Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
DETAILED OFFICE ACTION
Status of Claims
Claims 1-20 are pending in this Office Action.
Information Disclosure Statement
The Information Disclosure Statement (IDS) filed on10/03/2024 and 04/11/2025 have been considered.
Double Patenting
1. The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP §§ 706.02(l)(1) - 706.02(l)(3) for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/process/file/efs/guidance/eTD-info-I.jsp.
2. Claims 8,9,10,11,12,13,14,15,16,17,18,19 and 20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1,2,3,4,5,6,7,8,9,10,11,12 and 13 respectively of U.S. Patent No. 12,126,498. Although the claims at issue are not identical, they are not patentably distinct from each other because of the following similarity of the Claim limitations: (NOTE: Within the Instant application the matching claim limitation matching the Patent is underlined for Clarity of Comparison):
Present Application
Patent Application 12,126,498
As per claim 8, A method comprising: reading values associated with a health parameter of an optical transceiver, wherein each of the values are stored in a memory element of the optical transceiver and the health parameter is associated with a corresponding optical component of the optical transceiver; applying one or more defined regression functions to the values of the health parameter; and predicting a time to fail for the corresponding component of the optical transceiver based on a result of the one or more defined regression functions.
As per Claim 1, A method comprising: reading values associated with a health parameter of an optical component of an optical transceiver, wherein each of the values are stored in a memory element of the optical transceiver; extrapolating the values of the health parameter to predict a future data point of the health parameter; and computing an amount of time to fail for the optical component based on the predicted future data point of the health parameter, wherein the computed amount of time is an amount of time for the health parameter to reach the predicted future data point.
As per claim 9, The method of claim 8, wherein the one or more defined regression functions comprises a polynomial function.
As per claim 2, The method of claim 1, further comprising one or more defined regression functions to the values of the health parameter, wherein the one or more defined regression functions comprise a polynomial function.
As per claim 10, The method of claim 8, wherein applying the polynomial function to the values of the health parameter extrapolates historical data points associated with the health parameter to predict a future data point associated with the health parameter.
As per claim 3, The method of claim 2, wherein applying the polynomial function to the values of the health parameter extrapolates historical data points of the health parameter to predict the future data point of the health parameter.
As per claim 11, The method of claim 10, wherein the future data point is associated with a known fail value corresponding to the parameter.
As per claim 4, The method of claim 3, wherein the future data point is associated with a known fail value corresponding to the parameter.
As per claim 12, The method of claim 10, wherein a time parameter associated with the predicted future data point corresponds to a predicted time to fail for the optical transceiver.
As per claim 5, The method of claim 3, wherein a time parameter associated with the predicted future data point corresponds to a predicted time to fail for the optical transceiver.
As per claim 13, The method of claim 12, wherein the predicted time to fail indicates a number of days remaining before the health parameter drops below a known fail value or a total number of power on days before the parameter drops below a known fail value.
As per claim 6, The method of claim 5, wherein the predicted time to fail indicates a number of days remaining before the health parameter drops below a known fail value or a total number of power on days before the parameter drops below a known fail value.
As per claim 14, The method of claim 8, wherein the values associated with the health parameter corresponds to a current output power of an optical transmitter of the optical transceiver.
As per claim 7, The method of claim 1, wherein the values associated with the health parameter correspond to a current output power of an optical transmitter of the optical transceiver.
As per claim 15, An optical transceiver, comprising: optical communication components; a processor; a memory; a module health monitor, the module health monitor having stored thereon instructions that, when executed by the processor, cause the processor to; monitor, in real-time, health parameters associated with the optical communication components of the optical transceiver; determine whether at least one of the monitored health parameters are below a corresponding threshold value; and in response to determining that the monitored health parameter is below a corresponding threshold value, store one or more values associated with the monitored health parameter in the memory; and a time to fail predictor, the time to fail predictor having stored thereon instructions that, when executed by the processor, cause the processor to: read one or more values associated with the monitored health parameter, wherein each of the values are stored in the memory of the optical transceiver; apply one or more defined regression functions to the values of the monitored health parameter; and predict a time to fail for the corresponding component of the optical transceiver based on a result of the one or more defined regression functions.
As per claim 8, An optical transceiver, comprising: an optical communication component; one or more processors; and memory having stored thereon instructions that, when executed by the one or more processors cause the optical transceiver to: monitor, in real-time, health parameters associated with the optical communication component; determine whether at least one of the monitored health parameters are below a corresponding threshold value; in response to determining that the monitored health parameter is below a corresponding threshold value, store one or more values associated with the monitored health parameter in the memory; read one or more values associated with the monitored health parameter, wherein each of the values are stored in the memory of the optical transceiver; apply extrapolate the values of the health parameter to predict a future data point of the health parameter; and compute an amount of time to fail for the optical communication component based on the predicted future data point of the health parameter, wherein the computed amount of time is an amount of time for the health parameter to reach the predicted future data point.
As per claim 16, The optical transceiver of claim 15, wherein the time to fail predictor having stored thereon instructions that, when executed by the processor, further cause the processor to: automatically perform one or more corrective actions prior to the predicted time to fail.
As per claim 9, The optical transceiver of claim 8, wherein the time to fail predictor having stored thereon instructions that, when executed by the processor, further cause the processor to: automatically perform one or more corrective actions prior to the computed amount of time to fail.
