CTNF 18/977,894 CTNF 86129 DETAILED ACTION The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA. The application has been examined. Claims 1-20 are pending. Allowable Subject Matter Claims 4-5 and 7-8 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 and overcoming claim objections and 35 USC § 112 and 103 Rejections. Claim Objections 07-29-01 AIA Claim 12 is objected to because of the following informalities: Claim 12 , line 1, recites “comprising at least of:” and should be changed to -- comprising at least one of: --. Appropriate correction is required. Claim Rejections - 35 USC § 102 07-07-aia AIA 07-07 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 – 07-08-aia AIA (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. 07-15 AIA Claim s 1-3, 9-11, and 13-20 are rejected under 35 U.S.C. 102( a)(1 ) as being unpatentable by Shingari et al. (2016/0036718, hereinafter Shingari) . Regarding claim 1, Shingari discloses a method comprising: obtaining, by a processing system including at least one processor (Shingari, para. 31) , network performance information from a converged access device ( Shingari discloses that the network service analytics (access device) may achieve this through reporting regarding network service performance metrics, root cause analysis of customer issues, forecasting network service demand, capacity planning of network resources, and scheduling and dispatching the network service resources) (Shingari, para. 16) , wherein the converged access device is capable of a fiber access network connection to a communication network and at least one type of wireless access network connection to the communication network ( Shingari discloses that the network 250 (communication network) may include one or more wired and/or wireless (a type of wireless access network) networks associated with a network service provider, the network includes cellular network, a fiber optic-based network, a cloud computing network, etc.) (Shingari, para. 29) ; determining, by the processing system via a converged service management model ( Shingari discloses that the process generates a report for a performance metric, based on network service information associated with a service management process (converged service management model), that identifies a key question associated with the performance metric) (Shingari, para. 60; Fig. 6) in accordance with the network performance information from the converged access device, a network access modality distribution for the converged access device ( Shingari discloses that the performance metric (network performance information) may be an overall (e.g., end to end) performance metric that can be broken down into one or more sub-metrics (network access modality distribution), where each sub-metric may be determined based on the one or more categories of the network service information) (Shingari, para. 61) ; and transmitting, by the processing system to the converged access device, the network access modality distribution for implementation by the converged access device ( Shingari discloses that the analytics device associated with performing the network service analytics, may receive the network service information from the data model device, and perform the network service analytics associated with the network service management process (transmitting the network access modality distribution for implementation) (Shingari, para. 20; Fig. 1B) . Regarding claim 2, Shingari discloses the method of claim 1, wherein the at least one type of wireless access network connection comprises at least one of: a cellular access network connection ( Shingari discloses that the network 250 may include a cellular network, WAN, MAN, fiber optic-based network, cloud computing network, or another type of network) (Shingari, para. 29) ; or a fixed wireless broadband connection ( Shingari discloses that the network 250 may include one or more wired and/or wireless networks associated with the network service provider) (Shingari, para. 29) . Regarding claim 3, Shingari discloses the method of claim 1, wherein the network access modality distribution includes utilizations of both the fiber access network connection and the at least one type of wireless access network connection ( Shingari discloses that the network service management process may be optimized using a network services analytics solution that includes performance metric reporting, root cause analysis, network service demand forecasting, capacity planning (utilizations of network connection and the wireless access network connection), and scheduling and dispatching of network service resources (utilizations of both fiber access network connection and the at least one type of wireless access network connection) (Shingari, para. 23) . Regarding claim 9, Shingari discloses the method of claim 1, wherein the converged service management model comprises a machine learning model that is configured to generate an output ( Shingari discloses that the analytics device 220 may forecast (generate an output) the network service demand (machine learning model) based on historical network service information associated with the network service management process) (Shingari, para. 76) comprising the network access modality distribution for the converged access device in response to an input vector comprising at least the network performance information from the converged access device ( Shingari discloses that the analytics device 220 receives (e.g., based on the user input) an indication to schedule and dispatch the network service resources after analytics device 220 performs capacity planning based on the forecasted