CTNF 18/989,208 CTNF 85692 DETAILED ACTION Claims 1-20 are pending. 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 (IDS) submitted on 12/20/2024 is being considered by the examiner. Claim Rejections - 35 USC § 101 07-04-01 AIA 07-04 35 U.S.C. 101 reads as follows: Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title. Claims 1-3, 9, 11-12, 14-15 and 18 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim(s) recite(s) sending/receiving a message containing application model information from one device to another. The limitations of Independent claims 1, 14 and 18 of sending/receiving a message containing application model information, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for recitation of generic computer components. That is, other than reciting “sending by a first device”, nothing in the claim elements precludes the step from practically being performed in the mind. For example, but for “by a first device” language, “sending” and “receiving” in the in context of the claim encompasses a user manually sending the application model information. Regarding the dependent claims mentioned, in these claims merely describe the type of information being sent or just sending/receiving information with no further actions taking place. Examples of this include such as “application model information” which can merely be the identity information of at least one application model supported by the third device, “usage specification information” which can be merely functionality information of the at least one application model, indicating a function associated with the at least one application model, “first indication information”, which is merely whether the first device is allowed to send to the second device the application model information related to the third device, “second indication information” relating to whether the first device has a willingness or capability to provide the application model information related the third device for the second device. Regarding these claims, the examiner refers to the analysis of the independent claims, above. This judicial exception is not integrated into a practical application because the claim is directed to an abstract idea with additional generic computer elements, and the recited computer elements of a first device or second device do not add a meaningful limitation to the abstract idea because they amount to simply implementing the abstract idea on a computer. The claim(s) do not include additional elements that are sufficient to amount to significantly more than the judicial exception because they merely amount to using generic computing components to apply the abstract idea. Therefore, the claims are not patent eligible. 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 – 07-12-aia AIA (a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention. 07-15-03-aia AIA Claim s 1-4, 13-20 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Kelly (US 12,120,138 B1) . With regards to Claim 1, Kelly teaches a communication method, comprising: sending, by a first device, a first message to a second device, wherein the first message contains application model information related to a third device (i.e., …The software agent sends the modified neighboring device data (e.g., in the standardized format) to the scan engine, Col. 3, Lines 35-45; software agent (first device), scan engine (second device), neighboring device (third device); The software agent installed on a particular device responds to requests from the scan engine to provide information about the particular device, such as, for example, user data (e.g., usernames and corresponding permissions), file data (e.g., file names, file contents, file metadata, and the like), group data (e.g., group names, group members, group permissions, and the like), currently installed software applications, and other types of device-related information, Col. 3, Lines 1-14). With regards to Claim 2, Kelly teaches wherein the application model information comprises at least one of: identity information of at least one application model supported by the third device; identity information of at least one application model corresponding model data of which is stored in the third device; identity information of at least one application model corresponding model data of which is not stored in the third device; usage specification information of the at least one application model corresponding model data of which is stored in the third device; identity information of at least one application model that has been activated for use by the third device; or activation indication information of the at least one application model corresponding model data of which is stored in the third device, wherein the activation indication information of the at least one application model indicates whether the at least one application model has been activated for use (i.e., In some embodiments, the software agent 126 may be configured to collect a set of machine characteristics of individual computing devices 102 . The collected machine characteristics may include information that indicates the machine's operating system (OS) version, OS patches installed on the machine, installed applications and their version information, patches, settings, and metadata, files or file contents on the machine, and configuration data such as the machine's registry entries, security settings, usage data, etc., among other information, Col. 7, Line 60-Col. 8, Line 2). With regards to Claim 3, Kelly teaches herein the usage specification information of the at least one application model comprises at least one of: functionality information of the at least one application model, indicating a function associated with the at least one application model; scenario information of the at least one application model, indicating a scenario associated with the at least one application model; usage-range control information of the at least one application model, indicating a usage range of the at least one application model; an input information set