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 .
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Chou (US Publication 2021/0258866 A1) further in view of Seetharaman et al. (US Publication 2021/0306938 A1).
In regards to claims 1, 10 and 18 Chou (US Publication 2021/0258866 A1) teaches, a method, comprising: identify an event in a network (see paragraph 164; Special events, such as sports games, concerts, can cause traffic demand to shoot up at certain times and locations); identifying a template in response to the event, wherein the template identifies actions to be performed to service data traffic associated with the event (see paragraph 164; Therefore, the NSSI resource allocation optimization function trains the AI/ML model, based on historic performance data collected over time from O-RAN nodes. It then uses the AI/ML model to predict the traffic demand patterns of 5G networks in different times and locations for each network slice and automatically re-allocates the network resources ahead of the network issues surfaced); determining, by an event controller, that at least one wireless station in the network has capacity to service data traffic associated with the event (see paragraph 184; figure 8, step 814 and paragraph 184; At operation 814, the non-RT RIC 802 executes the action at the time determined by the model inference by performing the following operations: (functionality 4.1 in FIG. 8) reconfiguring the slice subnet attributes via the O1 interface (RAN node will be reconfigured thus the network has the capacity to service the data traffic), and (functionality 4.2 in FIG. 8) requesting OCMO 806 to update the VNF resources (e.g. scale in/out). The OCMO 806 updates the O-Cloud resources via the O2 interface); transmitting, template, instructions to at least one device to implement changes to the at least one wireless station (see paragraph 188 and figure 9 step 903; at 903, initiating one or more of the actions to reallocate resources of the NSSI. The actions may be, for example, adding or reducing resources for a particular time/location. The resources may be, for example, capacity (e.g., processing, storage, etc.), VNF resources, or slice subnet attributes); and instantiating the changes to the at least one wireless station (see paragraph 188; In some embodiments, initiating the one or more actions may be performed by sending instructions to various nodes including, but not limited to, RAN nodes or OCMO nodes).
In further regards to claims 1 and 10, Chou fails to teach, identifying a template, from a plurality of stored templates, in response to the event, wherein the template identifies actions to be performed to service data traffic associated with the event and the transmitting being based on the identified template.
Seetharaman et al. (US Publication 2021/0306938 A1) however teaches, identifying a template (see figure 4 for a flowchart of a method for template-based dynamic network slicing; where the type of service request reads on an event), from a plurality of stored templates, in response to the event, wherein the template identifies actions to be performed to service data traffic associated with the event (see figures 2 and 3 and paragraph 44; the SSNR-IN 216 may include details of network slice instances, slice subnet instances, services and network resources allocated to various slice and slice subnet instances and services. In addition to its existing data, the SSNR-IN 216 may include details of resource occupancy/usage levels for each service, slice instances and slice subnet instances, scaling limits for a slice/slice subnet, including dependencies across slice subnets, service requirement set and slice subnet requirements. The SSNR-IN 216 may also store adapted rules, as Adapted Service Characteristics Table (ADAPT-SRV-CHAR-TABLE). An exemplary ADAPT-SRV-CHAR-TABLE is depicted in FIG. 3 as a table 302. The SSNR-IN 216 may also store adapted service performance requirements as Adapted Service Performance Requirement Table (ADAPT-SRV-PERF-RQMTS-TABLE). An exemplary ADAPT-SRV-PERF-RQMTS-TABLE is depicted in FIG. 3 as a table 304) and the transmitting based on the identified template (see paragraph 76; the NESTC-SS 212 may check the feasibility to scale up the required resources to fulfill the relevant aspects of the requirements specified in the service requirement set for that attribute. This is done by checking the relevant data stored in SSNR-IN 216 (which may have been provisioned, policy-driven and/or determined by the capacity limits of the different subnetworks. This information may also be provided by the controller or orchestrator managing the sub-network (for example, a Software Defined Networking (SDN) controller, or a Network Function Virtualization Orchestrator (NFVO)), or by checking with the RESO-SS 206. Based on the feasibility to scale, the RES-SCORE-ATTRIB for each attribute may be adapted).
Chou and Seetharaman both relate to service provisioning with network slices.
Therefore, it would have been obvious for one of ordinary skill in the art for one of ordinary skill in the art before the effective filing date of the present application to use the stored adapted rules as shown by Seetharaman into the teachings of Chou. The motivation to do so would to reduce processing time because templates eliminate the need to evaluate requirements per even, allowing for rapid provisioning of network slices.