network service demand) (Shingari, para. 84; Fig. 6) . Regarding claim 10, Shingari discloses the method of claim 9, wherein the input vector further comprises at least one of: network performance information from other subscriber premises sharing a same fiber access network associated with the fiber access network connection of the converged access device ( Shingari discloses that the analytics device 220 generates the report based on the user input(s) for a particular performance metric (network performance information) for the user(s) to view the requested report) (Shingari, para. 64) ; a time of day ( Shingari discloses that the analytics device 220 provides the network service demand forecast such that the user may view the forecasted network service demand on a periodic basis) (Shingari, para. 79) ; a day of the week; an indicator of a holiday; or an indicator of a mass gathering event associated with an area of the converged access device. Regarding claim 11, Shingari discloses the method of claim 1, wherein at least one of: the network performance information comprises a data traffic demand ( Shingari discloses that the analytics device 220 receives (e.g., based on the user input) an indication to schedule and dispatch the network service resources after analytics device 220 performs capacity planning based on the forecasted network service demand) (Shingari, para. 84; Fig. 6) ; or the data traffic demand is predicted from the network performance information ( Shingari discloses that the analytics device 220 receives (e.g., based on the user input) an indication to schedule and dispatch the network service resources after analytics device 220 performs capacity planning based on the forecasted (predicted) network service demand) (Shingari, para. 84; Fig. 6) . Regarding claim 13, Shingari discloses a non-transitory computer-readable medium (Shingari, para. 31) storing instructions that, when executed by a processing system including at least one processor (Shingari, para. 31) , cause the processing system to perform operations, the operations comprising: obtaining network performance information from a converged access device ( Shingari discloses that the network service analytics (access device) may achieve this through reporting regarding network service performance metrics, root cause analysis of customer issues, forecasting network service demand, capacity planning of network resources, and scheduling and dispatching the network service resources) (Shingari, para. 16) , wherein the converged access device is capable of a fiber access network connection to a communication network and at least one type of wireless access network connection to the communication network ( Shingari discloses that the network 250 (communication network) may include one or more wired and/or wireless (a type of wireless access network) networks associated with a network service provider, the network includes cellular network, a fiber optic-based network, a cloud computing network, etc.) (Shingari, para. 29) ; determining, via a converged service management model ( Shingari discloses that the process generates a report for a performance metric, based on network service information associated with a service management process (converged service management model), that identifies a key question associated with the performance metric) (Shingari, para. 60; Fig. 6) in accordance with the network performance information from the converged access device, a network access modality distribution for the converged access device ( Shingari discloses that the performance metric (network performance information) may be an overall (e.g., end to end) performance metric that can be broken down into one or more sub-metrics (network access modality distribution), where each sub-metric may be determined based on the one or more categories of the network service information) (Shingari, para. 61) ; and transmitting, to the converged access device, the network access modality distribution for implementation by the converged access device ( Shingari discloses that the analytics device associated with performing the network service analytics, may receive the network service information from the data model device, and perform the network service analytics associated with the network service management process (transmitting the network access modality distribution for implementation) (Shingari, para. 20; Fig. 1B) . Regarding claim 14, Shingari discloses a method comprising: monitoring, by a processing system including at least one processor (Shingari, para. 31) of a converged access device, network performance information associated with the converged access device ( Shingari discloses that the network service analytics (access device) may achieve this through reporting regarding network service performance metrics, root cause analysis of customer issues, forecasting network service demand, capacity planning of network resources, and scheduling and dispatching the network service resources) (Shingari, para. 16) , wherein the converged access device is capable of a fiber access network connection to a communication network and at least one type of wireless access network connection to the communication network ( Shingari discloses that the network 250 (communication network) may include one or more wired and/or wireless (a type of wireless access network) networks associated with a network service provider, the network includes cellular network, a fiber optic-based network, a cloud computing network, etc.) (Shingari, para. 29) ; determining, by the processing system, a network performance level shortcoming in accordance with the network