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 .
Response to Arguments
Applicant's arguments filed on 012/30/2025 with respect to claims 1-5, 8-12 and 15-19 being rejected under 35 U.S.C. 102(a) as being anticipated over Van Wie (US 20140136726) have been fully considered but they are deemed persuasive. However, in order to provide further clarification in response to applicant’s argument regarding the possible errors in the previous rejection.
Point A:
Applicant argues that the Examiner’s rejection does not meet a prima facie case of unpatentability under 35 USC 102 as the Examiner admits the reference does not teach all elements. Applicant further states that a reference must disclose all limitations in the four corners of the document and those limitations must be arranged or combined in the same way as recited in Appellant's claim. The Examiner admits this standard is not met when in the "response to arguments" section on page 4 of the Final Office Action, the Examiner states that: While [Van] Wie does not explicitly teach a "simplified object model", this term is not specific to a particular function in the present invention, and instead is well-known in the art and refers to a basic collection and representation of objects (e.g., the communicants for instance), their attributes, and relationships, and one of ordinary skill in the art would find it obvious that the interaction database as recited in Van Wie performs the same functions and comprises the same attributes as the claimed "simplified object model", and would be an obvious and reasonable derivative of the claimed "simplified object model". Office Action, p. 4. (Emphasis Added) The Examiner explicitly admits that the rejection under 35 U.S.C. 102 is improper by admitting that the reference does not disclose a "simplified object model." The Examiner attempts to overcome this by arguing principles of obviousness. Obviousness is governed by a different statute --- 35 USC §103. As such, because, by the Examiner's own admission, the Van Wie reference fails to disclose all of the recitations claimed, the 102 rejection is improper and should be withdrawn.
As to Point A:
The current examiner agrees with applicant’s arguments that as to the fact the rejection was a 35 USC 102 rejection and not a 35 USC 103. The previous examiner’s assessment was incorrect. However, it is the position of the current examiner that the former examiner’s analysis of obviousness would have been correct if it were a 35 USC 103 rejection. The current examiner will provide a reference to make a 35 USC 103 rejection that shows obviousness of this particular feature.
Point B:
Applicant argues that Wie is an Interaction Database and not a simplified object model.
As to Point B:
It is the examiner’s position that the interaction database and the simplified object model complement each other.
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.
Claims 1, 2, 4-9, 11-16, and 18-20 are rejected under 35 U.S.C. 103 as being unpatentable over Wie et al. (Wie), US PGPUB 20140136726 in view of Agarwal et al. (Agarwal), US Patent No. 12,346,708 B1 in view of Telang et al. (Telang), US. 12,394,121 B1 in further view of Musku et al., (Musku), US PGPUB 20200162371.
Regarding claim 1, Wie discloses the invention substantially as claimed. Wie discloses a method for delivery of real-time telemetry data of a communication session, the communication session including a three-dimensional graphical representation (see Fig. 5A virtual area 86 and [0128]), the method comprising:
generating the three-dimensional graphical representation for display to participants of the communication session using data streamed from participants of the communication session (see [0128]: While the communicant interacts in the virtual area 86, the HUD 84 provides the communicant with independent control over his or her desired visualization … A communicant then can change his or her visualization schema and enter into a more immersive three-dimensional rendering of the virtual area 86. This is accomplished by changing the setting of the progressive immersion slider 88 in the HUD 84 from “Desktop” to “3D”. Once in the 3D visualization mode, the communicant's desktop displays a 3D rendition of the virtual are 86 (as shown in FIG. 5A). The communicants (represented by sprites 90, 92, 94 in the Desktop mode) now take the form of three- dimensional avatars 96, 98, 100, as shown in FIG. 5A (i.e. interpreted as generating the three-dimensional graphical representation for display to participants using data streamed from participants), the three-dimensional graphical representation updated based upon events of the communication session concurrently as the events occur (see [0144]: Should any communicant exit a virtual area or enter a virtual area, the presence indicators (i.e., the sprites shown by circles, which typically are associated with names or other identifiers) in that virtual area will automatically be updated in realtime. This feature demonstrates the ability of a virtual area designer to put application-specific realtime data into a place tile (i.e. the 3-D representation is updated based upon events as they occur); see also [0152]: The communicant can control the presented view of the virtual area by transmitting commands from a HID device (e.g., a computer mouse) to the realtime kernel 20, which transmits view control commands to the So3D engine. The So3D engine updates the view of the virtual area in accordance with the view control commands. The So3D engine also updates the graphic representation of the virtual area on the display monitor in accordance with updated object position information that is received from the area service 26 via the realtime kernel 20);
