Systems and methods for analysis of network equipment command line interface (CLI) and runtime management of user interface (UI) generation for same

• US 9,043,252 B2
• Filed: 04/17/2014
• Issued: 05/26/2015
• Est. Priority Date: 09/21/2011
• Status: Active Grant

• Current Assignee: Dell Products LP (Dell Technologies Inc.)
• Original Assignee: Dell Products LP (Dell Technologies Inc.)
• Inventors: Petrick, Christopher S.
• Primary Examiner(s): CHANG, LI WU
• Application Number:
  US14/255,617
• Publication Number:
  US 20140229599A1
• Time in Patent Office: 404 Days
• Field of Search: None
• US Class Current: 706/12
• CPC Class Codes: H04L 41/0213 Standardised network management protocols, e.g. simple network management protocol [SNMP]
• CPC Class Codes: H04L 41/142 using statistical or mathematical methods
• CPC Class Codes: H04L 41/145 involving simulating, designing, planning or modelling of a network
• CPC Class Codes: H04L 41/22 comprising specially adapted graphical user interfaces [GUI]

Abstract

Systems and methods are disclosed that may be implemented for network management system (NMS) configuration management support for network devices using a learning and natural language processing application to capture the usage and behavior of the Command Line Interface (CLI) of a network device with the aid of a CLI knowledge model, which in one example may be ontology-based.

Claims

1. An information handling system, comprising:

one or more processing devices configured to execute a network management system (NMS) that includes an ontology-based command line interface (CLI) knowledge model;

where the one or more processing devices of the information handling system are configured to be communicatively-coupled across a network to one or more network devices of a networking system;

where the one or more processing devices are configured to execute the NMS to maintain and administer the networking system using the ontology-based CLI knowledge model;

where the ontology-based command line interface (CLI) knowledge model includes one or more domain categories, each of the domain categories including multiple concepts therein that are interlinked with other concepts in the same or different domain category of the ontology-based CLI knowledge model to define the relationship between the separate interlinked concepts; and

where the ontology-based CLI knowledge model comprises an ontology build module and an ontology implementation module, the one or more processing devices configured to execute the ontology build module to initiate the CLI knowledge model with new CLI data for the CLI characteristics of new network devices and to update the CLI knowledge model with CLI data for changes in CLI characteristics of existing network devices as one or more ontology build steps, and to execute the ontology implementation module concurrently with the ontology build module as one or more ontology implementation steps such that the ontology implementation module continues to execute using the new CLI data and updated CLI data as it is provided by the ontology build module.

2. The information handling system of claim 1, where the information handling system further comprises at least one display device;

and where the one or more processing devices are configured to execute the ontology implementation module as ontology implementation steps that comprise;

presenting a created runtime GUI on the display device;

allowing a user of the information handling system to use the GUI to input and write one or more CLI queries to a network device having a given IP address; and

using the GUI to provide the user with CLI response information back received back from the same given network device in response to the one or more CLI queries.

3. An information handling system, comprising:

one or more processing devices configured to execute a network management system (NMS) that includes an ontology-based command line interface (CLI) knowledge model;

where the one or more processing devices of the information handling system are configured to be communicatively-coupled across a network to one or more network devices of a networking system;

where the one or more processing devices are configured to execute the NMS to maintain and administer the networking system using the ontology-based CLI knowledge model;

where the ontology-based command line interface (CLI) knowledge model includes one or more domain categories, each of the domain categories including multiple concepts therein that are interlinked with other concepts in the same or different domain category of the ontology-based CLI knowledge model to define the relationship between the separate interlinked concepts; and

where the ontology-based CLI knowledge model comprises an ontology build module, the one or more processing devices are configured to execute the ontology build module as one or more ontology build steps that comprise;

a seed learning step where build parameter information is received by the ontology build module,

a learning and knowledge building step for CLI command structure and network device behavior where each given one of the network devices is interrogated over the network to elicit and receive a response from the given network device describing one or more of the CLI characteristics it possesses, and

a CLI knowledge model creation step where the one or more CLI characteristics received from each given network device is organized as CLI data to create a CLI knowledge model.

4. The information handling system of claim 3, where the one or more processing devices are configured to organize the one or more CLI characteristics received from each given network device as CLI data using ontology related standards.

5. The information handling system of claim 3, where the one or more processing devices are configured to execute the NMS such that the ontology-based CLI knowledge model links the NMS to at least one of:

web content management systems, semantic web applications, shopping portals or services, warranty services, test and design tools, auto generated CLI manuals, or a combination thereof.

