CTFR 18/329,887 CTFR 88803 Notice of Pre-AIA or AIA Status 07-03-aia AIA 15-10-aia The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA. DETAILED ACTION This Office Action is in response to the amendment filed 04/07/2026. Claims 1-8 and 10-25 are pending in this application. Claims 1,12 and 21 are independent claims. Claims 1-2, 11-16 and 18-22 are currently amended. This Office Action is made final . Claim Objections Claim 18 is objected to because of the following inconsistency. “ wherein the conflating the bundles is executed ” should be “ wherein the conflating of the bundles is executed” . Appropriate correction is requested. Claim Rejections - 35 USC § 103 07-20-aia AIA The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action: A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102 of this title, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made. 07-21-aia AIA Claim s 1, 2, 12 and 21 are rejected under 35 U.S.C. 103 as being unpatentable over Singh (US 2021/0004270 A1) in view of Gottin (US 2023/0289169 A1) . As per claim 12, Singh teaches A computer-implemented method, comprising: receiving, via a processor, state bundles comprising full state bundles and delta bundles with dependencies corresponding to updates received via a transport layer from a lower layer in a multi-layer edge architecture; (Singh Fig 1 shows the edge architecture. Block 130 Network is taken to be transport layer and Block 111 Edge Stack is taken to be lower layer [0017] In addition, rather than providing a full software package to each of the edge systems for an update to an application hosted on an edge system, the centralized IoT manager may provide delta changes between the new version and a current version of the application to each edge system to make updating edge systems more efficient. The centralized IoT manager may manage the software updates of the edge systems by pushing the software updates according to a schedule managed by the centralized IoT manager, rather than being managed by the edge systems periodically checking for updates [0037] ….The centralized IoT manager 142 may be further configured to maintain the edge system using delta change communications. For example, an instance of the centralized IoT manager 142 may be configured to form a communication with the edge system of the centralized IoT manager 142, and detect a change of entity on the edge system based on an operation of the edge system. The centralized IoT manager 142; may be further configured to determine one or more additional edge systems that have associations with the detected change of entity, and transmit a respective message to the one or more additional edge systems…). Here the dependency is interpreted to be the former version depending on the delta changes (i.e. communication with edges) to be applied to it to arrive at a new version. The word “bundle” is not defined in the specification. The examiner will treat it to be information. In the context of this invention it is information that is combined with another information. The concept of dependency is inherent in Singh in that delta communications are applied to a former version before transmitting. sending ready to be processed bundles to a dispatcher for processing in a predefined order based on the dependencies; and processing, via the processor, the ready to be processed bundles. (Singh [0017] In addition, rather than providing a full software package to each of the edge systems for an update to an application hosted on an edge system, the centralized IoT manager [dispatcher] may provide delta changes between the new version and a current version of the application to each edge system to make updating edge systems more efficient. The centralized IoT manager may manage the software updates of the edge systems by pushing the software updates according to a schedule managed by the centralized IoT manager [scheduling determines the order of edge nodes receiving the delta change], rather than being managed by the edge systems periodically checking for updates. [0104] The method 700 may further maintain the edge system using a delta change communication and notification at operation 730. For example, the IoT manager may manage subsequent object model synchronizations after the initial synchronization using delta-based communication and update notification (e.g., WebSocket), which is more efficient than full object model synchronizations. For example, the IoT manager may monitor the changes of the object model of the IoT system and/or the changes of the object model for the edge system [0106] The method 800 may further determine a delta change between the new version and the current version of the application at operation 820. In some examples, the method 800 may compare the object model of the system with the object model of the edge system that hosts the application. Block 840 of Fig 8 (Provide the delta change between the new version and the current version of the application to the edge system)) Singh does not teach conflating, via the processor, the state bundles using a plurality of conflation units, wherein each of the plurality of conflation units conflate bundles of a group of dependent bundles, to generate ready to be processed bundles. However, Gottin teaches conflating, via the processor, the state bundles using a plurality of conflation units, wherein each of the plurality of conflation units conflate bundles of a group