DETAILED ACTION
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 .
This office action is responsive to request for continued examination (RCE) filed on 04/10/2026.
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 04/10/2026 has been entered.
Response to Amendment
The Examiner has acknowledged the amended claims 1, 12, 16, and the cancellation of claim 2. The rejection of claims 1, 2 – 21 under 35 U.S.C.112 first paragraph has been withdrawn.
Response to Arguments
Applicant's arguments filed 04/10/2026 have been fully considered but they are not persuasive.
Regarding Applicant’s argument that Xu detects performance degradation "based, for example, on the detection of a timing-based anomaly in a log file" by comparing "a typical, average, median or otherwise expected amount of time between consecutive log entries of particular types in each identified repeated pattern". (Xu, [0102.) This timing analysis of Xu relates to the time elapsed between log entries, not to comparing communication-performance metrics across different predefined time intervals before and after a configuration change as recited by amended Claim 1.
The Examiner respectfully disagrees with Applicant’s assertion because Xu discloses that the pattern being repeated at least a predefined number of times in the log file, detecting, subsequent to identifying the repeated pattern, a deviation from the repeated pattern, and identifying, based on detecting the deviation from the repeated pattern, an anomaly in the transport network (see paragraphs [0023], [0025]).
Xu also discloses that Xu discloses In some embodiments, taking corrective action may include initiating a trap or an interrupt in order to execute an exception or debugging routine, performing a further analysis to determine whether a change in the transport network caused the identified anomaly or to determine whether the identified anomaly represents a functional failure or a performance degradation only, initiating a reversal of a recent hardware configuration or software change, initiating an additional hardware configuration or software change, or disabling a network element or link in the transport network found to have failed or suffered a significant performance degradation, among other possible actions).(see paragraph (paragraph [0109]).
Xu further discloses that the techniques described herein for performance analysis for transport networks using frequent log sequence discovery may be implemented by analytics module 316. This may include extracting log templates from one or more log files, identifying repeated patterns of log entries of particular log template types in the log files, detecting deviations from the repeated patterns, identifying anomalies in the network based on the detected deviations from the repeated patterns, generating an indication of any deviations from the repeated pattern or identified anomalies, and/or taking (or initiating the taking of) one or more corrective actions to mitigate any identified anomalies (see paragraph [0058]).
Regarding Applicant’s argument that In contrast to Xu, Claim 1 recites "assessing an impact of the remedial action in different predefined time intervals before and after a configuration change". The Specification of the present application describes that "the computer system may dynamically assess the impact of a recommended configuration change by computing communication-performance metrics in different time intervals on a longitudinal timeline (where a given time interval has a central location, e.g., a day, and/or a width after a timestamp of a recommended configuration change in a network)" and that "the communication-performance metrics may be computed in time intervals before and after the recommended configuration change in order to assess the impact of the recommended configuration change". The Specification further explains that "the computer system may compute communication-performance metrics of the network on Monday following the system configuration change and the preceding Friday" to "assess system-performance impact of the system configuration change". Additionally, "the computer system may also compare the data on Monday (after the system configuration change) with other days during the preceding week(s) (before the system configuration change)" and "may compare the data for Monday with data for the preceding Monday (so that the comparison is of two Mondays)". This description in the Specification of the present application is a fundamentally different approach from Xu's log pattern deviation detection.
The Examiner respectfully disagrees with Applicant’s argument because while the claims are being examined in light of the specification, the Examiner is not going to bring anything into the claims such as “different time intervals on a longitudinal timeline (where a given time interval has a central location, e.g., a day, and/or a width after a timestamp of a recommended configuration change in a network)". Applicant can always insert the argued limitations in the claims as far as specific days and times to compare the collected data. Therefore, such argument is moot.
Applicant argued that the predetermined period of Wang is a general collection schedule, not a "predefined time interval" specifically triggered when a remedial action is unavailable. Claim 21 indicates the additional information collection for a predefined time interval is specifically triggered by the unavailability of the remedial action. Accordingly, Claim 21 is separately patentable.
