IP Library Granted Patent US 12,355,563
Granted Patent B2
US 12,355,563 · App. 17/582,838 · Granted Jul 8, 2025

Correlating transceiver parameters for insight into transceiver health

Inventors: Harsha Bharadwaj (Bangalore, IN); Paresh Gupta (La Crescenta, CA); Sunil John Varghese (Bangalore, IN); Joy Chatterjee (Bangalore, IN)
Assignee: CISCO TECHNOLOGY, INC.
H04L1/004H04B17/345H04B17/354H04W24/08
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12,355,563
App. No.
17/582,838
Granted
Jul 8, 2025
Kind
B2
Abstract

A method comprises: at a management entity configured to monitor a transceiver system having a transceiver to receive a signal that conveys data frames transmitted by a peer transceiver over a connection: collecting time series values for operating parameters of the transceiver associated with received data frames, including (i) a receive power, and (ii) counts of different media access control (MAC) layer frame errors that respectively indicate degradation levels for system performance ranked from highest to lowest; using the time series values, performing correlations of the receive power against the counts of the different MAC layer frame errors according to a correlation hierarchy that indicates which of the correlations correspond to which of the degradation levels, to produce correlation results; and responsive to the correlation results, determining a degraded component of the transceiver system.

Claims (53)

1. A method comprising:

at a management entity configured to monitor a transceiver system having a transceiver to receive a signal that conveys data frames transmitted by a peer transceiver over a connection:

collecting time series values for operating parameters of the transceiver associated with received data frames, including (i) a receive power, and (ii) counts of different media access control (MAC) layer frame errors that respectively indicate degradation levels for system performance ranked from highest to lowest, wherein the different MAC layer frame errors include, in order of degradation level from highest to lowest, link resets and other types of MAC layer frame errors

using the time series values, performing correlations of the receive power against the counts of the different MAC layer frame errors according to a correlation hierarchy that indicates which of the correlations correspond to which of the degradation levels, to produce correlation results; and

responsive to the correlation results, determining a degraded component of the transceiver system.

2. The method of claim 1 , further comprising:

sending an action message with an indication to replace the degraded component with an urgency that increases with increases in the degradation levels.

3. The method of claim 1 , further comprising:

generating, from the time series values, trend lines for the operating parameters that indicate increasing, decreasing, or constant trends over time for the operating parameters; and

upon determining that at least one of the trend lines has a slope that exceeds a threshold, performing the correlations and determining the degraded component.

4. The method of claim 3 , wherein:

generating includes generating the trend lines to include a receive power trend line for the receive power, and frame-error trend lines for the counts of the different MAC layer frame errors.

5. The method of claim 1 , wherein a negative correlation result among the correlation results indicates that the receive power is decreasing while one of the counts of the different MAC layer frame errors that produces the negative correlation result is increasing.

6. The method of claim 1 , further comprising:

performing at least one of the correlations only when at least one of the counts of the different MAC layer frame errors has a magnitude that exceeds a threshold.

7. The method of claim 1 , wherein:

the different MAC layer frame errors include, in order of degradation level from highest to lowest, the link resets, cyclic redundancy check (CRC) errors, and at least one type of forward error correction (FEC) errors.

8. The method of claim 1 , wherein the transceiver system is an optical transceiver system in which the transceiver, the signal, the peer transceiver, and the connection are an optical transceiver, an optical signal, an optical peer transceiver, and an optical connection, respectively.

9. The method of claim 1 , wherein determining further includes:

correlating a transmit power of the peer transceiver against the receive power of the transceiver, to produce a power correlation result; and

when the power correlation result is positive, declaring that the peer transceiver or the connection is the degraded component.

10. The method of claim 9 , wherein determining further includes:

when the power correlation result is negative, determining whether the receive power decreases over time; and

when the receive power does not decrease over time, declaring that the transceiver or the connection is the degraded component.

11. The method of claim 10 , wherein determining further includes:

when the receive power decreases over time, correlating time series values for a transmit power of the transceiver against time series values for a temperature of the transceiver to produce a temperature correlation result; and

when the temperature correlation result is negative, declaring there is no degraded component.

