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 .
This communication is in response to the remarks and amendments filed on 19 December, 2025.
Claims 1-20 are pending.
Claims 1, 19 and 20 have been amended.
Response to Arguments
Double Patenting
The Double Patenting rejection is withdrawn in view of the Terminal Disclaimer filed on 19 December, 2025.
35 USC § 103
Applicant’s request for a translation of Korean Patent No.20210149576 is no longer necessary in view of the new grounds of rejection. Amended claim limitations have necessitated a new ground of rejection.
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.
Claims 1-3, 5, 13, and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Song (WO 2021/034428), in view of Brazeau et al (US 10,911,505).
Regarding claim 1, Song teaches a method comprising:
configuring, by the processing circuitry, the edge device to collect the telemetry flow data output by the network device and to generate the processed telemetry flow data based on the collected telemetry flow data (Song fig.1 and [0035] provides “The network 100 includes a plurality of network devices 102 including one or more network edge devices 104. The network devices 102 may be configured to route data packets across various network paths in the network 100. The network edge devices 104 are network nodes that are located on the edge of the network 100. In the depicted embodiment, the network 100 also includes a telemetry data collector device 120. A telemetry data collector device 120 is configured to collect data related to the network's performance from the network edge devices 104 for storage and analysis…alternative embodiments may readily include a greater number of such edge devices that provide telemetry data to telemetry data collector device 120”, wherein the provision of telemetry data by the edge devices to the collector device can be interpreted as the edge devices being configured to provide said data, said data generated by collection);
and storing, by the processing circuitry, an indication of the processed telemetry flow data (fig.1 and [0035] provides “A telemetry data collector device 120 is configured to collect data related to the network's performance from the network edge devices 104 for storage and analysis”).
Song teaches the above including the edge device to collect telemetry flow data output by the network device and to generate processed telemetry flow data based on the collected telemetry flow data (Song fig.1 and [0035] provides “The network 100 includes a plurality of network devices 102 including one or more network edge devices 104. The network devices 102 may be configured to route data packets across various network paths in the network 100. The network edge devices 104 are network nodes that are located on the edge of the network 100. In the depicted embodiment, the network 100 also includes a telemetry data collector device 120. A telemetry data collector device 120 is configured to collect data related to the network's performance from the network edge devices 104 for storage and analysis…alternative embodiments may readily include a greater number of such edge devices that provide telemetry data to telemetry data collector device 120”, wherein the provision of telemetry data by the edge devices to the collector device can be interpreted as the edge devices being configured to provide said data, said data generated by collection)but Song does not explicitly teach selecting, by the processing circuitry, [[and]] based on the RTT between the network device and the edge device, and from a plurality of edge devices. However, in a similar field of endeavor, Brazeau teaches selecting, by the processing circuitry, [[and]] based on the RTT between the network device and the edge device, and from a plurality of edge devices (Brazeau col.3 lines 62-65 provides “A typical method of measuring how close an edge server is to a user device is the round-trip time (RTT) metric. The RTT metric is typically used to select an edge server for requests sent by a particular user device.”).
One of ordinary skill in the art before the effective filing date of the claimed invention would have recognized the ability to utilize the teachings of Brazeau for edge device selection from a plurality of edge devices. The teachings of Brazeau, when implemented in the Song system, will allow one of ordinary skill in the art to efficiently collect data and maintain optimal round-trip time. Therefore, the examiner concludes it would have been obvious to one of ordinary skill in the art before the effective filing date of applicant’s invention to arrive at the above-claimed invention.
Regarding claim 2, the method of claim 1, wherein configuring the edge device to generate the processed telemetry flow data comprises configuring the edge device to perform one or more of filtering, aggregating, or compressing the telemetry flow data (Song [0034]).
Regarding claim 3, the method of claim 1, wherein configuring the edge device to collect the telemetry flow data comprises configuring a telemetry collector to collect the telemetry flow data (Song [0035]).
Regarding claim 5, the method of claim 1, further comprising receiving, by the processing circuitry, the processed telemetry flow data from the edge device (Song fig.1 and [0035] provides “…edge devices that provide telemetry data to telemetry data collector device 120”).