of dependent bundles, to generate ready to be processed bundles; (Gottin [0025] Example embodiments may be implemented in an environment that includes a central node, near-edge nodes [conflation units], and edge nodes such as sensors. The group, or federation, of near-edge nodes may span multiple organizations such as multiple different companies, or multiple business units within a company. Initially, a model may be distributed to the edge nodes, which may each train the model using data collected by that edge node. The model may be a model that may employ sensor data from the collective organizations to predict behavior in a particular organization. [0026] Differences between the model outputs and ground truths may be communicated by the edge nodes to the central node which may aggregate the differences from all the edge nodes to generate an updated version of the model which may then be communicated from the central node to the edge nodes and [0045] One approach for relying on machine learning may comprise the training of a model at the near edge [conflation unit]. This is depicted in FIG. 3 which, in particular, discloses training of a machine learning model 302 at a near-edge node 304 and the deployment of the resulting model at the edge 306. The model M 302 obtained may then be deployed at each edge-node 306 and [0063] The communication from the edge node 504 may go through the near-edge 506 node with which the transmitting edge node 504 is associated, and the near-edge node 506 may or may not perform an aggregation step 'agg,' as shown in FIG. 5.). The examiner is taking this dependency to both among edge nodes that use the same near-edge node in Gottin. The concept of having multiple near-edge nodes in Gottin is consistent with what is disclosed in Singh ([0035] In some examples, the centralized IoT manager 142 may be deployed in multiple instances that are each instance respectively configured to connect to a respective group of one or more edge systems ). It would have been obvious to a person in the ordinary skill in the art before the filing date of the claimed invention to combine Gottin with the system of Singh to conflate bundles. One having ordinary skill in the art would have been motivated to use Gottin into the system of Singh for the purpose of implementing event detection across multiple environments (Gottin paragraph 01) As per claim 2, Gottin teaches wherein the full state bundles comprise updates of a same type received from the at least one lower layer bundled into a single versioned full state bundle. (Gottin [0025] Example embodiments may be implemented in an environment that includes a central node, near-edge nodes [conflation units], and edge nodes such as sensors. The group, or federation, of near-edge nodes may span multiple organizations such as multiple different companies, or multiple business units within a company. Initially, a model may be distributed to the edge nodes, which may each train the model using data collected by that edge node. The model may be a model that may employ sensor data from the collective organizations to predict behavior in a particular organization. [0026] Differences between the model outputs and ground truths may be communicated by the edge nodes to the central node which may aggregate the differences from all the edge nodes to generate an updated version of the model which may then be communicated from the central node to the edge nodes and [0045] One approach for relying on machine learning may comprise the training of a model at the near edge [conflation unit]. This is depicted in FIG. 3 which, in particular, discloses training of a machine learning model 302 at a near-edge node 304 and the deployment of the resulting model at the edge 306. The model M 302 obtained may then be deployed at each edge-node 306 and [0063] The communication from the edge node 504 may go through the near-edge 506 node with which the transmitting edge node 504 is associated, and the near-edge node 506 may or may not perform an aggregation step 'agg,' as shown in FIG. 5) As to claims 1 and 21, they are rejected based on the same reason as claim 12 . 07-21-aia AIA Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over Singh (US 2021/0004270 A1) in view of Gottin (US 2023/0289169 A1) in further view of Iyer (US 2019/0149474 A1) . As per claim 3, Singh and Gottin do not teach wherein the full state bundles comprise a managed endpoints bundle that contains a status of all managed endpoints of a reporting regional hub. However, Iyer teaches wherein the full state bundles comprise a managed endpoints bundle that contains a status of all managed endpoints of a reporting regional hub . (Iyer [0037] FIG. 1 illustrates a software-defined wide area network (SD-WAN) 100. As illustrated, the SD-WAN spans three regions 150 and includes multiple interconnected endpoints 102, regional hubs 104, and a SD-WAN controller 106. In operation, endpoints may be branch offices having several terminals connected via a local area network managed by a local router (not shown). Endpoints can be configured to send data, to receive data, and to forward data. For simplicity of explanation herein, endpoints from which data originates are referred to as “source endpoints” and endpoints that receive the data are referred to as “destination endpoints,” but each endpoint can be configured to send and receive data in practice. Regional hubs, or “hubs”, interconnect