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 is a non-final office action. Claims 1-20 were considered.
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 07/23/2025 has been entered.
Response to Amendment
This action is in response to communication filed on 06/24/2025.
a. Claims 1-20 are pending in this application.
b. Claims 1, 7-9, 13-15, 19 and 20 has been amended.
Response to Arguments Regarding Claim Rejections – 35 USC § 103
Applicant's arguments, see page 7-10 of REMARKS, filed on 06/24/2025, with respect to Claim Rejections - 35 USC § 103 have been fully considered. Applicant’s arguments with respect to claim(s) 1-20 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Claim Rejections - 35 USC § 101
5. 35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 15-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim(s) does/do not fall within at least one of the four categories of patent eligible subject matter because the claim is directed towards signals per se. Claims 15-20 recites in part “A computer-readable medium” however the specification does not define a “computer-readable medium” to exclude transitory signals. At most specification in [23] describes “NMS 170 includes one or more processors and one or more non-transient storage devices storing computer-readable instructions configured to perform management functions of network 100”. The claim language in claims 15-20 is not clear if the computer-readable medium is non-transitory, therefore claim 15-20 are directed towards signals per se and not one of the four categories of statutory subject matter. Claims 15-20 can be amended to include language such as “non-transitory computer-readable medium…” to solve these issue.
Claim Rejections - 35 USC § 103
6. 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.
Claim 1-6, 9-12 and 15-18 are rejected under 35 U.S.C. 103 as being unpatentable over Muddu et al. (US 2017/0063897A1, hereinafter Muddu) in view of Gopalakrishnan et al. (US 20170034720 A1, hereinafter Gopal) in view of Eleftheriadis et al. (US 2022/0400394 A1, hereinafter Eleftheriadis).
Regarding claim 1, Muddu teaches a method executed by a processor, the method comprising:
displaying trend data of a network in a first user interface module (Fig. 40E (4070) and [471]: FIG. 40E additionally includes Threat Anomalies Trend 4070. This provides a line graph indicating the number of anomalies during periods of time. With this illustration, a GUI user can quickly discern whether a large number of anomalies occurred on a particular date or time period, and whether there is a trend of increasing or decreasing anomalies (i.e. displaying trend data as in Fig. 40E(4060, 4070)));
activating an annotation to the displayed trend data of the network performance indicator in the first user interface module ([471]: By hovering over a point on the line, the GUI generates a bubble indicating the date and number of anomalies on that date.(i.e. bubbles are the annotations that are activated in trend data as shown in Fig. 40E(4060, 4070)));
in response to a user input associated with the annotation, displaying performance data of the site of the plurality of sites in a second user interface module ([471]: Similar to the Threat Anomalies Timeline 4060, upon clicking on a bubble, the GUI generates an associated Anomalies Table view 4200, in the format shown in FIG. 42 (i.e. user clicking on the bubble displays performance data in second interface as shown in Fig. 42(4200))).
Muddu however does not teach wherein the network comprises a plurality of sites, each site of the plurality of sites generates a corresponding performance indicator, and the trend data comprise values of a network performance indicator separate from the performance indicators of the plurality of sites, the values of the network performance indicator comprising a combination of values of the performance indicators of the plurality of sites; in response to a value of the network performance indicator having a first predefined relationship to a first level associated with the network performance indicator, activating an annotation, wherein the annotation comprises a representation of a value of the performance indicator of a site of the plurality of sites having a second predefined relationship to a second threshold level associated with the performance indicators of the plurality of sites.