As per claim 17, The optical transceiver of claim 16, wherein the one or more corrective actions comprise: transmit an alert, execute an autonomous self-healing action, and execute a power off.
As per claim 10, The optical transceiver of claim 9, wherein the one or more corrective actions comprise: transmit an alert, execute an autonomous self-healing action, and execute a power off.
As per claim 18, The optical transceiver of claim 15, wherein the optical communication components comprise a transmitter optical subassembly (TOSA) and a receiver optical sub-assembly (ROSA).
As per claim 11, The optical transceiver of claim 8, wherein the optical communication components comprise a transmitter optical subassembly (TOSA) and a receiver optical sub-assembly (ROSA).
As per claim 19, The optical transceiver of claim 16, wherein the monitored health parameters comprise an output power of the TOSA and an input power of the ROSA.
As per claim 12,The optical transceiver of claim 11, wherein the monitored health parameters comprise an output power of the TOSA and an input power of the ROSA.
As per claim 20, The optical transceiver of claim 15, wherein the processor comprises a Field Programmable Gate Array (FPGA).
As per claim 13, The optical transceiver of claim 8, wherein the processor comprises a Field Programmable Gate Array (FPGA).
( A) The features of claim 8 of the current application that are not present in claim 1 of the U.S. Patent No. 12,126,498 are :
“is associated with a corresponding optical component of the optical transceiver; applying one or more defined regression functions to the values of the health parameter; and predicting a time to fail for the corresponding component of the optical transceiver based on a result of the one or more defined regression functions,”
However, in an analogues art, AZADEH ( USPUB 20130251361) in view of JORNOD et al. ( USPUB 20210297171) teaches “is associated with a corresponding optical component of the optical transceiver( Paragraph [0040]- “FIG. 3 illustrates an exemplary statistics generation and status indication control structure 300 in accordance with embodiments of the present disclosure. The present control structure 300 can be utilized to calculate and store statistical information on monitored parameter values, as well as generate status indications (e.g., alarms and warnings) based on the monitored parameter values and statistical information. In some embodiments, control structure 300 may calculate statistical information as a function of time (e.g., using a clock circuit and a counter). Control structure 300 can provide more accurate information regarding trends in optical transceiver operation…” AND Paragraphs [0068-0069]- “… CPU 110 can compare the output power value data to corresponding thresholds stored in data memory 160' and determine a status indication. Once calculated, the status indication can be stored in a status indication register. Additionally, the output power value data (e.g., stored in a parameter register in data memory 160') can be provided to statistics logic 380 so that statistical information can be calculated thereon…”) ; applying one or more defined regression functions to the values of the health parameter ( Paragraphs [0112]- “…This feature of the distribution may prevent the usage of classical regression aiming at directly predicting the PIR. Indeed, as the lower values are heavily more represented than the larger values, a naïve prediction would result in a systematic prediction of the more represented values, which happens to be the transmission period. Instead, the distribution of the target value may be predicted, which adds an operation of distribution modeling before addressing the learning approach…”); and predicting a time to fail for the corresponding component of the optical transceiver based on a result of the one or more defined regression functions( Paragraphs [0065-0068]- “…the future quality of service is predicted for a plurality of points in time of the future (i.e., at least two points in time of the future). For example, the method may comprise predicting a development of the future quality of service over the plurality of points in time of the future. Disclosed embodiments of the present disclosure may be scaled over the plurality of points in time of the future by determining the predicted future environmental model (or rather a plurality of predicted future environmental models) at the plurality of points in time of the future, and using the predicted future environmental models as input to the machine-learning model. In other words, the future quality of service of the wireless communication link may be predicted for the at least two points in time of the future by determining 120 the predicted future environmental model of the one or more active transceivers …”).” , Accordingly, the prior art references teach all of the claimed elements ( i.e Optical transceiver , failure calculation/prediction, memory ,storage and integrated module ) . The combination of the known elements is achieved by the Enhanced Status Monitoring, Storage And Reporting For Optical Transceivers mentioned by AZADEH and the Method, apparatus and computer program for predicting a future quality of service of a wireless communication link mentioned JORNOD et al. within Intelligent Time To Fail Prediction For Optical Transceivers taught in claim 1 of U.S. Patent No. 12,126,498 .
Therefore, the results would have been predictable to one of ordinary skill in the art.
Based on the above findings, it would have been obvious to one of ordinary skill before the
effective filing date of the invention to add the elements taught in AZADEH in view of JORNOD et al. to the system taught in claim 1 of U.S. Patent No. 12,126,498 as no more “than the predictable use of prior-art elements according to their established functions.”
( B) The features of claim 15 of the current application that are not present in claim 8 of the U.S. Patent No. 12,126,498 are :
“ a time to fail predictor, the time to fail predictor having stored thereon instructions that, when executed by the processor, cause the processor to: …apply one or more defined regression functions to the values of the monitored health parameter; and predict a time to fail for the corresponding component of the optical transceiver based on a result of the one or more defined regression functions.”