of the at least one application model, indicating a type and/or number of input information of the at least one application model; an output information set of the at least one application model, indicating a type and/or number of output information of the at least one application model; input processing information of the at least one application model, indicating a pre-processing manner for the input information of the at least one application model; or output processing information of the at least one application model, indicating a post-processing manner for the output information of the at least one application model (i.e., In some embodiments, the software agent 126 may be configured to collect a set of machine characteristics of individual computing devices 102 . The collected machine characteristics may include information that indicates the machine's operating system (OS) version, OS patches installed on the machine, installed applications and their version information, patches, settings, and metadata, files or file contents on the machine, and configuration data such as the machine's registry entries, security settings, usage data, etc., among other information, Col. 7, Line 60-Col. 8, Line 2; i.e., In some embodiments, the software agent 126 may be configured to collect a set of machine characteristics of individual computing devices 102 . The collected machine characteristics may include information that indicates the machine's operating system (OS) version, OS patches installed on the machine, installed applications and their version information, patches, settings, and metadata, files or file contents on the machine, and configuration data such as the machine's registry entries, security settings, usage data, etc., among other information, Col. 7, Line 60-Col. 8, Line 2, Col. 9, Lines 17-25). With regards to Claim 4, Kelly teaches wherein before sending, by the first device, the first message to the second device, the method further comprises: receiving, by the first device, a second message sent by the second device, wherein the second message is used to trigger the first device to send the first message (i.e., After the scan engine 108 determines that the computing device 102 (N) that is being scanned has the software agent 126 installed, the scan engine 108 sends the request 120 to the software agent 126 to provide information about the neighboring devices of the computing device 102 (N), Col. 6, Lines 47-61). With regards to Claim 13, Kelly teaches wherein the first device is a first terminal device, the second device is a network device or a second terminal device, and the first terminal device and the second terminal device are different terminal devices; or the first device is a first network device, the second device is a second network device or a terminal device, and the first network device and the second network device are different network devices; or the third device is the first terminal device (i.e., …The software agent sends the modified neighboring device data (e.g., in the standardized format) to the scan engine, Col. 3, Lines 35-45; software agent (first device), scan engine (second device), neighboring device (third device); Figure 1). The limitations of Claim 14 are rejected in the analysis of Claim 1 above, and the claim is rejected on that basis. The limitations of Claim 15 are rejected in the analysis of Claim 2 above, and the claim is rejected on that basis. The limitations of Claim 16 are rejected in the analysis of Claim 4 above, and the claim is rejected on that basis. The limitations of Claim 17 are rejected in the analysis of Claim 13 above, and the claim is rejected on that basis. The limitations of Claim 18 are rejected in the analysis of Claim 1 above, and the claim is rejected on that basis. The limitations of Claim 19 are rejected in the analysis of Claim 2 above, and the claim is rejected on that basis. The limitations of Claim 20 are rejected in the analysis of Claim 13 above, and the claim is rejected on that basis . 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 5-12 are rejected under 35 U.S.C. 103 as being unpatentable over Kelly (US 12,120,138 B1) in view of Patel (US 2023/0107309 A1) . With regards to Claim 5, Kelly teaches the above disclosed subject matter. However, Kelly does not explicitly disclose activating and/or deactivating, by the first device based on a first preset condition, an application model corresponding model data of which is stored. Patel does teach activating and/or deactivating, by the first device based on a first preset condition, an application model corresponding model data of which is stored (i.e., iteratively generating query data for query of a machine learning model in dependence on the service request data; responsive to the generating of the query data, iteratively examining model data of a plurality of candidate machine learning models; iteratively selecting at least one model from the candidate machine learning models in dependence on the examining, wherein the at least one model defines a selected at least one model; and iteratively sending the query data for return of responsive prediction data to the at least one model. In some embodiments, iteratively performing examining model data and selecting of at least one MLM can be independent of a sensed condition. In one embodiment, iterative performance of examining and MLM model selection can be dependent on and triggered by a sensed condition, e.g., a sensed migration of an MLM or query generating application 20, as set forth herein. The triggering of model examining and selection can be incorporated into tactical autonomic language (TAL) functionality of a 5G service orchestration layer, an example of which is shown in FIG. 5 , Paragraph 109) in order to select machine learning model in dependence on the determined model requirement (Paragraph 4). Therefore, based on Kelly in view of Patel, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to utilize the teachings of Patel with the system of Kelly in order to select machine learning model in