12. The method of claim 11 , wherein determining further includes:

when the temperature correlation result is positive, declaring there is a high ambient temperature at the transceiver.

13. An apparatus comprising:

a network input/output interface to communicate with one or more networks; and

a processor of a management entity configured to monitor a transceiver system having a transceiver to receive a signal that conveys data frames transmitted by a peer transceiver over a connection, the processor coupled to the network input/output interface and configured to perform:

collecting time series values for operating parameters of the transceiver associated with received data frames, including (i) a receive power, and (ii) counts of different media access control (MAC) layer frame errors that respectively indicate degradation levels for system performance ranked from highest to lowest, wherein the different MAC layer frame errors include, in order of degradation level from highest to lowest, link resets and other types of MAC layer frame errors

using the time series values, performing correlations of the receive power against the counts of the different MAC layer frame errors according to a correlation hierarchy that indicates which of the correlations correspond to which of the degradation levels, to produce correlation results; and

responsive to the correlation results, determining a degraded component of the transceiver system.

14. The apparatus of claim 13 , wherein the processor is further configured to perform:

sending an action message with an indication to replace the degraded component with an urgency that increases with increases in the degradation levels.

15. The apparatus of claim 13 , wherein the processor is further configured to perform:

generating, from the time series values, trend lines for the operating parameters that indicate increasing, decreasing, or constant trends over time for the operating parameters; and

upon determining that at least one of the trend lines has a slope that exceeds a threshold, performing the correlations and determining the degraded component.

16. The apparatus of claim 13 , wherein:

the different MAC layer frame errors include, in order of degradation level from highest to lowest, the link resets, cyclic redundancy check (CRC) errors, and at least one type of forward error correction (FEC) errors.

17. A non-transitory computer readable medium encoded with instructions that, when executed by a processor of a management entity configured to monitor a transceiver system having a transceiver to receive a signal that conveys data frames transmitted by a peer transceiver over a connection, cause the processor to perform:

collecting time series values for operating parameters of the transceiver associated with received data frames, including (i) a receive power, and (ii) counts of different media access control (MAC) layer frame errors that respectively indicate degradation levels for system performance ranked from highest to lowest, wherein the different MAC layer frame errors include, in order of degradation level from highest to lowest, link resets and other types of MAC layer frame errors

using the time series values, performing correlations of the receive power against the counts of the different MAC layer frame errors according to a correlation hierarchy that indicates which of the correlations correspond to which of the degradation levels, to produce correlation results; and

responsive to the correlation results, determining a degraded component of the transceiver system.

18. The non-transitory computer readable medium of claim 17 , further comprising instructions to cause the processor to perform:

sending an action message with an indication to replace the degraded component with an urgency that increases with increases in the degradation levels.

19. The non-transitory computer readable medium of claim 17 , further comprising instructions to cause the processor to perform:

generating, from the time series values, trend lines for the operating parameters that indicate increasing, decreasing, or constant trends over time for the operating parameters; and

upon determining that at least one of the trend lines has a slope that exceeds a threshold, performing the correlations and determining the degraded component.