endpoints within a region and traffic from endpoints in the region is routed through the regional hub. For example, endpoints NY1, NY2, and NY3 are in a New York region and are interconnected through a NY Hub. Traffic to endpoints in other regions from endpoints NY1-NY3 is routed through the NY Hub. Endpoints and hubs can be managed by a single SD-WAN controller (as illustrated in FIG. 1) or each region can be managed by a separate SD-WAN controller (not shown). In an embodiment, traffic between endpoints and hubs travels over in-band communication channels 108 using, for example, a connection-based protocol like Transmission Control Protocol/Internet Protocol (TCP/IP) or a connectionless protocol like User Datagram Protocol (UDP). Management traffic between the SD-WAN controller and endpoints or hubs travels over “out-of-band” communication channels 110 using, for example, Border Gateway Protocol (BGP). In other embodiments, traffic between endpoints and hubs as well as management traffic can both travel over the same communication channels. [0039] In an Enterprise WAN environment, an SD-WAN may include hundreds or thousands of endpoints. In order to monitor the status of endpoints in the SD-WAN, a heartbeat protocol, such as a keepalive message, can be used to confirm that endpoints in the network are alive. In an embodiment, heartbeat traffic, such as a service level agreement protocol data unit (SLA PDU) generated by the heartbeat protocol, can be sent via a network control channel as described below). It would have been obvious to a person in the ordinary skill in the art before the filing date of the claimed invention to combine Iyer with the system of Singh and Gottin to determine the status of endpoints. One having ordinary skill in the art would have been motivated to use Iyer into the system of Singh and Gottin for the purpose of handling network traffic based on a SLA (Iyer paragraph 13) . 07-21-aia AIA Claim s 4 and 5 are rejected under 35 U.S.C. 103 as being unpatentable over Singh(US 2021/0004270 A1) in view of Gottin (US 2023/0289169 A1) in further view of Sethi (US 2024/0385935 A1) . As per claim 4, Singh and Gottin do not teach wherein the full state bundles comprise an endpoints per resource bundle that contains a mapping between a resource that was deployed and the endpoints associated with the deployed resource. However, Sethi teaches wherein the full state bundles comprise an endpoints per resource bundle that contains a mapping between a resource that was deployed and the endpoints associated with the deployed resource. (Sethi [0198] In Step 600, the learning model receives a first set of data that includes one or more infrastructure files, a prediction of resources, a list of assigned disaster recovery resources, and a status report of an application that used disaster recovery resources. In one or more embodiments, the first set of data is received from one or more data centers and/or one or more cloud systems. The first data set may include a complete picture of the data center infrastructure, the prediction of resources needed to provide one or more services provided by the data center, the list of disaster recovery resources assigned to each application, and how the application performed during a disaster recovery operation. The amount of data in the first data set may be of such a large amount that no human is able to make any inferences from the data without the aid of a computer-implemented method. [0201] In Step 606, the trained learning model receives a second set of data that includes one or more infrastructure files, a prediction of resources, a list of assigned disaster recovery resources, and a status report of an application that used disaster recovery resources, which may all be different than the data received in the first set of data. Over time, more data is generated and may be useable to update the learning model. As such, continuing to provide the trained learning model with more data may increase the functionality of the learning model). It would have been obvious to a person in the ordinary skill in the art before the filing date of the claimed invention to combine Sethi with the system of Singh and Gottin to map the resources and the endpoints. One having ordinary skill in the art would have been motivated to use Sethi into the system of Singh and Gottin for the purpose of executing their operations with maximum efficiency (Sethi paragraph 17) As per claim 5, Sethi teaches wherein the full state bundles comprise a resource status bundle that contains a mapping between a resource and a list of endpoints that the resource was deployed to along with their status. (Sethi [0198] In Step 600, the learning model receives a first set of data that includes one or more infrastructure files, a prediction of resources, a list of assigned disaster recovery resources, and a status report of an application that used disaster recovery resources. In one or more embodiments, the first set of data is received from one or more data centers and/or one or more cloud systems. The first data set may include a complete picture of the data center infrastructure, the prediction of resources needed to provide one or more services provided by the data center, the list of disaster recovery resources assigned to each application, and how the application performed during a disaster recovery operation. The amount of data in the first data set may be of such a large amount that no human is able to make any inferences from the data without the aid of a computer-implemented method. [0201] In Step 606, the trained learning model receives a second set of data that includes one or more infrastructure files, a prediction of resources, a list of assigned disaster recovery resources, and a status report of an application that used disaster recovery resources, which may all be different than the data received in the first set of data. Over time, more data is generated and may be useable to update the learning model. As such, continuing to provide the trained learning model with more data may increase the functionality of the learning model) . 