INTEGRATED DIGITAL NETWORK MANAGEMENT PLATFORM

• US 20170310542A1
• Filed: 04/22/2016
• Published: 10/26/2017
• Est. Priority Date: 04/22/2016
• Status: Abandoned Application

• Current Assignee: Netsights360 Co.
• Original Assignee: Netsights360 Co.
• Inventors: Nair, Jithesh Kizhakkekkara, Nair, Sunil Ponnangath, Irimpan, Navin Babu, Nair, Krishnakumar
• Application Number:
  US15/136,135
• Publication Number:
  US 20170310542A1
• Time in Patent Office: Days
• CPC Class Codes: H04L 41/0654 using network fault recovery ring fault isolation or reconfiguration in loop networks without recovery actions by a network management system H04L12/437
• CPC Class Codes: H04L 41/0816 the condition being an adaptation, e.g. in response to network events
• CPC Class Codes: H04L 41/0823 characterised by the purposes of a change of settings, e.g. optimising configuration for enhancing reliability for optimising operational conditions of wireless networks H04W24/02
• CPC Class Codes: H04L 41/0863 by rolling back to previous configuration versions
• CPC Class Codes: H04L 41/0886 Fully automatic configuration
• CPC Class Codes: H04L 41/142 using statistical or mathematical methods
• CPC Class Codes: H04L 41/16 using machine learning or artificial intelligence
• CPC Class Codes: H04L 41/22 comprising specially adapted graphical user interfaces [GUI]
• CPC Class Codes: H04M 2203/359 Augmented reality
• CPC Class Codes: H04M 3/2227 Quality of service monitoring
• CPC Class Codes: H04W 24/02 Arrangements for optimising operational condition
• CPC Class Codes: H04W 24/08 Testing, supervising or monitoring using real traffic

Abstract

A digital network assistant which can detect network anomalies, identify actions likely to remediate them, and assist the user in carrying out those actions. In particular, a digital network assistant constantly monitors data streams associated with the network to determine key performance indicators for the network. When these key performance indicators indicate a network anomaly, the digital network assistant associates it with a digital string to one or more actions likely to remediate similar network issues. The digital network assistant can take these actions automatically or present them to a user to be taken. The system can also aid the user in taking the required actions via an augmented reality interface. In addition, the system can create narratives embedding findings from data analysis eliminating subjectivity. The system can also find optimal parameter sets by continuously analyzing anomaly-free parts of the network and their key performance indicators.

Claims

1. A method of automatically identifying and remediating faults in a complex network, comprising the steps of:

ingesting a plurality of data streams from a respective plurality of network elements;

analyzing the data streams to determine a key performance indicator;

identifying an anomaly in the key performance indicator;

identifying a digital string associated with the anomaly and including a plurality of actions likely to remediate the anomaly;

for each action of the plurality of actions;

determining if the action can be performed automatically;

calculating a confidence score for the action;

if the calculated confidence score is above a predetermined threshold and

the action can be performed automatically, automatically performing the action; and

otherwise, adding the action to an action sheet for the anomaly;

determining an effective action for the anomaly, wherein the effective action remediates the anomaly; and

storing the effective action as an action likely to resolve the anomaly.

2. The method of claim 1, wherein the action involves reconfiguring the network element.

3. The method of claim 1, wherein the action involves replacing the network element.

4. The method of claim 1, wherein the action involves power cycling the network element.

5. The method of claim 1, wherein the step of storing the effective action as an action likely to resolve the anomaly comprises updating an effectiveness score for the action in the digital string.

6. The method of claim 1, wherein the step of storing the effective action as an action likely to resolve the anomaly comprises adding the action to the digital string.

7. A system for managing a network, comprising:

an augmented reality interface; and

one or more computer readable media storing computer-executable instructions that, when executed by a processor perform a method of identifying and remediating faults in a network, comprising the steps of;

ingesting a plurality of data streams from a respective plurality of network elements;

analyzing the data streams to determine a key performance indicator;

identifying an anomaly in the key performance indicator;

identifying a digital string associated with the anomaly and including a plurality of actions likely to remediate the anomaly;

for each action of the plurality of actions;

determining if the action can be performed automatically;

if the action can be performed automatically, performing the action;

if the action cannot be performed automatically, adding the action to an action sheet for the anomaly;

presenting, to a user and via the augmented reality interface, the action sheet;

automatically presenting, to the user and via the augmented reality interface, a visualization relevant to a network element associated with an action item on the action sheet,

wherein the augmented reality interface is programmed to allow the user to issue a gestural command to effect a physical change on the network element; and

automatically tracking completion of the action item as the user interacts with the network element.

8. The system of claim 7, wherein the action item involves reconfiguring the network element.

9. The system of claim 7, wherein the action item involves repositioning the network element and the physical change on the network element involves repositioning the network element.

10. The system of claim 7, wherein the action item involves power cycling the network element and the physical change on the network element involves power cycling the network element.

11. The system of claim 7, wherein the augmented reality interface is further operable to display a network dashboard associated with the user.

12. The system of claim 7, wherein the action sheet includes the physical change on the network element and a software change on the network element.

13. The system of claim 7, wherein the visualizations relevant to the network element include a virtual representation of the network element.

14. The system of claim 7,

wherein the method further comprises the step of determining an effective action item on the action sheet, and

wherein the effective action item, when completed by the user, remediates the anomaly.

15. A digital network assistant, programmed to:

determine, for a user, an action sheet associated with managing a network;

present, to the user and via an augmented reality interface, the action sheet;

automatically present, to the user and via the augmented reality interface, visualizations relevant to a network element associated with an action item on the action sheet,

wherein the augmented reality interface is programmed to allow the user to issue a gestural command to effect a physical change on the network element; and

automatically track completion of the action item as the user interacts with the network element.

16. The digital network assistant of claim 15, wherein the physical change on the network element involves power cycling the network element.

17. The digital network assistant of claim 15, wherein the physical change on the network element involves repositioning the network element.

18. The digital network assistant of claim 15, wherein the action sheet includes the physical change on the network element and a software change on the network element.

19. The digital network assistant of claim 18, wherein the software change on the network element involves changing a configuration parameter for the network element.

20. The digital network assistant of claim 15, wherein the visualizations relevant to the network element include a key performance indicator associated with the network element.