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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 11/28/2023 and 04/16/2026 is
in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Rejections - 35 USC § 101
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 1-20 are rejected under U.S.C 101 for containing an abstract idea without significantly more.
Regarding claim 1:
Step 1 – Is the claim to a process, machine, manufacture or composition of matter?
Yes, the claim is a process.
Step 2A – Prong 1 – Does the claim recite an abstract idea, law of nature, or natural phenomenon?
Yes, the claim recites an abstract idea.
verifying the reliability of the AI model based on information collected while the AI model is executed on the digital twin network. - This limitation is directed to the abstract idea of a mental process (including an observation, evaluation, judgement, opinion) which can be performed in the human mind, or by a human using pen and paper (see MPEP 2106.04(a)(2) Ill. C.)
Step 2A – Prong 2 – Does the claim recite additional elements that integrate the judicial exception into a practical application?
No, there are no additional elements that integrate the judicial exception into a practical application. The additional elements:
receiving an AI model request; This limitation is directed to insignificant extra-solution activity (see MPEP 2106.05(g)).
creating a verification twin for evaluating the reliability of the AI model; and Adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea [see MPEP 2106.05(f)] and therefore fails to integrate the exception into a practical application.
Step 2B – Does the claim recite additional elements that amount to significantly more than the judicial exception?
No, there are no additional elements that amount to significantly more than the judicial exception. The additional elements are:
receiving an AI model request; – This limitation is directed to receiving or transmitting data over a network. The courts have recognized receiving or transmitting data over a network as well understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity (see MPEP 2106.05(d) II.).
creating a verification twin for evaluating the reliability of the AI model; and Adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea [see MPEP 2106.05(f)] and therefore fails to integrate the exception into a practical application.
Regarding claim 2,
Claim 2 is rejected under 35 U.S.C 101 because the claimed invention is directed to an abstract idea without significantly more. The claim is dependent on claim 1 which includes an abstract idea (see rejection for claim 1). The additional limitations:
wherein the receiving of the AI model request includes receiving network configuration reference information, and This claim merely recites a further limitation on the receiving an AI model request from claim 1 which was directed to receiving or transmitting data over a network. The courts have recognized receiving or transmitting data over a network as well understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity (see MPEP 2106.05(d) II.).
the creating of a digital twin network for evaluating the reliability of the AI model creates the digital twin network based on the network configuration reference information. This claim merely recites a further limitation on the creating a verification twin for evaluating the reliability of the AI model from claim 1 which was directed to Adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea [see MPEP 2106.05(f)] and therefore fails to integrate the exception into a practical application.
Regarding claim 3,
Claim 3 is rejected under 35 U.S.C 101 because the claimed invention is directed to an abstract idea without significantly more. The claim is dependent on claim 2 which includes an abstract idea (see rejection for claim 2). The additional limitations:
wherein the network configuration reference information includes at least one of an identifier of an actual network, network function (NF) instance information of the actual network, context information of the actual network, an address at which information on the actual network is obtained, location information by which information on the actual network is obtained, and filter information of an instance constituting the digital twin network. This limitation is directed to field of use and technological environment (see MPEP 2106.05(h))
Regarding claim 4,
Claim 4 is rejected under 35 U.S.C 101 because the claimed invention is directed to an abstract idea without significantly more. The claim is dependent on claim 1 which includes an abstract idea (see rejection for claim 1). The additional limitations:
wherein the receiving of the AI model request includes receiving a performance evaluation metric and an operational stability evaluation metric of the AI model, and This claim merely recites a further limitation on the receiving an AI model request from claim 1 which was directed to receiving or transmitting data over a network. The courts have recognized receiving or transmitting data over a network as well understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity (see MPEP 2106.05(d) II.).
the verifying of the reliability of the AI model evaluates the reliability of the AI model using the performance evaluation metric and the operational stability evaluation metric. - This limitation is directed to the abstract idea of a mental process (including an observation, evaluation, judgement, opinion) which can be performed in the human mind, or by a human using pen and paper (see MPEP 2106.04(a)(2) Ill. C.)
Regarding claim 5,
Claim 5 is rejected under 35 U.S.C 101 because the claimed invention is directed to an abstract idea without significantly more. The claim is dependent on claim 1 which includes an abstract idea (see rejection for claim 1). The additional limitations:
wherein the receiving of the AI model request includes receiving an evaluation duration and/or an evaluation period of the AI model, and This claim merely recites a further limitation on the receiving an AI model request from claim 1 which was directed to receiving or transmitting data over a network. The courts have recognized receiving or transmitting data over a network as well understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity (see MPEP 2106.05(d) II.).
the verifying of the reliability of the AI model evaluates the reliability of the AI model over the evaluation duration or for each evaluation period. - This limitation is directed to the abstract idea of a mental process (including an observation, evaluation, judgement, opinion) which can be performed in the human mind, or by a human using pen and paper (see MPEP 2106.04(a)(2) Ill. C.)
Regarding claim 6,
Claim 6 is rejected under 35 U.S.C 101 because the claimed invention is directed to an abstract idea without significantly more. The claim is dependent on claim 1 which includes an abstract idea (see rejection for claim 1). The additional limitations:
when the digital twin network is created, instructing a user plane function (UPF) to forward traffic of an actual network to the digital twin network. Adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea [see MPEP 2106.05(f)] and therefore fails to integrate the exception into a practical application.