However, in an analogues art, AZADEH ( USPUB 20130251361) in view of JORNOD et al. ( USPUB 20210297171) teaches “ a time to fail predictor, the time to fail predictor having stored thereon instructions that( Paragraph [0080]- “…predetermined time interval, or over the entire operating life of the optical transceiver. The present method can provide more accurate information regarding trends in optical transceiver operation, predict an impending transceiver failure, and be used to enhance failure analysis by providing details of the optical transceiver just prior to failure….”), when executed by the processor, cause the processor ( Paragraph [0038]- “…Once CPU 110 receives the operational status and/or statistical information request(s) via command signal/bus(es) 220, CPU 110 can send a memory read request to data memory 160 via signal 210. Once the request, command, or a version or derivative thereof (e.g., an operational status and/or statistical information identifier) received on host communications interface 122 is sent to CPU 110 via command signal 220, CPU 110 can issue a read command via bus(es) 210 to data memory 160 and address and pointer memory 112….”)to: …apply one or more defined regression functions to the values of the monitored health parameter( Paragraphs [0112]- “…This feature of the distribution may prevent the usage of classical regression aiming at directly predicting the PIR. Indeed, as the lower values are heavily more represented than the larger values, a naïve prediction would result in a systematic prediction of the more represented values, which happens to be the transmission period. Instead, the distribution of the target value may be predicted, which adds an operation of distribution modeling before addressing the learning approach…”); and predict a time to fail for the corresponding component of the optical transceiver based on a result of the one or more defined regression functions( Paragraphs [0065-0068]- “…the future quality of service is predicted for a plurality of points in time of the future (i.e., at least two points in time of the future). For example, the method may comprise predicting a development of the future quality of service over the plurality of points in time of the future. Disclosed embodiments of the present disclosure may be scaled over the plurality of points in time of the future by determining the predicted future environmental model (or rather a plurality of predicted future environmental models) at the plurality of points in time of the future, and using the predicted future environmental models as input to the machine-learning model. In other words, the future quality of service of the wireless communication link may be predicted for the at least two points in time of the future by determining 120 the predicted future environmental model of the one or more active transceivers …”).” , Accordingly, the prior art references teach all of the claimed elements ( i.e Optical transceiver , failure calculation/prediction, memory ,storage and integrated module ) . The combination of the known elements is achieved by the Enhanced Status Monitoring, Storage And Reporting For Optical Transceivers mentioned by AZADEH and the Method, apparatus and computer program for predicting a future quality of service of a wireless communication link mentioned JORNOD et al. within Intelligent Time To Fail Prediction For Optical Transceivers taught in claim 1 of U.S. Patent No. 12,126,498 .
Therefore, the results would have been predictable to one of ordinary skill in the art.
Based on the above findings, it would have been obvious to one of ordinary skill before the
effective filing date of the invention to add the elements taught in AZADEH in view of JORNOD et al. to the system taught in claim 1 of U.S. Patent No. 12,126,498 as no more “than the predictable use of prior-art elements according to their established functions.”
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless -
(a)(1) The claimed invention was patented, described in a printed publication, or in public use, on sale or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
2. Claims 1,2,3 and 6 are rejected under 35 U.S.C. 102(a) (2) as being unpatentable over AZADEH ( USPUB 20130251361).
As per claim 1, AZADEH teaches A method, comprising: monitoring health parameters associated with an optical transceiver in real-time ( FIG. 1 teaches Optical Transceiver, Paragraph [0008 ] – “…The method generally comprises (1) monitoring one or more parameters related to operation of the electronic device over time to determine a plurality of parameter values, (2) storing the plurality of parameter values in one or more memories, (3) calculating statistical information on the plurality of parameter values, (4) comparing the statistical information to one or more corresponding thresholds stored in the memory(ies), and (5) generating a status indication or flag when the statistical information crosses one or more of the corresponding thresholds. …”) ; determining whether at least one of the monitored health parameters are below a corresponding threshold value ( Paragraph [0050]- “… Status indication registers 316 can be configured to store a result of a comparison (e.g., of a parameter value in parameter registers 308 with corresponding thresholds in threshold registers 312 by comparator 306 received on bus 324) or a statistical value in statistics registers 360 with a corresponding threshold in threshold registers 324 received on bus 334….”) ; and in response to determining that at least one of the monitored health parameters are below the corresponding threshold value, storing a value associated with the health parameter ( Paragraphs [0069-0070]- “…(ii) storing the plurality of parameter values in one or more memories, (iii) calculating statistical information on the plurality of parameter values, (iv) comparing the statistical information to one or more corresponding thresholds, and (v) generating a status indication or flag when the statistical information crosses one or more of the corresponding thresholds. The present method can advantageously provide an approach for monitoring an electronic device over time…”) .
As per claim 2, AZADEH teach claim 1,
AZADEH teaches wherein the stored value indicates a health of a component corresponding to an optical component of the optical transceiver ( Paragraph [0035]- “…a user may store a predetermined number of parameters and/or thresholds in address and pointer memory 112 such that an associated operational status indication (e.g., an operational alarm or warning) or associated statistical information can be provided to host 102 in less processing time than methods not utilizing address and pointer memory 112. A "warning" status indication may indicate an operable system…”) .
As per claim 3, AZADEH teach claim 2,
AZADEH teaches wherein monitoring the health parameters comprises: obtaining a value corresponding to a current output power of an optical transmitter of the optical transceiver ( Paragraph [0066]- “… optical and/or optoelectronic transceiver 400 is configured to monitor at least one operating parameter related to transceiver operation. The operating parameter(s) may include a temperature, a voltage, a current, an optical power, an output power, a modulation amplitude, a frequency, an amplifier gain, a channel spacing, a wavelength, etc. For example, the operating parameter may include an output power provided to ADC 106' (e.g., an output power of laser diode 445 via signal 441)….”) .