20. The non-transitory computer readable medium of claim 17 , wherein:

the different MAC layer frame errors include, in order of degradation level from highest to lowest, the link resets, cyclic redundancy check (CRC) errors, and at least one type of forward error correction (FEC) errors.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 25, 2022
From: BHARADWAJ, HARSHA; GUPTA, PARESH; VARGHESE, SUNIL JOHN; CHATTERJEE, JOY
To: CISCO TECHNOLOGY, INC.
Reel/Frame 058753/0659 →
Continuity (1)
Related Publication 20230239073A1 · Jul 27, 2023
References Cited (102)
US 6215565B1 · Davis · 2001 [cited by examiner]
US 6526261B1 · Takeuchi · 2003 [cited by examiner]
US 6574226B1 · Nakano et al. · 2003 [cited by applicant]
US 6665497B1 · Hamilton-Gahart · 2003 [cited by examiner]
US 6765659B1 · Bhatnagar et al. · 2004 [cited by applicant]
US 6950865B1 · Depaolantonio · 2005 [cited by applicant]
US 7035262B1 · Joshi · 2006 [cited by applicant]
US 7043541B1 · Bechtolsheim et al. · 2006 [cited by applicant]
US 7103149B1 · Depaolantonio · 2006 [cited by applicant]
US 7142504B1 · Uzun · 2006 [cited by applicant]
US 7181137B1 · Tamburello et al. · 2007 [cited by applicant]
US 7190896B1 · Wang et al. · 2007 [cited by applicant]
US 7224898B1 · Depaolantonio · 2007 [cited by applicant]
US 7228447B1 · Day · 2007 [cited by applicant]
US 7457725B1 · Civilini · 2008 [cited by applicant]
US 7774444B1 · George · 2010 [cited by examiner]
US 7886031B1 · Taylor · 2011 [cited by examiner]
US 8995829B2 · Barbieri et al. · 2015 [cited by applicant]
US 9112645B2 · Hassan · 2015 [cited by examiner]
US 9425893B1 · Srinivasan · 2016 [cited by examiner]
US 9585175B2 · Sung · 2017 [cited by examiner]
US 9780878B2 · Sackman · 2017 [cited by examiner]
US 9838317B1 · Yadav · 2017 [cited by applicant]
US 10346239B1 · Ortega Gutierrez et al. · 2019 [cited by applicant]
US 10396897B1 · Malave et al. · 2019 [cited by applicant]
US 10686695B1 · Nainar et al. · 2020 [cited by applicant]
US 10924944B2 · Seol · 2021 [cited by examiner]
US 11128541B2 · Sattiraju et al. · 2021 [cited by applicant]
US 11778354B2 · Chaouch · 2023 [cited by examiner]
US 20020030867A1 · Iannone et al. · 2002 [cited by applicant]
US 20020039217A1 · Saunders · 2002 [cited by examiner]
US 20020047862A1 · Aoki · 2002 [cited by examiner]
US 20020097463A1 · Saunders et al. · 2002 [cited by applicant]
US 20030151801A1 · Jayaram · 2003 [cited by examiner]
US 20030169998A1 · Premaratne · 2003 [cited by examiner]
US 20030179701A1 · Salch et al. · 2003 [cited by applicant]
US 20030179742A1 · Ogier et al. · 2003 [cited by applicant]
US 20040218919A1 · Hunsche · 2004 [cited by examiner]
US 20050010681A1 · Katukam et al. · 2005 [cited by applicant]
US 20050010849A1 · Ryla et al. · 2005 [cited by applicant]
US 20050090911A1 · Ingargiola et al. · 2005 [cited by applicant]
US 20050111843A1 · Takeuchi et al. · 2005 [cited by applicant]
US 20050209806A1 · Yoneyama · 2005 [cited by applicant]
US 20050216783A1 · Sundaram et al. · 2005 [cited by applicant]
US 20060002709A1 · Dybsetter · 2006 [cited by examiner]
US 20060044725A1 · Robinson et al. · 2006 [cited by applicant]
US 20060104641A1 · Casanova et al. · 2006 [cited by applicant]
US 20070118546A1 · Acharya · 2007 [cited by applicant]
US 20070124625A1 · Hassan · 2007 [cited by examiner]
US 20070217794A1 · Sakamoto et al. · 2007 [cited by applicant]
US 20070280684A1 · Onoda · 2007 [cited by examiner]
US 20080010661A1 · Kappler · 2008 [cited by examiner]
US 20080040302A1 · Perrizo · 2008 [cited by applicant]