Gopal teaches wherein the network comprises a plurality of sites ([46]: At 310, a number of sets of data points (e.g., data points 202 in FIG. 2) of a number of network elements (NEs, e.g., NEs 112 in FIG. 1) are received, for example, by operation of a processing apparatus (e.g., the processor 126 of a network element 112 in FIG. 1). Each set of data points corresponds to a respective network element.), each site of the plurality of sites generates a corresponding performance indicator (Fig. 2(205) and [28-29, 46]: A cell's individual network behavior pattern can be determined based on one or more KPIs and performance counter values of the cell. The performance counter values can include one or more traffic-resource attributes, such as a number of active users in the network, a number of traffic bytes in the network, a throughput of the network, an interference level, a downlink (DL) total transmit power level, or other types of indicators representing traffic information, coverage, and interference of the cell. Unlike UE MRs or CHRs, performance counter values are monitored and collected on a regular basis in the operator network (i.e. each cell generates performance data)), and
the trend data comprise values of a network performance indicator separate from the performance indicators of the plurality of sites (Fig. 2(205) and [28-31, 48-49]: A cell's individual network behavior pattern can be determined based on one or more KPIs and performance counter values of the cell. As shown in plot 205, each circle 202 represents a set of data points for a cell. The plot 205 shows a global regression model 210 that represents the global relationship pattern between the KPI (represented by the y-axis 201) and the performance counter value (represented by the x-axis 203). In this case, the global regression model 210 can also be referred to as the global behavior curve that represents the cells' global behavior in terms of network KPI versus the performance counter values (i.e. the behavior curve of network showing combination of performance for multiple cells)), the values of the network performance indicator comprising a combination of values of the performance indicators of the plurality of sites ([31, 46-48]: The plot 205 shows a global regression model 210 that represents the global relationship pattern between the KPI (represented by the y-axis 201) and the performance counter value (represented by the x-axis 203) (i.e. performance indicator having combination of performances for plurality of cells)).
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Muddu to incorporate the teachings of Gopal and the network comprises a plurality of sites, each site of the plurality of sites generates a corresponding performance indicator; the trend data comprise values of a network performance indicator separate from the performance indicators of the plurality of sites, the values of the network performance indicator comprising a combination of values of the performance indicators of the plurality of sites. One of ordinary skilled in the art would have been motivated to combine the teachings in order for predicting network performance (Gopal, [44]).
Muddu in view of Gopal however does not teach in response to a value of the network performance indicator having a first predefined relationship to a first threshold level associated with the network performance indicator, activating an annotation; wherein the annotation comprises a representation of a value of the performance indicator of a site of the plurality of sites having a second predefined relationship to a second threshold level associated with the performance indicators of the plurality of sites.
Eleftheriadis teaches in response to a value of the network performance indicator having a first predefined relationship to a first threshold level associated with the network performance indicator (Fig. 8(S82-S83) and [168]: In process step S82 of FIG. 8, the processing module 22 compares the respective values of the performance metric of the at least one network node to the corresponding normality threshold in order to classify the first data set as normal or abnormal. In process step S83 of FIG. 8, if the first data set is classified as abnormal based on the comparison of the respective values of the performance metric of the at least one network node to the corresponding normality threshold, the process 80 proceeds to process step S84 (i.e. determine if the performance metric value is towards abnormal based on normality threshold)), activating an annotation ([170]: In process step S84 of FIG. 8, the processing module 22 outputs an alert. [159]: Outputting an alert, may comprise, for example, outputting an alert to a network operator, network engineer or other user, e.g. via a suitable network entity or to a device (e.g. a mobile phone, laptop, etc.) associated with that user (i.e. output alert annotation to the user device interface)),
wherein the annotation comprises a representation of a value of the performance indicator of a site of the plurality of sites having a second predefined relationship to a second threshold level associated with the performance indicators of the plurality of sites ([171]: The alert output may vary depending on whether the alert is due to the first data set being classified as abnormal or due to the probability of the plurality of network nodes 110-162 being classified as normal being less than the predetermined likelihood (i.e. the alert also represents performance metric of nodes having probability to be classified as normal being less than predetermined likelihood (second threshold)).
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Muddu in view of Gopal to incorporate the teachings of Eleftheriadis and in response to a value of the network performance indicator having a first predefined relationship to a first threshold level associated with the network performance indicator, activating an annotation, wherein the annotation comprises a representation of a value of the performance indicator of a site of the plurality of sites having a second predefined relationship to a second threshold level associated with the performance indicators of the plurality of sites. One of ordinary skilled in the art would have been motivated to combine the teachings in order to output an alert (Eleftheriadis, [121]).