Regarding claim 13, Song-Brazeau has taught the method of claim 1, wherein selecting the edge device is based on the RTT between the network device and the edge device (Brazeau col.3 lines 62-65 provides “A typical method of measuring how close an edge server is to a user device is the round-trip time (RTT) metric. The RTT metric is typically used to select an edge server for requests sent by a particular user device”) and further based on an RTT between the edge device and an instance of a collector device (Brazeau col.3 lines 62-65 provides “A typical method of measuring how close an edge server is to a user device is the round-trip time (RTT) metric. The RTT metric is typically used to select an edge server for requests sent by a particular user device”).
Motivation to combine provided with reference to claim 1.
Regarding claim 19, this claim contains limitations found within those of claim 1, and the same rationale of rejection applies, where applicable.
Regarding claim 20, this claim contains limitations found within those of claim 1, and the same rationale of rejection applies, where applicable.
Claims 6 and 9 are rejected under 35 U.S.C. 103 as being unpatentable over Song (WO 2021/034428), in view of Brazeau et al (US 10,911,505), further in view of Guim-Bernat et al (US 2021/0006972).
Regarding claim 6, Song-Brazeau has taught the method of claim 1, wherein selecting the edge device is based on the RTT (Brazeau col.3 lines 62-65 provides “A typical method of measuring how close an edge server is to a user device is the round-trip time (RTT) metric. The RTT metric is typically used to select an edge server for requests sent by a particular user device”) but Song-Brazeau does not explicitly teach further based on a determination that the edge device and the network device satisfy a geographical restriction. However, in a similar field of endeavor, Guim-Bernat teaches a determination that the edge device and the network device satisfy a geographical restriction (Guim-Bernat [0185] provides “ Example 34 is an edge computing device operable in an edge computing system, the edge computing device comprising: a network interface card (NIC); and processing circuitry coupled to the NIC, the processing circuitry configured to perform operations to: encode a current geolocation information of the edge computing device for transmission to a network management device via the NIC; decode a configuration message with a workflow execution plan for an edge workload and an edge-to-edge location graph (ELG) received from the network management device via the NIC, the ELG based on the geolocation information and indicating a plurality of connectivity nodes within the edge computing system that are available for executing a plurality of services associated with an edge workload; retrieve a geofence policy within metadata of the workflow execution plan, the geofence policy specifying geofence restrictions associated with each of the plurality of services; and select a service of the plurality of services for execution based on a successful verification that the edge computing device is within the ELG and a geofence restriction of the geofence restrictions specified by the geofence policy for the selected service is satisfied by the geolocation information of the edge computing device”).
One of ordinary skill in the art before the effective filing date of the claimed invention would have recognized the ability to utilize the teachings of Guim-Bernat for edge device selection based on a geographical restriction. The teachings of Guim-Bernat, when implemented in the Song-Brazeau system, will allow one of ordinary skill in the art to minimize latency and provide compliance with data security. Therefore, the examiner concludes it would have been obvious to one of ordinary skill in the art before the effective filing date of applicant’s invention to arrive at the above-claimed invention.
Regarding claim 9, Song-Brazeau has taught the method of claim 1, wherein selecting the edge device is based on the RTT (Brazeau col.3 lines 62-65 provides “A typical method of measuring how close an edge server is to a user device is the round-trip time (RTT) metric. The RTT metric is typically used to select an edge server for requests sent by a particular user device”) but Song-Brazeau does not explicitly teach further based on a determination that data is allowed to be exchanged between the network device and the edge device. However, in a similar field of endeavor, Guim-Bernat teaches a determination that data is allowed to be exchanged between the network device and the edge device(Guim-Bernat [0185] provides “ Example 34 is an edge computing device operable in an edge computing system, the edge computing device comprising: a network interface card (NIC); and processing circuitry coupled to the NIC, the processing circuitry configured to perform operations to: encode a current geolocation information of the edge computing device for transmission to a network management device via the NIC; decode a configuration message with a workflow execution plan for an edge workload and an edge-to-edge location graph (ELG) received from the network management device via the NIC, the ELG based on the geolocation information and indicating a plurality of connectivity nodes within the edge computing system that are available for executing a plurality of services associated with an edge workload; retrieve a geofence policy within metadata of the workflow execution plan, the geofence policy specifying geofence restrictions associated with each of the plurality of services; and select a service of the plurality of services for execution based on a successful verification that the edge computing device is within the ELG and a geofence restriction of the geofence restrictions specified by the geofence policy for the selected service is satisfied by the geolocation information of the edge computing device”).