07-21-aia AIA Claim s 6 and 7 are rejected under 35 U.S.C. 103 as being unpatentable over Singh(US 2021/0004270 A1) in view of Gottin (US 2023/0289169 A1) in further view of Sethi (US 2024/0385935 A1) and Nash (US 2018/0205666 A1) . As per claim 6, Singh and Gottin and Sethi do not teach wherein the delta state bundles comprise a resource status delta state bundle. However, Nash teaches wherein the delta state bundles comprise a resource status delta state bundle. (Nash [0041] The analysis and classification module may use external sources, cognitive systems and other information based analysis tools to categorize what is triggering any changes/deltas in resource changes in classes of application. Based on available classifications, the resource usage predictor module may provide an updated prediction of resource usage for a new application instance). The examiner believes this is consistent with what is disclosed in the specification ([0015] As used herein, a delta state bundle represents incremental changes to a resource since a last received full state bundle). It would have been obvious to a person in the ordinary skill in the art before the filing date of the claimed invention to combine Nash with the system of Singh and Gottin and Sethi to receive a status delta bundle. One having ordinary skill in the art would have been motivated to use Nash into the system of Singh and Gottin and Sethi for the purpose of running an efficient cloud computing environment that relates to the allocation and/or distribution of application workload. (Nash paragraph 02) As per claim 7, Nash teaches wherein the resource comprises an application. (Nash [0041] The analysis and classification module may use external sources, cognitive systems and other information based analysis tools to categorize what is triggering any changes/deltas in resource changes in classes of application. Based on available classifications, the resource usage predictor module may provide an updated prediction of resource usage for a new application instance) . 07-21-aia AIA Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Singh(US 2021/0004270 A1) in view of Gottin (US 2023/0289169 A1) in further view of Hurchalla (US 2024/0262361 A1) . As per claim 8, Singh and Gottin do not teach wherein the processor is to treat endpoints according to a most frequent status and only receive updates for resources on endpoints that have a status other than the most frequent status, wherein the processor is to treat endpoints that were not reported as having reported the most frequent status. However, Hurchalla teaches wherein the processor is to treat endpoints according to a most frequent status and only receive updates for resources on endpoints that have a status other than the most frequent status, wherein the processor is to treat endpoints that were not reported as having reported the most frequent status . (Hurchalla [0053] In some exemplary embodiments, the micro-value application may be indicative only of the micro-value application and a failure condition. In some exemplary embodiments, if no failure conditions are realized, the micro-value application may not generate an output 430 and the method returns to retrieving 415 subsequent sensor data for use in updating the data repository). The examiner is interpreting this according to what is disclosed in the specification ([0051] if the assumption can be made that most of the applications are in status “Running” most of the time, on most of the clusters, then regional hubs can report only applications that run on clusters and are in a status other than “Running.” The centralized hub may then accordingly be configured to treat clusters that are reported in “Clusters Per Application” bundle and are not reported in current bundle as “Running”) It would have been obvious to a person in the ordinary skill in the art before the filing date of the claimed invention to combine Hurchalla with the system of Singh and Gottin to treat endpoints according to a most frequent status. One having ordinary skill in the art would have been motivated to use Hurchalla into the system of Singh and Gottin for the purpose of using of a state driven micro-value architecture (Hurchalla paragraph 01) 07-21-aia AIA Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable over Singh(US 2021/0004270 A1) in view of Gottin (US 2023/0289169 A1) in further view of Ezrielev (US 2023/0344779 A1) . As per claim 10, Singh and Gottin do not teach comprising a transport reader that reads messages including the state bundles from the transport layer, extracts the state bundles, and inserts the extracted state bundles into a matching conflation unit. However, Ezrielev teaches comprising a transport reader that reads messages including the state