Regarding claim 2, Muddu in view of Gopal and Eleftheriadis teaches the method of claim 1.
Gopal teaches wherein the performance indicator of the network and each site of the plurality of sites comprises an availability, accessibility, retainability, integrity, or mobility indicator ([17, 29]: A KPI is a metric of the performance of essential operations and/or processes of a NE. A KPI can keep track and indicate the availability and performance of the network infrastructure. As shown in plot 205, each circle 202 represents a set of data points for a cell. In this example, the set of data points includes a KPI value (reflected by a y-axis coordinate) and a performance counter value (reflected by a x-axis coordinate) of the cell (i.e. performance metric of the cell/ nodes includes availability)).
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Muddu in view of Gopal and Eleftheriadis to incorporate the teachings of Gopal and the performance indicator of the network and each site of the plurality of sites comprises an availability, accessibility, retainability, integrity, or mobility indicator. One of ordinary skilled in the art would have been motivated to combine the teachings in order for predicting network performance (Gopal, [44]).
Regarding claim 3, Muddu in view of Gopal and Eleftheriadis teaches the method of claim 1.
Gopal teaches wherein the performance data of the site of the plurality of sites comprise a value of the performance indicator of the site of the plurality of sites ([26, 29]: Cells 114 with similar characteristics can have similar relationship behaviors between the cells' KPIs and the cells' traffic and/or resource attributes (referred to as traffic-resource attributes). Instead of using cell physics (e.g., inter-site distance, antenna height or tilt, raw measurement values from UE MRs or CHRs) to separate cells into clusters, the computing system 122 can use performance behavior-based clustering techniques to cluster cells based on the cells' network behavior patterns directly. KPI and traffic behavior patterns are learned via regression (i.e. performance data comprises KPI for multiple cells)).
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Muddu in view of Gopal and Eleftheriadis to incorporate the teachings of Gopal and the performance data of the site of the plurality of sites comprise a value of the performance indicator of the site of the plurality of sites. One of ordinary skilled in the art would have been motivated to combine the teachings in order for predicting network performance (Gopal, [44]).
Regarding claim 4, Muddu in view of Gopal and Eleftheriadis teaches the method of claim 1.
Eleftheriadis teaches wherein the annotation further comprises an alarm count corresponding to the site of the plurality of sites ([170-171]: In process step S84 of FIG. 8, the processing module 22 outputs an alert. [159]: Outputting an alert, may comprise, for example, outputting an alert to a network operator, network engineer or other user, e.g. via a suitable network entity or to a device (e.g. a mobile phone, laptop, etc.) associated with that user (i.e. output annotation includes alert/alarm for the network node, here alarm count is one)).
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Muddu in view of Gopal and Eleftheriadis to incorporate the teachings of Eleftheriadis and the annotation further comprises an alarm count corresponding to the site of the plurality of sites. One of ordinary skilled in the art would have been motivated to combine the teachings in order to output an alert (Eleftheriadis, [121]).
Regarding claim 5, Muddu in view of Gopal and Eleftheriadis teaches the method of claim 4.
Eleftheriadis teaches wherein the performance data of the site of the plurality of sites comprise individual alarm data corresponding to the site of the plurality of sites ([169-170]: In process step S83 of FIG. 8, if the first data set is classified as abnormal based on the comparison of the respective values of the performance metric of the at least one network node to the corresponding normality threshold, the process 80 proceeds to process step S84. In process step S84 of FIG. 8, the processing module 22 outputs an alert (i.e. output an alert for the performance metric of each node in the network not within normality threshold as described in fig. 8(S81-S84)).
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Muddu in view of Gopal and Eleftheriadis to incorporate the teachings of Eleftheriadis and the performance data of the site of the plurality of sites comprise individual alarm data corresponding to the site of the plurality of sites. One of ordinary skilled in the art would have been motivated to combine the teachings in order to output an alert (Eleftheriadis, [121]).
Regarding claim 6, Muddu in view of Gopal and Eleftheriadis teaches the method of claim 4.