Motivation to combine provided with reference to claim 6.
Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Song (WO 2021/034428), in view of Brazeau et al (US 10,911,505), further in view of Hale et al (US 2020/0028756).
Regarding claim 4, Song-Brazeau teaches the method of claim 3, but Song-Brazeau does not explicitly teach wherein configuring the edge device to collect the telemetry flow data comprises configuring the edge device to load balance the telemetry collector with another telemetry collector. However, in a similar field of endeavor, Hale teaches wherein configuring the edge device to collect the telemetry flow data comprises configuring the edge device to load balance the telemetry collector with another telemetry collector (Hale [0034] provides “The depicted edge collection device 200 includes edge collectors operating on a container orchestration engine (e.g., such as a Kubernetes® brand open-source container orchestration engine) behind a load balancer (e.g., service 220) in an autoscaling set. The example edge collection device 200 in FIG. 2 utilizes pods 216, each pod 216 including a scheduling unit (e.g., service 220) that groups containerized components of the network infrastructure, and utilizes a horizontal pod autoscaler 218. The number and content of pods 216 may be managed in real-time for load balancing or other considerations…”).
One of ordinary skill in the art before the effective filing date of the claimed invention would have recognized the ability to utilize the teachings of Hale for load balancing the telemetry collection workload on an edge device. The teachings of Hale, when implemented in the Song-Brazeau system, will allow one of ordinary skill in the art to prevent overloading the device or reduce its functional efficiency. Therefore, the examiner concludes it would have been obvious to one of ordinary skill in the art before the effective filing date of applicant’s invention to arrive at the above-claimed invention.
Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over Song (WO 2021/034428), in view of Brazeau et al (US 10,911,505), further in view of Chintalapally (EP3336697A1).
Regarding claim 7, Song-Brazeau teaches the method of claim 1, wherein selecting the edge device is based on the RTT (Brazeau col.3 lines 62-65 provides “A typical method of measuring how close an edge server is to a user device is the round-trip time (RTT) metric. The RTT metric is typically used to select an edge server for requests sent by a particular user device”) but Song-Brazeau does not explicitly teach further based on whether a collection type for the edge device comprises polling or streaming. However, in a similar field of endeavor, Chintalapally teaches based on whether a collection type for the edge device comprises polling or streaming (Chintalapally [0008] provides “…accurately determining the types of edge devices that are connected and the capabilities of the edge devices, as well as determining and assigning execution tasks to the edge devices”; Chintalapally [0015] provides “ For example, the communication hardware may communicate an application to a specific edge device 110 for execution on the edge device 110. Processed data generated by an edge device 110 may be received via the communication hardware and forwarded to an external system 115”; Chintalapally [0016] provides “For example, edge device information may include edge device type, edge device hardware and software capabilities, sensor types connected to the edge device 110 and data provided by the sensors (111 and 112), and actuators and data provided to the actuators”; Chintalapally [0017] provides “Application metadata may include hardware and software requirements of the application that facilitate proper execution of the application and data requirements that specify the type, speed, format, etc., of data to be ingested by the application”; Chintalapally [0018] provides “Applications 305 may require data 313, capabilities 318, and an associated business entity 323. In other words, a device based on the graph 300 may be able to generate data (e.g., video, sensor data), have certain capabilities (e.g., a graphics processing unit (GPU), WiFi), and be associated with a particular business entity. An application based on the graph can require certain types of data (e.g., sensor data) and hardware capabilities (e.g., GPU) to perform certain analytics”).
One of ordinary skill in the art before the effective filing date of the claimed invention would have recognized the ability to utilize the teachings of Chintalapally for edge device selection for data collection. The teachings of Chintalapally, when implemented in the Song-Brazeau system, will implement edge device discovery and device capability mapping, and that defines and delivers application requirements templates, as well as controls the technical communication parameters of edge devices (Chintalapally [0002]). Therefore, the examiner concludes it would have been obvious to one of ordinary skill in the art before the effective filing date of applicant’s invention to arrive at the above-claimed invention.