bundles from the transport layer, extracts the state bundles, and inserts the extracted state bundles into a matching conflation unit. (Ezrielev [0016] To attempt to reduce data transmission, the data aggregator may obtain reduced-size data from the data collectors, reduced-size data being based on: (i) data obtained via measurements performed by the data collectors and (ii) the copy of the consensus sequence obtained from the data aggregator. The reduced-size data may contain fewer bits of information than the original data set and may include condensed representations of sub-sequences (e.g., segments) of data. The reduced-size data may be in a packaged (e.g., compressed) form and may require extraction by the data aggregator prior to data reconstruction. [0110] At operation 303, data aggregator 102 may obtain reduced-size data from data collectors 100. Reduced-size data may be obtained in a packaged (e.g., compressed) form and may require extraction by data aggregator 102. Reduced-size data may be a condensed representation of a data set made up of pointer pairs and/or sub-sequences (e.g., segments) of data. Pointer pairs may represent a sub-sequence of data that matches at least a portion of the consensus sequence. By transmitting reduced-size data during data collection, data aggregator 102 may access measurements performed by data collectors 100 without data collectors 100 transmitting full data sets across communication system 101. Consequently, network bandwidth may be conserved and power consumption by data collectors 100 due to data transmission may be reduced. Refer to FIG. 2A for additional details regarding obtaining reduced-size data. Refer to FIG. 4D for an example of reduced-size data generation). It would have been obvious to a person in the ordinary skill in the art before the filing date of the claimed invention to combine Ezrielev with the system of Singh and Gottin to extract state bundles. One having ordinary skill in the art would have been motivated to use Ezrielev into the system of Singh and Gottin for the purpose of limiting the transmission of data over a communication system during data collection ( Ezrielev paragraph 01) 07-21-aia AIA Claim s 11, 14, 15, 23 and 24 are rejected under 35 U.S.C. 103 as being unpatentable over Singh(US 2021/0004270 A1) in view of Gottin (US 2023/0289169 A1) in further view of Chng (US 12,524,275 B2) . As per claim 11, Singh and Gottin do not teach wherein the dispatcher requests one of the ready to be processed bundles and assigns a worker from a workers pool to process the ready to be processed bundle. However, Chng teaches wherein the dispatcher requests one of the ready to be processed bundles and assigns a worker from a workers pool to process the ready to be processed bundle. (Chng [col 4, lines 32-41] Each computer system 150 includes some or all traditional resources (e.g., processors, communication interface(s), primary and/or secondary data storage), which are not depicted in FIG. 1, hosts ledger(s) 154, and also hosts a portion of the workers that constitute worker pool 152. As described previously, worker pool 152 comprises worker entities that handle incoming tasks by performing computer operations dictated by the tasks (e.g., to update data, to copy or move data, to initiate communications, to generate a report). It would have been obvious to a person in the ordinary skill in the art before the filing date of the claimed invention to combine Chng with the system of Singh and Gottin to use a dispatcher to request a ready to be processed bundle. One having ordinary skill in the art would have been motivated to use Chng into the system of Singh and Gottin for the purpose of avoiding idle workers for executing tasks. (Chng col 1, lines 20-25) As to claims 14, 15, 23 and 24 they are rejected based on the same reason as claim 11 . 07-21-aia AIA Claim s 13 and 22 are rejected under 35 U.S.C. 103 as being unpatentable over Singh(US 2021/0004270 A1) in view of Gottin (US 2023/0289169 A1) in further view of Sabath (US 2020/0153898 A1) . As per claim 13, Singh and Gottin do not teach the processing the ready to be processed bundles comprises processing different state bundle types in a predefined order that is based on the dependencies between the different state bundle types. However, Sabath teaches the processing the ready to be processed bundles comprises processing different state bundle types in a predefined order that is based on the dependencies between the different state bundle types (Sabath [0058] In accordance with one or more embodiments of the present invention, the update service code 404 communicates with the master infrastructure code 406 on the master node 402 to obtain the information about the worker nodes used by the update service code 404 to determine an order of node updates and to perform the updates. The order of node updates can be determined, for example, using a planner micro-service container of the update service code 404 such as that described below in reference to block 702 of FIG. 7.) It would have been obvious to a person in the ordinary skill in the art before the filing date of the claimed invention to combine Sabath with the system of Singh and Gottin to determine order of updates. One having ordinary skill in the art would have been motivated to use Sabath into the system of Singh and Gottin for the purpose of selecting an optimal set of one or more nodes in a cluster to update (Sabath paragraph 17) As to claim 22, it is rejected based on the same reason as claim 13 . 