Eleftheriadis teaches wherein the alarm count is based on an alarm time range and/or alarm selection criteria ([170-171]: In process step S84 of FIG. 8, the processing module 22 outputs an alert. The alert output may vary depending on whether the alert is due to the first data set being classified as abnormal or due to the probability of the plurality of network nodes 110-162 being classified as normal being less than the predetermined likelihood. [159]: Outputting an alert, may comprise, for example, outputting an alert to a network operator, network engineer or other user, e.g. via a suitable network entity or to a device (e.g. a mobile phone, laptop, etc.) associated with that user (i.e. alert output varies based on the selection criteria)).
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Muddu in view of Gopal and Eleftheriadis to incorporate the teachings of Eleftheriadis and the alarm count is based on alarm selection criteria. One of ordinary skilled in the art would have been motivated to combine the teachings in order to output an alert (Eleftheriadis, [121]).
Regarding Claims 9 and 15, they do not teach or further define over claim 1. Therefore, claims 9 and 15 are rejected for the same reason as set forth above in claim 1.
Regarding claim 10, Gopal in view of Eleftheriadis and Muddu teaches the system of claim 9.
Muddu teaches wherein the computer-readable instructions and the processor are configured to cause the system to: display the trend data comprising the values of the network performance indicator (Fig. 40E and [470-471]: FIG. 40E additionally includes Threat Anomalies Trend 4070. This provides a line graph indicating the number of anomalies during periods of time. By hovering over a point on the line, the GUI generates a bubble indicating the date and number of anomalies on that date.).
Gopal teaches the network performance indicator being one of an availability, accessibility, retainability, integrity, or mobility indicator ([17, 29]: A KPI is a metric of the performance of essential operations and/or processes of a NE. A KPI can keep track and indicate the availability and performance of the network infrastructure. As shown in plot 205, each circle 202 represents a set of data points for a cell. In this example, the set of data points includes a KPI value (reflected by a y-axis coordinate) and a performance counter value (reflected by a x-axis coordinate) of the cell (i.e. performance metric of the cell/ nodes includes availability)).
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Muddu in view of Gopal and Eleftheriadis to incorporate the teachings of Gopal and the network performance indicator being one of an availability, accessibility, retainability, integrity, or mobility indicator. One of ordinary skilled in the art would have been motivated to combine the teachings in order for predicting network performance (Gopal, [44]).
Regarding claim 11, Muddu in view of Gopal and Eleftheriadis teaches the system of claim 9.
Gopal teaches wherein the computer-readable instructions and the processor are configured to cause the system to: display the performance data of the site of the plurality of sites comprising a value of the performance indicator of the site of the plurality of sites ([26, 29]: Cells 114 with similar characteristics can have similar relationship behaviors between the cells' KPIs and the cells' traffic and/or resource attributes (referred to as traffic-resource attributes). Instead of using cell physics (e.g., inter-site distance, antenna height or tilt, raw measurement values from UE MRs or CHRs) to separate cells into clusters, the computing system 122 can use performance behavior-based clustering techniques to cluster cells based on the cells' network behavior patterns directly. KPI and traffic behavior patterns are learned via regression (i.e. performance data comprises KPI for multiple cells)).
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Muddu in view of Gopal and Eleftheriadis to incorporate the teachings of Gopal and display the performance data of the site of the plurality of sites comprising a value of the performance indicator of the site of the plurality of sites. One of ordinary skilled in the art would have been motivated to combine the teachings in order for predicting network performance (Gopal, [44]).
Regarding claim 12, Muddu in view of Gopal and Eleftheriadis teaches the system of claim 9.