In regards to claims 2 and 11 Chou teaches, monitoring the network, wherein the monitoring comprises: monitoring control plane data associated with usage of the network (see paragraph 166; the non-RT RIC monitors the radio network(s) by collecting resource usage and performance-related data via the O1 interface), receiving and reviewing inputs from a web site (see paragraph 220; The communication device 1700 may be a UE, eNB, PC, a tablet PC, an STB, a PDA, a mobile telephone, a smartphone, a web appliance), and receiving and reviewing data associated with a particular application executed in the network (see paragraph 164; the network traffic tends to be sporadic, where there may be different usage patterns in terms of time, location, UE distribution, and types of applications. For example, most IoT sensor applications may run during off-peak hours or weekends).
In regards to claims 3-4, 12-13 and 19 Chou teaches assigning an event type and a location to the event (see paragraph 167; the non-RT RIC may analyze the data to train an A or ML model (referred collectively as AI/ML model), and then determine the actions needed to add or reduce the resources (e.g. capacity. VNF resources, slice subnet attributes, etc.) for the NSSI at a specific time and location) and wherein the identifying the template comprises: identifying the template based on the event type and the location (see paragraph 167; the determination of then determine the actions needed to add or reduce the resources (e.g. capacity. VNF resources, slice subnet attributes, etc.) for the NSSI at a specific time and location).
In regards to claims 5, 14 and 20 Chou teaches, wherein the identifying the template comprises: identifying, from a plurality of stored templates, the template that most closely matches the event type and the location (see paragraphs 83-84; The UDM may include a UDM-FE, which is in charge of processing credentials, location management, subscription management, and so on. Several different front ends may serve the same user in different transactions. The UDM-FE accesses subscription information stored in the UDR and performs authentication credential processing, user identification handling, access authorization. registration/mobility management, and subscription management. In addition to communicating with other NFs over reference points as shown, the UDM 258 may exhibit the Nudm service-based interface. The AF 260 may provide application influence on traffic routing, provide access to NEF. and interact with the policy framework for policy control).
In regards to claims 6 and 15, Chou teaches, determining, by the event controller, that at least one of a new device or a new network element is needed to service the data traffic associated with the event (see paragraph 188 and figure 9, step 903; at 903, initiating one or more of the actions to reallocate resources of the NSSI. The actions may be, for example, adding or reducing resources for a particular time/location. The resources may be, for example, capacity (e.g., processing, storage, etc.), VNF resources, or slice subnet attributes. In some embodiments, initiating the one or more actions may be performed by sending instructions to various nodes including, but not limited to, RAN nodes or OCMO nodes); and instantiating the at least one new device or new network element to service the data traffic associated with the event (see paragraph 66; The RAN 204 is communicatively coupled to CN 220 that includes network elements to provide various functions to support data and telecommunications services to customers/subscribers (for example, users of UE 202). The components of the CN 220 may be implemented in one physical node or separate physical nodes. In some embodiments, NFV may be utilized to virtualize any or all of the functions provided by the network elements of the CN 220 onto physical compute/storage resources in servers, switches, etc. A logical instantiation of the CN 220 may be referred to as a network slice, and a logical instantiation of a portion of the CN 220 may be referred to as a network sub-slice).
In regards to claims 7 and 16, Chou teaches, determining that the event has ended; and reconfiguring the at least one wireless station to return to a configuration associated with the at least one wireless station prior to instantiating the changes (see figure 10 decommissioning 1010; see paragraph 192; Decommissioning phase involves the deactivation of the NSI and releasing of the resources assigned to it; implies a return to the previous state before the instantiating).
In regards to claim 8, Chou teaches, wherein the identifying the template comprises: using machine learning to identify the template (see paragraph 167; the non-RT RIC may analyze the data to train an A or ML model (referred collectively as AI/ML model), and then determine the actions needed to add or reduce the resources (e.g. capacity. VNF resources, slice subnet attributes, etc.) for the NSSI at a specific time and location).
In regards to claims 9 and 17, Chou teaches dynamically modifying network elements to support event-related data traffic (see paragraphs 168-170; The non-RT RIC executes the actions (or functions) to adjust or reallocate network resources (e.g., NSSI resources) that include. Example actions include: (3a) Re-configuring the NSSI attributes via an O1 interface: and (3b) Update the cloud resources via the O2 interface (which functionality may be performed by the O-Cloud Management and Orchestration function); the adjusting and reallocating implies the dynamic modification).
Response to Arguments
Applicant’s arguments with respect to the rejection under 35 USC 102 and the Chou reference have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JAY P PATEL whose telephone number is (571)272-3086. The examiner can normally be reached M-F 9:30-6.
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/JAY P PATEL/Primary Examiner, Art Unit 2466
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