DETAILED ACTION
This communication is in response to applicant’s response filed under 37 C.F.R. §1.111 in response to a non-final office action. Claims 1, 7, and 14 have been amended. Claims 1-20 are subject to examination.
Response to Arguments
Applicant’s arguments with respect to claims 1, 7, and 14 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 § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
Claims 1-20 are rejected under 35 U.S.C. 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor regards as the invention.
Regarding Claims 1, 7, and 14, the claims each recite the limitations “selecting ... one or more applications from a plurality of applications for determining an issue related to an event” and “automatically applying corrective actions based on ... an issue determined by the selected one or more applications”. These limitations renders the claim indefinite because it is unclear whether the “one or more applications” recited in these limitations corresponds to the event-generating “applications associated with the cellular network system” previously recited in the antepenultimate paragraphs of claims 1, 7, and 14.
Regarding Claims 2-6, 8-13, and 15-20, claims 2-6, 8-13, and 15-20 each depend on independent claims 1, 7, or 14, and therefore inherit the 35 U.S.C. 112 issues of the independent claims.
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 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.
Claims 1-4 and 7-11 are rejected under 35 U.S.C. 103 as being unpatentable over Fitzer et al. (US 2020/0186441 A1, hereinafter “Fitzer”) in view of Herman Saffar et al. (US 10,936,717 B1, hereinafter “HS”) and further in view of Patil et al. (US 2018/0196723 A1, hereinafter “Patil”).
Regarding Claim 1, Fitzer teaches a cellular network system for collecting data on the cellular network system, the system comprising: a cellular core network located on a public network and comprising a central unit (CU) (Fitzer: The application server … may be connected by the network … the network may be ... a wireless network (e.g., a mobile or cellular network) ... The network may include one or more portions that constitute ... a public network, see paragraph [0020]; The communication module receives data sent to the application server, see paragraph [0022]);
a series of clusters where each are located in at least one private network and includes at least one distributed unit (DU) (Fitzer: the cluster nodes ... may be connected by the network …. The network may include one or more portions that constitute a private network, see paragraph [0020]); and
at least one server configured for: collecting data from the cellular network using container clusters created using a containerized application, public network and private network (Fitzer: The application server, the Kubernetes API server, the cluster nodes, and the client devices may be connected by the network …. the network may be … a wireless network (e.g., a mobile or cellular network ... The network may include one or more portions that constitute a private network, a public network (e.g., the Internet), or any suitable combination thereof, see paragraph [0020]; The communication module receives data sent to the application server, see paragraph [0022]); and
parsing the collected data (Fitzer: the communication module provides the data to the Kubernetes module. The Kubernetes module parses a file for the selected containerized application, see paragraph [0022]).
Fitzer does not explicitly teach filtering events based on the parsed data based on an identified type of data being collected, the events being generated by applications associated with the cellular network system;
selecting, based on the filtered events and the identified type of the collected data, one or more applications from a plurality of applications for determining an issue related to an event; and
automatically applying corrective actions based on the filtered events and an issue determined by the selected one or more applications.
However, in the same field of endeavor, HS teaches filtering events based on the parsed data based on an identified type of data being collected, the events being generated by applications associated with the cellular network system (HS: Container monitoring includes data monitoring module 302, which monitors different sectors of containers, such as ... applications 324 ... Raw data that is collected from the different sources 320, 322 and 324 by the data monitoring module 302 is preprocessed in the data preprocessing module 304, so as to obtain various behavior metrics for a container. The preprocessed data from the data preprocessing module 304 is provided as container data 306. The container data 306 may be used in machine learning network to detect more general anomaly behavior. The machine learning network may rely on statistics or behavior metrics in the container data 306 including but not limited to CPU and memory utilization, input/output (IO) and network usage, see col. 8 lines 19-41; the decision making algorithm is composed of a series of threshold decisions for specific container behavior metrics (e.g., where different thresholds may be used for different container behavior metrics), see col. 9 lines 17-21); and
automatically applying corrective actions based on the filtered events (HS: remedial action may be performed ... automatically in response to generated alerts indicating detection of anomalous container behavior, see col. 10 lines 8-10).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Fitzer to include the features as taught by HS above in order to detect and correct anomalous cluster behavior in real-time (HS: see col. 10 lines 4-5).
Fitzer-HS does not explicitly teach, selecting, based on the filtered events and the identified type of the collected data, one or more applications from a plurality of applications for determining an issue related to an event.
While Fitzer-HS teaches automatically applying corrective actions (HS: remedial action may be performed ... automatically, see col. 10 lines 8-10), it does not teach basing this action on an issue determined by the selected one or more applications.