Eleftheriadis teaches wherein the computer-readable instructions and the processor are configured to cause the system to:
activate the annotation comprising an alarm count corresponding to the site of the plurality of sites ([170-171]: In process step S84 of FIG. 8, the processing module 22 outputs an alert. [159]: Outputting an alert, may comprise, for example, outputting an alert to a network operator, network engineer or other user, e.g. via a suitable network entity or to a device (e.g. a mobile phone, laptop, etc.) associated with that user (i.e. output annotation includes alert/alarm for the network node, here alarm count is one));
display the performance data of the site of the plurality of sites comprising individual alarm data corresponding to the site of the plurality of sites ([169-170]: In process step S83 of FIG. 8, if the first data set is classified as abnormal based on the comparison of the respective values of the performance metric of the at least one network node to the corresponding normality threshold, the process 80 proceeds to process step S84. In process step S84 of FIG. 8, the processing module 22 outputs an alert (i.e. output an alert for the performance metric of each node in the network not within normality threshold as described in fig. 8(S81-S84)).
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Muddu in view of Gopal and Eleftheriadis to incorporate the teachings of Eleftheriadis and activate the annotation comprising an alarm count corresponding to the site of the plurality of sites, display the performance data of the site of the plurality of sites comprising individual alarm data corresponding to the site of the plurality of sites. One of ordinary skilled in the art would have been motivated to combine the teachings in order to output an alert (Eleftheriadis, [121]).
Regarding Claims 16-18, they do not teach or further define over claims 10-12 respectively. Therefore, claims 16-18 are rejected for the same reason as set forth above in claims 10-12 respectively.
Claim 7-8, 13-14 and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Muddu in view of Gopal and Eleftheriadis further in view of Wiley et al. (US 2014/0064086 A1, hereinafter Wiley).
Regarding claim 7, Muddu in view of Gopal and Eleftheriadis teaches the method of claim 1.
Muddu in view of Gopal and Eleftheriadis however does not teach teaches wherein the activating the annotation to the first user interface module comprises
receiving a user input associated with the trend data corresponding to the network performance indicator value having the first predefined relationship to the first threshold level.
Wiley teaches wherein the activating the annotation to the first user interface module comprises
receiving a user input associated with the trend data corresponding to the network performance indicator value having the first predefined relationship to the first threshold level ([247]: The user 2720 may access the network performance information stored in the database 2717 and also perform various other management operations on the databases 2717. For example, the user 2720 may generate additional tables, reconfigure the tables, design new database architectures, and so forth, so that network performance information may be expanded and provide customers, partners, vendors, etc., with different or more detailed information, for example. In addition, the user may generate different ways of managing the network performance information, such as generating statistics based on the modified Y.1731 counter bins, setting up thresholds to cause event messages for alerts to be created (i.e. receiving user operation associated with performance information and user setting for the threshold to generate alerts. Here, providing alert based on set threshold is activation of annotation)).
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Muddu in view of Gopal and Eleftheriadis to further incorporate the teachings of Wiley and activating the annotation to the first user interface module comprises receiving a user input associated with the trend data corresponding to the network performance indicator value having the first predefined relationship to the first threshold level. One of ordinary skilled in the art would have been motivated to combine the teachings in order to perform management operation (Wiley, [247]).
Regarding claim 8, Muddu in view of Gopal and Eleftheriadis teaches the method of claim 1.
Muddu in view of Gopal and Eleftheriadis however does not teach further comprising receiving user selections of each of the first predefined relationship, the first threshold level, the second threshold level, and whether to include alarm data in the annotation.
Wiley teaches further comprising receiving user selections of each of the first predefined relationship, the first threshold level, the second threshold level, and whether to include alarm data in the annotation ([247]: The user 2720 may access the network performance information stored in the database 2717 and also perform various other management operations on the databases 2717. For example, the user 2720 may generate additional tables, reconfigure the tables, design new database architectures, and so forth, so that network performance information may be expanded and provide customers, partners, vendors, etc., with different or more detailed information, for example. In addition, the user may generate different ways of managing the network performance information, such as generating statistics based on the modified Y.1731 counter bins, setting up thresholds to cause event messages for alerts to be created (i.e. receiving user setting for the thresholds (first, second) to cause event messages for alerts to be created. Here, user setting event messages for alerts is selecting the information included in the annotation)).
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Muddu in view of Gopal and Eleftheriadis to further incorporate the teachings of Wiley and receiving user selections of each of the predefined relationship, the first threshold level, the second threshold level, and whether to include alarm data in the annotation. One of ordinary skilled in the art would have been motivated to combine the teachings in order to perform management operation (Wiley, [247]).
