic

Abstract

The apparatus includes a network monitor coupled to the communications network and providing numeric data representative of at least one operating parameter of the communications network. A fuzzifier module is coupled to the network monitor and converts the numeric data into fuzzy input data. A fuzzy inference engine is coupled to the fuzzifier module and processes the fuzzy input data according to at least one fuzzy rule to provide fuzzy output data representative of control actions to effect a desired state of the communications network. A defuzzifier module is coupled to the fuzzy inference engine and converts the fuzzy output data into numeric data which may be then used by a network controller to control at least one network parameter in response to the output data. The apparatus may also include a user interface and a display to allow the fuzzy input data, and the fuzzy output data to be displayed to a user. Using the user interface, the user can then modify the fuzzy input data, the fuzzy output data, and the fuzzy rules. A method for monitoring and controlling communications networks is also disclosed. A methodology for designing membership functions and fuzzy rules useful for monitoring and control of communications networks is disclosed. The system provides for reporting of network behavior in common sense terms, providing recommendations to a user regarding network operational parameters, and, in one embodiment, complete automatic monitoring and control network operational parameters.

Claims

1. An apparatus for monitoring and controlling a communications network, comprising:

a separate network monitor and controller, coupled to the communications network, providing numeric data representative of at least one operating parameter of the communications network and controlling at least one network parameter;

a separate system that requires only fuzzy logic operations to control the communications network, comprising;

a fuzzifier module, coupled to the network monitor, converting the numeric data into fuzzy input data;

a fuzzy inference engine, coupled to the fuzzifier module, for processing the fuzzy input data according to at least one fuzzy rule to provide fuzzy output data representative of control actions that effect a desired state of the communications network;

a defuzzifier module, coupled to the fuzzy inference engine, converting the fuzzy output data into numeric data for the separate network monitor and controller to control at least one network parameter in response thereto; and

an operator interface allowing user observation of the fuzzy input data and the fuzzy output data, and user modification of said at least one fuzzy rule before converting the fuzzy output data into the numeric data to modify said fuzzy logic operations performed by said fuzzy inference engine during said control of the communications network.

2. The apparatus of claim 1, wherein the fuzzy input data comprises at least one linguistic variable.

3. The apparatus of claim 2, wherein the fuzzifier module converts the numeric data into fuzzy input data using at least one membership function.

4. The apparatus of claim 3, wherein the membership function additionally comprises a weighting function that describes the degree to which a particular numeric value participates in a linguistic variable.

5. The apparatus of claim 4, wherein there are at least two membership functions for each linguistic variable and wherein each membership function produces different fuzzy input data for identical numeric data.

6. The apparatus of claim 5, wherein the defuzzifier module converts the fuzzy output data into numeric data using at least one membership function.

8. The method of claim 2, wherein the fuzzy input data comprises at least one linguistic variable.

10. The method of claim 3, wherein the step of converting the numeric data into fuzzy input data includes the step of converting numeric data into fuzzy input data using at least one membership function.

11. The method of claim 10, wherein the membership function additionally comprises a weighting function that describes the degree to which a particular numeric value participates in a linguistic variable.

12. The method of claim 11, wherein the step of converting the numeric data into fuzzy input data includes the step of converting numeric data into fuzzy input data using at least two membership functions for each linguistic variable and wherein each membership function produces different fuzzy input data for identical numeric data.

13. The method of claim 12, wherein the step of converting the fuzzy output data into numeric data includes the step of converting the fuzzy output data into numeric data using at least one membership function.

14. The apparatus of claim 3, wherein the fuzzy input data comprises at least one linguistic variable.

15. The apparatus of claim 14, wherein the means for converting the numeric data into fuzzy input data includes means for converting the numeric data into fuzzy input data using at least one membership function.

16. The apparatus of claim 15, wherein the membership function additionally comprises a weighting function that describes the degree to which a particular numeric value participates in a linguistic variable.

17. The apparatus of claim 16, wherein there are at least two membership functions for each linguistic variable and wherein each membership function produces different fuzzy input data for identical numeric data.

18. The apparatus of claim 17, wherein the means for converting the fuzzy output data into numeric data includes means for converting the fuzzy output data into numeric data using at least one membership function.

7. A method for monitoring and controlling a communications network, comprising the steps of:

receiving numeric data representative of at least one operating parameter of the communications network from a separate network monitor and controller;

converting the numeric data representative of at least one operating parameter into fuzzy input data;

processing the fuzzy input data according to at least one fuzzy rule to provide fuzzy output data representative of control actions that effect a desired state of the communications network;

displaying at least one of the fuzzy input data and the fuzzy output data to a user;

receiving user modifications of said at least one fuzzy rule;

repeating said processing step with said at least one user-modified fuzzy rule to provide modified fuzzy output data;

repeating said displaying step with said at least one the fuzzy input data and said modified fuzzy output data;

converting said modified fuzzy output data into numeric data; and

controlling at least one network parameter in response thereto;

wherein the method uses only fuzzy logic operations to control the communications network.

9. An apparatus for monitoring and controlling a communications network, comprising:

means, including a separate network monitor and controller, for receiving numeric data representative of at least one operating parameter of the communications network;

means including a separate system that requires only fuzzy logic operations to control the communications network, comprising;

means for converting the numeric data representative of at least one operating parameter into fuzzy input data;

means for processing the fuzzy input data according to at least one fuzzy rule to provide fuzzy output data representative of control actions that effect a desired state of the communications network;

means for converting the fuzzy output data into numeric data for the separate network monitor and controller to control at least one network parameter in response thereto;

means for displaying at least one of the fuzzy input data and the fuzzy output data to a user;

means for incorporating user modifications of said at least one fuzzy rule into said processing means before converting the fuzzy output data into the numeric data enabling the user to modify said fuzzy logic operations during said control of the communications network; and

means for controlling at least one network parameter in response to the numeric data.