DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Amendment
Acknowledgment is made that claims 1, 21 and 30 are amended. Claims 10-20 are canceled. Claims 1-9 and 21-31 are pending in the instant application.
Response to Arguments
Applicant’s arguments, see Remarks, filed on 02/13/2026 is fully considered.
Claim Rejections under 35 USC § 102
Claims 1-7, 21-27 and 30-31 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Cionca et al. (US 2024/0040433), hereinafter Cionca.
Claim 1 is amended as follows:
“combining the resources as part of generating a package; and
deploying the predesigned, prebuilt product of the network service design solution based on the generating of the package, wherein the deploying occurs without testing the generated package.” (Emphasis added)
Claim 31 is amended as follows:
“generating, by the processing system and based on the third identification, a package to support the predesigned, prebuilt product of the network service design solution, wherein the package includes the resources; and
deploying, by the processing system and based on the generating, the predesigned, prebuilt product of the network service design solution using the package, wherein the deploying occurs without testing the generated package.” (Emphasis added)
On page 7 of the Remarks, Applicant argues Cionca fails to disclose the amended features recited in claims 1 and 21. Applicant’s arguments are persuasive, therefore, a new ground of rejection is made in light of the amendment.
Dependent Claims 2-9, 22-29 and 31
Applicant argues these claims conditionally based on the arguments presented to their parent claim(s). Applicant’s arguments are persuasive, therefore, a new ground of rejection is made in light of the amendment.
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 1-7, 21-27 and 30-31 are rejected under 35 U.S.C. 103 for being unpatentable over Cionca (US 2024/0040433) in view of Floyd et al. (US 2024/0354097), hereinafter Floyd.
As for claim 1, Cionca teaches a device (Fig. 38; paragraph [0166] describes a computer system), comprising:
a processing system including a processor (Fig. 38; Processing Unit(s) 3810; paragraph [0166] describes a processing unit(s)); and
a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations (Fig. 38; memories 3825, 3840; paragraph [0166] describe memories; paragraph [0168] describe various memory units and the processing unit(s) retrieves instructions from the memories to execute operations), the operations comprising:
identifying at least one environment in respect of a deployment of a predesigned, prebuilt product of a network service design solution, resulting in a first identification (paragraphs [0047]-[0050] and [0061] describe a process of identifying, for a potential deployment of a telecommunication network for a particular geographic area, a model that includes a potential access network, a potential edge network, and a potential core network. The process is performed by a network administrator using an algorithm for generating models of 5G infrastructures. The network administrator identifies a model for a potential deployment of the telecommunications network for a geographic area);
identifying, based on the first identification, a plurality of configurations that are to be supported as part of the deployment of the predesigned, prebuilt product of the network service design solution, resulting in a second identification (paragraph [0064] describes the process identifies a number of access nodes and locations across the geographic areas for the access nodes of the telecommunication network. The access nodes connect to FCPs of a potential access network and provide connections between UEs and the telecommunication network. The process also determines load capacities for transport links that connect potential UEs);
identifying, based on the second identification, resources to support the plurality of configurations (paragraph [0065] describes the process determines compute resources allocation for components of the potential deployment of the telecommunications network);
combining the resources as part of generating a package (paragraph [0095] describes the process deploys a final allocation of computing resources to PoPs for consumptions by applications, the final allocation includes specific numbers of vCPUs, NVIDIA RTX servers, storage); and
deploying the predesigned, prebuilt product of the network service design solution based on the package (paragraphs [0060]-[0067] describe a process for deploying a telecommunications network based on simulations performed using a model of a potential deployment of the telecommunications network. The process determines compute resources allocation for components of the potential deployment of the telecommunications network; simulates performance of the components; determines the simulation was successful and transitions to deploy the modeled telecommunications network for the geographic area).
Cionca fails to teach
wherein deploying a product is based on a generating of a package, wherein the deploying occurs without testing the generated package.
Floyd discloses
wherein deploying a product is based on a generating of a package (paragraph [0055] describes the modular update delivery module enables new services to be deployed across many mobile venues due at least in part to it being configured to receive software, to maintain the software in a registry, and to package the software in containers that are compatible with targeted mobile venues), wherein the deploying occurs without testing the generated package (paragraph [0041] describes a software is developed for mobile venues, the software is developed that provides additional capabilities and functionality; paragraphs [0045]-[0046] describe a deployment of the software using containers. Software is packaged into containers, the software is automatically configured to run in the specific environment on the venue server without employing typical extensive development and testing cycles).