Claims 8, 10-12 and 14-18 are rejected under 35 U.S.C. 103 as being unpatentable over Song (WO 2021/034428), in view of Brazeau et al (US 10,911,505), further in view of Singhal et al (US 11,223,516).
Regarding claim 8, Song-Brazeau teaches the method of claim 1, but Song-Brazeau does not explicitly teach wherein determining the RTT is based on one or more of a vendor of the network device, a product type of the network device, a platform of the network device, an operating system (OS) provisioned at the network device, or a version of the network device. However, in a similar field of endeavor, Singhal teaches wherein determining the RTT is based on one or more of a vendor of the network device, a product type of the network device, a platform of the network device, an operating system (OS) provisioned at the network device, or a version of the network device (Singhal col.18 lines 45-60 provides “…sending a new version of software to the cluster as part of an upgrade…”).
One of ordinary skill in the art before the effective filing date of the claimed invention would have recognized the ability to utilize the teachings of Singhal for decisions based on RTT between devices. The teachings of Singhal, when implemented in the Song-Brazeau system, will allow one of ordinary skill in the art to collect data from various strategic points of a network without degradation in RTT. Therefore, the examiner concludes it would have been obvious to one of ordinary skill in the art before the effective filing date of applicant’s invention to arrive at the above-claimed invention.
Regarding claim 10, Song-Brazeau teaches the method of claim 1, wherein selecting the edge device is based on the RTT (Brazeau col.3 lines 62-65 provides “A typical method of measuring how close an edge server is to a user device is the round-trip time (RTT) metric. The RTT metric is typically used to select an edge server for requests sent by a particular user device”) but Song-Brazeau does not explicitly teach and further based on a determination that an aggregated loading of a plurality of telemetry collectors of the edge device is less than a loading threshold. However, in a similar field of endeavor, Singhal teaches based on a determination that an aggregated loading of a plurality of telemetry collectors of the edge device is less than a loading threshold (Singhal col.6 lines 5-28 provides that “The server side 120 can push new configurations based on the calculated health of the cluster/service or the state of the cluster/service or some external events which influence these configuration setting”).
Motivation to combine provided with reference to claim 8.
Regarding claim 11, Song-Brazeau teaches the method of claim 10, but Song-Brazeau does not explicitly teach wherein the edge device is a first edge device, the method further comprising, after storing the indication of the processed telemetry flow data, selecting, by the processing circuitry, a second edge device from the plurality of edge devices based on a determination that the aggregating loading of the plurality of telemetry collectors on the first edge device is greater than the loading threshold. However, in a similar field of endeavor, Singhal teaches wherein the edge device is a first edge device, the method further comprising, after storing the indication of the processed telemetry flow data, selecting, by the processing circuitry, a second edge device from the plurality of edge devices based on a determination that the aggregating loading of the plurality of telemetry collectors on the first edge device is greater than the loading threshold (Singhal col.3 lines 40-45 provides “…each edge processing unit has its own configuration which is used by the edge processing system to control the behavior of the intelligent edge device in a virtualized, hyper-converged environment. These configurations may control the amount of data processed by the intelligent edge device, processing logic and rules run on the edge device, frequency of the processing rules, and also the amount of processed data sent to the cloud server”).
Motivation to combine provided with reference to claim 8.
Regarding claim 12, Song-Brazeau teaches the method of claim 1, wherein selecting the edge device is based on the RTT (Brazeau col.3 lines 62-65 provides “A typical method of measuring how close an edge server is to a user device is the round-trip time (RTT) metric. The RTT metric is typically used to select an edge server for requests sent by a particular user device”) but Song-Brazeau does not explicitly teach and further based on a stability of the edge device. However, in a similar field of endeavor, Singhal teaches based on a stability of the edge device (Singhal col.6 lines 5-28 provides that “The server side 120 can push new configurations based on the calculated health of the cluster/service or the state of the cluster/service or some external events which influence these configuration setting”, wherein health can be interpreted as stability).
Motivation to combine provided with reference to claim 8.