As per claim 6, AZADEH teach claim 1,
AZADEH teaches comprising: storing the value associated with the health parameter in a memory element of the optical transceiver ( Paragraph [0068]- “…Once calculated, the statistical information on the output parameter power values can be stored in data memory 160' (e.g., in one or more statistics registers). When a request for statistical information and/or a status indication is received from host 102 via electrical interface 420, data stored in address and pointer memory 112 or data memory 160 can be provided to electrical interface 420 via bus 367 …”) ; and predicting a time to fail for the optical transceiver based on the stored value associated with the health parameter ( Paragraph [0080-0081]- “…. The present method can provide more accurate information regarding trends in optical transceiver operation, predict an impending transceiver failure, and be used to enhance failure analysis by providing details of the optical transceiver just prior to failure. …”).
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b) (2) (C) for any potential 35 U.S.C. 102(a) (2) prior art against the later invention.
3. Claim 7 is rejected under 35 U.S.C 103 as being patentable over AZADEH ( USPUB 20130251361) in view of Dybsetter et al.( USPUB 20090028574).
As per claim 7, AZADEH teach claim 6,
Within analogous art, Dybsetter et al. teaches wherein the memory element comprises an electrically erasable programmable read-only memory (EEPROM) of the optical transceiver ( Paragraph [0028]- “… The control module 105 may have access to a persistent memory 106, which in one embodiment, is an Electrically Erasable and Programmable Read Only Memory (EEPROM). …”) .
One of ordinary skill in the art would have been motivated to combine the teaching of Dybsetter et al. within the modified teaching of the Enhanced Status Monitoring, Storage And Reporting For Optical Transceivers mentioned by AZADEH because the SELF-TESTING OPTICAL TRANSCEIVER mentioned Dybsetter et al. provides a system and method for implementing diagnosis within optical transceiver module.
Therefore, it would have been obvious for one in the ordinary skills in the art before the effective filing date of the claimed invention to implement the SELF-TESTING OPTICAL TRANSCEIVER mentioned Dybsetter et al. within the modified teaching of the Enhanced Status Monitoring, Storage And Reporting For Optical Transceivers mentioned by AZADEH for implementation of a system and method for diagnosis within optical transceiver module.
4. Claims 8,9,10,11,12,13,14,15,16 and 17 is rejected under 35 U.S.C 103 as being patentable over AZADEH ( USPUB 20130251361) in view of JORNOD et al. ( USPUB 20210297171).
As per claim 8, AZADEH teaches A method comprising: reading values associated with a health parameter of an optical transceiver ( Paragraph [0038]- “…Once CPU 110 receives the operational status and/or statistical information request(s) via command signal/bus(es) 220, CPU 110 can send a memory read request to data memory 160 via signal 210. Once the request, command, or a version or derivative thereof (e.g., an operational status and/or statistical information identifier) received on host communications interface 122 is sent to CPU 110 via command signal 220, CPU 110 can issue a read command via bus(es) 210 to data memory 160 and address and pointer memory 112….”) , wherein each of the values are stored in a memory element of the optical transceiver and the health parameter is associated with a corresponding optical component of the optical transceiver ( Paragraph [0040]- “FIG. 3 illustrates an exemplary statistics generation and status indication control structure 300 in accordance with embodiments of the present disclosure. The present control structure 300 can be utilized to calculate and store statistical information on monitored parameter values, as well as generate status indications (e.g., alarms and warnings) based on the monitored parameter values and statistical information. In some embodiments, control structure 300 may calculate statistical information as a function of time (e.g., using a clock circuit and a counter). Control structure 300 can provide more accurate information regarding trends in optical transceiver operation…” AND Paragraphs [0068-0069]- “… CPU 110 can compare the output power value data to corresponding thresholds stored in data memory 160' and determine a status indication. Once calculated, the status indication can be stored in a status indication register. Additionally, the output power value data (e.g., stored in a parameter register in data memory 160') can be provided to statistics logic 380 so that statistical information can be calculated thereon…”) ;
AZADEH does not explicitly teach applying one or more defined regression functions to the values of the health parameter; and predicting a time to fail for the corresponding component of the optical transceiver based on a result of the one or more defined regression functions.
However, within analogous art, JORNOD et al. teaches applying one or more defined regression functions to the values of the health parameter ( Paragraphs [0112]- “…This feature of the distribution may prevent the usage of classical regression aiming at directly predicting the PIR. Indeed, as the lower values are heavily more represented than the larger values, a naïve prediction would result in a systematic prediction of the more represented values, which happens to be the transmission period. Instead, the distribution of the target value may be predicted, which adds an operation of distribution modeling before addressing the learning approach…”) ; and predicting a time to fail for the corresponding component of the optical transceiver based on a result of the one or more defined regression functions ( Paragraphs [0065-0068]- “…the future quality of service is predicted for a plurality of points in time of the future (i.e., at least two points in time of the future). For example, the method may comprise predicting a development of the future quality of service over the plurality of points in time of the future. Disclosed embodiments of the present disclosure may be scaled over the plurality of points in time of the future by determining the predicted future environmental model (or rather a plurality of predicted future environmental models) at the plurality of points in time of the future, and using the predicted future environmental models as input to the machine-learning model. In other words, the future quality of service of the wireless communication link may be predicted for the at least two points in time of the future by determining 120 the predicted future environmental model of the one or more active transceivers …”) .