dependence on the determined model requirement. With regards to Claim 6, Kelly teaches the above disclosed subject matter. However, Kelly does not explicitly disclose wherein the first preset condition comprises at least one of: in a case where a source device of the application model provides the model data of the application model for the first device, the source device indicates to the first device whether the application model is to be activated; in a case where the source device of the application model provides the model data of the application model for the first device, the application model is in an inactive state by default or the application model is in an active state by default; in a case where the source device of the application model provides the model data of the application model for the first device, the source device provides an activation condition and/or a deactivation condition associated with the application model for the first device; and in a case where the activation condition is satisfied or the deactivation condition is not satisfied, the first device activates the application model or keeps the application model in the active state, and/or in a case where the deactivation condition is satisfied or the activation condition is not satisfied, the first device deactivates the application model or keeps the application model in the inactive state; the first device storing the model data of the application model autonomously determines to activate or deactivate the application model; or the first device receives an activation or deactivation instruction sent by a non-first device to activate or deactivate the application model, wherein the non-first device is the source device of the application model, or the non-first device is another device other than the source device of the application model and the first device. Patel does teach wherein the first preset condition comprises at least one of: in a case where a source device of the application model provides the model data of the application model for the first device, the source device indicates to the first device whether the application model is to be activated; in a case where the source device of the application model provides the model data of the application model for the first device, the application model is in an inactive state by default or the application model is in an active state by default; in a case where the source device of the application model provides the model data of the application model for the first device, the source device provides an activation condition and/or a deactivation condition associated with the application model for the first device; and in a case where the activation condition is satisfied or the deactivation condition is not satisfied, the first device activates the application model or keeps the application model in the active state, and/or in a case where the deactivation condition is satisfied or the activation condition is not satisfied, the first device deactivates the application model or keeps the application model in the inactive state; the first device storing the model data of the application model autonomously determines to activate or deactivate the application model; or the first device receives an activation or deactivation instruction sent by a non-first device to activate or deactivate the application model, wherein the non-first device is the source device of the application model, or the non-first device is another device other than the source device of the application model and the first device (i.e., …In one embodiment, iterative performance of examining and MLM model selection can be dependent on and triggered by a sensed condition, e.g., a sensed migration of an MLM or query generating application 20, as set forth herein. The triggering of model examining and selection can be incorporated into tactical autonomic language (TAL) functionality of a 5G service orchestration layer, an example of which is shown in FIG. 5 ., Paragraph 109) in order to select machine learning model in dependence on the determined model requirement (Paragraph 4). Therefore, based on Kelly in view of Patel, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to utilize the teachings of Patel with the system of Kelly in order to select machine learning model in dependence on the determined model requirement. With regards to Claim 7, Kelly teaches the above disclosed subject matter. However, Kelly does not explicitly disclose deleting, by the first device based on a second preset condition, stored model data of an application model. Patel does teach deleting, by the first device based on a second preset condition, stored model data of an application model (i.e., …Thus, by running polling process 111 , orchestrator 110 updates infrastructure data area 2121 and MLM registry area 2122 in order to include at all times recent and comprehensive infrastructure performance metrics data and MLM performance metrics data for all computing nodes 10 …., Paragraph 43) in order to select machine learning model in dependence on the determined model requirement (Paragraph 4). Therefore, based on Kelly in view of Patel, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to utilize the teachings of Patel with the system of Kelly in order to select machine learning model in dependence on the determined model requirement. With regards to Claim 8, Kelly teaches the above disclosed subject matter. However, Kelly does not explicitly disclose wherein the second preset condition comprises at least one of: in a case where the first device storing model data of the application model receives a deletion instruction sent by a non-first device, the first device deletes the model data of the application model; in a case where a deletion condition associated with the application model is satisfied, the first device deletes the model data of the application model, wherein the deletion condition is configured by the non-first device; or the first device storing the model data of the application model autonomously