performance information ( Shingari discloses that the performance metric (network performance level shortcoming) may be an overall (e.g., end to end) performance metric that can be broken down into one or more sub-metrics (network access modality distribution), where each sub-metric may be determined based on the one or more categories of the network service information) (Shingari, para. 61) ; selecting, by the processing system, a network access modality distribution for implementation by the converged access device ( Shingari discloses that the user indicates (e.g., by selecting corresponding radio buttons), that the user wishes to view a report that includes a summary of various performance metrics for the broadband product within a time frame) (Shingari, para. 109; Fig. 8B) , in response to the determining of the network performance level shortcoming, wherein the network access modality distribution includes at least a first portion of data traffic of the converged access device being allocated to the fiber access network connection and at least a second portion of the data traffic of the converged access device being allocated to the at least one type of wireless access network connection ( Shingari discloses that the performance metric (network performance information) may be an overall (e.g., end to end) performance metric that can be broken down into one or more sub-metrics (network access modality distribution), where each sub-metric may be determined based on the one or more categories of the network service information) (Shingari, para. 61) ; and transmitting, by the processing system to the communication network, an indication of the network access modality distribution that is selected for implementation by the converged access device ( Shingari discloses that the analytics device associated with performing the network service analytics, may receive the network service information from the data model device, and perform the network service analytics associated with the network service management process (transmitting the network access modality distribution for implementation) (Shingari, para. 20; Fig. 1B) . Regarding claim 15, Shingari discloses the method of claim 14, further comprising: implementing, by the processing system, the network access modality distribution that is selected ( Shingari discloses that the user indicates (implementing) (e.g., by selecting corresponding radio buttons), that the user wishes to view a report that includes a summary of various performance metrics for the broadband product within a time frame) (Shingari, para. 109; Fig. 8B) . Regarding claim 16, Shingari discloses the method of claim 14, wherein the network access modality distribution is selected in accordance with a rule set defined by the communication network and provided to the processing system ( Shingari discloses that the user interface may be pre-configured to a standard configuration (rule set defined by the communication network), a specific configuration based on the type of device on which the user interface is displayed, and/or a set of configurations based on capabilities and/or specifications associated with a device on which the user interface is displayed) (Shingari, para. 121) . Regarding claim 17, Shingari discloses the method of claim 14, further comprising: obtaining, by the processing system, from the communication network, an instruction altering the network access modality distribution that is selected for implementation by the converged access device ( Shingari discloses that the analytics device 220 may provide the network service demand forecast such that the user may view the forecasted network service demand or update (alter) the forecasted network service demand when the analytics device 220 receives additional network service information associated with the forecast) (Shingari, para. 79) ; and implementing, by the processing system, the network access modality distribution that is altered in accordance with the instruction ( Shingari discloses that the analytics device 220 may provide the network service demand forecast such that the user may view the forecasted network service demand or update (alter) the forecasted network service demand when the analytics device 220 receives additional network service information associated with the forecast) (Shingari, para. 79) . Regarding claim 18, Shingari discloses the method of claim 14, wherein the network performance level shortcoming is determined via a forecasting model based upon at least the network performance information ( Shingari discloses that the analytics device 220 may provide the network service demand forecast such that the user may view the forecasted network service demand or update (alter) the forecasted network service demand when the analytics device 220 receives additional network service information associated with the forecast) (Shingari, para. 79) . Regarding claim 19, Shingari discloses the method of claim 18, wherein the network performance level shortcoming is determined via the forecasting model ( Shingari discloses that the performance metric (network performance level shortcoming) may be an overall (e.g., end to end) performance metric that can be broken down into one or more sub-metrics (network access modality distribution), where each sub-metric may be determined based on the one or more categories of the network service information) (Shingari, para. 61) further based on network performance information from other subscriber premises sharing a same fiber access network associated with the fiber access network connection of the converged access device ( Shingari discloses that the analytics device 