One of ordinary skill in the art would have been motivated to combine the teaching of JORNOD et al. within the modified teaching of the Enhanced Status Monitoring, Storage And Reporting For Optical Transceivers mentioned by AZADEH because the Method, apparatus and computer program for predicting a future quality of service of a wireless communication link mentioned JORNOD et al. provides a system and method for implementing of predicting quality of communication within the optical communication link.
Therefore, it would have been obvious for one in the ordinary skills in the art before the effective filing date of the claimed invention to implement the Method, apparatus and computer program for predicting a future quality of service of a wireless communication link mentioned JORNOD et al. within the modified teaching of the Enhanced Status Monitoring, Storage And Reporting For Optical Transceivers mentioned by AZADEH for implementation of a system and method for predicting quality of communication within the optical communication link.
As per claim 9, Combination of AZADEH and JORNOD et al. teach claim 8,
AZADEH does not explicitly teach wherein the one or more defined regression functions comprises a polynomial function.
Within analogous art, JORNOD et al. teaches wherein the one or more defined regression functions comprises a polynomial function ( Paragraphs [0110-0112]- “… the prediction target is the PIR time. In the following, F denotes the PIR as random variable. As shown in FIG. 3D, its distribution is heavy tailed. This feature of the distribution may prevent the usage of classical regression aiming at directly predicting the PIR. Indeed, as the lower values are heavily more represented than the larger values, a naïve prediction would result in a systematic prediction of the more represented values, which happens to be the transmission period. Instead, the distribution of the target value may be predicted, which adds an operation of distribution modeling before addressing the learning approach. …”) .
As per claim 10, Combination of AZADEH and JORNOD et al. teach claim 8,
AZADEH does not explicitly teach wherein applying the polynomial function to the values of the health parameter extrapolates historical data points associated with the health parameter to predict a future data point associated with the health parameter.
Within analogous art, JORNOD et al. teaches wherein applying the polynomial function to the values of the health parameter extrapolates historical data points associated with the health parameter to predict a future data point associated with the health parameter (Paragraphs [0052-0054]- “…the time-series projection may be performed 125 based on a statistical fitting function or based on a time autocorrelation function. In a statistical fitting function, a trend of a numerical value may be predicted by performing fitting on historical data on the numerical value. Time autocorrelation is an autocorrelation function that is performed on a time series, to predict a development of the time series over a point or period of time of the future. Both functions may be applied to the above objective. For example, the statistical fitting function or the time autocorrelation function may applied in the plurality of environmental models, to determine the predicted future environmental model (at the point of time of the future, or at least two points in time of the future)….”) .
As per claim 11, Combination of AZADEH and JORNOD et al. teach claim 10,
AZADEH does not explicitly teach wherein the future data point is associated with a known fail value corresponding to the parameter.
Within analogous art, JORNOD et al. teaches wherein the future data point is associated with a known fail value corresponding to the parameter (future data point for prediction taught within Paragraphs [0054-0056]- “… prediction of the future quality of service (since that might be less reliable without some additional inputs), but instead to the environmental model underlying the prediction of the future quality of service. In other words, the time-series projection may yield the predicted future environmental model, with the future quality of service being predicted based on the predicted future environmental model….”) .
As per claim 12, Combination of AZADEH and JORNOD et al. teach claim 10,
AZADEH does not explicitly teach wherein a time parameter associated with the predicted future data point corresponds to a predicted time to fail for the optical transceiver.
Within analogous art, JORNOD et al. teaches wherein a time parameter associated with the predicted future data point corresponds to a predicted time to fail for the optical transceiver ( Paragraphs [0054-0055]- “…predicted future environmental model for the prediction of the future quality of service. In other words, the time-series projection may be determined 125 such, that a progression of the environmental models towards the predicted future environmental model is predicted…”) .
As per claim 13, Combination of AZADEH and JORNOD et al. teach claim 12,
AZADEH does not explicitly teach wherein the predicted time to fail indicates a number of days remaining before the health parameter drops below a known fail value or a total number of power on days before the parameter drops below a known fail value.
Within analogous art, JORNOD et al. teaches wherein the predicted time to fail indicates a number of days remaining before the health parameter drops below a known fail value or a total number of power on days before the parameter drops below a known fail value ( Paragraphs [0067-0068]- “…future quality of service is predicted for a plurality of points in time of the future (i.e., at least two points in time of the future). For example, the method may comprise predicting a development of the future quality of service over the plurality of points in time of the future. Disclosed embodiments of the present disclosure may be scaled over the plurality of points in time of the future by determining the predicted future environmental model (or rather a plurality of predicted future environmental models) at the plurality of points in time of the future, and using the predicted future environmental models as input to the machine-learning model. In other words, the future quality of service of the wireless communication link may be predicted for the at least two points in time of the…”) .
As per claim 14, Combination of AZADEH and JORNOD et al. teach claim 8,
AZADEH teaches wherein the values associated with the health parameter corresponds to a current output power of an optical transmitter of the optical transceiver ( Paragraphs [0040-0041]- “…statistics generation and status indication control structure 300 in accordance with embodiments of the present disclosure. The present control structure 300 can be utilized to calculate and store statistical information on monitored parameter values, as well as generate status indications (e.g., alarms and warnings) based on the monitored parameter…”) .
