CTNF 18/785,195 CTNF 100774 DETAILED ACTION Notice of Pre-AIA or AIA Status 07-03-aia AIA 15-10-aia The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA. Information Disclosure Statement The Information Disclosure Statement filed on 08/19/2024 and 03/06/2025 complies with 37 CFR 1.97. Therefore, the information referred therein has been considered. Claim Rejections - 35 USC § 102 07-06 AIA 15-10-15 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. 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 1-2, 4-6, and 8-9 are rejected under 35 U.S.C. 102( a)(1 ) as being anticipated by Senarath et al. (US 2016/0359682) . Regarding claim 1, Senarath discloses a first method comprising receiving (16-1, 17-1), at a first apparatus (120) that is configured to manage or orchestrate network resources of a first stakeholder, a requirement ([0070], “In operation, the Global Customer Service Management (G-CSM) 187 function of the OSS/BSS 125 receives a request, such as a Network Service Request (NS Request) 130. The G-CSM 187 then determines whether the NS Request 130 can be accommodated on an existing network slice using the current (SSVNFs) 199 with or without modification, or whether a new network slice is required.”) , determining, at the first apparatus (120), at least a part of the requirement that needs to be orchestrated with a second apparatus (128) that is configured to manage or orchestrate network resources for a second stakeholder ([0070], “This determination is then sent to the first Orchestrator 204 function and the Orchestrator 204 function proceeds to instantiate each necessary function for provision of the NS Request 130 by creating a new network slice (i.e. instantiating an new set of SSVNFs) or adding necessary functions to an existing network slice (SSVNF). Those skilled in the art will appreciate that the trigger for determining whether more resources are required can originate with an EM 111 in response to performance measurements of the VNFs 112 for which the EM 111 is managing operation. These measurements can be sent to the OSS/BSS 125 where a function similar to that described above can be triggered.”) , and sending (16-3, 17-3) a request regarding at least a part of the requirement that needs to be orchestrated with the second apparatus (128) to the second apparatus (128) ([0070], “This can result in new requests being assigned to a new slice, or an existing service being migrated to its own slice. The OSS/BSS 125 can, upon determining that additional infrastructure, spectrum or both resources are required, can inform the Orchestrator 204 of the first Operator 200. The Orchestrator 204 can then negotiate with the Orchestrator 254 of the second Operator 250 for the required resources that will allow a scale up or scale out. This provision of the required resources by the second Operator 250 can enable the provision of suitable network resources by the first Operator 200 to accommodate the NS Request 130.”) . Regarding claim 2, Senarath discloses the method according to claim 1, characterized in that the requirement comprises a network intent, a network resource, a network service, a machine learning model, a composition of a machine learning model, or an information about a trust relationship between the first stakeholder and the second stakeholder ([0034], “In some embodiments a method for managing network resources includes receiving a network service request with a first network domain and determining whether there are sufficient resources to perform the network service request with the first network domain. In some embodiments, if there are insufficient resources, the method further includes borrowing network resources from a second network domain to provision the network service request.”) . Regarding claim 4, Senarath discloses the method according to claim 1, characterized in that the method comprises determining, sending, receiving, or requesting a report regarding a network resource, a service requirement, a machine learning model performance, or a machine learning model configuration ([0079], “If the first Orchestrator function of the first NFV-MANO entity (corresponding to Operator A) determines there are insufficient internal resources to fulfill the NS request, it may request to borrow infrastructure from Operator B. Operator B would then provide the requested networking resources and Operator A could manage the VNFs associated with the requested network resources.”) . Regarding claim 5, Senarath discloses a second method comprising receiving (16-1, 17-1), from a first apparatus (120) that is configured to manage or orchestrate network resources of a first stakeholder ([0070], “In operation, the Global Customer Service Management (G-CSM) 187 function of the OSS/BSS 125 receives a request, such as a Network Service Request (NS Request) 130. The G-CSM 187 then determines whether the NS Request 130 can be accommodated on an existing network slice using the current (SSVNFs) 199 with or without modification, or whether a new network slice is required.”) , at a second apparatus (128) that is configured to manage or orchestrate network resources of a second stakeholder, a request regarding at least a part of a requirement that needs to be orchestrated with the second apparatus (128) ([0070], “This determination is then sent to the first Orchestrator 204 function and the Orchestrator 204 function proceeds to instantiate each necessary function for provision of the NS Request 130 by creating a new network slice (i.e. instantiating an new set of SSVNFs) or adding necessary functions to an existing network slice (SSVNF). Those skilled in the art will appreciate that the trigger for determining whether more resources are required can originate with an EM 111 in response to performance measurements of the VNFs 112 for which the EM 111 is managing operation. These measurements can be sent to the OSS/BSS 125 where a function similar to that described above can be triggered.”) , determining at the second apparatus (128) at least a part of the requirement that can be orchestrated with the second apparatus (128), and sending (16-18, 17-9) the response regarding the requirement, to the first apparatus (120) ([0070], “This can result in new requests being assigned to a new slice, or an existing service being migrated to its own slice. The OSS/BSS 125 can, upon determining that additional infrastructure, spectrum or both resources are required, can inform the Orchestrator 204 of the first Operator 200. The Orchestrator 204 can then negotiate with the Orchestrator 