Regarding claim 14, Song-Brazeau teaches the method of claim 1, wherein selecting the edge device is based on the RTT (Brazeau col.3 lines 62-65 provides “A typical method of measuring how close an edge server is to a user device is the round-trip time (RTT) metric. The RTT metric is typically used to select an edge server for requests sent by a particular user device”) but Song-Brazeau does not explicitly teach further based on one or more of a sensor-type of the network device, a sensor-frequency of the network device, a number of metrics output by the network device, or a cardinality of the network device. However, in a similar field of endeavor, Singhal teaches based on one or more of a sensor-type of the network device, a sensor-frequency of the network device, a number of metrics output by the network device, or a cardinality of the network device (Singhal col.4 lines 40-60 provides “The collector 240d is in communication with the log processor 240a, the config processor 240b, and the metric processor 240c. The collector 240d may aggregate their respective logs, configs, and metrics, define the frequency of collection, how much to aggregate, and send (e.g., publishes, pushes) the aggregated/raw data to the server side 120 (via the CFS 150)”).
Motivation to combine provided with reference to claim 8.
Regarding claim 15, Song-Brazeau teaches the method of claim 1, but Song-Brazeau does not explicitly teach wherein selecting the edge device comprises outputting a recommendation to setup the edge device. However, in a similar field of endeavor, Singhal teaches wherein selecting the edge device comprises outputting a recommendation to setup the edge device (Singhal col.17 lines 18-22 provides “In some embodiments, the state change includes at least one of adding a node…”).
Motivation to combine provided with reference to claim 8.
Regarding claim 16, Song-Brazeau teaches the method of claim 1, wherein the edge device is a first edge device (Song fig.1, [0035]), but Song-Brazeau does not explicitly teach the method further comprising, after selecting the edge device, selecting, by the processing circuitry, a second edge device from the plurality of edge devices based on a change in end-to-end parameters. However, in a similar field of endeavor, Singhal teaches after selecting the edge device, selecting, by the processing circuitry, a second edge device from the plurality of edge devices based on a change in end-to-end parameters (Singhal col. provides “In some embodiments, the recommendation service 350 identifies the difference in configuration between the two sets of clusters where the metric differs”).
Motivation to combine provided with reference to claim 8.
Regarding claim 17, Song-Brazeau teaches the method of claim 1, but Song-Brazeau does not explicitly teach further comprising, after selecting the edge device, periodically reevaluating, by the processing circuitry, the selection of the edge device. However, in a similar field of endeavor, Singhal teaches after selecting the edge device, periodically reevaluating, by the processing circuitry, the selection of the edge device (Singhal col.6 lines 5-28 provides that “The server side 120 can push new configurations based on the calculated health of the cluster/service or the state of the cluster/service or some external events which influence these configuration setting”, wherein health monitoring can be interpreted as periodic checking).
Motivation to combine provided with reference to claim 8.
Regarding claim 18, Song-Brazeau teaches the method of claim 1, further comprising: analyzing, by the processing circuitry, the stored indication of the processed telemetry flow data (Song [0035] provides “A telemetry data collector device 120 is configured to collect data related to the network's performance from the network edge devices 104 for storage and analysis”) but Song-Brazeau does not explicitly teach performing, by the processing circuitry, one or more actions based on the analyzing of the stored indication of the processed telemetry flow data However, in a similar field of endeavor, Singhal teaches performing, by the collector device, one or more actions based on the analyzing of the stored indication of the processed telemetry flow data (Singhal col.4 lines 10-20 provides “The server side 120 can be connected to a plurality of edge network sides such as the edge network side 110. Each edge network side sends health data of its HCl clusters 130 to the server side 120 using a telemetry platform. The health data is analyzed by the discovery service 160 at the server side 120. The health data can be analyzed for multiple purposes, one of which is to detect any false positives generated by any of the edge processing units 140. Once a false positive is detected by the discovery service 160, the cloud control plane 180 at the server side 120 automatically defines a new configuration”).
Motivation to combine provided with reference to claim 8.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure: Segal et al US 2021/0258370.
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.
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/I.R/Examiner, Art Unit 2459 /TONIA L DOLLINGER/Supervisory Patent Examiner, Art Unit 2459