The Examiner respectfully disagrees with Applicant’s argument because Wang discloses that a collecting unit 101 configured to collect information on a symptom of the problem in the system. The term "symptom" here refers to a description of the appearance of the problem, i.e., the system behaviors or states caused by the problem. For example, the symptom information may include occurrence time of the problem, the system state at that moment, system behavior, system context, exceptions thrown by the system, and the like.(see paragraph [0024]).
Wang further discloses that the collecting unit 101 in the monitoring apparatus 100, for example, may continuously collect various kinds of problem information at background. Alternatively, the collecting unit 101 may operate intermittently based on a predetermined period (see paragraph [0027]).
The Examiner contends that the combination of the prior art reads on the claimed invention.
It appears that applicants are interpreting the claims very narrow without considering the broad teaching of the references used in the rejection. Applicants are reminded that the examiner is entitled to the broadest reasonable interpretation of the claims. The Applicants always have the opportunity to amend the claims during prosecution and broad interpretation by the examiner reduces the possibility that the claim, once issued, will be interpreted more broadly than is justified. In re Prater 162 USPQ 541,550-51 (CCPA 1969).
Claim Rejections - 35 USC § 103
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 (i.e., changing from AIA to pre-AIA ) 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 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 as a whole 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 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.
Claims 1, and 21 are rejected under 35 U.S.C. 103 as being unpatentable over Wang et al (US 2014/0114613; hereinafter Wang) in view of Dunn et al (US 2023/0336581; hereinafter Dunn), and further in view of Xu et al (US 2020/0021511; hereinafter Xu).
Regarding claim 1, Wang discloses a computer system, comprising:
an interface circuit (fig. 5; paragraphs [paragraphs [0053], [0069]);
a memory configured to store program instructions (502-503, fig. 5; paragraphs [0038], [0067 - 0068]); and
a processor coupled to the interface circuit and the memory, wherein the processor is configured to execute the program instructions (502-503, fig. 5; paragraphs [0038], [0067 - 0068]), and wherein, when executed by the processor, the program instructions cause the computer system to perform operations comprising:
receiving information specifying communication in a network (abstract; paragraphs [0024 - 0025]; Wang discloses that the monitoring apparatus 100 comprises a collecting unit 101 configured to collect information on a symptom of the problem in the system);
computing communication-performance metrics for the network based at least in part on the information (paragraphs [0024 - 0025], [0027], [0042]; Wang discloses that the monitoring apparatus 100 comprises a collecting unit 101 configured to collect information on a symptom of the problem in the system. The term "symptom" here refers to a description of the appearance of the problem, i.e., the system behaviors or states caused by the problem. For example, the symptom information may include occurrence time of the problem, the system state at that moment, system behavior, system context, exceptions thrown by the system, and the like );
detecting a network problem based at least in part on the communication-performance metrics (abstract; paragraphs [0024 - 0025], [0027], [0042]; Wang discloses that the collecting unit 101 in the monitoring apparatus 100, for example, may continuously collect various kinds of problem information at background. Alternatively, the collecting unit 101 may operate intermittently based on a predetermined period. Further, the collecting unit 101 may also be interactively enabled and disabled by a user of the system); and
performing a first group of operations or a second group of operations, wherein the first group of operations comprises automatically determining a remedial action based at least in part on the detected network problem (paragraphs [0012]; [0024 – 0025]; Wang discloses that upon receiving such information, the diagnosis apparatus, for example, may automatically determine a root cause of the problem by querying a backend knowledge repository); and
wherein the second group of operations comprises:
when the remedial action cannot be determined, selectively and automatically instructing one or more edge electronic devices or one or more controllers in the network to collect additional information for a predefined time interval (paragraphs [0009], [0012]; [0024 – 0025], [0052]; Wang discloses that a control unit configured to communicate with the monitoring apparatus to control the monitoring apparatus to collect additional information on the problem in response to being unable to determine the root cause or a confidence of the determined root cause below a predetermined threshold);
after receiving the additional information, automatically diagnosing the network problem (paragraphs [0032 - 0033], [0052]; Wang discloses that a receiving unit 103 configurable to receive from the diagnosis apparatus a command of collecting additional information on the problem and to cause the collecting unit 101 to collecting the additional information responsively);
automatically computing a second remedial action based at least in part on the diagnosis of the network problem (paragraphs [0033], [0052]; Wang discloses that the diagnosis apparatus may issue a command to the receiving unit 103 to instruct the monitoring apparatus 100 to collect information on further symptoms of the problem. In these embodiments, the receiving unit 103 receives the command and informs the collecting unit 101 to operate correspondingly);
providing information specifying the second remedial action for approval; and receiving approval of the second remedial action, wherein, based at least in part on the received approval, the computer system is configured to automatically perform the second remedial action when a subsequent instance of the network problem is detected (paragraphs [0033 - 0034]; Wang discloses that the information as collected will be transmitted to the diagnosis apparatus by the transmitting unit 102).