As per claim 15, AZADEH teaches An optical transceiver ( FIG. 1- Optical Transceiver ( 104)) , comprising: optical communication components ( FIG. 1 teaches optical communication components within the Optical Transceiver) ; a processor ( Paragraph [0023]- “…Host 102 can be a host processor, circuit board, stand-alone optical network device (e.g., repeater, optical switch, set-top box, etc.) or any other component or device including a suitable controller or processor….”) ; a memory ( Paragraph [0024]- “Optical transceiver 104 can include a microcontroller unit (MCU) 120, a clock circuit 130, a battery 135, an optical receiver 140, an optical transmitter 150, and data memory 160….”) ; a module health monitor ( Paragraph [0034]- “…address and pointer memory 112 may store copies of certain parametric data and associated thresholds that are most likely to be requested by CPU 110 for operational status determination…” AND Paragraph [0037]) , the module health monitor having stored thereon instructions that, when executed by the processor ( Paragraph [0026]- “…memory 108 includes non-volatile memory (e.g., instruction memory 108) and volatile memory (e.g., address and pointer memory 112 [see FIG. 2]). Generally, thresholds are stored in volatile memory. In some applications, instructions can be stored in the volatile memory (e.g., RAM) …”) , cause the processor to; monitor, in real-time ( FIG. 1 teaches Optical Transceiver, Paragraph [0008 ] – “…The method generally comprises (1) monitoring one or more parameters related to operation of the electronic device over time to determine a plurality of parameter values, (2) storing the plurality of parameter values in one or more memories, (3) calculating statistical information on the plurality of parameter values, (4) comparing the statistical information to one or more corresponding thresholds stored in the memory(ies), and (5) generating a status indication or flag when the statistical information crosses one or more of the corresponding thresholds. …”), health parameters associated with the optical communication components of the optical transceiver ( Paragraphs [0034-0037]) ; determine whether at least one of the monitored health parameters are below a corresponding threshold value( Paragraph [0050]- “… Status indication registers 316 can be configured to store a result of a comparison (e.g., of a parameter value in parameter registers 308 with corresponding thresholds in threshold registers 312 by comparator 306 received on bus 324) or a statistical value in statistics registers 360 with a
corresponding threshold in threshold registers 324 received on bus 334….”); and in response to determining that the monitored health parameter is below a corresponding threshold value, store one or more values associated with the monitored health parameter in the memory( Paragraphs [0069-0070]- “…(ii) storing the plurality of parameter values in one or more memories, (iii) calculating statistical information on the plurality of parameter values, (iv) comparing the statistical information to one or more corresponding thresholds, and (v) generating a status indication or flag when the statistical information crosses one or more of the corresponding thresholds. The present method can advantageously provide an approach for monitoring an electronic device over time…”); and a time to fail predictor, the time to fail predictor having stored thereon instructions that ( Paragraph [0080]- “…predetermined time interval, or over the entire operating life of the optical transceiver. The present method can provide more accurate information regarding trends in optical transceiver operation, predict an impending transceiver failure, and be used to enhance failure analysis by providing details of the optical transceiver just prior to failure….”) , when executed by the processor, cause the processor to: read one or more values associated with the monitored health parameter ( Paragraph [0038]- “…Once CPU 110 receives the operational status and/or statistical information request(s) via command signal/bus(es) 220, CPU 110 can send a memory read request to data memory 160 via signal 210. Once the request, command, or a version or derivative thereof (e.g., an operational status and/or statistical information identifier) received on host communications interface 122 is sent to CPU 110 via command signal 220, CPU 110 can issue a read command via bus(es) 210 to data memory 160 and address and pointer memory 112….”), wherein each of the values are stored in the memory of the optical transceiver( Paragraph [0040]- “FIG. 3 illustrates an exemplary statistics generation and status indication control structure 300 in accordance with embodiments of the present disclosure. The present control structure 300 can be utilized to calculate and store statistical information on monitored parameter values, as well as generate status indications (e.g., alarms and warnings) based on the monitored parameter values and statistical information. In some embodiments, control structure 300 may calculate statistical information as a function of time (e.g., using a clock circuit and a counter). Control structure 300 can provide more accurate information regarding trends in optical transceiver operation…” AND Paragraphs [0068-0069]- “… CPU 110 can compare the output power value data to corresponding thresholds stored in data memory 160' and determine a status indication. Once calculated, the status indication can be stored in a status indication register. Additionally, the output power value data (e.g., stored in a parameter register in data memory 160') can be provided to statistics logic 380 so that statistical information can be calculated thereon…”);
AZADEH does not explicitly teach apply one or more defined regression functions to the values of the monitored health parameter; and predict a time to fail for the corresponding component of the optical transceiver based on a result of the one or more defined regression functions.
However, within analogous art, JORNOD et al. teaches apply one or more defined regression functions to the values of the monitored health parameter ( Paragraphs [0112]- “…This feature of the distribution may prevent the usage of classical regression aiming at directly predicting the PIR. Indeed, as the lower values are heavily more represented than the larger values, a naïve prediction would result in a systematic prediction of the more represented values, which happens to be the transmission period. Instead, the distribution of the target value may be predicted, which adds an operation of distribution modeling before addressing the learning approach…”) ; and predict a time to fail for the corresponding component of the optical transceiver based on a result of the one or more defined regression functions s ( Paragraphs [0065-0068]- “…the future quality of service is predicted for a plurality of points in time of the future (i.e., at least two points in time of the future). For example, the method may comprise predicting a development of the future quality of service over the plurality of points in time of the future. Disclosed embodiments of the present disclosure may be scaled over the plurality of points in time of the future by determining the predicted future environmental model (or rather a plurality of predicted future environmental models) at the plurality of points in time of the future, and using the predicted future environmental models as input to the machine-learning model. In other words, the future quality of service of the wireless communication link may be predicted for the at least two points in time of the future by determining 120 the predicted future environmental model of the one or more active transceivers …”) .