Regarding claim 7,
Claim 7 is rejected under 35 U.S.C 101 because the claimed invention is directed to an abstract idea without significantly more. The claim is dependent on claim 6 which includes an abstract idea (see rejection for claim 6). The additional limitations:
wherein the instructing the UPF to forward traffic of the actual network to the digital twin network includes: Adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea [see MPEP 2106.05(f)] and therefore fails to integrate the exception into a practical application.
generating a packet data forwarding policy based on traffic forwarding reference information, and Adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea [see MPEP 2106.05(f)] and therefore fails to integrate the exception into a practical application.
sending the packet data forwarding policy to the UPF. This limitation is directed to receiving or transmitting data over a network. The courts have recognized receiving or transmitting data over a network as well understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity (see MPEP 2106.05(d) II.).
Regarding claim 8,
Claim 8 is rejected under 35 U.S.C 101 because the claimed invention is directed to an abstract idea without significantly more. The claim is dependent on claim 6 which includes an abstract idea (see rejection for claim 6). The additional limitations:
wherein the instructing the UPF to forward traffic of the actual network to the digital twin network includes: Adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea [see MPEP 2106.05(f)] and therefore fails to integrate the exception into a practical application.
generating a data forwarding rule based on a packet data forwarding policy and Adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea [see MPEP 2106.05(f)] and therefore fails to integrate the exception into a practical application.
sending the data forwarding rule to the UPF. This limitation is directed to receiving or transmitting data over a network. The courts have recognized receiving or transmitting data over a network as well understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity (see MPEP 2106.05(d) II.).
Regarding claim 9,
Claim 9 is rejected under 35 U.S.C 101 because the claimed invention is directed to an abstract idea without significantly more. The claim is dependent on claim 8 which includes an abstract idea (see rejection for claim 8). The additional limitations:
wherein the data forwarding rule includes at least one of a packet detection rule (PDR) and a forwarding action rule (FAR). This limitation is directed to field of use and technological environment (see MPEP 2106.05(h))
Regarding claim 10,
Claim 10 is rejected under 35 U.S.C 101 because the claimed invention is directed to an abstract idea without significantly more. The claim is dependent on claim 1 which includes an abstract idea (see rejection for claim 1). The additional limitations:
receiving the AI model or receiving a storage location of the AI model. This claim merely recites a further limitation on the receiving an AI model request from claim 1 which was directed to receiving or transmitting data over a network. The courts have recognized receiving or transmitting data over a network as well understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity (see MPEP 2106.05(d) II.).
Regarding claim 11,
Claim 11 is rejected under 35 U.S.C 101 because the claimed invention is directed to an abstract idea without significantly more. The claim is dependent on claim 1 which includes an abstract idea (see rejection for claim 1). The additional limitations:
sending the AI model and a verification result of the reliability of the AI model to a device which has request the AI model. This limitation is directed to receiving or transmitting data over a network. The courts have recognized receiving or transmitting data over a network as well understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity (see MPEP 2106.05(d) II.).
Regarding claim 12:
Step 1 – Is the claim to a process, machine, manufacture or composition of matter?
Yes, the claim is a process.
Step 2A – Prong 1 – Does the claim recite an abstract idea, law of nature, or natural phenomenon?
Yes, the claim recites an abstract idea.
duplicating the traffic of the actual network; and - This limitation is directed to the abstract idea of a mental process (including an observation, evaluation, judgement, opinion) which can be performed in the human mind, or by a human using pen and paper (see MPEP 2106.04(a)(2) Ill. C.)
Step 2A – Prong 2 – Does the claim recite additional elements that integrate the judicial exception into a practical application?
No, there are no additional elements that integrate the judicial exception into a practical application. The additional elements:
receiving a request for forwarding traffic of an actual network to the digital twin network; This limitation is directed to insignificant extra-solution activity (see MPEP 2106.05(g)).
forwarding the duplicated traffic to the digital twin network. Adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea [see MPEP 2106.05(f)] and therefore fails to integrate the exception into a practical application.
Step 2B – Does the claim recite additional elements that amount to significantly more than the judicial exception?
No, there are no additional elements that amount to significantly more than the judicial exception. The additional elements are:
receiving a request for forwarding traffic of an actual network to the digital twin network; This limitation is directed to receiving or transmitting data over a network. The courts have recognized receiving or transmitting data over a network as well understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity (see MPEP 2106.05(d) II.).
forwarding the duplicated traffic to the digital twin network Adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea [see MPEP 2106.05(f)] and therefore fails to integrate the exception into a practical application.
Regarding claim 13,
Claim 13 is rejected under 35 U.S.C 101 because the claimed invention is directed to an abstract idea without significantly more. The claim is dependent on claim 12 which includes an abstract idea (see rejection for claim 12). The additional limitations:
wherein the receiving of the request for forwarding traffic of the actual network to the digital twin network includes receiving traffic forwarding reference information. This claim merely recites a further limitation on the receiving a request for forwarding traffic of an actual network to the digital twin network from claim 12 which was directed to receiving or transmitting data over a network. The courts have recognized receiving or transmitting data over a network as well understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity (see MPEP 2106.05(d) II.).
Regarding claim 14,
Claim 14 is rejected under 35 U.S.C 101 because the claimed invention is directed to an abstract idea without significantly more. The claim is dependent on claim 13 which includes an abstract idea (see rejection for claim 13). The additional limitations:
generating a packet data forwarding policy based on the traffic forwarding reference information by a policy control function (PCF) in the actual network. Adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea [see MPEP 2106.05(f)] and therefore fails to integrate the exception into a practical application.