07-21-aia AIA Claim 17 is rejected under 35 U.S.C. 103 as being unpatentable over Singh(US 2021/0004270 A1) in view of Gottin (US 2023/0289169 A1) in further view of Mehr (US 11,842,224 B1) . As per claim 17, Singh and Gottin do not teach further comprising reporting a latest status of the processing of the ready to be processed bundles. However, Mehr teaches further comprising reporting a latest status of the processing of the ready to be processed bundles (Mehr [col 7, lines 44-53] In some configurations, the resource status service will wait until all of the requested resource status data has been obtained and stored in the cache (i.e., for a multitude of computing resources) before sending the aggregated resource status data to the client application or sending a notice that the data is available. In other configurations, the resource status service will provide partial results stored in the cache, or a notice of partial results, to the client application as the partial results are returned from the network service). This will be taken to be the latest status of resource/application ([0044] updates from the same type are bundled to a single versioned full state bundle message that contains the latest status of each resource). It would have been obvious to a person in the ordinary skill in the art before the filing date of the claimed invention to combine Mehr with the system of Singh and Gottin to report a latest status of the processing of the ready to be processed bundles. One having ordinary skill in the art would have been motivated to use Mehr into the system of Singh and Gottin for the purpose of arriving at an optimal decision at the time of each function call (col 5, lines 38-40) 07-21-aia AIA Claim 18 is rejected under 35 U.S.C. 103 as being unpatentable over Singh(US 2021/0004270 A1) in view of Gottin (US 2023/0289169 A1) in further view of Shiran (US 2017/0371926 A1) . As per claim 18, Singh and Gottin do not teach wherein the conflating the state bundles is executed in response to detecting that a processing rate of the processor is slower than the rate of data received by the transport layer. However, Shiran teaches wherein the conflating the bundles is executed in response to detecting that a processing rate of the processor is slower than the rate of data received by the transport layer . (Shiran [0090] For example, the platform may normally be able to aggregate data faster locally compared to aggregating the data at a data source. Under normal network conditions, it would be preferable to receive data from the data source and aggregate the data locally at the platform. However, under slower network conditions, it is preferable to aggregate data at the data source and transfer the aggregated data over the network rather than transferring un-aggregated data for aggregation by the platform. On the other hand, if daemons of the platform are co-located with data sources, the cost of transferring data is relatively low such that the location where data is aggregated would not negatively affect query execution). The examiner believes this is consistent with what is disclosed in the specification ([0006] Preferably, conflating the bundles is executed in response to detecting that a processing rate of the processor is slower than the rate of data received by the transport layer. In this embodiment, the method provides efficient conflation of data while processing rate is slower than the rate of data received by transport.) It would have been obvious to a person in the ordinary skill in the art before the filing date of the claimed invention to combine Shiran with the system of Singh and Gottin to conflate the bundles. One having ordinary skill in the art would have been motivated to use Shiran into the system of Singh and Gottin for the purpose of optimizing data structures based on the obtained data.(Shiran paragraph 38) 07-21-aia AIA Claim s 19 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Singh(US 2021/0004270 A1) in view of Gottin (US 2023/0289169 A1) in further view of Cherp (US 2023/0195883 Al) and Coster (US 2023/0117824 A1) . As per claim 19, Singh and Gottin do not teach wherein the processing the ready to be processed bundles comprises processing groups of dependent bundles received. However, Cherp teaches wherein the processing the ready to be processed bundles comprises processing groups of dependent bundles received (Cherp [0082] Module listing 251 may also manage dependencies within a list of modules associated with an operating system. In some embodiments, module listing 251 may also manage the generation of bundles (e.g., bundles 125 of FIG. 1) of dependent modules by combining them as a bundle. Module listing 251 may include sub-lists of bundles associated with an operating system). It would have been obvious to a person in the ordinary skill in the art before the filing date of the claimed invention to combine Cherp with the system of Singh and Gottin to process groups of dependent bundles received. One having ordinary skill in the art would have been motivated to use Cherp into the system of Singh and Gottin for the purpose of implementing application executing in dynamically generated operating system execution environment to avoid access to restricted functionality by malicious actors. (Cherp paragraph 01) Cherp does not teach from a same regional