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 .
DETAILED ACTION
This action is responsive to claims filed on September 11, 2024. Claims 10, 12-21 and 30-37 have been canceled. Claims 1-9, 11 and 22-29 are pending and presented for examination.
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Abstract
Applicant is reminded of the proper language and format for an abstract of the disclosure.
The abstract should be in narrative form and generally limited to a single paragraph on a separate sheet within the range of 50 to 150 words. It is important that the abstract not exceed 150 words in length since the space provided for the abstract on the computer tape used by the printer is limited. The form and legal phraseology often used in patent claims, such as "means" and "said," should be avoided. The abstract should describe the disclosure sufficiently to assist readers in deciding whether there is a need for consulting the full patent text for details.
The language should be clear and concise and should not repeat information given in the title. It should avoid using phrases which can be implied, such as, "The disclosure concerns," "The disclosure defined by this invention," "The disclosure describes," etc.
Examiner's note: It is recommended to amend the abstract to briefly describe the claimed invention according to the above guidelines.
Claim Rejections - 35 USC § 102
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 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 the appropriate paragraphs of pre-AIA 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 –
(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.
Claims 1-9, 11 and 22-29 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Han et al “Han”, US-PGPub. No. 20230090022.
As per claims 1 and 11, Han teaches a method and a network node for implementing a server Network Data Analytics Function (Figs. 3 & 4, Paragraph(s) [0071]), NWDAF, the network node comprising processing circuitry (Paragraph(s) [0033]) configured to cause the network node to:
transmit, to each of a set of client NWDAFs (Paragraph(s) [0027]; transmitting, to a network repository function (NRF), a discovery message for discovering another NWDAF. Han further discloses the request for network analytics information may be distributed to the plurality of NWDAF instances and processed by the plurality of NWDAF instances (Paragraph(s) [0124-0125])), a preparation request for Distributed Machine Learning, DML, or Federated Learning, FL (Paragraph(s) [0149]; an NWDAF instance may use federated learning, for which it is required to share learning factors according to a type of an analytical model, whereby many instances share results of separate learning and share the common learning factors to increase the learning efficiency);
receive, from each of at least some of the set of client NWDAFs, a response to the preparation request for DML or FL (Paragraph(s) [0027]; receiving, from the NRF, a response message with respect to the discovery message; based on information about the other NWDAF); and
select one or more client NWDAFs based on the responses to the preparation requests for DML or FL (Paragraph(s) [0043-0044]; selecting the optimal NWDAF instance by considering a purpose of use of the analytics information and a network situation, when there are NWDAF instances providing the analytics information and having different performance levels and specific functions. In detail, a selected optimal algorithm for generating analytics information may be changed according to a purpose of use of the network analytics information);
during an execution phase of DML or FL between the server NWDAF and the one or more client NWDAFs:
monitor an updated status of each of the one or more client NWDAFs (Paragraph(s) [0098]; when a result obtained via cumulative collection of the feedback information is greater than a predetermined critical value or corresponds to a predetermined period, the NWDAF instance may determine to update NFProfile in the NRF. Han further discloses the operation, administration, and maintenance (OAM) may may perform functions related to operation, management, maintenance, provision, problem solving of a communication network (Paragraph(s) [0061]));
determine whether reselection of client NWDAFs is needed based on the updated statuses of the one or more client NWDAFs (Paragraph(s) [0044]; an optimal NWDAF instance is selected in a specific situation according to a network situation and a resource situation, by comprehensively taking into account information about geographical locations, delay levels, specifications, and loads of NWDAF instances. In addition, Han discloses when a previous configuration of modules of an NWDAF is updated or a state of each module is changed, Nnrf_NFmanagement_NFupdate may be used (Paragraph [0084])); and
perform reselection of client NWDAFs responsive to determining that reselection of client NWDAFs is needed (Paragraph(s) [0044]; selecting an optimal NWDAF instance by considering a purpose of use of the analytics information and a network situation, when there are NWDAF instances providing the analytics information and having different performance levels and specific functions. In detail, a selected optimal algorithm for generating analytics information may be changed according to a purpose of use of the network analytics information).
As per claim 2, Han teaches registering a profile of the server NWDAF into a registry (Paragraph(s) [0058], [0084], [0098]).
As per claim 3, Han teaches wherein the registry is a Network Repository Function, NRF (Paragraph(s) [0014], [0027]).
As per claim 4, Han teaches wherein the profile comprises any one or more of: (a) a capability of computation and communication, (b) supported analytics identification(s), (c) Machine Learning, ML, relevant capability, (d) available data, or (e) availability to join in DML or FL (Paragraph(s) [0058], [0140]).