220 generates the report based on the user input(s) for a particular performance metric (network performance information) for the user(s) to view the requested report) (Shingari, para. 64) . Regarding claim 20, Shingari discloses the method of claim 14, wherein the selecting of the network access modality distribution is via a converged service management model comprising a machine learning model that is configured to generate an output ( Shingari discloses that the analytics device 220 may forecast (generate an output) the network service demand (machine learning model) based on historical network service information associated with the network service management process) (Shingari, para. 76) comprising the network access modality distribution that is selected for the converged access device in response to an input vector comprising at least the network performance information from the converged access device ( Shingari discloses that the analytics device 220 receives (e.g., based on the user input) an indication to schedule and dispatch the network service resources after analytics device 220 performs capacity planning based on the forecasted network service demand) (Shingari, para. 84; Fig. 6) . Claim Rejections - 35 USC § 103 07-20-aia AIA 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 of this title, 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. 07-22-aia AIA Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Shingari et al. (2016/0036718, hereinafter Shingari) as applied to claim 1 above, and further in view of Gray et al. (2020/0267580, hereinafter Gray) . Regarding claim 6, Shingari discloses the method of claim 1, but does not explicitly disclose wherein the converged access device is deployed at a subscriber premises, wherein the fiber access network connection comprises one of: a fiber-to-the -premises connection, a fiber-to-the-curb connection, or a fiber-to-the-node connection. In analogous art, Gray teaches wherein the converged access device is deployed at a subscriber premises, wherein the fiber access network connection comprises one of: a fiber-to-the-premises connection ( Gray discloses that the node has a node type of FTTN and other node that has FTTP) (Gray, para. 31) , a fiber-to-the-curb connection, or a fiber-to-the-node connection ( Gray discloses that the node has a node type of FTTN and other node that has FTTP) (Gray, para. 31) . Therefore it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention to take the teachings of Gray related to the converged access device is deployed at a subscriber premises, wherein the fiber access network connection and to combine with Shingari in order to reduce the level of impact with the performance analytics for the communications node for the node type (Gray, para. 27) . 07-22-aia AIA Claim 12 is rejected under 35 U.S.C. 103 as being unpatentable over Shingari et al. (2016/0036718, hereinafter Shingari) as applied to claim 1 above, and further in view of Crespo et al. (2023/0138271, hereinafter Crespo) . Regarding claim 12, Shingari discloses the method of claim 1, but does not explicitly disclose further comprising at least of: activating at least one sector of at least one cellular access point in response to the determining of the network access modality distribution for the converged access device; or adjusting a beam of the at least one sector of the at least one cellular access point in response to the determining of the network access modality distribution for the converged access device. In analogous art, Crespo teaches activating at least one sector of at least one cellular access point in response to the determining of the network access modality distribution for the converged access device; or adjusting a beam of the at least one sector of the at least one cellular access point in response to the determining of the network access modality distribution for the converged access device ( Crespo discloses that the location information may also include other parameter values (adjusting) relating to azimuth, vertical angle (beam), elevation, and/or other similar parameters values) (Crespo, para. 32; Fig. 2A) . Therefore it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention to take the teachings of Crespo related to adjusting the beam of the sector of the cellular access point and to combine with Shingari in order to efficiently mitigate or prevent a degradation or impairment in the network associated with the network performance spread (Crespo, para. 11) . Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to ANDREW WOO whose telephone number is (571)270-7521. The examiner can normally be reached Telework 9:00AM-6:00PM | IFP M-F 9:00AM-6:00PM. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Umar Cheema can be reached at 571-270-3037. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /ANDREW WOO/Examiner, Art Unit 2441 Application/Control Number: 18/977,894 Page 2 Art Unit: 2458 Application/Control Number: 18/977,894 Page 4 Art Unit: 2458 Application/Control Number: 18/977,894 Page 5 Art Unit: 2458 Application/Control Number: 18/977,894 Page 6 Art Unit: 2458 Application/Control Number: 18/977,894 Page 7 Art Unit: 2458 Application/Control Number: 18/977,894 Page 8 Art Unit: 2458 Application/Control Number: 18/977,894 Page 9 Art Unit: 2458 Application/Control Number: 18/977,894 Page 10 Art Unit: 2458 Application/Control Number: 18/977,894 Page 11 Art Unit: 2458 Application/Control Number: 18/977,894 Page 12 Art Unit: 2458 Application/Control Number: 18/977,894 Page 13 Art Unit: 2458 Application/Control Number: 18/977,894 Page 14 Art Unit: 2458
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