Regarding claim 15,
Claim 15 is rejected under 35 U.S.C 101 because the claimed invention is directed to an abstract idea without significantly more. The claim is dependent on claim 14 which includes an abstract idea (see rejection for claim 14). The additional limitations:
generating a data forwarding rule based on the packet data forwarding policy by a session management function (SMF) in the actual network, and Adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea [see MPEP 2106.05(f)] and therefore fails to integrate the exception into a practical application.
Regarding claim 16,
Claim 16 is rejected under 35 U.S.C 101 because the claimed invention is directed to an abstract idea without significantly more. The claim is dependent on claim 15 which includes an abstract idea (see rejection for claim 15). The additional limitations:
duplicating the traffic in the actual network based on the data forwarding rule and This limitation is directed to the abstract idea of a mental process (including an observation, evaluation, judgement, opinion) which can be performed in the human mind, or by a human using pen and paper (see MPEP 2106.04(a)(2) Ill. C.)
sending the duplicated traffic to the digital twin network by the UPF. This limitation is directed to receiving or transmitting data over a network. The courts have recognized receiving or transmitting data over a network as well understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity (see MPEP 2106.05(d) II.).
Regarding claim 17,
Claim 17 is rejected under 35 U.S.C 101 because the claimed invention is directed to an abstract idea without significantly more. The claim is dependent on claim 15 which includes an abstract idea (see rejection for claim 15). The additional limitations:
filtering a packet in the actual network using a packet detection rule (PDR), duplicates the filtered packet, and Adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea [see MPEP 2106.05(f)] and therefore fails to integrate the exception into a practical application.
sending the duplicated packet to the digital twin network using a Forwarding Action Rule (FAR) by the UPF, wherein the data forwarding rule includes the PDR and the FAR. This limitation is directed to receiving or transmitting data over a network. The courts have recognized receiving or transmitting data over a network as well understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity (see MPEP 2106.05(d) II.).
Regarding claim 18:
Step 1 – Is the claim to a process, machine, manufacture or composition of matter?
Yes, the claim is a process.
Step 2A – Prong 1 – Does the claim recite an abstract idea, law of nature, or natural phenomenon?
Yes, the claim recites an abstract idea.
verifying the reliability of the AI model based on information collected while the AI
model is executed on the digital twin network- This limitation is directed to the abstract idea of a mental process (including an observation, evaluation, judgement, opinion) which can be performed in the human mind, or by a human using pen and paper (see MPEP 2106.04(a)(2) Ill. C.)
Step 2A – Prong 2 – Does the claim recite additional elements that integrate the judicial exception into a practical application?
No, there are no additional elements that integrate the judicial exception into a practical application. The additional elements:
a processor, a memory, and a communication device, wherein the processor executes a program stored in the memory to perform: – This limitation is directed to a computer merely used as a tool to perform an existing process (see MPEP 2106.05(f) (2)).
receiving an AI model request; This limitation is directed to insignificant extra-solution activity (see MPEP 2106.05(g)).
creating a digital twin network for evaluating the reliability of the AI model; and Adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea [see MPEP 2106.05(f)] and therefore fails to integrate the exception into a practical application.
Step 2B – Does the claim recite additional elements that amount to significantly more than the judicial exception?
No, there are no additional elements that amount to significantly more than the judicial exception. The additional elements are:
a processor, a memory, and a communication device, wherein the processor executes a program stored in the memory to perform: – This limitation is directed to a computer merely used as a tool to perform an existing process (see MPEP 2106.05(f) (2)).
receiving an AI model request; – This limitation is directed to receiving or transmitting data over a network. The courts have recognized receiving or transmitting data over a network as well understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity (see MPEP 2106.05(d) II.).
creating a digital twin network for evaluating the reliability of the AI model; and Adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea [see MPEP 2106.05(f)] and therefore fails to integrate the exception into a practical application.
Regarding claim 19,
Claim 19 is rejected under 35 U.S.C 101 because the claimed invention is directed to an abstract idea without significantly more. The claim is dependent on claim 18 which includes an abstract idea (see rejection for claim 18). The additional limitations:
wherein, when the processor performs the receiving of the AI model, the processor performs: receiving location information of the AI model; and – This limitation is directed to receiving or transmitting data over a network. The courts have recognized receiving or transmitting data over a network as well understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity (see MPEP 2106.05(d) II.).
downloading the AI model from storage corresponding to the location information. Adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea [see MPEP 2106.05(f)] and therefore fails to integrate the exception into a practical application
Regarding claim 20:
Step 1 – Is the claim to a process, machine, manufacture or composition of matter?
Yes, the claim is a process.
Step 2A – Prong 1 – Does the claim recite an abstract idea, law of nature, or natural phenomenon?
Yes, the claim recites an abstract idea.
verifying the reliability of the AI model based on information collected while the AI model is executed on the digital twin network. - This limitation is directed to the abstract idea of a mental process (including an observation, evaluation, judgement, opinion) which can be performed in the human mind, or by a human using pen and paper (see MPEP 2106.04(a)(2) Ill. C.)
Step 2A – Prong 2 – Does the claim recite additional elements that integrate the judicial exception into a practical application?