6. The information handling system of claim 3, where the one or more processing devices are configured to execute the ontology build module to control the starting and stopping points of the ontology build steps.

7. The information handling system of claim 3, where the one or more processing devices are configured to execute the learning and knowledge building step to:

classify CLI response data received from the given network device;

analyze the classified CLI data, current location of the classified data in the CLI command structure of the given network device, and the current state of the given network device; and

determine a next set of commands based on the analyzed classified CLI data.

8. The information handling system of claim 3, where the one or more processing devices are configured to execute the ontology build module as one or more ontology build steps that further comprise:

reviewing the created CLI knowledge model data to determine at least one of;

whether CLI response data has been collected for all CLI commands initiated in seed learning step and then found in the learning and knowledge building step and the CLI knowledge model creation step,

whether the CLI response data is in the expected format defined in the seed learning step, or

a combination thereof.

9. The information handling system of claim 8, where the one or more processing devices are configured to execute the ontology build module as one or more ontology build steps that further comprise:

determining whether or not to tune the CLI knowledge model data based on at least one of a review of the knowledge model data by one or more human users to ensure that CLI response data has been properly captured, based on execution of the captured device commands of the CLI data and monitoring how they execute, or a combination thereof.

10. The information handling system of claim 8, where the one or more processing devices are configured to execute the ontology build module as one or more ontology build steps that further comprise:

then tuning the CLI knowledge model data by making any required adjustments to at least one of how the CLI response data is parsed, how a state of the current network device is determined, or a combination thereof.

11. The information handling system of claim 3, where the one or more processing devices are configured to execute the learning and knowledge building step to:

collect and parse the CLI response data received from the given network device to determine if additional CLI response data is needed; and

interrogate the given one of the network devices over the network to elicit and receive additional CLI response data from the network device.

12. The information handling system of claim 11, where the additional CLI response data from the network device comprises at least one of child commands, command keywords, command arguments, command parameters, command flags, command switches, help message, command output content, command output data, or a combination thereof.

13. The information handling system of claim 4, where the one or more processing devices are configured to execute the CLI knowledge model creation step to organize the one or more CLI characteristics received from each given network device as CLI data using at least one of the following ontology related standards:

ISO 13584/15926 Industrial automation systems and integration, ISO15944 Business Operation View, ISO 24800 Registration, identification and management of schema and ontology, ISO 19132 Geographical Information—

Location-based services—

Reference model, ISO 11179 Metadata Registries standard, ISO 19763 Meta-Model Framework Standard, ISO 20944 Metadata Registry Interoperability and Bindings, ISO 19763 Meta Model for interoperability and for ontology registration, ISO 13250 Topic Maps, ISO 18048 Topic Map Query Language (TMQL), ISO 19756 Topic Maps Constraint Language, ISO 18629 Process Specific Language, ISO 19115 Geospatial Meta Standards, ISO 24707 Common Logic Standard, ISO 21127 Cultural Heritage Information Ontology, OMG Ontology Definition Meta-Model Standard, or W3C Semantic Web Services Framework.

14. A method of managing a networking system, comprising:

providing an information handling system, the information handling system comprising one or more processing devices communicatively-coupled across a network to one or more network devices of the networking system; and

using the one or more processing devices to execute a network management system (NMS) that includes an ontology-based command line interface (CLI) knowledge model to maintain and administer the networking system using the ontology-based CLI knowledge model;

where the ontology-based command line interface (CLI) knowledge model includes one or more domain categories, each of the domain categories including multiple concepts therein that are interlinked with other concepts in the same or different domain category of the ontology-based CLI knowledge model to define the relationship between the separate interlinked concepts;

where the ontology-based CLI knowledge model comprises an ontology build module and an ontology implementation module, and where the method further comprises using the one or more processing devices to execute the ontology build module to initiate the CLI knowledge model with new CLI data for the CLI characteristics of new network devices and to update the CLI knowledge model with CLI data for changes in CLI characteristics of existing network devices as one or more ontology build steps, and to execute the ontology implementation module concurrently with the ontology build module as one or more ontology implementation steps such that the ontology implementation module continues to execute using the new CLI data and updated CLI data as it is provided by the ontology build module.

15. The method of claim 14, where the information handling system further comprises at least one display device;

and where the method further comprises using the one or more processing devices to execute the ontology implementation module as ontology implementation steps that comprise;

presenting a created runtime GUI on the display device;

allowing a user of the information handling system to use the GUI to input and write one or more CLI queries to a network device having a given IP address; and

using the GUI to provide the user with CLI response information back received back from the same given network device in response to the one or more CLI queries.