One of ordinary skill in the art before the effective filing date of the claimed invention would have recognized the ability to utilize the teachings of Floyd for deploying a software using containers without testing. The teachings of Floyd, when implemented in the Cionca system, will allow one of ordinary skill in the art to provide a enable software distributer to develop and manage the software that provides additional capabilities and functionality to mobile venues. One of ordinary skill in the art would be motivated to utilize the teachings of Floyd in the Cionca system in order to utilize configurations that more closely align with what is on the mobile venue, as opposed to configurations within test environments.
As for claim 2, the combined system of Cionca and Floyd teaches wherein the at least one environment includes a data center and wherein the predesigned, prebuilt product of the network service design solution is deployed as part of the data center (Cionca: paragraph [0052] describes the core datacenters).
As for claim 3, the combined system of Cionca and Floyd teaches wherein the at least one environment includes a core private network, and wherein the predesigned, prebuilt product of the network service design solution is deployed as part of the core private network (Cionca: paragraphs [0047] and [0050] describe the core networks).
As for claim 4, the combined system of Cionca and Floyd teaches wherein the at least one environment includes a mobile edge computing (MEC) environment (Cionca: paragraph [0050] describes mobile edge cloud (MEC)), and wherein the predesigned, prebuilt product of the network service design solution is deployed as part of the MEC environment (Cionca: paragraph [0099] describes applications are deployed to PoPs in the edge network).
As for claim 5, the combined system of Cionca and Floyd teaches wherein the resources include hardware, software, firmware, a function, an application, or any combination thereof (Cionca: paragraphs [0072]-[0073], [0077], [0078] describe access nodes deployment, compute resources deployment, transport network links; paragraphs [0087], [0094]-[0095] describe CPU, vCPU, GPU, memory and storage resources are distributed throughout the telecommunications network to support the deployment of a variety of services and network slices).
As for claim 6, the combined system of Cionca and Floyd teaches wherein the operations further comprise:
subjecting the predesigned, prebuilt product of the network service design solution to testing (Cionca: paragraphs [0066]-[0067] describe a process of simulating performance of the components of the potential deployment of the telecommunications network and the process determines whether the simulation was successful).
As for claim 7, the combined system of Cionca and Floyd teaches wherein the operations further comprise:
based on the testing, determining that there is at least one error in the predesigned, prebuilt product of the network service design solution relative to a specification associated with a second environment (Cionca: paragraph [0067] describes the process determines whether the simulation was successful. When the process determines that the simulation was not successful); and
modifying, based on the determining, the predesigned, prebuilt product of the network service design solution, resulting in a modified product (Cionca: paragraph [0067] describes when the process determines that the simulation was not successful, the process transitions to modify the potential deployment. A network administrator modifies the quantify of resources allocated, the locations of the allocated resources, the locations of the access nodes to achieve a desired result); and
deploying the modified product as part of the second environment (Cionca: paragraph [0067] describes a network administrator modifies the quantity of resources allocated to achieve a desired result. The process then returns to simulate the performance of the potential deployment).
As for claim 30, Cionca teaches a method, comprising:
identifying, by a processing system including a processor, at least one environment in respect of a deployment of a predesigned, prebuilt product of a network service design solution, resulting in a first identification (paragraphs [0047]-[0050] and [0061] describe a process of identifying, for a potential deployment of a telecommunication network for a particular geographic area, a model that includes a potential access network, a potential edge network, and a potential core network. The process is performed by a network administrator using an algorithm for generating models of 5G infrastructures. The network administrator identifies a model for a potential deployment of the telecommunications network for a geographic area; paragraph [0166] describes processing unit(s) retrieves instructions from the memories to execute operations);
identifying, by the processing system and based on the first identification, a plurality of configurations that are to be supported as part of the deployment of the predesigned, prebuilt product of the network service design solution, resulting in a second identification (paragraph [0064] describes the process identifies a number of access nodes and locations across the geographic areas for the access nodes of the telecommunication network. The access nodes connect to FCPs of a potential access network and provide connections between UEs and the telecommunication network. The process also determines load capacities for transport links that connect potential UEs);
identifying, by the processing system and based on the second identification, resources to support the plurality of configurations, resulting in a third identification (paragraph [0065] describes the process determines compute resources allocation for components of the potential deployment of the telecommunications network); and
deploying, by the processing system and based on the generating, the predesigned, prebuilt product of the network service design solution (paragraphs [0060]-[0067] describe a process for deploying a telecommunications network based on simulations performed using a model of a potential deployment of the telecommunications network. The process determines compute resources allocation for components of the potential deployment of the telecommunications network; simulates performance of the components; determines the simulation was successful and transitions to deploy the modeled telecommunications network for the geographic area).