No, there are no additional elements that integrate the judicial exception into a practical application. The additional elements:
An apparatus for verifying reliability of an artificial intelligence (AI) model, the apparatus comprising: a processor, a memory, and a communication device, wherein the processor executes a program stored in the memory to perform – This limitation is directed to a computer merely used as a tool to perform an existing process (see MPEP 2106.05(f) (2)).
receiving a reliability verification request of the AI model; This limitation is directed to insignificant extra-solution activity (see MPEP 2106.05(g)).
creating a digital twin network for evaluating the reliability of the AI model;
Adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea [see MPEP 2106.05(f)] and therefore fails to integrate the exception into a practical application.
when the digital twin network is created, requesting a device which has sent the reliability verification request to provide the AI model; and Adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea [see MPEP 2106.05(f)] and therefore fails to integrate the exception into a practical application.
Step 2B – Does the claim recite additional elements that amount to significantly more than the judicial exception?
No, there are no additional elements that amount to significantly more than the judicial exception. The additional elements are:
An apparatus for verifying reliability of an artificial intelligence (AI) model, the apparatus comprising: a processor, a memory, and a communication device, wherein the processor executes a program stored in the memory to perform – This limitation is directed to a computer merely used as a tool to perform an existing process (see MPEP 2106.05(f) (2)).
receiving a reliability verification request of the AI model; – This limitation is directed to receiving or transmitting data over a network. The courts have recognized receiving or transmitting data over a network as well understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity (see MPEP 2106.05(d) II.).
creating a digital twin network for evaluating the reliability of the AI model;
Adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea [see MPEP 2106.05(f)] and therefore fails to integrate the exception into a practical application.
when the digital twin network is created, requesting a device which has sent the reliability verification request to provide the AI model; and Adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea [see MPEP 2106.05(f)] and therefore fails to integrate the exception into a practical application.
Claim Rejections - 35 USC § 103
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.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1-6, 11-13 and 18, 20 are rejected under 35 U.S.C. 103 as being unpatentable over Wang et al. (“Leverage Digital Twins Technology for Network Lifecycle Management”) in view of Mozo et al. (“B5GEMINI: AI-Driven Network Digital Twin”).
Regarding claim 1, Wang explicitly teaches:
A method for verifying reliability of an artificial intelligence (AI) model, the method
comprising: (Wang, Pg. 3, Col. 1, Section D, ¶[2]: “Besides that we can also simulate the operation of network equipment in the digital twin network to verify and predict the reliability of operation life for the network equipment and give the device optimization scheme.”)
receiving an AI model request; (Wang, Pg. 2, Col. 2, Section III.A, ¶[3]: “For example, when a new network coverage requirement is proposed, we should firstly pay attention to the information of existing network in this coverage. Then based on the customer’s requirements, the digital twins of the base station are built in digital space to simulate the signal strength, coverage area and blind area information of the base station. Based on the above information, the new network coverage requirement can be verified in the digital space”)
verifying the reliability of the AI model based on information collected while the AI model is executed on the digital twin network. (Wang, Pg. 3, Col. 1, Section D, ¶[2]: “For example, according to the reliability evaluation method of network equipment, the equipment operation reliability model can be trained. Based on the collected real-time operation data, the digital twin network can predict the health degree of the devices and give the device optimization scheme. Besides that we can also simulate the operation of network equipment in the digital twin network to verify and predict the reliability of operation life for the network equipment and give the device optimization scheme.”)
Wang fails to teach:
creating a verification twin for evaluating the reliability of the AI model; and
However, Mozo explicitly teaches:
creating a verification twin for evaluating the reliability of the AI model; and (Mozo, Pg. 5, ¶[3]: “In this particular context, with the objective of improving road safety and traffic management, the Spirent team proposes to achieve this goal by creating a Digital Twin of a 5G SDVN to emulate all aspects of a 5G network and its interactions with vehicles under different realistic scenarios (e.g., congestion and vehicle density) in a controlled manner [16]. In this approach, AI methods can be introduced to understand and evaluate vehicle behavior, optimize vehicle-to-vehicle communication, and enable end-to-end validation of the entire 5G SDVN. In this way, the built NDT serves as a testbed to verify vehicle performance prior to deployment in a real-world environment.”)
It would have obvious to one of ordinary skill in the art before the effective filing date of the present application to combine Wang and Mozo. Wang teaches digital twins technology for network lifecycle management. Mozo teaches the application of the digital twins network in the field of communication networks to evaluate and verify the reliability of AI models in real time. One of ordinary skill would have motivation to combine Wang and Mozo to improve the convenience for evaluating the reliability of AI models in real-time and enable cost reduction and flexibility for network managers.
Regarding claim 2, the combination of Wang and Mozo discloses all the limitations of claim 1 (as shown in the rejections above).
Wang in view of Mozo further discloses:
wherein the receiving of the AI model request includes receiving network configuration reference information, and (Wang, Pg. 2, Col. 2, Section III.A, ¶[3]: “when a new network coverage requirement is proposed, we should firstly pay attention to the information of existing network in this coverage. Then based on the customer’s requirements, the digital twins of the base station are built in digital space to simulate the signal strength, coverage area and blind area information of the base station.”)
the creating of a digital twin network for evaluating the reliability of the AI model creates the digital twin network based on the network configuration reference information. (Wang, Pg. 2, Col. 2, Section III.A, ¶[3]: “when a new network coverage requirement is proposed, we should firstly pay attention to the information of existing network in this coverage. Then based on the customer’s requirements, the digital twins of the base station are built in digital space to simulate the signal strength, coverage area and blind area information of the base station. Based on the above information, the new network coverage requirement can be verified in the digital space. If the verification is successful, the information can be configured to the physical space for execution, which include the base station configuration information, base station location, the quantity of base station and so on.”)