Wang discloses all the limitations, but fails to specifically disclose that when the determined remedial action is preapproved, automatically performing the determined remedial action.
Dunn, in an analogous art, discloses that when the determined remedial action is preapproved, automatically performing the determined remedial action (paragraphs [0090], [0101], [0135]; Dunn discloses that the autonomous response module located in the endpoint agent may take one or more autonomous response actions preapproved by a human user when predefined conditions of suspicious behavior and/or anomaly level are met).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the teaching of Wang by showing that when the determined remedial action is preapproved, automatically performing the determined remedial action as evidenced by Dunn for the purpose of enabling users of the system to rank different alerts in a rigorous manner and prioritize those that most urgently require action, simultaneously removing the problem of numerous false positives associated with a rule-based approach (see [0198]).
Wang and Dunn disclose substantively all the limitations, but fail to specifically disclose that wherein the operations comprise assessing an impact of the remedial action in different predefined time intervals before and after a configuration change to determine whether a configuration change associated with the remedial action should be reversed.
Xu, in an analogous art, discloses that wherein the operations comprise assessing an impact of the remedial action in different predefined time intervals before and after a configuration change (paragraph [0023], [0025], [0058]; Xu discloses that the pattern being repeated at least a predefined number of times in the log file, detecting, subsequent to identifying the repeated pattern, a deviation from the repeated pattern, and identifying, based on detecting the deviation from the repeated pattern, an anomaly in the transport network) to determine whether a configuration change associated with the remedial action should be reversed (paragraph [0109], [0058]; Xu discloses In some embodiments, taking corrective action may include initiating a trap or an interrupt in order to execute an exception or debugging routine, performing a further analysis to determine whether a change in the transport network caused the identified anomaly or to determine whether the identified anomaly represents a functional failure or a performance degradation only, initiating a reversal of a recent hardware configuration or software change, initiating an additional hardware configuration or software change, or disabling a network element or link in the transport network found to have failed or suffered a significant performance degradation, among other possible actions).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the teaching of Wang and Dunn by showing that wherein the operations comprise assessing an impact of the remedial action in different predefined time intervals before and after a configuration change to determine whether a configuration change associated with the remedial action should be reversed as evidenced by Xu for the purpose of taking corrective action to mitigate the identified anomaly in the transport network.
Regarding claim 3, Wang discloses the computer system of claim 1, wherein the network problem is detected using a pretrained model (paragraphs [0044], [0046]; Wang discloses that Alternatively or additionally, data mining and training methods may be utilized to manage the knowledge repository.); and
wherein, when detecting the network problem, the information is input to the pretrained model and information specifying the network problem is output from the pretrained model (paragraphs [0044], [0046]; Wang discloses that based on relevant information of a previously occurring problem, various currently known or future developed techniques may be utilized to train the knowledge repository to thereby obtain "symptom-root cause" and "root cause-solution" mapping ).
Regarding claim 4, Wang discloses the computer system of claim 3, wherein the pretrained model comprises a machine-learning model or a neural network (paragraphs [0044], [0046]).
Regarding claim 5, Wang discloses the computer system of claim 1, wherein the remedial action is determined using a rule engine, a look-up table or a second pretrained model (paragraphs [0044], [0046]); and
wherein, when determining the remedial action, the information specifying the network problem is used as an input to the rule engine, the look-up table or the second pretrained model and the remedial action is an output from the rule engine, the look-up table or the second pretrained model (paragraphs [0044], [0046]).