One of ordinary skill in the art would have been motivated to combine the teaching of JORNOD et al. within the modified teaching of the Enhanced Status Monitoring, Storage And Reporting For Optical Transceivers mentioned by AZADEH because the Method, apparatus and computer program for predicting a future quality of service of a wireless communication link mentioned JORNOD et al. provides a system and method for implementing of predicting quality of communication within the optical communication link.
Therefore, it would have been obvious for one in the ordinary skills in the art before the effective filing date of the claimed invention to implement the Method, apparatus and computer program for predicting a future quality of service of a wireless communication link mentioned JORNOD et al. within the modified teaching of the Enhanced Status Monitoring, Storage And Reporting For Optical Transceivers mentioned by AZADEH for implementation of a system and method for predicting quality of communication within the optical communication link.
As per claim 16, Combination of AZADEH and JORNOD et al. teach claim 15,
AZADEH teaches wherein the time to fail predictor having stored thereon instructions that, when executed by the processor, further cause the processor to: automatically perform one or more corrective actions prior to the predicted time to fail ( FIG. 3 AND Paragraph [0040]- “…The present control structure 300 can be utilized to calculate and store statistical information on monitored parameter values, as well as generate status indications (e.g., alarms and warnings) based on the monitored parameter values and statistical information. In some embodiments, control structure 300 may calculate statistical information as a function of time (e.g., using a clock circuit and a counter). Control structure 300 can provide more accurate information regarding trends in optical transceiver operation, predict an impending transceiver failure, and be used as a type of "black box" to enhance failure analysis by providing details of the optical transceiver just prior to failure….”) .
As per claim 17, Combination of AZADEH and JORNOD et al. teach claim 16,
AZADEH teaches wherein the one or more corrective actions comprise: transmit an alert, execute an autonomous self-healing action, and execute a power off ( Paragraphs [0035-0036]- “… An "alarm" status indication may represent a possible imminent shutdown of the system. Thus, the status indications may indicate that the system is at risk of faulty operation or shutdown due at least in part to the associated operational parametric data crossing the designated threshold in a predetermined direction. For example, the status indications may be represented by indicators such as or corresponding to "NORMAL," "OVER LIMIT," "UNDER LIMIT," "WARNING," "ALARM," and high and low variations of the warning and alarm indications (e.g., "LOW WARNING," "HIGH ALARM," etc.)….”) .
5. Claims 18,19 and 20 are rejected under 35 U.S.C 103 as being patentable over AZADEH ( USPUB 20130251361) in view of JORNOD et al. ( USPUB 20210297171) in further view of Dybsetter et al.( USPUB 20090028574).
As per claim 18, Combination of AZADEH and JORNOD et al. teach claim 15,
Combination of AZADEH and JORNOD et al. does not explicitly teach wherein the optical communication components comprise a transmitter optical subassembly (TOSA) and a receiver optical sub-assembly (ROSA).
Within analogous art, Dybsetter et al. teaches wherein the optical communication components comprise a transmitter optical subassembly (TOSA) and a receiver optical sub-assembly (ROSA) ( Paragraph [0020]- “As depicted in FIG. 1, an exemplary transceiver module 10 includes a transmitter optical subassembly ("TOSA") 12, a receiver optical subassembly ("ROSA") 14, a printed circuit board (PCB) 16 and a housing 18 for containing the components of module 10. TOSA 12 and ROSA 14 are configured to be electrically and/or mechanically connected to PCB 16. …”) .
One of ordinary skill in the art would have been motivated to combine the teaching of Dybsetter et al. within the combined modified teaching of the Enhanced Status Monitoring, Storage And Reporting For Optical Transceivers mentioned by AZADEH and because the SELF-TESTING OPTICAL TRANSCEIVER mentioned Dybsetter et al. the Method, apparatus and computer program for predicting a future quality of service of a wireless communication link mentioned JORNOD et al. provides a system and method for implementing diagnosis within optical transceiver module.
Therefore, it would have been obvious for one in the ordinary skills in the art before the effective filing date of the claimed invention to implement the SELF-TESTING OPTICAL TRANSCEIVER mentioned Dybsetter et al. within the combined modified teaching of the Enhanced Status Monitoring, Storage And Reporting For Optical Transceivers mentioned by AZADEH and because the SELF-TESTING OPTICAL TRANSCEIVER mentioned Dybsetter et al. the Method, apparatus and computer program for predicting a future quality of service of a wireless communication link mentioned JORNOD et al. for implementation of a system and method for diagnosis within optical transceiver module.
As per claim 19, Combination of AZADEH and JORNOD et al. teach claim 16,
Combination of AZADEH and JORNOD et al. does not explicitly teach wherein the monitored health parameters comprise an output power of the TOSA and an input power of the ROSA.
Within analogous art, Dybsetter et al. teaches wherein the monitored health parameters comprise an output power of the TOSA and an input power of the ROSA ( Paragraphs [0058-0060]- “…a self-test may be performed that measures the voltage or current level at a specific portion of the optical transceiver module. For example, a sensor 211 may be configured to measure the expected voltage level at the laser driver 103 or at the post-amplifier 102. This level may then be compared with expected values or otherwise analyzed. For instance, if the excepted voltage level at the specified portion was 3.3 volts and the measured value was 4.0 volts, then it could be ascertained that any failure of optical transceiver module 100 was due to an excess amount of voltage being applied….”) .
