DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 02/15/2024 and 04/23/2025 have been considered by the examiner.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Vandikas et al. (US 2022/0150131) in view of Chapalamadugu et al. (US 2025/0184237).
Regarding claims 19, 1, and 12, Vandikas discloses a method, a system for dynamic edge computing resource management, and a telecommunications network, the method comprising:
determining, using a network function of an operator core network for a telecommunications network, event data corresponding to a planned event instance, wherein the event data includes at least an indication of an event type and an event location (paragraphs [0075]-[0078]; e.g., Events in relevant location and time (e.g. sport event, concert etc.));
assign the planned event instance with a network service classification based at least on the event type (paragraphs [0006], [0018], [0043]; e.g., to map a service category to a virtual network instance based on service requirements of the service category);
orchestrating a service augmentation platform on an edge server of the operator core network based at least on the network service classification and a proximity of the edge server to at least one radio access network having a coverage area that includes at least a portion of the event location (paragraphs [0018], [0050], [0148]; e.g., classify which services (such as video, augmented reality, virtual reality, audio, VoIP, email, synching, message, data storage etc.) are needed based on the given request and then predict (e.g. a number of requests of a service category)).
Vandikas discloses selectively allocate a network slice in relation to allocation of resources in each layer of network layers (paragraph [0141]), but fails to specifically disclose providing access to the service augmentation platform to one or more user equipment (UE) in communication with the at least one radio access network based on a location of the one or more UE with respect to a geolocation region associated with the event location.
However, Chapalamadugu discloses selectively allocate a network slice providing access to the service augmentation platform to one or more user equipment (UE) in communication with the at least one radio access network based on a location of the one or more UE with respect to a geolocation region associated with the event location (paragraphs [0023], [0050]; see NSSF 514 may select a set of network slice instances to serve a particular UEs 102, determine network slice selection assistance information (NSSAI)).
Therefore, taking the teachings of Vandikas in combination of Chapalamadugu as a whole, it would have been obvious to one having ordinary skill in the art at the time of the invention by applicant to allocate a network slice providing access to the service augmentation platform to one or more user equipment (UE) in communication with the at least one radio access network based on a location of the one or more UE with respect to a geolocation region associated with the event location for advantages of improving network services to User Equipment devices (UEs) wirelessly connected to the cellular network (Chapalamadugu: paragraph [0002]).
Regarding claims 2 and 13, Vandikas in combination with Chapalamadugu discloses the system and the network of claims 1 and 12, the one or more processors further to: instantiate, at the service augmentation platform, one or more instances of network functions of the operator core network based at least in part on the network service classification (Vandikas: paragraphs [0006], [0018]; e.g., map a service category to a virtual network instance based on service requirements of the service category).
Regarding claims 3 and 14, Vandikas in combination with Chapalamadugu discloses the system and the network of claims 1 and 12, the one or more processors further to: instantiate, at the service augmentation platform, one or more instances of cloud-based service supplemental applications based at least in part on the network service classification, wherein the one or more instances of cloud-based service supplemental applications are associated with at least one cloud-based service accessible to the one or more UE via the at least one radio access network (Vandikas: paragraphs [0018], [0043], [0050]).
Regarding claim 4, Vandikas in combination with Chapalamadugu discloses the system of claim 1, the one or more processors further to: de-orchestrate the service augmentation platform based on a duration of the planned event instance indicated by the event data (Vandikas: paragraphs [0147]-[0148]).
Regarding claims 5 and 16, Vandikas in combination with Chapalamadugu discloses the system and the network of claims 1 and 12, the one or more processors further to: deallocate the network slice providing access to the service augmentation platform to the one or more UE based at least on one or more of: the one or more UE leaving a geolocation area associated with the event location, or a duration of the planned event instance indicated by the event data (Vandikas: paragraphs [0068], [0105]-[0106]; e.g., the service category in the next time interval is lower than predicted, some resources may be released to compensate 280 for the prediction error).
Regarding claims 6 and 18, Vandikas in combination with Chapalamadugu discloses the system and the network of claims 1 and 12, wherein the proximity of the edge server to the at least one radio access network is based on at least one of: a number of network device hops or a physical distance (Vandikas: paragraphs [0105]-[0106]; see based on the predicted number of requests for the service category and a current allocation of resources in the plurality of network layers then allocating of resources).
Regarding claims 7 and 15, Vandikas in combination with Chapalamadugu discloses the system and the network of claims 1 and 12, the one or more processors further to: determine the network service classification from the event data based on at least one of: a machine learning model trained as an inference engine, or a natural language processing (NLP) algorithm (Vandikas: paragraphs [0072]-[0073], [0093]; e.g., using machine learning 222 by means of a neural network, a linear regression neural network is built specifically trained for the service category).
Regarding claim 8, Vandikas in combination with Chapalamadugu discloses the system of claim 1, the one or more processors further to: instantiate, at the service augmentation platform, a virtual private network (VPN) service accessible to the one or more user equipment (UE) (Vandikas: paragraphs [0006], [0043]).
Regarding claims 9, 17, and 20, Vandikas in combination with Chapalamadugu discloses the system, the network, and the method of claims 1, 12, and 19, the one or more processors further to, using the network function: monitor for a presence of the one or more UE within a geolocation region associated with the event location (Vandikas: paragraph [0078]; e.g., Events in relevant location and time (e.g., sport event, concert etc.)); based at least on detecting the presence, sending a notification message to the one or more UE displaying an option to elect access to the service augmentation platform; and based on an authorization from the one or more UE in response to the notification message, trigger the one or more UE to transmit a request to the operator core network to allocate the network slice providing access to the service augmentation platform to the one or more UE (Vandikas: paragraphs [0093], [0105]).
Regarding claim 10, Vandikas in combination with Chapalamadugu discloses the system of claim 9, wherein the request to the operator core network comprises a packet data unit (PDU) modification request indicating a network slice identifier associated with the service augmentation platform (Vandikas: paragraphs [0141],[0147]).
Regarding claim 11, Vandikas in combination with Chapalamadugu discloses the system of claim 9, wherein the request to the operator core network comprises a network slice identifier provided to the one or more UE by the network function, the network slice identifier associated with the service augmentation platform (Vandikas: paragraphs [0048], [0141]).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to TIMOTHY X PHAM whose telephone number is (571)270-7115. The examiner can normally be reached Mon-Fri: 8:30-5:00.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Vladimir Magloire can be reached at 571-270-5144. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/TIMOTHY X PHAM/Primary Examiner, Art Unit 3648