Regarding claim 3, the combination of Wang and Mozo discloses all the limitations of claim 2 (as shown in the rejections above).
Wang in view of Mozo further discloses:
wherein the network configuration reference information includes at least one of an identifier of an actual network, network function (NF) instance information of the actual network, context information of the actual network, an address at which information on the actual network is obtained, location information by which information on the actual network is obtained, and filter information of an instance constituting the digital twin network. (Wang, Pg. 2, Col. 2, Section III.A, ¶[3]: “Based on the above information, the new network coverage requirement can be verified in the digital space. If the verification is successful, the information can be configured to the physical space for execution, which include the base station configuration information, base station location, the quantity of base station and so on.”)
Regarding claim 4, the combination of Wang and Mozo discloses all the limitations of claim 1 (as shown in the rejections above).
Wang in view of Mozo further discloses:
wherein the receiving of the AI model request includes receiving a performance evaluation metric and an operational stability evaluation metric of the AI model, and (Wang, Pg. 3, Col. 2, Section IV, ¶[4]: “Then the performance data of the network, such as delay, packet loss rate and jitter, are transformed into vector form, and the optimal path of the comprehensive dimension is calculated by matrix operation and Graph”)
the verifying of the reliability of the AI model evaluates the reliability of the AI model using the performance evaluation metric and the operational stability evaluation metric. (Wang, Pg. 3, Col. 1, Section C: “When there is an alarm or fault in the network operation, the root cause of the fault can be displayed quickly and visually. We can firstly find out the best solution to solve this alarm or fault in the network operation in the digital space. Then, the solution can be simulated and verified in the digital space. If the verification is successful, the solution can be distributed to physical space to solve the alarm or fault in the network maintenance”)
Regarding claim 5, the combination of Wang and Mozo discloses all the limitations of claim 1 (as shown in the rejections above).
Wang in view of Mozo further discloses:
wherein the receiving of the AI model request includes receiving an evaluation duration and/or an evaluation period of the AI model, and (Wang, Pg. 3, Col. 1, Section D, ¶[2]: “Based on the collected real-time operation data, the digital twin network can predict the health degree of the devices and give the device optimization scheme.”)
the verifying of the reliability of the AI model evaluates the reliability of the AI model over the evaluation duration or for each evaluation period. (Wang Pg. 3, Col. 1, Section D, ¶[2]: “For example, according to the reliability evaluation method of network equipment, the equipment operation reliability model can be trained. Based on the collected real-time operation data, the digital twin network can predict the health degree of the devices and give the device optimization scheme. Besides that we can also simulate the operation of network equipment in the digital twin network to verify and predict the reliability of operation life for the network equipment and give the device optimization scheme.”)
Regarding claim 6, the combination of Wang and Mozo discloses all the limitations of claim 1 (as shown in the rejections above).
Wang in view of Mozo further discloses:
when the digital twin network is created, instructing a user plane function (UPF) to forward traffic of an actual network to the digital twin network. (Mozo, Pg. 11: “User Plane Function (UPF): Function that manages all the functionality related to the user plane, enabling data forwarding and packet processing.”)
Regarding claim 11, the combination of Wang and Mozo discloses all the limitations of claim 1 (as shown in the rejections above).
Wang in view of Mozo further discloses:
sending the AI model and a verification result of the reliability of the AI model to a device which has request the AI model. (Wang, Pg. 4, Col. 1, ¶[1]: “Send the result to the network management platform of the live network in the form of suggestions to assist operation and maintenance personnel to continuously optimize the network.”)
Regarding claim 12, Wang explicitly discloses:
A method for forwarding traffic to a digital twin network for verifying reliability of an artificial intelligence (AI) model, the method comprising: receiving a request for forwarding traffic of an actual network to the digital twin network; (Wang, Pg. 2, Col. 2, Section III.A, ¶[3]: “For example, when a new network coverage requirement is proposed, we should firstly pay attention to the information of existing network in this coverage. Then based on the customer’s requirements, the digital twins of the base station are built in digital space to simulate the signal strength, coverage area and blind area information of the base station. Based on the above information, the new network coverage requirement can be verified in the digital space”)
Wang fails to teach:
duplicating the traffic of the actual network; and
forwarding the duplicated traffic to the digital twin network
However, Mozo explicitly teaches:
duplicating the traffic of the actual network; and (Mozo, Pg. 2, ¶[1]: “By leveraging network data, NDTs can be used to build a virtual representation of a network. The data should replicate the expected behavior of the network”, Pg. 5, ¶[3]: “In this particular context, with the objective of improving road safety and traffic management, the Spirent team proposes to achieve this goal by creating a Digital Twin of a 5G SDVN to emulate all aspects of a 5G network and its interactions with vehicles under different realistic scenarios (e.g., congestion and vehicle density) in a controlled manner [16]. In this approach, AI methods can be introduced to understand and evaluate vehicle behavior, optimize vehicle-to-vehicle communication, and enable end-to-end validation of the entire 5G SDVN.”)
forwarding the duplicated traffic to the digital twin network. (Mozo, Pg. 7, Section 3.2, ¶[1]: “Digital Twin (DT): Treated as an intelligent system in charge of modeling all the characteristics of a specific physical component. In the case of the DT, the communication performs a one-to-one mapping between the physical twin and its DT, allowing bidirectional feedback between both. From this point of view, using a bidirectional data flow between both worlds, the DT is able to continuously adapt to operational changes based on real-time data and information coming from the physical twin, being able, among other things, to monitor and even predict the future state of the physical twin.”)
