IP Library Granted Patent US 11,153,152
Granted Patent B2
US 11,153,152 · App. 16/393,162 · Granted Oct 19, 2021

System and methods to validate issue detection and classification in a network assurance system

Inventors: Waseem A Siddiqi (Campbell, CA); Rajesh S. Pazhyannur (Fremont, CA); Kedar Krishnanand Gaonkar (San Jose, CA); Aruna Nukala (Fremont, CA)
Assignee: CISCO TECHNOLOGY, INC.
H04L41/0677H04L41/145H04L41/22H04W84/12
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Quick Facts
Patent No.
US 11,153,152
App. No.
16/393,162
Granted
Oct 19, 2021
Kind
B2
Abstract

Systems, methods and computer-readable storage media are provided for detecting and simulating issues in a network.

Claims (44)

1. A computer-implemented method comprising:

receiving network traffic data;

identifying event sequences within the network traffic data;

generating definition groups by performing clustering on the identified event sequences, the definition groups comprising event sequence characteristics associated with one or more network issues;

first simulating the identified event sequences in an issue simulation engine to simulate the one or more of the event sequences;

generating, based on results of the first simulating, a first issue identification by an assurance platform;

second simulating a most recent one of the identified event sequences;

generating, based on results of the second simulating and the generated definition groups, a second issue identification; and

validating the first issue identification with the second issue identification.

2. The method of claim 1 , wherein the issue simulation engine includes a client simulation for simulating a portion of the event sequences from a client device perspective.

3. The method of claim 1 , wherein the definition groups are associated with onboarding failures.

4. The method of claim 3 , wherein the onboarding failures comprise an excess onboarding transaction.

5. The method of claim 1 , wherein the network traffic data is generated by network devices comprising one of a wireless local area network controller (WLC) or an access point (AP).

6. The method of claim 1 , wherein the network traffic data comprises a data model including one of a wireless client state, client statistics, AP radio frequency (RF) statistics, an over air packet capture, a network services key performance indicator (KPI), or a device health KPI.

7. The method of claim 1 , wherein generating the first issue identification comprises applying, by the assurance platform, a rules-based issue identification process to the simulated event sequences.

8. A system comprising:

one or more processors; and

a memory comprising instructions to:

receive network traffic data;

identify event sequences within the network traffic data;

first simulate the identified event sequences;

generate, based on the results of the first simulate, definition groups by performing clustering on the identified event sequences, the definition groups comprising event sequence characteristics associated with one or more network issues;

second simulate a most recent one of the identified event sequences in an issue simulation engine to simulate the one or more of the event sequences and generating a first issue identification by an assurance platform;

generate, based on the results of the second simulate and the generated definition groups, a second issue identification based on the definition groups and the one or more of the event sequences; and

validate the first issue identification with the second issue identification.

9. The system of claim 8 , wherein the issue simulation engine includes a client simulation for simulating a portion of the event sequences from a client device perspective.

10. The system of claim 8 , wherein the definition groups are associated with onboarding failures.

11. The system of claim 10 , wherein the onboarding failures comprise an excess onboarding transaction.

12. The system of claim 8 , wherein the network traffic data is generated by network devices comprising one of a wireless local area network controller (WLC) or an access point (AP).

13. The system of claim 8 , wherein the network traffic data comprises a data model including one of a wireless client state, client statistics, AP radio frequency (RF) statistics, an over air packet capture, a network services key performance indicator (KPI), or a device health KPI.

14. The system of claim 8 , wherein generating the first issue identification comprises applying, by the assurance platform, a rules-based issue identification process to the simulated event sequences.

15. A non-transitory computer readable medium comprising instructions that, when executed by one or more processors, cause the one or more processors to:

receive network traffic data;

identify event sequences within the network traffic data;

first simulate the identified event sequences;

generate, based on the results of the first simulate, definition groups by performing clustering on the identified event sequences, the definition groups comprising event sequence characteristics associated with one or more network issues;

second simulating a most recent one of the identified event sequences in an issue simulation engine to simulate the one or more of the event sequences and generating a first issue identification by an assurance platform;

generate, based on the results of the second simulate and the generated definition groups, a second issue identification based on the definition groups and the one or more of the event sequences; and

validate the first issue identification with the second issue identification.

16. The non-transitory computer readable medium of claim 15 , wherein the issue simulation engine includes a client simulation for simulating a portion of the event sequences from a client device perspective.

17. The non-transitory computer readable medium of claim 15 , wherein the definition groups are associated with onboarding failures each comprising an excess on-boarding transaction.

18. The non-transitory computer readable medium of claim 15 , wherein the network traffic data is generated by network devices comprising one of a wireless local area network controller (WLC) or an access point (AP).

19. The non-transitory computer readable medium of claim 15 , wherein the network traffic data comprises a data model including one of a wireless client state, client statistics, AP radio frequency (RF) statistics, an over air packet capture, a network services key performance indicator (KPI), or a device health KPI.

20. The non-transitory computer readable medium of claim 15 , wherein generating the first issue identification comprises applying, by the assurance platform, a rules-based issue identification process to the simulated event sequences.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 24, 2019
From: SIDDIQI, WASEEM A; PAZHYANNUR, RAJESH S.; GAONKAR, KEDAR KRISHNANAND; NUKALA, ARUNA
To: CISCO TECHNOLOGY, INC.
Reel/Frame 048983/0185 →
Continuity (2)
Provisional Application 62770279 · Nov 21, 2018
Related Publication 20200162315A1 · May 21, 2020
Cited By (3)
US 12,401,578 US 12,414,019 US 12,726,505