However, in the same field of endeavor, Patil teaches selecting, based on the filtered events and the identified type of the collected data, one or more applications from a plurality of applications for determining an issue related to an event (Patil: Application monitoring logic 156 illustratively monitors the running applications for events and stores those events in log data 140 ... and event identifier logic 162 identifies the particular events that are logged in log data 140. Issue detection logic 164 illustratively detects when an issue is occurring in one more of the applications 122-124, based upon the particular events identified by event identifier logic 160. When an issue has occurred, assistant logic 166 is launched. Logic 166 ... aggregates log data 140 and sends it to assistance service computing system 106, see paragraphs [0022]-[0023]; assistance service computing system 106 illustratively includes ... troubleshooter control logic 174, service issue identification logic 176, last known good state identifier logic 178, roll back control logic 180, permission determination logic 182, remedial action control logic 184, and it can include other items 186, see paragraph [0026]); and
automatically applying corrective actions based on an issue determined by the selected one or more applications (Patil: Assistant Logic 166 ... determines whether the issue came about because of a state change in the identified application ... If so, it rolls the state of the application back to its last known good state and reports the issue and roll back to both analysis computing system 104 and assistance service computing system 106. If the error did not occur because of a state change, then assistance logic 166 obtains instructions from either troubleshooting logic 146 or from assistance service computing system 106 indicating steps that can be taken in order to remedy the issue, see paragraph [0023]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Fitzer-HS to include the features as taught by Patil above in order to enhance the operation of integrated applications and the computing system as a whole (Patil: see paragraph [0051]).
Regarding Claim 2, Fitzer-HS-Patil teaches the cellular network system of claim 1.
HS further teaches, the at least one server is further configured for: identifying the type of the data being collected (HS: Container monitoring includes data monitoring module 302, which monitors different sectors of containers, such as file systems 320 (e.g., to determine files that have been changed, deleted, added, etc.), processes 322 (e.g., running processes in a container) and applications 324 (e.g., information gathered using monitoring tools)… Raw data that is collected from the different sources 320, 322 and 324 by the data monitoring module 302 is preprocessed in the data preprocessing module 304, so as to obtain various behavior metrics for a container, see paragraph (46)).
The rationale and motivation for adding the teaching of HS is the same as the rationale and motivation for Claim 1.
Regarding Claim 3, Fitzer-HS-Patil teaches the cellular network system of claim 2.
HS further teaches, the identified type of data collected comprises the category of data (HS: FIG. 3 shows container monitoring which may be implemented using the container monitoring module 114. Container monitoring includes data monitoring module 302, which monitors different sectors of containers, such as file systems 320 (e.g., to determine files that have been changed, deleted, added, etc.), processes 322 (e.g., running processes in a container) and applications 324 (e.g., information gathered using monitoring tools), see paragraph (46)).
The rationale and motivation for adding the teaching of HS is the same as the rationale and motivation for Claim 1.
Regarding Claim 4, Fitzer-HS-Patil teaches the cellular network system of claim 2.
Patil further teaches, the at least one server is further configured for: after identifying the data being collected, the data is sent to the one or more applications based on the identification of that data (Patil: Client computing system 108 ... includes one or more processors or servers 136 ... event identifier logic 162, issue detection logic 164, assistant logic 166, see paragraph [0019]; Issue detection logic 164 illustratively detects when an issue is occurring in one more of the applications 122-124, based upon the particular events identified by event identifier logic 160. When an issue has occurred, assistant logic 166 is launched. Logic 166 ... aggregates log data 140 and sends it to assistance service computing system 106, see paragraph [0023]; assistance service computing system 106 illustratively includes ... troubleshooter control logic 174, service issue identification logic 176, last known good state identifier logic 178, roll back control logic 180, permission determination logic 182, remedial action control logic 184, and it can include other items 186, see paragraph [0026]).
The rationale and motivation for adding the teaching of Patil is the same as the rationale and motivation for Claim 1.
Regarding Claim 7-8, the limitations of claims 7-8 are substantially the same as the limitations of claims 1-2, and claims 7-8 are therefore rejected for the same reasons.
Regarding Claim 9, Fitzer-HS-Patil teaches the method of claim 8.
HS further teaches the parsing the collected data comprises parsing the collected data based on the identified type of data being collected (HS: Raw data that is collected from the different sources 320, 322 and 324 by the data monitoring module 302 is preprocessed in the data preprocessing module 304, so as to obtain various behavior metrics for a container, see paragraph (46)).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Fitzer to include the features as taught by HS above in order to detect and correct anomalous cluster behavior in real-time (HS: see col. 10 lines 4-5).
Regarding Claim 10-11, the limitations of claims 10-11 are substantially the same as the limitations of claims 3-4, and claims 10-11 are therefore rejected for the same reasons.