Cionca fails to teach
generating, by a processing system and based on a third identification, a package to support a predesigned, prebuilt product of a network service design solution, wherein the package includes the resources; and
wherein a deploying uses the package, wherein the deploying occurs without testing the generated package.
Floyd discloses
generating, by a processing system and based on a third identification, a package to support a predesigned, prebuilt product of a network service design solution (paragraphs [0054]-[0055] describe a software deployment system includes a container orchestrator, a modular update delivery module, and a venue update manager. The venue update manager receives orders for software for the mobile venue and generates venue specifications based on the ordered software. The modular update delivery module maintains a registry of containers as well as a configuration management repository with software components that may be deployed on a mobile venue. The modular update delivery mobile enables new services to be deployed across many mobile venues due at least in part to it being configured to receive software, to maintain the software registry, and to package the software in containers that are compatible with targeted mobile venues), wherein the package includes the resources (paragraphs [0044] and [0051] describe the containers provide the necessary computing environment/resources to run the software); and
wherein a deploying uses the package (paragraph [0055] describes the modular update delivery module enables new services to be deployed across many mobile venues due at least in part to it being configured to receive software, to maintain the software in a registry, and to package the software in containers that are compatible with targeted mobile venues), wherein the deploying occurs without testing the generated package (paragraph [0041] describes a software is developed for mobile venues, the software is developed that provides additional capabilities and functionality; paragraphs [0045]-[0046] describe a deployment of the software using containers. Software is packaged into containers, the software is automatically configured to run in the specific environment on the venue server without employing typical extensive development and testing cycles).
One of ordinary skill in the art before the effective filing date of the claimed invention would have recognized the ability to utilize the teachings of Floyd for deploying a software using containers without testing. The teachings of Floyd, when implemented in the Cionca system, will allow one of ordinary skill in the art to provide a enable software distributer to develop and manage the software that provides additional capabilities and functionality to mobile venues. One of ordinary skill in the art would be motivated to utilize the teachings of Floyd in the Cionca system in order to utilize configurations that more closely align with what is on the mobile venue, as opposed to configurations within test environments.
As for claim 31, the combined system of Cionca and Floyd teaches wherein the predesigned, prebuilt product of the network service design solution involves a cloud computing solution (Cionca: paragraph [0089] describes a process that selects an application from the identified set of applications and identifies per-user resource requirements for the application. A particular server is specified to support users for a cloud gaming application).
As for claims 21-26 and 27, the claims list all the same elements of claims 1-6 and 7, but in a non-transitory machine-readable medium, comprising executable instructions that, when executed by a processing system including a processor (Cionca” paragraph [0168] describe various memory units and the processing unit(s) retrieves instructions from the memories to execute operations), facilitate performance of operations to carry out the steps of rather than system form, Therefore, the supporting rationale of the rejection to claims 1-6 and 7 applies equally as well to claims 21-26 and 27.
Claims 8 and 28 are rejected under 35 U.S.C. 103 as being unpatentable over Cionca (US 2024/0040433) in view of Floyd (US 2024/0354097) further in view of Peh et al. (US 2020/0364618), hereinafter Peh.
As for claim 8, the combined system of Cianco and Floyd fails to teach wherein an at least one error comprises a first plurality of errors that occur at a first rate, and wherein a modified product incurs a second plurality of errors at a second rate that is less than the first rate.
