Expert system for communications network

• US 5,159,685 A
• Filed: 12/06/1989
• Issued: 10/27/1992
• Est. Priority Date: 12/06/1989
• Status: Expired due to Term

• Current Assignee: Nextiraone France (Nippon Telegraph and Telephone Corporation)
• Original Assignee: Racal Data Communications Incorporated
• Inventors: Kung, Ching Y.
• Primary Examiner(s): Fleming, Michael R.
• Assistant Examiner(s): Downs, Robert W.
• Application Number:
  US07/447,485
• Time in Patent Office: 1,056 Days
• Field of Search: 364/513, 364/550, 364/200, 371/11, 371/15.1, 358/406, 379/10
• US Class Current: 714/26
• CPC Class Codes: G06F 11/2257 using expert systems
• CPC Class Codes: G06F 11/327 Alarm or error message display
• 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 41/0659 by isolating or reconfiguring faulty entities
• CPC Class Codes: H04L 41/16 using machine learning or artificial intelligence
• CPC Class Codes: H04L 43/00 Arrangements for monitoring or testing data switching networks
• CPC Class Codes: H04L 43/0829 Packet loss
• CPC Class Codes: H04L 43/106 using time related information in packets, e.g. by adding timestamps
• CPC Class Codes: H04L 43/50 Testing arrangements
• CPC Class Codes: Y10S 706/908 Electronic or computer, internal or network, circuit
• CPC Class Codes: Y10S 706/909 Communication
• CPC Class Codes: Y10S 706/911 Nonmedical diagnostics
• CPC Class Codes: Y10S 706/917 Communication

Abstract

An Expert System 10 for providing diagnostics to a data communications network 5. Alarms from a Network Manager 24 are received and queued by an Event Manager 117 and then filtered by an Alarm Filter 118 to remove redundant alarms. Alarms which are ready for processing are then posted to a queue referred to as a Bulletin Board 120. A Controller 112 determines which one of the posted goals has the highest priority by considering a priority number associated with the goal plus a time of arrival of the goal. An Inference Engine 122 uses information from an Expert Information Structure 111 to solve the highest priority goal by a process called instantiation. The process of solving the goal may be interrupted by a pause or suspension in order to perform tests under the direction of a Network Test Manager 124 or retrieve other information during which time other goals may be processed. Expert information is entered using a user friendly User Interface 104 which reduces need for the participation of a Knowledge Engineer. Configuration information about the network is maintained in a Network Structure Knowledge Base 109 by a Network Configuration Module 108. The Expert System 10 may operate in any of three modes: manual, wherein tests must be approved by or directed by an operator; automatic, where the tests are run automatically without operator intervention; and semiautomatic, where operator approval is required for certain tests such as interruptive tests and other tests such as non-interruptive tests may proceed without operator intervention.

Claims

1. In a data communication network, a method of processing alarms from network objects, comprising the steps of:

receiving an alarm;

determining whether or not said alarm is a redundant alarm by comparing said alarm with previously received alarms;

placing said alarm in a queue for processing by an inference engine if said alarm is not a redundant alarm;

retrieving said alarm from said queue and processing said alarm in said inference engine;

determining that further information is required to complete processing of said alarm;

suspending processing of said alarm by said inference engine;

assigning a status indicator to said alarm which indicates that processing of said alarm has been suspended;

requesting said further information from a network test managing means; and

retrieving a next alarm from said queue for processing by said inference engine while said network test managing means is obtaining said further information.

2. The method of claim 1, further comprising the step of prioritizing said alarm for processing by said inference engine by assigning a priority to said alarm.

3. The method of claim 2, and further comprising the step of retrieving said alarm from said queue when it has a higher priority than any other alarm in said queue, and processing said alarm with said inference engine.

4. The method of claim 1, further comprising the steps of:

receiving said further information from said network test managing means;

placing said further information in a response queue; and

reassigning said status indicator of said alarm to indicate that said alarm is ready for further processing.

5. The method of claim 4, further comprising the steps of retrieving said alarm for a second time from said queue and retrieving said further information from said response queue;

and resuming said processing of said alarm by said inference engine.

6. The method of claim 1, wherein said queue comprises a Bulletin Board queue.

7. The method of claim 1, wherein said determining step is carried out by determining that said alarm is time correlated with a previously received alarm.

8. The method of claim 1, wherein said determining step is carried out by determining that a source of said alarm is space correlated with a source of a previously received alarm.

9. A method of processing events in an expert system, comprising the steps of:

receiving an event;

determining whether or not said event is a redundant event by comparing said event with other events which have been received;

placing said event in a queue for processing by an inference engine if said event is not a redundant event;

retrieving said event from said event queue and beginning processing said event in said inference engine;

determining that further information is required to complete processing of said event;

suspending processing of said event by said inference engine;

assigning a status indicator to said event which indicates that processing of said event has been suspended;

requesting said further information; and

retrieving another event from said queue for processing by said inference engine while obtaining said further information.

10. The method of claim 9, further comprising the step of prioritizing said event for processing by said inference engine by assigning a priority to said event.

11. The method of claim 10, and further comprising the step of retrieving said event from said queue when it has a higher priority than any other event in said queue, and processing said event with said inference engine.

12. The method of claim 9, further comprising the steps of:

receiving said further information;

placing said further information in a response queue; and

reassigning said status indicator of said event to indicate that said event is ready for further processing.

13. The method of claim 12, further comprising the step of retrieving said event for a second time from said queue and retrieving said further information from said response queue and resuming said processing of said event by said inference engine.

14. The method of claim 9, wherein said determining step is carried out by determining that said event is time correlated with a previously received event.

15. The method of claim 9, wherein said determining step is carried out by determining that a source of said event is space correlated with a source of a previously received event.

16. A method for applying expert knowledge to an alarm in a data communication network to be diagnosed by an expert system residing on a computer, the method comprising the steps of:

receiving an alarm from said data communications network, said alarm having an alarm type and being generated by a network object by virtue of said object detecting a problem in said network;

mapping said alarm to an expert knowledge source which corresponds to said alarm type, said corresponding expert knowledge source being one of a plurality of available expert knowledge sources;

retrieving said corresponding expert knowledge source; and

invoking an inference engine to find a solution to said problem by instantiating at least a portion of said corresponding expert knowledge source to a diagnostic procedure specific to said problem.

17. The method of claim 16, wherein said corresponding expert knowledge source comprises a hypothesis tree having at least one leaf node with respect to said hypothesis tree, said leaf node leading into a flow-chart representation of a procedure.

18. The method of claim 17, wherein said instantiating step further comprises the steps of:

traversing said corresponding expert knowledge source including said hypothesis tree and said flow-chart by descending said hypothesis tree and said flow chart on a node-by-node basis; and

instantiating nodes of said hypothesis tree and said flow-chart to a diagnostic procedure as each said node is traversed.

19. The method of claim 18, wherein said invoking step is peformed as each said node is traversed.