determines to delete the model data of the application model, wherein the non-first device is a source device of the application model, or the non-first device is another device other than the source device of the application model and the first device. Patel does teach wherein the second preset condition comprises at least one of: in a case where the first device storing model data of the application model receives a deletion instruction sent by a non-first device, the first device deletes the model data of the application model; in a case where a deletion condition associated with the application model is satisfied, the first device deletes the model data of the application model, wherein the deletion condition is configured by the non-first device; or the first device storing the model data of the application model autonomously determines to delete the model data of the application model, wherein the non-first device is a source device of the application model, or the non-first device is another device other than the source device of the application model and the first device (i.e., …Thus, by running polling process 111 , orchestrator 110 updates infrastructure data area 2121 and MLM registry area 2122 in order to include at all times recent and comprehensive infrastructure performance metrics data and MLM performance metrics data for all computing nodes 10 …., Paragraph 43) in order to select machine learning model in dependence on the determined model requirement (Paragraph 4). Therefore, based on Kelly in view of Patel, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to utilize the teachings of Patel with the system of Kelly in order to select machine learning model in dependence on the determined model requirement. With regards to Claim 9, Kelly teaches the above disclosed subject matter. However, Kelly does not explicitly disclose sending, by the first device, assistance information to the second device, wherein the assistance information comprises at least one of: identity information of at least one application model expected by the first device to be activated; identity information of at least one application model expected by the first device to be deactivated; or identity information of at least one application model expected by the first device to be deleted. Patel does teach sending, by the first device, assistance information to the second device, wherein the assistance information comprises at least one of: identity information of at least one application model expected by the first device to be activated; identity information of at least one application model expected by the first device to be deactivated; or identity information of at least one application model expected by the first device to be deleted (i.e., embodiments herein can provide a mechanism to discover the MLMs by a job submission router in the 5G plane and enquire for all the performance-based functionality of the machine learning models. When any MLM is activated on a server and the infrastructure is allocated to virtual machines in the 5G core (or edge network) cloud, then embodiments herein running in the MLM can collect the information and share it with the router functions…, Paragraph 111) in order to select machine learning model in dependence on the determined model requirement (Paragraph 4). Therefore, based on Kelly in view of Patel, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to utilize the teachings of Patel with the system of Kelly in order to select machine learning model in dependence on the determined model requirement. With regards to Claim 10, Kelly teaches the above disclosed subject matter. However, Kelly does not explicitly disclose wherein after the first device is shut down or deregistered or deactivated or dormant, the first device performs any one of the following behaviors: not deleting stored model data of an application model; deactivating a stored application model but not deleting the stored model data of the application model; deleting the stored model data of the application model; not deleting model data of an application model that satisfies a storage condition and deleting model data of an application model that does not satisfy the storage condition; determining, according to indication information associated with the stored application model, to delete or not delete model data of the application model; and determining, according to a default rule, an application model to be deleted and/or an application model to be stored. Patel does teach wherein after the first device is shut down or deregistered or deactivated or dormant, the first device performs any one of the following behaviors: not deleting stored model data of an application model; deactivating a stored application model but not deleting the stored model data of the application model; deleting the stored model data of the application model; not deleting model data of an application model that satisfies a storage condition and deleting model data of an application model that does not satisfy the storage condition; determining, according to indication information associated with the stored application model, to delete or not delete model data of the application model; and determining, according to a default rule, an application model to be deleted and/or an application model to be stored (i.e., Orchestrator 110 running polling process 111 can include orchestrator 110 polling respective data repositories R of respective managers M of the various computing environments A-Z in order to return copies of the returned local infrastructure performance metrics data and MLM registry performance metrics data stored in the respective data repositories R for storage into infrastructure data area 2121 and MLM registry 2122 of data repository 108 of orchestrator 110 . Thus, by running polling process 111 , orchestrator 110 updates infrastructure data area 2121 and MLM registry area 2122 in order to include at all times recent and comprehensive infrastructure performance metrics data and MLM performance metrics data for