US 20080205900A1 · Cole · 2008 [cited by examiner]
US 20080279092A1 · Hassan · 2008 [cited by examiner]
US 20080279093A1 · Hassan · 2008 [cited by examiner]
US 20100014855A1 · Arnone et al. · 2010 [cited by applicant]
US 20100080562A1 · Perkins · 2010 [cited by examiner]
US 20100157824A1 · Thompson · 2010 [cited by examiner]
US 20120195195A1 · Rai et al. · 2012 [cited by applicant]
US 20120275510A1 · Jakubczak · 2012 [cited by examiner]
US 20120300801A1 · McLeod · 2012 [cited by examiner]
US 20130028597A1 · Ye · 2013 [cited by examiner]
US 20130286846A1 · Atlas et al. · 2013 [cited by applicant]
US 20150256825A1 · Priest · 2015 [cited by examiner]
US 20160112155A1 · Koga · 2016 [cited by examiner]
US 20160378150A1 · Sega et al. · 2016 [cited by applicant]
US 20170093907A1 · Srivastava · 2017 [cited by applicant]
US 20170279666A1 · Alshinnawi et al. · 2017 [cited by applicant]
US 20170289912A1 · Ishii · 2017 [cited by examiner]
US 20180060752A1 · Gross et al. · 2018 [cited by applicant]
US 20180324198A1 · Borthakur et al. · 2018 [cited by applicant]
US 20190158175A1 · Shrikhande et al. · 2019 [cited by applicant]
US 20190182120A1 · Coccia et al. · 2019 [cited by applicant]
US 20190188070A1 · Das · 2019 [cited by examiner]
US 20190238400A1 · Yang et al. · 2019 [cited by applicant]
US 20190303726A1 · Cote et al. · 2019 [cited by applicant]
US 20200021358A1 · MacCaglia · 2020 [cited by examiner]
US 20200350990A1 · Beattie, Jr. · 2020 [cited by examiner]
US 20210028994A1 · Sattiraju et al. · 2021 [cited by applicant]
US 20210143909A1 · Beattie, Jr. · 2021 [cited by examiner]
US 20210367397A1 · Shirai · 2021 [cited by examiner]
US 20220021449A1 · Kawahara · 2022 [cited by examiner]
US 20220075683A1 · Ghatak · 2022 [cited by examiner]
US 20220100939A1 · Mishra · 2022 [cited by examiner]
US 20220131627A1 · Beacall · 2022 [cited by examiner]
US 20220295316A1 · Vos · 2022 [cited by examiner]
US 20230010692A1 · Sjödin · 2023 [cited by examiner]
CN 101046501A · 2007 [cited by applicant]
CN 101344439A · 2009 [cited by applicant]
CN 103886374A · 2014 [cited by applicant]
WO 2007051843A1 · 2007 [cited by applicant]
WO 2008150754A1 · 2008 [cited by applicant]
Abhijit Chakravarty, et al., “Characterizing Large-Scale Production Reliability for 100G Optical Interconnect in Facebook Data Center,” Facebook, 2017, 1 page. [cited by applicant]
“Simplify HBA Management and Remediate Network Performance Problems,” Broadcom, Emulex SAN Manager, Feb. 26, 2021, 6 pages. [cited by applicant]
“Pearson correlation coefficient,” Wikipedia, Last edited Jan. 18, 2022, 18 pages. [cited by applicant]
SFF Committee, “Diagnostic Monitoring Interface for Optical Transceivers,” SFF-8472, Rev 10.01, Mar. 1, 2017, 2 pages. [cited by applicant]
“k-nearest neighbors algorithm,” Wikipedia, https://en.wikipedia.org/wiki/K-nearest_neighbors_algorithm, Oct. 8, 2019., 11 pages. [cited by applicant]
“Statistical population,” Wikipedia, https://en.wikipedia.org/wiki/Statistical_population, Sep. 25, 2019, 3 pages. [cited by applicant]
“Covariance,” Wikipedia, https://en.wikipedia.org/wiki/Covariance, https://en.wikipedia.org/wiki/Covariance, Oct. 31. 2019, 6 pages. [cited by applicant]
“Standard deviation,” Wikipedia, https://en.wikipedia.org/wiki/Standard_deviation, Nov. 13, 2019, 23 pages. [cited by applicant]
“knn.predict: KNN Prediction Routine using Pre-Calculated Distances,” RDocumentation, Kodama, Version 0.0.1, https://www.rdocumentation.org/packages/KODAMA/versions/0.0.1/topics/knn.predict, downloaded Jan. 24, 2022, 3 … [cited by applicant]