Peh discloses
wherein an at least one error comprises a first plurality of errors that occur at a first rate (paragraph [0006] and [0009] and [0038]-[0040] describe an evaluation of a model quality to determine a risk score. An early warning system determines which rules checks that the model fails. The early warning system calculates a risk score or an overall risk score for the model by summing risk sub-scores, each sub-score characterizing a degree to which the received data failed a respective rule. The early warning system generates reports based on the risk scores to aid users in identifying sources of errors), and wherein a modified product incurs a second plurality of errors at a second rate that is less than the first rate (paragraphs [0007] and [0044] describe the early warning system tunes hyperparameters of the model to improve the model and reduce the risk score. The early warning system performs automated model update and hyperparameter tuning, determines whether a risk score associated with the new output data warrants an alert indicating poor quality, and repeating this process until no alert is warranted. A semi-autonomous pipeline is used where the early warning system automatically updates and redeploys the model if it can reduce the resulting risk score below a threshold).
One of ordinary skill in the art before the effective filing date of the claimed invention would have recognized the ability to utilize the teachings of Peh for determining a model’s risk score. The teachings of Peh, when implemented in the Cianco and Floyd system, will allow one of ordinary skill in the art to vest the quality of a model. One of ordinary skill in the art would be motivated to utilize the teachings of Peh in the Cianco and Floyd system in order to identify sources of error and perform speedier root cause analysis of a model.
As for claim 28, the claim lists all the same elements of claim 8, but in a non-transitory machine-readable medium, comprising executable instructions that, when executed by a processing system including a processor (Cionca: paragraph [0168] describe various memory units and the processing unit(s) retrieves instructions from the memories to execute operations), facilitate performance of operations to carry out the steps of rather than system form, Therefore, the supporting rationale of the rejection to claim 8 applies equally as well to claim 28.
Claims 9 and 29 are rejected under 35 U.S.C. 103 as being unpatentable over Cionca (US 2024/0040433) in view of Floyd (US 2024/0354097) further in view of Sgobba et al. (US 2022/0345518), hereinafter Sgobba.
As for claim 9, the combined system of Cianco and Floyd fails to teach wherein the identifying of the at least one environment is based on a use of machine learning, artificial intelligence, or a combination thereof.
Sgobba discloses
wherein the identifying of the at least one environment is based on a use of machine learning, artificial intelligence, or a combination thereof (paragraphs [0018]-[0019] describe a computing environments including on premise and off-premise system that can be used to execute a computer program or software component; paragraph [0039]-[0040] describe the off-premise system is a cloud and a trained machine learning model is configured to determine one of the private cloud, public cloud and hybrid cloud for the deployment of the input application module).
One of ordinary skill in the art before the effective filing date of the claimed invention would have recognized the ability to utilize the teachings of Sgobba for applying machine learning model. The teachings of Sgobba, when implemented in the Cianco and Floyd system, will allow one of ordinary skill in the art to deploy an application in a computing environment. One of ordinary skill in the art would be motivated to utilize the teachings of Sgobba in the Cianco and Floyd system in order to reduce decision errors and can thus save processing resources that would otherwise be required to deploy wrongly classified programs (Sgobba: paragraph [0004]).
As for claim 29, the claim lists all the same elements of claim 9, but in a non-transitory machine-readable medium, comprising executable instructions that, when executed by a processing system including a processor (Cianco: paragraph [0168] describe various memory units and the processing unit(s) retrieves instructions from the memories to execute operations), facilitate performance of operations to carry out the steps of rather than system form, Therefore, the supporting rationale of the rejection to claim 9 applies equally as well to claim 29.
Conclusions
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Desai et al. (US 2024/0289264) teach component testing framework
Yeap et al. (US 2022/0111516) teach reliable real-time deployment of robot safety updates
Wisnovsky et al. (US 2019/0107968) teach criteria-based cost-efficient routing and deployment of metadata packages in an on-demand environment.
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 L. T N. whose telephone number is (571)272-1013. The examiner can normally be reached M & Th 5:30 am - 2:30 pm EST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, TONIA DOLLINGER can be reached at 571-272-4170. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/L. T. N/
Examiner, Art Unit 2459
/TONIA L DOLLINGER/Supervisory Patent Examiner, Art Unit 2459
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