hub one at a time. However, Coster teaches from a same regional hub one at a time (Coster [claim8] … aggregate datasets of the sensor data across the multiple systems, which are located at different geographic regions, and wherein the standardized sensor data includes the aggregate sensor data and the classification is based on the different geographic regions) . It would have been obvious to a person in the ordinary skill in the art before the filing date of the claimed invention to combine Coster with the system of Singh and Gottin and Cherp to use the same regional hub. One having ordinary skill in the art would have been motivated to use Coster into the system of Singh and Gottin and Cherp for the purpose of optimizing a group of servers (Coster paragraph 10). As per claim 20, Singh and Gottin do not teach comprising receiving the state bundles is from a plurality of regional hubs. However, Coster teaches comprising receiving the state bundles is from a plurality of regional hubs (Coster [claim8] … aggregate datasets of the sensor data across the multiple systems, which are located at different geographic regions, and wherein the standardized sensor data includes the aggregate sensor data and the classification is based on the different geographic regions) The examiner is treating this to be any information that is obtained from a geographic region that has dependencies. It would have been obvious to a person in the ordinary skill in the art before the filing date of the claimed invention to combine Coster with the system of Singh and Gottin to use regional hubs. One having ordinary skill in the art would have been motivated to use Coster into the system of Singh and Gottin for the purpose of optimizing a group of servers (Coster paragraph 10). Coster does not teach conflating the state bundles is based on the dependencies. However, Cherp teaches conflating the state bundles is based on the dependencies. (Cherp [0082] Module listing 251 may also manage dependencies within a list of modules associated with an operating system. In some embodiments, module listing 251 may also manage the generation of bundles (e.g., bundles 125 of FIG. 1) of dependent modules by combining them as a bundle. Module listing 251 may include sub-lists of bundles associated with an operating system). It would have been obvious to a person in the ordinary skill in the art before the filing date of the claimed invention to combine Cherp with the system of Singh and Gottin and Coster to conflate state bundles based on dependencies. One having ordinary skill in the art would have been motivated to use Cherp into the system of Singh and Gottin and Coster for the purpose of implementing application executing in dynamically generated operating system execution environment to avoid access to restricted functionality by malicious actors. (Cherp paragraph 01) Allowable Subject Matter 12-151-08 AIA 07-43 12-51-08 Claim s 16 and 25 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims. Response to Arguments 07-37 AIA Applicant's arguments filed on 04/07/2026 have been fully considered but they are not persuasive. Applicant’s arguments with respect to claims 1, 12 and 21 have been considered but are moot because the arguments do not apply because of the introduction of new art by Gottin . Conclusion 07-40 AIA 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 extension fee 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 date of this final action. Any inquiry concerning this communication or earlier communications from the examiner should be directed to MEHRAN KAMRAN whose telephone number is (571)272-3401. The examiner can normally be reached on 9-5. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor April Blair, can be reached on (571)270-1014. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. 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If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /MEHRAN KAMRAN/Primary Examiner, Art Unit 2196 Application/Control Number: 18/329,887 Page 2 Art Unit: 2196 Application/Control Number: 18/329,887 Page 3 Art Unit: 2196 Application/Control Number: 18/329,887 Page 4 Art Unit: 2196 Application/Control Number: 18/329,887 Page 5 Art Unit: 2196 Application/Control Number: 18/329,887 Page 6 Art Unit: 2196 Application/Control Number: 18/329,887 Page 7 Art Unit: 2196 Application/Control Number: 18/329,887 Page 8 Art Unit: 2196 Application/Control Number: 18/329,887 Page 9 Art Unit: 2196 Application/Control Number: 18/329,887 Page 10 Art Unit: 2196 Application/Control Number: 18/329,887 Page 11 Art Unit: 2196 Application/Control Number: 18/329,887 Page 12 Art Unit: 2196 Application/Control Number: 18/329,887 Page 13 Art Unit: 2196 Application/Control Number: 18/329,887 Page 14 Art Unit: 2196 Application/Control Number: 18/329,887 Page 15 Art Unit: 2196 Application/Control Number: 18/329,887 Page 16 Art Unit: 2196 Application/Control Number: 18/329,887 Page 17 Art Unit: 2196 Application/Control Number: 18/329,887 Page 18 Art Unit: 2196 Application/Control Number: 18/329,887 Page 19 Art Unit: 2196 Application/Control Number: 18/329,887 Page 20 Art Unit: 2196 Application/Control Number: 18/329,887 Page 21 Art Unit: 2196 Application/Control Number: 18/329,887 Page 22 Art Unit: 2196 Application/Control Number: 18/329,887 Page 23 Art Unit: 2196 Application/Control Number: 18/329,887 Page 24 Art Unit: 2196
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