As per claim 5, Han teaches the method of claim 2, wherein the server NWDAF is discovered from the registry based on one of more of (i) a requirement on capability, (ii) a capability of model aggregation, (iii) a capability of processing or aggregating heterogenous model parameters, (iv) a capability to communication with other NWDAFs, (v) a capability of providing model to other NWDAFs or running models from other NWDAFs, of (vi) an indication of online or offline learning (Paragraph(s) [0067], [0129-0130]).
As per claim 6, Han teaches discovering the set of client NWDAFs from the registry, based on any one or more of: (a) a requirement on capability, (b) an analytics identification, (c) an output strategy for intermediate results report during a training process, (d) a requirement on capability of processing intermediate ML models, results, or parameters, (e) a capability of running models from other NWDAFs, (f) an indication of online or offline learning, or (g) data source (Paragraph(s) [0048], [0080], [0130]).
As per claim 7, Han teaches wherein the response to the preparation request comprises a result of performing one or more test tasks at the client NWDAF (Paragraph(s) [0043-0044]).
As per claim 8, Han teaches wherein the preparation request for DML or FL comprises the one or more test tasks (Paragraph(s) [0043-0044]).
As per claim 9, Han teaches wherein the result of performing the one or more test tasks at the client NWDAF comprises time and resource usage for completing the one or more test tasks, resource and energy consumption for completing the one or more test tasks, accuracy, or any combination of two or more thereof (Paragraph(s) [0044], [0046], [0067]).
As per claim 22, Han teaches wherein:
the updated status of at least one client NWDAF from among the one or more client NWDAFs indicates that the at least one client NWDAF chooses to leave the DML or FL or is not available for the DML or FL (Paragraph(s) [0084], [0098]); and
performing reselection of client NWDAFs comprises sending, to the at least one client NWDAF, a terminate request (Paragraph(s) [0154], [0164]).
As per claim 23, Han teaches wherein performing reselection of client NWDAFs further comprises performing client NWDAF discovery for discovery of one or more new client NWDAFs (Paragraph(s) [0154]).
As per claim 24, Han teaches wherein performing client NWDAF discovery for discovery of one or more new client NWDAFs comprises:
transmitting, to each of a new set of client NWDAFs, a new preparation request for DML or FL (Paragraph(s) [0164]);
receiving, from each of at least some of the new set of client NWDAFs, a response to the new preparation request for DML or FL (Paragraph(s) [0154]); and
selecting the one or more new client NWDAFs from the new set of client NWDAFs based on the responses to the new preparation requests for DML or FL (Paragraph(s) [0143], [0154]).
As per claim 25, Han teaches wherein the response to the new preparation request comprises a result of performing one or more new test tasks at the client NWDAF (Paragraph(s) [0044], [0124]).
As per claim 26, Han teaches wherein the new preparation request for DML or FL comprises the one or more new test tasks (Paragraph(s) [0132], [0137]).
As per claim 27, Han teaches wherein the result of performing the one or more new test tasks at the client NWDAF comprises time and resource usage for completing the one or more new test tasks, resource and energy consumption for completing the one or more new test tasks, accuracy, or any combination of two or more thereof (Paragraph(s) [0044], [0130]).
As per claim 28, Han teaches wherein each of the updated statuses comprises any one or more of: (i) change of willingness and availability, (ii) change of ML relevant capability, (iii) change of supported analytics identification, (iv) change of the available computation resource, (v) change of computation capability, (vi) change of communication quality, (vii) change of the available energy, or (viii) change of data availability (Paragraph(s) [0044], [0058], [0067], [0129-0130]).
As per claim 29, Han teaches wherein monitoring the updated status of each of the one or more client NWDAFs comprises receiving the updated status of each of the one or more client NWDAFs from a Network Repository Function, NRF, or NWDAF (Paragraph(s) [0027-0028], [0098]).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Please refer to form PTO-892 (Notice of Reference Cited) for a list of relevant prior art.
Ouyang et al – US 20230146099 – directed to an improved mechanism for NWDAFs in a telecom communication system, by means of federated learning, to increase work efficiency.
Lee et al - US 20220108214 - directed to managing a machine learning (ML) model for a network data analytics function (NWDAF) device, and more particularly, proposes a process of learning, provisioning, and updating an ML model.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MOHAMED A WASEL whose telephone number is (571) 272-2669. The examiner can normally be reached Mon-Fri (8:00 am – 4:30 pm).
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Glenton Burgess can be reached on (571)272-3949. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MOHAMED A. WASEL/Primary Examiner, Art Unit 2454