254 of the second Operator 250 for the required resources that will allow a scale up or scale out. This provision of the required resources by the second Operator 250 can enable the provision of suitable network resources by the first Operator 200 to accommodate the NS Request 130.”) . Regarding claim 6, Senarath discloses the method according to claim 5, characterized in that the request comprises a network intent, a network resource, a network service, a machine learning model, a composition of a machine learning model, or an information about a trust relationship between the first stakeholder and the second stakeholder ([0034], “In some embodiments a method for managing network resources includes receiving a network service request with a first network domain and determining whether there are sufficient resources to perform the network service request with the first network domain. In some embodiments, if there are insufficient resources, the method further includes borrowing network resources from a second network domain to provision the network service request.”) . Regarding claim 8, Senarath discloses the method according to claim 5, characterized in that the method comprises receiving a request for a report regarding a network resource, a service requirement, a machine learning model performance, or a machine learning model configuration from the first apparatus (120), determining the report, and sending the report to the first apparatus (120) ([0079], “If the first Orchestrator function of the first NFV-MANO entity (corresponding to Operator A) determines there are insufficient internal resources to fulfill the NS request, it may request to borrow infrastructure from Operator B. Operator B would then provide the requested networking resources and Operator A could manage the VNFs associated with the requested network resources.”) . Regarding claim 9, Senarath discloses the method according to claim 5, characterized in that the method comprises sending (16-4, 17-4) a request regarding at least a part of the requirement that needs to be orchestrated to an apparatus (124, 126) of the second stakeholder ([0070], “In operation, the Global Customer Service Management (G-CSM) 187 function of the OSS/BSS 125 receives a request, such as a Network Service Request (NS Request) 130. The G-CSM 187 then determines whether the NS Request 130 can be accommodated on an existing network slice using the current (SSVNFs) 199 with or without modification, or whether a new network slice is required.”) , receiving (16-17, 17-8) a response regarding at least a part of the requirement that needs to be orchestrated from the apparatus (124, 126) of the second stakeholder, and determining the response to the first apparatus (120) depending on the response from the apparatus (124, 126) ([0070], “This can result in new requests being assigned to a new slice, or an existing service being migrated to its own slice. The OSS/BSS 125 can, upon determining that additional infrastructure, spectrum or both resources are required, can inform the Orchestrator 204 of the first Operator 200. The Orchestrator 204 can then negotiate with the Orchestrator 254 of the second Operator 250 for the required resources that will allow a scale up or scale out. This provision of the required resources by the second Operator 250 can enable the provision of suitable network resources by the first Operator 200 to accommodate the NS Request 130.”) . 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, 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. 07-21-aia AIA Claim s 3 and 7 are rejected under 35 U.S.C. 103 as being unpatentable over Senarath et al. (US 2016/0359682) in view of Parker et al. (US 2024/0014831) . Regarding claim 3, Senarath does not disclose the machine learning model configuration. Parker discloses the method according to claim 1, characterized in that the requirement comprises a machine learning model performance, or a machine learning model configuration ([0286], “In the illustrated example of FIG. 27, if, at block 2714, the wireless measurement engine circuitry 200 determines to change the policy based on a machine learning recommendation, control returns to block 2704 to configure the wireless measurement engine based on the AI/ML recommended change to the policy. Otherwise (e.g., if the wireless measurement engine circuitry 200 determines not to change the policy based on a machine learning recommendation), control proceeds to block 2716.”) . 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 Senarath in view of Parker to have the machine learning model configuration. The motivation would have been to improve output and accuracy (e.g., Parker [0107]). Regarding claim 7, Senarath does not disclose the machine learning model configuration. Parker discloses the method according to claim 5, characterized in that the requirement comprises a machine learning model performance or a machine learning model configuration ([0286], “In the illustrated example of FIG. 27, if, at block 2714, the wireless measurement engine circuitry 200 determines to change the policy based on a machine learning recommendation, control returns to block 2704 to configure the wireless measurement engine based on the AI/ML recommended change to the policy. Otherwise (e.g., if the wireless measurement engine circuitry 200 determines not to change the policy based on a machine learning recommendation), control proceeds to block 2716.”) . 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 Senarath in view of Parker to have the machine learning model configuration. The motivation would have been to improve output and accuracy (e.g., Parker [0107]). Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to Nick A Sundara whose telephone number is (571)272-6749. The examiner can normally be reached M-TH 7:30-5:30 EST. 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, Jae Y. Lee can be reached at (571) 270-3936. 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. /NICK ANON SUNDARA/Examiner, Art Unit 2479 /JAE Y LEE/Supervisory Patent Examiner, Art Unit 2479 Application/Control Number: 18/785,195 Page 2 Art Unit: 2479 Application/Control Number: 18/785,195 Page 3 Art Unit: 2479 Application/Control Number: 18/785,195 Page 4 Art Unit: 2479 Application/Control Number: 18/785,195 Page 5 Art Unit: 2479 Application/Control Number: 18/785,195 Page 6 Art Unit: 2479 Application/Control Number: 18/785,195 Page 7 Art Unit: 2479 Application/Control Number: 18/785,195 Page 8 Art Unit: 2479
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