all computing nodes 10 ., Paragraph 43) in order to select machine learning model in dependence on the determined model requirement (Paragraph 4). Therefore, based on Kelly in view of Patel, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to utilize the teachings of Patel with the system of Kelly in order to select machine learning model in dependence on the determined model requirement. With regards to Claim 11, Kelly teaches the above disclosed subject matter. However, Kelly does not explicitly disclose receiving, by the first device, first indication information sent by the second device, wherein the first indication information indicates at least one of the following meanings: whether the first device is allowed to send to the second device the application model information related to the third device; whether the first device is allowed to autonomously determine to activate and/or deactivate an application model; whether the first device is allowed to autonomously determine to delete model data of the application model; or whether the first device is allowed to send assistance information to the second device. Patel does teach receiving, by the first device, first indication information sent by the second device, wherein the first indication information indicates at least one of the following meanings: whether the first device is allowed to send to the second device the application model information related to the third device; whether the first device is allowed to autonomously determine to activate and/or deactivate an application model; whether the first device is allowed to autonomously determine to delete model data of the application model; or whether the first device is allowed to send assistance information to the second device (i.e., Embodiments herein recognize there can be many MLMs in the service orchestration plane and a job router function can be configured to have authorization to some or all of the MLMs…., Paragraph 112) in order to select machine learning model in dependence on the determined model requirement (Paragraph 4). Therefore, based on Kelly in view of Patel, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to utilize the teachings of Patel with the system of Kelly in order to select machine learning model in dependence on the determined model requirement. With regards to Claim 12, Kelly teaches the above disclosed subject matter. However, Kelly does not explicitly disclose sending, by the first device, second indication information to the second device, wherein the second indication information indicates at least one of the following meanings: whether the first device has a willingness or capability to provide the application model information related to the third device for the second device; whether the first device has a capability to autonomously determine to activate and/or deactivate an application model; whether the first device has a capability to autonomously determine to delete model data of the application model; or whether the first device has a willingness or capability to provide assistance information for the second device. Patel does teach sending, by the first device, second indication information to the second device, wherein the second indication information indicates at least one of the following meanings: whether the first device has a willingness or capability to provide the application model information related to the third device for the second device; whether the first device has a capability to autonomously determine to activate and/or deactivate an application model; whether the first device has a capability to autonomously determine to delete model data of the application model; or whether the first device has a willingness or capability to provide assistance information for the second device ((i.e., …In one embodiment, iterative performance of examining and MLM model selection can be dependent on and triggered by a sensed condition, e.g., a sensed migration of an MLM or query generating application 20, as set forth herein. The triggering of model examining and selection can be incorporated into tactical autonomic language (TAL) functionality of a 5G service orchestration layer, an example of which is shown in FIG. 5 ., Paragraph 109) in order to select machine learning model in dependence on the determined model requirement (Paragraph 4). Therefore, based on Kelly in view of Patel, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to utilize the teachings of Patel with the system of Kelly in order to select machine learning model in dependence on the determined model requirement. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to SURAJ M JOSHI whose telephone number is (571)270-7209. The examiner can normally be reached Monday - Friday 8-6 ET. 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, Joon Hwang can be reached at (571)272-4036. 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. 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If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /SURAJ M JOSHI/Primary Examiner, Art Unit 2447 March 25, 2026 Application/Control Number: 18/989,208 Page 2 Art Unit: 2447 Application/Control Number: 18/989,208 Page 3 Art Unit: 2447 Application/Control Number: 18/989,208 Page 4 Art Unit: 2447 Application/Control Number: 18/989,208 Page 5 Art Unit: 2447 Application/Control Number: 18/989,208 Page 6 Art Unit: 2447 Application/Control Number: 18/989,208 Page 7 Art Unit: 2447 Application/Control Number: 18/989,208 Page 8 Art Unit: 2447 Application/Control Number: 18/989,208 Page 9 Art Unit: 2447 Application/Control Number: 18/989,208 Page 10 Art Unit: 2447 Application/Control Number: 18/989,208 Page 11 Art Unit: 2447 Application/Control Number: 18/989,208 Page 12 Art Unit: 2447 Application/Control Number: 18/989,208 Page 13 Art Unit: 2447 Application/Control Number: 18/989,208 Page 14 Art Unit: 2447 Application/Control Number: 18/989,208 Page 15 Art Unit: 2447 Application/Control Number: 18/989,208 Page 16 Art Unit: 2447
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