It would have obvious to one of ordinary skill in the art before the effective filing date of the present application to combine Wang and Mozo. Wang teaches digital twins technology for network lifecycle management. Mozo teaches the application of the digital twins network in the field of communication networks to evaluate and verify the reliability of AI models in real time. One of ordinary skill would have motivation to combine Wang and Mozo to improve the convenience for evaluating the reliability of AI models in real-time and enable cost reduction and flexibility for network managers.
Regarding claim 13, the combination of Wang and Mozo discloses all the limitations of claim 12 (as shown in the rejections above).
Wang in view of Mozo further discloses:
wherein the receiving of the request for forwarding traffic of the actual network to the digital twin network includes receiving traffic forwarding reference information (Wang, Pg. 2, Col. 2, Section III.A, ¶[3]: “when a new network coverage requirement is proposed, we should firstly pay attention to the information of existing network in this coverage. Then based on the customer’s requirements, the digital twins of the base station are built in digital space to simulate the signal strength, coverage area and blind area information of the base station.”)
Regarding claim 18, Wang explicitly teaches:
An apparatus for verifying reliability of an artificial intelligence (AI) model, the apparatus
comprising: receiving the AI model request; (Wang, Pg. 2, Col. 2, Section III.A, ¶[3]: “For example, when a new network coverage requirement is proposed, we should firstly pay attention to the information of existing network in this coverage. Then based on the customer’s requirements, the digital twins of the base station are built in digital space to simulate the signal strength, coverage area and blind area information of the base station. Based on the above information, the new network coverage requirement can be verified in the digital space”)
verifying the reliability of the AI model based on information collected while the AI
model is executed on the digital twin network. (Wang, Pg. 3, Col. 1, Section D, ¶[2]: “For example, according to the reliability evaluation method of network equipment, the equipment operation reliability model can be trained. Based on the collected real-time operation data, the digital twin network can predict the health degree of the devices and give the device optimization scheme. Besides that we can also simulate the operation of network equipment in the digital twin network to verify and predict the reliability of operation life for the network equipment and give the device optimization scheme.”)
Wang fails to teach:
a processor, a memory, and a communication device, wherein the processor executes a
program stored in the memory to perform:
creating a digital twin network for evaluating the reliability of the AI model; and
However, Mozo explicitly teaches:
a processor, a memory, and a communication device, wherein the processor executes a program stored in the memory to perform: (Mozo, Pg. 7, Figure 1:
PNG
media_image1.png
512
918
media_image1.png
Greyscale
)
creating a digital twin network for evaluating the reliability of the AI model; and (Mozo, Pg. 5, ¶[3]: “In this particular context, with the objective of improving road safety and traffic management, the Spirent team proposes to achieve this goal by creating a Digital Twin of a 5G SDVN to emulate all aspects of a 5G network and its interactions with vehicles under different realistic scenarios (e.g., congestion and vehicle density) in a controlled manner [16]. In this approach, AI methods can be introduced to understand and evaluate vehicle behavior, optimize vehicle-to-vehicle communication, and enable end-to-end validation of the entire 5G SDVN. In this way, the built NDT serves as a testbed to verify vehicle performance prior to deployment in a real-world environment.”)
It would have obvious to one of ordinary skill in the art before the effective filing date of the present application to combine Wang and Mozo. Wang teaches digital twins technology for network lifecycle management. Mozo teaches the application of the digital twins network in the field of communication networks to evaluate and verify the reliability of AI models in real time. One of ordinary skill would have motivation to combine Wang and Mozo to improve the convenience for evaluating the reliability of AI models in real-time and enable cost reduction and flexibility for network managers.
Regarding claim 20, Wang explicitly teaches:
An apparatus for verifying reliability of an artificial intelligence (AI) model, the apparatus comprising: receiving a reliability verification request of the AI model; (Wang, Pg. 2, Col. 2, Section III.A, ¶[3]: “For example, when a new network coverage requirement is proposed, we should firstly pay attention to the information of existing network in this coverage. Then based on the customer’s requirements, the digital twins of the base station are built in digital space to simulate the signal strength, coverage area and blind area information of the base station. Based on the above information, the new network coverage requirement can be verified in the digital space”)
verifying the reliability of the AI model based on information collected while the AI model is executed on the digital twin network. (Wang, Pg. 3, Col. 1, Section D, ¶[2]: “For example, according to the reliability evaluation method of network equipment, the equipment operation reliability model can be trained. Based on the collected real-time operation data, the digital twin network can predict the health degree of the devices and give the device optimization scheme. Besides that we can also simulate the operation of network equipment in the digital twin network to verify and predict the reliability of operation life for the network equipment and give the device optimization scheme.”)