16. A method of managing a networking system, comprising:

providing an information handling system, the information handling system comprising one or more processing devices communicatively-coupled across a network to one or more network devices of the networking system; and

using the one or more processing devices to execute a network management system (NMS) that includes an ontology-based command line interface (CLI) knowledge model to maintain and administer the networking system using the ontology-based CLI knowledge model;

where the ontology-based command line interface (CLI) knowledge model includes one or more domain categories, each of the domain categories including multiple concepts therein that are interlinked with other concepts in the same or different domain category of the ontology-based CLI knowledge model to define the relationship between the separate interlinked concepts; and

where the ontology-based CLI knowledge model comprises an ontology build module, and where the method further comprises using the one or more processing devices to execute the ontology build module as one or more ontology build steps that comprise;

a seed learning step where build parameter information is received by the ontology build module,

a learning and knowledge building step for CLI command structure and network device behavior where each given one of the network devices is interrogated over the network to elicit and receive a response from the given network device describing one or more of the CLI characteristics it possesses, and

a CLI knowledge model creation step where the one or more CLI characteristics received from each given network device is organized as CLI data to create a CLI knowledge model.

17. The method of claim 16, further comprising using the one or more processing devices to organize the one or more CLI characteristics received from each given network device as CLI data using ontology related standards.

18. The method of claim 17, where the one or more processing devices are configured to execute the CLI knowledge model creation step to organize the one or more CLI characteristics received from each given network device as CLI data using at least one of the following ontology related standards:

ISO 13584/15926 Industrial automation systems and integration, ISO15944 Business Operation View, ISO 24800 Registration, identification and management of schema and ontology, ISO 19132 Geographical Information —

Location-based services —

Reference model, ISO 11179 Metadata Registries standard, ISO 19763 Meta-Model Framework Standard, ISO 20944 Metadata Registry Interoperability and Bindings, ISO 19763 Meta Model for interoperability and for ontology registration, ISO 13250 Topic Maps, ISO 18048 Topic Map Query Language (TMQL), ISO 19756 Topic Maps Constraint Language, ISO 18629 Process Specific Language, ISO 19115 Geospatial Meta Standards, ISO 24707 Common Logic Standard, ISO 21127 Cultural Heritage Information Ontology, OMG Ontology Definition Meta-Model Standard, or W3C Semantic Web Services Framework.

19. The method of claim 16, further comprising using the one or more processing devices to execute the NMS such that the ontology-based CLI knowledge model links the NMS to at least one of web content management systems, semantic web applications, shopping portals or services, warranty services, test and design tools, auto generated CLI manuals, or a combination thereof.

20. The method of claim 16, further comprising executing the ontology build module to control the starting and stopping points of the ontology build steps.

21. The method of claim 16, further comprising using the one or more processing devices to execute the learning and knowledge building step to:

classify CLI response data received from the given network device;

analyze the classified CLI data, current location of the classified data in the CLI command structure of the given network device, and the current state of the given network device; and

determine a next set of commands based on the analyzed classified CLI data.

22. The method of claim 16, further comprising using the one or more processing devices to execute the ontology build module as one or more ontology build steps that further comprise:

reviewing the created CLI knowledge model data to determine at least one of;

whether CLI response data has been collected for all CLI commands initiated in seed learning step and then found in the learning and knowledge building step and the CLI knowledge model creation step,

whether the CLI response data is in the expected format defined in the seed learning step, or

a combination thereof.

23. The method of claim 22, further comprising using the one or more processing devices to execute the ontology build module as one or more ontology build steps that further comprise:

determining whether or not to tune the CLI knowledge model data based on at least one of a review of the knowledge model data by one or more human users to ensure that CLI response data has been properly captured, based on execution of the captured device commands of the CLI data and monitoring how they execute, or a combination thereof.

24. The method of claim 22, further comprising using the one or more processing devices to execute the ontology build module as one or more ontology build steps that further comprise:

then tuning the CLI knowledge model data by making any required adjustments to at least one of how the CLI response data is parsed, how a state of the current network device is determined, or a combination thereof.

25. The method of claim 16, further comprising using the one or more processing devices to execute the learning and knowledge building step to:

collect and parse the CLI response data received from the given network device to determine if additional CLI response data is needed; and

interrogate the given one of the network devices over the network to elicit and receive additional CLI response data from the network device.

26. The method of claim 25, where the additional CLI response data from the network device comprises at least one of child commands, command keywords, command arguments, command parameters, command flags, command switches, help message, command output content, command output data, or a combination thereof.