Claims 5, 6, 12, and 13 are rejected under 35 U.S.C. 103 as being unpatentable over Fitzer-HS-Patil in further view of Kelam et al. (US 2020/0310899 A1, hereinafter “Kelam”).
Regarding Claim 5, Fitzer-HS-Patil teaches the cellular network system of claim 4, but does not explicitly teach, wherein, in response to identifying the data relates to a cluster failing, the data is sent to an application that automatically determines an issue causing the cluster failing based on predetermined issues that have been prestored by the user or based on historical data.
However, in the same field of endeavor, Kelam teaches, wherein, in response to identifying the data relates to a cluster failing, the data is sent to an application that automatically determines an issue causing the cluster failing based on predetermined issues that have been prestored by the user or based on historical data (Kelam: Referring to FIG. 4, application instance failure instructions 425, when executed by processor 410, may cause the processor to monitor and detect failure of an application instance in at least one container in one node from the one or more clusters. ... Metadata retrieval instructions 445, when executed by the one or more processors 410, may cause the processor to retrieve metadata associated with the failed application instance and associated application instances. Fault analysis instructions, when executed by the one or more processors, may cause the processors to determine potential one or more root causes for the failure of the failed application instance based on the analysis of the metadata associated with the failed application instance and associated application instances, see paragraph [0030]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Fitzer-HS-Patil to include the features as taught by Kelam above in order to detect and analyze system failures (Kelam: see paragraph [0030]).
Regarding Claim 6, Fitzer-HS-Patil-Kelam teaches the cellular network system of claim 5.
HS further teaches in response to determining that certain data exceeds preset thresholds, the system automatically determines that certain tasks need to be taken (HS: On detecting anomalous behavior, the alert generation module can generate an alert or other notification for delivery to a security response team... In some embodiments, the decision making algorithm is composed of a series of threshold decisions for specific container behavior metrics, see paragraph (49)).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Fitzer to include the features as taught by HS above in order to detect and correct anomalous cluster behavior in real-time (HS: see col. 10 lines 4-5).
Regarding Claims 12-13, the limitations of the claims are substantially the same as the limitations of claims 5-6, and claims 12-13 are therefore rejected for the same reasons.
Claims 14-18 are rejected under 35 U.S.C. 103 as being unpatentable over Fitzer-HS-Patil in view of Sharma et al. (US 2021/0224245 A1, hereinafter “Sharma”).
Regarding Claim 14, Fitzer teaches a cellular network system for collecting data on the cellular network system, the system comprising: at least one server configured for: collecting data from the cellular network using container clusters created using a containerized application (Fitzer: The application server, the Kubernetes API server, the cluster nodes, and the client devices may be connected by the network …. the network may be … a wireless network (e.g., a mobile or cellular network, see paragraph [0020]; The communication module receives data sent to the application server, see paragraph [0022]); and
parsing the collected data (Fitzer: the communication module provides the data to the Kubernetes module. The Kubernetes module parses a file for the selected containerized application, see paragraph [0022]).
Fitzer does not explicitly teach a 5G cellular network;
filtering events based on the parsed data, the events being generated by applications that support the operation of the cellular network system;
selecting, based on the filtered events and an identified type of the collected data, one or more applications from a plurality of applications for determining an issue related to an event; and
automatically applying corrective actions based on the filtered events and an issue determined by the selected one or more applications.
However, in the same field of endeavor, HS teaches filtering events based on the parsed data, the events being generated by applications that support the operation of the cellular network system (HS: Container monitoring includes data monitoring module 302, which monitors different sectors of containers, such as ... applications 324 ... Raw data that is collected from the different sources 320, 322 and 324 by the data monitoring module 302 is preprocessed in the data preprocessing module 304, so as to obtain various behavior metrics for a container. The preprocessed data from the data preprocessing module 304 is provided as container data 306. The container data 306 may be used in machine learning network to detect more general anomaly behavior. The machine learning network may rely on statistics or behavior metrics in the container data 306 including but not limited to CPU and memory utilization, input/output (IO) and network usage, see col. 8 lines 19-41; the decision making algorithm is composed of a series of threshold decisions for specific container behavior metrics (e.g., where different thresholds may be used for different container behavior metrics), see col. 9 lines 17-21 ); and
automatically applying corrective actions based on the filtered events (HS: remedial action may be performed ... automatically in response to generated alerts indicating detection of anomalous container behavior, see col. 10 lines 8-10).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Fitzer to include the features as taught by HS above in order to detect and correct anomalous cluster behavior in real-time (HS: see col. 10 lines 4-5).