Wang fails to teach:
a processor, a memory, and a communication device, wherein the processor executes a program stored in the memory to perform:
creating a digital twin network for evaluating the reliability of the AI model;
when the digital twin network is created, requesting a device which has sent the reliability verification request to provide the AI model; and
However, Mozo explicitly teaches:
a processor, a memory, and a communication device, wherein the processor executes a program stored in the memory to perform: (Mozo, Pg. 7, Figure 1:
PNG
media_image1.png
512
918
media_image1.png
Greyscale
)
creating a digital twin network for evaluating the reliability of the AI model; (Mozo, Pg. 5, ¶[3]: “In this particular context, with the objective of improving road safety and traffic management, the Spirent team proposes to achieve this goal by creating a Digital Twin of a 5G SDVN to emulate all aspects of a 5G network and its interactions with vehicles under different realistic scenarios (e.g., congestion and vehicle density) in a controlled manner [16]. In this approach, AI methods can be introduced to understand and evaluate vehicle behavior, optimize vehicle-to-vehicle communication, and enable end-to-end validation of the entire 5G SDVN. In this way, the built NDT serves as a testbed to verify vehicle performance prior to deployment in a real-world environment.”)
when the digital twin network is created, requesting a device which has sent the reliability verification request to provide the AI model; and (Mozo, Pg. 17, ¶[2]: “B5GEMINI can provide a real-time assessment of the 5G network with little overhead, allowing for faster and more accurate assessment”)
It would have obvious to one of ordinary skill in the art before the effective filing date of the present application to combine Wang and Mozo. Wang teaches digital twins technology for network lifecycle management. Mozo teaches the application of the digital twins network in the field of communication networks to evaluate and verify the reliability of AI models in real time. One of ordinary skill would have motivation to combine Wang and Mozo to improve the convenience for evaluating the reliability of AI models in real-time and enable cost reduction and flexibility for network managers.
Claim(s) 7-10, 14-17 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Wang et al. (“Leverage Digital Twins Technology for Network Lifecycle Management”) in view of Mozo et al. (“B5GEMINI: AI-Driven Network Digital Twin”) and further in view of 3GPP (“Interface between the Control Plane and the User Plane nodes”).
Regarding claim 7, the combination of Wang and Mozo discloses all the limitations of claim 6 (as shown in the rejections above).
Wang in view of Mozo fails to teach:
generating a packet data forwarding policy based on traffic forwarding reference information, and
sending the packet data forwarding policy to the UPF
However, 3GPP explicitly teaches:
generating a packet data forwarding policy based on traffic forwarding reference information, and (3GPP, Pg. 50, Section 5.4.8, ¶[4]: “Traffic Steering is supported over the Sxb, Sxc and N4 reference points by instructing the UP function to apply a specific Forwarding Policy, that is locally configured in the UP function and that can be used for the uplink, the downlink or for both directions. A Forwarding Policy is identified by a Forwarding Policy Identifier.”)
sending the packet data forwarding policy to the UPF. (3GPP, Pg. 50, Section 5.4.8, ¶[4-5]: “Traffic steering is alternatively supported over the N4 reference point by instructing the UP function to route packets according to N6 routing information in the FAR. When so instructed, the UP function shall perform the necessary actions to enforce the forwarding policy referenced by the CP function, e.g. performing packet marking and routing the traffic towards the service functions within the (S)Gi LAN or N6-LAN.”)
It would have obvious to one of ordinary skill in the art before the effective filing date of the present application to combine Wang, Mozo and 3GPP. Wang teaches digital twins technology for network lifecycle management. Mozo teaches the application of the digital twins network in the field of communication networks to evaluate and verify the reliability of AI models in real time. 3GPP teaches interface between the control plane and the user plane nodes in communication networks. One of ordinary skill would have motivation to combine Wang, Mozo and 3GPP because MPEP 2143 sets forth the Supreme Court rationales for obviousness including: (D) Applying a known technique to a known device (method, or product) ready for improvement to yield predictable results; (E): “Obvious to try” choosing from a finite number of identified, predictable solutions, with a reasonable expectation of success; (F) Known work in one field of endeavor may prompt variations of it for use in either the same field or a different one based on design incentives or other market forces if the variations are predictable to one of the ordinary skill in the art.
Regarding claim 8, the combination of Wang, Mozo and 3GPP discloses all the limitations of claim 6 (as shown in the rejections above).
Wang in view of Mozo and 3GPP further teaches:
wherein the instructing the UPF to forward traffic of the actual network to the digital twin network includes: generating a data forwarding rule based on a packet data forwarding policy and sending the data forwarding rule to the UPF. (3GPP, Pg. 42, Section 5.3 discloses Data Forwarding between the CP and UP Functions, Table 5.3.1-1 discloses Data forwarding scenarios between the CP and UP functions:
PNG
media_image2.png
266
848
media_image2.png
Greyscale
User plane packets shall be forwarded between the CP and UP functions by encapsulating the user plane packets using GTP-U encapsulation)
Regarding claim 9, the combination of Wang, Mozo and 3GPP discloses all the limitations of claim 8 (as shown in the rejections above).
Wang in view of Mozo and 3GPP further teaches:
wherein the data forwarding rule includes at least one of a packet detection rule (PDR) and a forwarding action rule (FAR). (3GPP, Pg. 37, Section 5.2.3 discloses the Forwarding Action Rule Handling: “The FAR provides instructions to the UP function on how to process the packets matching the PDR.”)
Regarding claim 10, the combination of Wang, Mozo and 3GPP discloses all the limitations of claim 1 (as shown in the rejections above).
Wang in view of Mozo and 3GPP further teaches:
receiving the AI model or receiving a storage location of the AI model.(3GPP, Pg. 22, Section 4.3.2: “The IP Destination Address of a Request message shall be an IP address of the peer entity.”)