Regarding claim 13, Muddu in view of Gopal and Eleftheriadis teaches the system of claim 9.
Muddu in view of Gopal and Eleftheriadis however does not teach wherein the computer-readable instructions and the processor are configured to cause the system to: activate the annotation by further receiving a user input associated with the trend data corresponding to the network performance indicator value having the first predefined relationship to the first threshold level.
Wiley teaches wherein the computer-readable instructions and the processor are configured to cause the system to:
activate the annotation by further receiving a user input associated with the trend data corresponding to the network performance indicator value having the first predefined relationship to the first threshold level ([247]: The user 2720 may access the network performance information stored in the database 2717 and also perform various other management operations on the databases 2717. For example, the user 2720 may generate additional tables, reconfigure the tables, design new database architectures, and so forth, so that network performance information may be expanded and provide customers, partners, vendors, etc., with different or more detailed information, for example. In addition, the user may generate different ways of managing the network performance information, such as generating statistics based on the modified Y.1731 counter bins, setting up thresholds to cause event messages for alerts to be created (i.e. receiving user operation associated with performance information and user setting for the threshold to generate alerts. Here, providing alert based on set threshold is activation of annotation)).
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Muddu in view of Gopal and Eleftheriadis to further incorporate the teachings of Wiley and activating the annotation by receiving a user input associated with the trend data corresponding to the network performance indicator value having the first predefined relationship to the first threshold level. One of ordinary skilled in the art would have been motivated to combine the teachings in order to perform management operation (Wiley, [247]).
Regarding claim 14, Muddu in view of Gopal and Eleftheriadis teaches the system of claim 9.
Muddu in view of Gopal and Eleftheriadis however does not teach wherein the computer-readable instructions and the processor are configured to cause the system to: receive user selections of each of the first predefined relationship, the first threshold level, the second threshold level, and whether to include alarm data in the annotation.
Wiley teaches wherein the computer-readable instructions and the processor are configured to cause the system to:
receive user selections of each of the first predefined relationship, the first threshold level, the second threshold level, and whether to include alarm data in the annotation ([247]: The user 2720 may access the network performance information stored in the database 2717 and also perform various other management operations on the databases 2717. For example, the user 2720 may generate additional tables, reconfigure the tables, design new database architectures, and so forth, so that network performance information may be expanded and provide customers, partners, vendors, etc., with different or more detailed information, for example. In addition, the user may generate different ways of managing the network performance information, such as generating statistics based on the modified Y.1731 counter bins, setting up thresholds to cause event messages for alerts to be created (i.e. receiving user setting for the thresholds (first, second) to cause event messages for alerts to be created. Here, user setting event messages for alerts is selecting the information included in the annotation)).
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Muddu in view of Gopal and Eleftheriadis to incorporate the teachings of Wiley and receiving user selections of each of the first predefined relationship, the first threshold level, the second threshold level, and whether to include alarm data in the annotation. One of ordinary skilled in the art would have been motivated to combine the teachings in order to perform management operation (Wiley, [247]).
Regarding Claims 19-20, they do not teach or further define over claims 13-14 respectively. Therefore, claims 19-20 are rejected for the same reason as set forth above in claims 13-14 respectively.
Additional References
7. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Chawathe et al., US 11627034 B1: Automated Processes And Systems For Troubleshooting A Network Of An Application.
Brown et al., US 11640465 B1: Methods And Systems For Troubleshooting Applications Using Streaming Anomaly Detection.
Conclusion
8. Any inquiry concerning this communication or earlier communications from the examiner should be directed to SUJANA KHAKURAL whose telephone number is (571)272-3704. The examiner can normally be reached on M-F: 7:30AM - 5:30PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Kamal B Divecha can be reached on 571-272-5863. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/SUJANA KHAKURAL/Examiner, Art Unit 2453
/KAMAL B DIVECHA/Supervisory Patent Examiner, Art Unit 2453