One of ordinary skill in the art would have been motivated to combine the teaching of Dybsetter et al. within the combined modified teaching of the Enhanced Status Monitoring, Storage And Reporting For Optical Transceivers mentioned by AZADEH and because the SELF-TESTING OPTICAL TRANSCEIVER mentioned Dybsetter et al. the Method, apparatus and computer program for predicting a future quality of service of a wireless communication link mentioned JORNOD et al. provides a system and method for implementing diagnosis within optical transceiver module.
Therefore, it would have been obvious for one in the ordinary skills in the art before the effective filing date of the claimed invention to implement the SELF-TESTING OPTICAL TRANSCEIVER mentioned Dybsetter et al. within the combined modified teaching of the Enhanced Status Monitoring, Storage And Reporting For Optical Transceivers mentioned by AZADEH and because the SELF-TESTING OPTICAL TRANSCEIVER mentioned Dybsetter et al. the Method, apparatus and computer program for predicting a future quality of service of a wireless communication link mentioned JORNOD et al. for implementation of a system and method for diagnosis within optical transceiver module.
As per claim 20, Combination of AZADEH and JORNOD et al. teach claim 15,
Combination of AZADEH and JORNOD et al. does not explicitly teach wherein the processor comprises a Field Programmable Gate Array (FPGA).
Within analogous art, Dybsetter et al. teaches wherein the processor comprises a Field Programmable Gate Array (FPGA) ( Paragraphs [0036-0038]- “…[0036] Two general-purpose processors 203A and 203B are also included. The processors recognize instructions that follow a particular instruction set, and may perform normal general-purpose operation such as shifting, branching, adding, subtracting, multiplying, dividing, Boolean operations, comparison operations, and the like. In one embodiment, the general-purpose processors 203A and 203B are each a 16-bit processor and may be identically structured. The precise structure of the instruction set is not important to the principles of the present invention as the instruction set may be optimized around a particular hardware environment…”) .
One of ordinary skill in the art would have been motivated to combine the teaching of Dybsetter et al. within the combined modified teaching of the Enhanced Status Monitoring, Storage And Reporting For Optical Transceivers mentioned by AZADEH and because the SELF-TESTING OPTICAL TRANSCEIVER mentioned Dybsetter et al. the Method, apparatus and computer program for predicting a future quality of service of a wireless communication link mentioned JORNOD et al. provides a system and method for implementing diagnosis within optical transceiver module.
Therefore, it would have been obvious for one in the ordinary skills in the art before the effective filing date of the claimed invention to implement the SELF-TESTING OPTICAL TRANSCEIVER mentioned Dybsetter et al. within the combined modified teaching of the Enhanced Status Monitoring, Storage And Reporting For Optical Transceivers mentioned by AZADEH and because the SELF-TESTING OPTICAL TRANSCEIVER mentioned Dybsetter et al. the Method, apparatus and computer program for predicting a future quality of service of a wireless communication link mentioned JORNOD et al. for implementation of a system and method for diagnosis within optical transceiver module.
It is noted that any citations to specific, pages, columns, lines, or figures in the prior art references and any interpretation of the reference should not be considered to be limiting in any way. A reference is relevant for all it contains and may be relied upon for all that it would have reasonably suggested to one having ordinary skill in the art. See MPEP 2123.
Allowable Subject Matter
6. Claims 4 and 5 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
7. The following is an examiner’s statement of reasons for objecting the claims as allowable subject matter:
As to claim 4, prior art of record does not teach or suggest the limitation mentioned within claim 4 : “…determining whether the monitored health parameter is below a corresponding threshold value comprises: determining that the value corresponding to the current output power of the optical transmitter is lower than a minimum threshold value associated with the current output power of the optical transmitter.”
As to claim 5, prior art of record does not teach or suggest the limitation mentioned within claim 5 : “…whether the monitored health parameter is below a corresponding threshold value comprises: determining that the difference between the value corresponding to the current output power of the optical transmitter and a day zero output power of the optical transmitter is lower than a difference threshold value associated with the current output power of the optical transmitter.”
Any comments considered necessary by applicant must be submitted no later than the payment of the issue fee and, to avoid processing delays, should preferably accompany the issue fee. Such submissions should be clearly labeled “Comments on Statement of Reasons for Allowance.”
Examiner’s Notes
8. The Examiner acknowledges the following prior arts below as pertinent to the current applications claim limitations and inventive concept, although the following prior arts shown below were not relied upon to address the limitations within the claim, they are analogous art mentioning the inventive concept key points on (Optical transceiver system, Failure prediction, memory storage, Data processing within the optical transceiver system, power detection and prediction of change etc.).
1) Francesco Musumeci et al.," A Tutorial on Machine Learning for Failure
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Conclusion
9. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Refer to PTO-892, Notice of Reference Cited for a listing of analogous art.
10. Any inquiry concerning this communication or earlier communications from the examiner should be directed to OMAR S. ISMAIL whose telephone number is (571)272-9799 and Fax # (571)273-9799. The examiner can normally be reached on M-F: 9:00 AM - 6:00 PM.
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/OMAR S ISMAIL/Primary Examiner, Art Unit 2635
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