Regarding claim 14, the combination of Wang, Mozo and 3GPP discloses all the limitations of claim 13 (as shown in the rejections above).
Wang in view of Mozo and 3GPP further teaches:
generating a packet data forwarding policy based on the traffic forwarding reference information by a policy control function (PCF) in the actual network. (3GPP, Pg. 50, Section 5.4.8, ¶[4]: “Traffic Steering is supported over the Sxb, Sxc and N4 reference points by instructing the UP function to apply a specific Forwarding Policy, that is locally configured in the UP function and that can be used for the uplink, the downlink or for both directions. A Forwarding Policy is identified by a Forwarding Policy Identifier.”)
Regarding claim 15, the combination of Wang, Mozo and 3GPP discloses all the limitations of claim 14 (as shown in the rejections above).
Wang in view of Mozo and 3GPP further teaches:
generating a data forwarding rule based on the packet data forwarding policy by a session management function (SMF) in the actual network, and (Mozo, Pg. 11: “Session Management Function (SMF): Responsible for the interaction with the data plane and managing Protocol Data Unit (PDU) sessions.”)
sending the data forwarding rule to a user plane function (UPF) in the actual network. (3GPP, Pg. 50, Section 5.4.8, ¶[4-5]: “Traffic steering is alternatively supported over the N4 reference point by instructing the UP function to route packets according to N6 routing information in the FAR. When so instructed, the UP function shall perform the necessary actions to enforce the forwarding policy referenced by the CP function, e.g. performing packet marking and routing the traffic towards the service functions within the (S)Gi LAN or N6-LAN.”)
Regarding claim 16, the combination of Wang, Mozo and 3GPP discloses all the limitations of claim 15 (as shown in the rejections above).
Wang in view of Mozo and 3GPP further teaches:
duplicating the traffic in the actual network based on the data forwarding rule and (Mozo, Pg. 2, ¶[1]: “By leveraging network data, NDTs can be used to build a virtual representation of a network. The data should replicate the expected behavior of the network”, Pg. 5, ¶[3]: “In this particular context, with the objective of improving road safety and traffic management, the Spirent team proposes to achieve this goal by creating a Digital Twin of a 5G SDVN to emulate all aspects of a 5G network and its interactions with vehicles under different realistic scenarios (e.g., congestion and vehicle density) in a controlled manner [16]. In this approach, AI methods can be introduced to understand and evaluate vehicle behavior, optimize vehicle-to-vehicle communication, and enable end-to-end validation of the entire 5G SDVN.”)
sending the duplicated traffic to the digital twin network by the UPF. (Mozo, Pg. 7, Section 3.2, ¶[1]: “Digital Twin (DT): Treated as an intelligent system in charge of modeling all the characteristics of a specific physical component. In the case of the DT, the communication performs a one-to-one mapping between the physical twin and its DT, allowing bidirectional feedback between both. From this point of view, using a bidirectional data flow between both worlds, the DT is able to continuously adapt to operational changes based on real-time data and information coming from the physical twin, being able, among other things, to monitor and even predict the future state of the physical twin.”, Pg. 11: “User Plane Function (UPF): Function that manages all the functionality related to the user plane, enabling data forwarding and packet processing.”)
Regarding claim 17, the combination of Wang, Mozo and 3GPP discloses all the limitations of claim 15 (as shown in the rejections above).
Wang in view of Mozo and 3GPP further teaches:
filtering a packet in the actual network using a packet detection rule (PDR), duplicates the filtered packet, and (3GPP, Pg. 27, Section 5.2.1 A.3: “the UP function shall apply any modification of a bidirectional SDF Filter to all PDRs of the PFCP/N4 session making use of this SDF Filter;”)
sending the duplicated packet to the digital twin network using a Forwarding Action Rule (FAR) by the UPF, wherein the data forwarding rule includes the PDR and the FAR. (3GPP, Pg. 50, Section 5.4.8, ¶[4-5]: “Traffic steering is alternatively supported over the N4 reference point by instructing the UP function to route packets according to N6 routing information in the FAR. When so instructed, the UP function shall perform the necessary actions to enforce the forwarding policy referenced by the CP function, e.g. performing packet marking and routing the traffic towards the service functions within the (S)Gi LAN or N6-LAN.”)
Regarding claim 19, the combination of Wang, Mozo and 3GPP discloses all the limitations of claim 18 (as shown in the rejections above).
Wang in view of Mozo and 3GPP further teaches:
when the processor performs the receiving of the AI model, the processor performs:
receiving location information of the AI model; and (Mozo, Pg. 10, Fig. 3:
PNG
media_image3.png
67
291
media_image3.png
Greyscale
)
downloading the AI model from storage corresponding to the location information. (3GPP, Pg. 71, Section 5.20.2.4, ¶[1]: “Once traffic for which MPTCP is applicable is detected by the UPF, the UPF shall internally forward this traffic to the MPTCP Proxy for IP translation. The MPTCP Proxy shall use the stored information in MPTCP session entry to perform IP translation to the detected MPTCP IP packets, e.g. replace the source IP address+port and/or destination IP address+port accordingly”)
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to AMY TRAN whose telephone number is (571)270-0693. The examiner can normally be reached Monday - Friday 7:30 am - 5:00 pm 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, David Yi can be reached at (571) 270-7519. 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.
/AMY TRAN/Examiner, Art Unit 2126
/DAVID YI/Supervisory Patent Examiner, Art Unit 2126
Prosecution Insights