Fitzer-HS does not explicitly teach, a 5G cellular network; and
selecting, based on the filtered events and an identified type of the collected data, one or more applications from a plurality of applications for determining an issue related to an event.
While Fitzer-HS teaches automatically applying corrective actions (HS: remedial action may be performed ... automatically, see col. 10 lines 8-10), it does not teach basing this action on an issue determined by the selected one or more applications.
However, in the same field of endeavor, Patil teaches selecting, based on the filtered events and the identified type of the collected data, one or more applications from a plurality of applications for determining an issue related to an event (Patil: Issue detection logic 164 illustratively detects when an issue is occurring in one more of the applications 122-124, based upon the particular events identified by event identifier logic 160. When an issue has occurred, assistant logic 166 is launched. Logic 166 ... aggregates log data 140 and sends it to assistance service computing system 106, see paragraphs [0022]-[0023]; assistance service computing system 106 illustratively includes ... troubleshooter control logic 174, service issue identification logic 176, last known good state identifier logic 178, roll back control logic 180, permission determination logic 182, remedial action control logic 184, and it can include other items 186, see paragraph [0026]); and
automatically applying corrective actions based on an issue determined by the selected one or more applications (Patil: Assistant Logic 166 ... determines whether the issue came about because of a state change in the identified application ... If so, it rolls the state of the application back to its last known good state and reports the issue and roll back to both analysis computing system 104 and assistance service computing system 106. If the error did not occur because of a state change, then assistance logic 166 obtains instructions from either troubleshooting logic 146 or from assistance service computing system 106 indicating steps that can be taken in order to remedy the issue, see paragraph [0023]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Fitzer-HS to include the features as taught by Patil above in order to enhance the operation of integrated applications and the computing system as a whole (Patil: see paragraph [0051]).
Fitzer-HS-Patil does not explicitly teach a 5G cellular network.
However, in the same field of endeavor, Sharma teaches a 5G cellular network (Sharma: Network 240 includes one or more wired and/or wireless networks. For example, network 240 may include a cellular network (e.g., a long-term evolution (LTE) network, … a 5G network, see paragraph [0091]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Fitzer-HS-Patil to include the features as taught by Sharma above in order to conserve computing and network resources (Sharma: see paragraph [0014]).
Regarding Claims 15-18, Fitzer-HS-Patil-Sharma teaches the 5G cellular network system of claim 14.
Regarding all other limitations of claims 15-18, the limitations are substantially the same as the limitations of claims 8-11, and claims 15-18 are therefore rejected for the same reasons.
Claims 19 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Fitzer-HS-Patil-Sharma in view of Kelam.
Regarding Claim 19, Fitzer-HS-Patil-Sharma teaches the 5G cellular network system of claim 18, but does not explicitly teach, wherein, in response to identifying the data relates to an issue, the data is sent to an application that automatically determines whatever is causing the issue based on predetermined issues that have been prestored by the user or based on historical data.
However, in the same field of endeavor, Kelam teaches, wherein, in response to identifying the data relates to an issue, the data is sent to an application that automatically determines whatever is causing the issue based on predetermined issues that have been prestored by the user or based on historical data (Kelam: Referring to FIG. 4, application instance failure instructions 425, when executed by processor 410, may cause the processor to monitor and detect failure of an application instance in at least one container in one node from the one or more clusters ... Metadata retrieval instructions 445, when executed by the one or more processors 410, may cause the processor to retrieve metadata associated with the failed application instance and associated application instances. Fault analysis instructions, when executed by the one or more processors, may cause the processors to determine potential one or more root causes for the failure of the failed application instance based on the analysis of the metadata associated with the failed application instance and associated application instances, see paragraph [0030]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Fitzer-HS-Patil-Sharma to include the features as taught by Kelam above in order to detect and analyze system failures (Kelam: see paragraph [0030]).
Regarding Claim 20, Fitzer-HS-Patil-Sharma-Kelam teaches the cellular network system of claim 19.
HS further teaches, in response to determining that certain data exceeds preset thresholds, the system automatically determines what tasks need to be taken (HS: On detecting anomalous behavior, the alert generation module can generate an alert or other notification for delivery to a security response team... In some embodiments, the decision making algorithm is composed of a series of threshold decisions for specific container behavior metrics, see paragraph (49)).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Fitzer to include the features as taught by HS above in order to detect and correct anomalous cluster behavior in real-time (HS: see col. 10 lines 4-5).
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to PHILLIP J EGAN KEARNS whose telephone number is 571-272-4869. The examiner can normally be reached M-Th 10-6 MST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, NOEL BEHARRY can be reached at 571-270-5630. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/P.K./Examiner, Art Unit 2416
/NOEL R BEHARRY/Supervisory Patent Examiner, Art Unit 2416
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