Regarding claim 6, Wang discloses the computer system of claim 5, wherein the second pretrained model comprises a machine-learning model or a neural network (paragraphs [0043 - 0043]; Wang discloses that the root cause determined by the expert may be fed to the knowledge repository for the training and learning of the knowledge repository to thereby update the knowledge).
Regarding claim 7, Wang discloses the computer system of claim 5, wherein the operations comprise, based at least in part on the received approval, adding the second remedial action to the rule engine, the look-up table or the second pretrained model (paragraph 0043]; Wang discloses that the analyzing unit 202 may analyze the received information based on rules. For example, a series of predetermined rules may be maintained at the diagnosis apparatus 200 side, indicating the correspondence between problem symptoms and root causes).
Regarding claim 8, Wang discloses the computer system of claim 1, wherein, when the subsequent instance of the network problem is detected, the computer system is configured to automatically perform the second remedial action in one or more portions of the network, or one or more regions of the network associated with the network problem (paragraphs [0037 – 0038]).
Regarding claim 9, Wang discloses the computer system of claim 8, wherein the one or more portions of the network or the one or more regions of the network comprise:
a zone, a wireless local area network (WLAN) group, a WLAN, a group of access points, and/or an access point (paragraph [0029]; Wang discloses that the network, for example, may be a wired network, a wireless network, or a combination thereof, including, but not limited to, at least one of the following: a cellular telephone network, Ethernet, a wireless local area network (WLAN) based on IEEE 802.11, 802.16, 802.20, and/or Worldwide Interoperability for Microwave Access (WiMAX) network).
Regarding claim 10, Wang discloses the computer system of claim 1, wherein providing the information specifying the second remedial action for approval comprises presenting the information specifying the second remedial action in a user interface, and the received approval corresponds to user-interface activity specifying a user selection in the user interface (paragraphs [0034], [0046]; Wang discloses that if the analysis unit 202 cannot locate a root cause of the problem matching the symptom in the knowledge repository, it may turn to a human expert. The root cause determined by the expert may be fed to the knowledge repository for the training and learning of the knowledge repository to thereby update the knowledge.).
Regarding claim 11, Wang discloses the computer system of claim 1, wherein the remedial action or the second remedial action comprises a configuration change in the network (paragraph [0038]; Wang discloses that such additional information, for example, may comprise the configuration of the physical machine where the system is located, software environment, OS environment, network environment, memory and/or processor utilization, etc. The collected additional information will be transmitted from the transmitting unit 102 to the diagnosis apparatus so as to generate the executable software package for recovering the problem).
Regarding claim 21, Wang discloses the computer system of claim 1, wherein the additional information is collected for the predefined time interval when the determined remedial action is unavailable (paragraphs [0011], [0024], [0027], [0038]; Wang discloses that analyzing the received information to determine a root cause of the problem; and communicating with the monitoring apparatus to control the monitoring apparatus to collect additional information on the problem in response to being unable to determine the root cause or a confidence of the determined root cause below a predetermined threshold).
Regarding claim 22, Wang discloses the computer system of claim 1, wherein the predefined time interval is configurable and is user-defined (paragraphs [0022], [0027], [0034]; Wang discloses that the collecting unit 101 may operate intermittently based on a predetermined period. Further, the collecting unit 101 may also be interactively enabled and disabled by a user of the system.).
Claims 12 – 20 incorporate substantively all the limitations of claims 1, and 3 - 11 in computer product and method form rather than system form. The reasons for rejecting claims 1, and 3 - 11 apply in claims 12 – 20. Therefore, claims 12 – 20 are rejecting for the same reasons.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Jacob Cherkas (US 2021/0328891) discloses a system and method for determination of network operation metrics and generation of network operation metrics visualizations.
Contact Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to YVES DALENCOURT whose telephone number is (571)272-3998. The examiner can normally be reached M-F 8AM-5:30PM.
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/YVES DALENCOURT/Primary Examiner, Art Unit 2457
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