generating an object model of the communication session, the object model comprising objects representing data about elements of the three- dimensional graphical representation and the communication session and object links between objects representing a hierarchical relationship between the elements of the three-dimensional graphical representation, objects in the object model created or destroyed (the examiner takes Official Notice regarding this feature of the claim limitation) responsive to their appearance or disappearance in the three- dimensional graphical representation as it is updated based upon the events of the communication session (see [0098]: For every interaction between communicants, one or more services in the virtual area communication environment 10 (e.g., the area service 26) transmit interaction data to the interaction service. In response, the interaction service generates one or more respective interaction records (i.e. the object model) in the relationship database. Each interaction record describes the context of an interaction. For example, in some embodiments, an interaction record contains an identifier for each of the communicants, an identifier for the place of interaction (e.g., a virtual area instance), a description of the hierarchy of the interaction place (e.g., a description of how the interaction room relates to a larger area), start and end times of the interaction, and a list of all files and other streams shared during the interaction (i.e. the object model comprises object representing data about elements of the 3-dimensional representation and the communication session). Thus, for each realtime interaction, the interaction service tracks when it occurred, where it occurred, and what happens during the interaction in terms of communicants involved (e.g., entering and exiting), objects that are activated/deactivated, and the files that were shared (i.e. object links between objects); see also [0144] and [0157]) (Furthermore it is extremely well known in the art for objects to be deleted as further shown by the cited prior art in the rejection as well as Bugenhagen et al., US PG PUB 20180219959 A1, Figure 5); (see also Wie, paras. 0090-0097 (objects enter/leave the virtual area and are tracked in global state; paras, 0157-0158, updating objects register; paras. 0366-0371, failure/recovery and session state changes (SODA)
receiving a subscription from the monitoring computing device, the subscription comprising a selection of an object in the object model, a query against the object model and subscribing to telemetry data of the communication session matching the query and the object (see [0195]: The realtime kernel 20 subscribes to state data describing the current state of the virtual area instance (FIG. 9, block 164). In response to the subscription request, the area service 26 publishes the state data to a channel on the link between the realtime kernel 20 and the area service 26; see also [0260-261]: The realtime kernel 260 subscribes only to the data the client network node needs (i.e. subscribing by selecting an object in the simplified object model). To subscribe, the realtime kernel 260 creates a STRAW channel to the desired server … The realtime kernel 260 then sends subscribe messages for the desired data streams. Any changes to area service data for the subscribed channels are sent as SODA definition records to all client network nodes that have subscribed to those channels; see also [0271]: In some embodiments, the area/zone manager 264 additionally subscribes to relationship data, which the area/zone manager 264 uses to control avatar orientation/movement/pose within the virtual area via social processors 277 (see FIG. 15). In this process, the area/zone manager 264 sets parameter values of the social processors 277 based on the positions of the avatars in the virtual area and the relationship data. In this way, relationships can be indicated by changing the positions and orientations of an avatar's head when a communicant speaks (e.g., turning the avatar to face another avatar as it enters a zone of the virtual area, or orienting the avatar for optimal viewing of a view screen when a media zone of the virtual area is entered));
identifying a stream of telemetry data (see [0198]: FIG. 10 shows an embodiment of a method that is implemented by the realtime kernel 20 in response to a realtime kernel API call requesting entry into a virtual area (i.e. identify telemetry data); see also [0210]: The realtime kernel 20 monitors the processing of the at least one realtime data stream (FIG. 13, block 234). In some embodiments, the realtime kernel 20 monitors one or more of the following parameters: the rate at which the resultant data stream is produced; utilization of at least one processor of the local network node; and bandwidth utilization by at least one networking resource of the local network node (i.e. streams of telemetry data));
determining that data within the stream of telemetry data matches the telemetry subscription (see [199]: In response, the area service 26 determines if the users capabilities satisfy the capability requirements that are associated with the virtual area instance. If the users capabilities meet the capability requirements, the area service 26 returns configuration data to the realtime kernel 20. The configuration data typically includes a definition of the virtual area instance, a register of the objects currently in the virtual area instance, and a set of realtime data stream sources and sinks that are associated with objects in the virtual area in accordance with the specification of the virtual area instance (i.e. determining that the telemetry data matches the telemetry subscription)); and
causing the data within the stream of telemetry data to be transmitted to the monitoring computing device responsive to determining that data within the stream of telemetry data matches the query (see [0200]: The realtime kernel 20 initiates transfer of at least one realtime data stream over at least one network connection with at least one realtime data stream source respectively associated with at least one object in the virtual area (FIG. 10, block 170) … The realtime kernel 20 then initiates transfer of at least one realtime data stream over at least one network connection with at least one of the ascertained network nodes; see also [0275]: In this process, the STRAW service 268 sends to the remote network node records defining the local publish channels and a record of each of the local subscribe channels having an identifier that matches an identifier of one of the remote publish channels). However, Wie does not explicitly discloses generating a simplified object model, the simplified object model created from the object model and a set of filters, causing the simplified object model to be displayed to a monitoring computing device, receiving a telemetry subscription from the monitoring computing device, the telemetry subscription comprising a selection of an object in the simplified object model, a query against the object model and subscribing to telemetry data of the communication session matching the query and the object.
But, in the same field of endeavor Agarwal discloses generating a simplified object model (see Agarwal, paras. 31, 46, 54, 58, 70, 71, FIGS. 3A, 4A, 4B, 3B, 6 provide an example of the relationship between a GUI and its corresponding DOM. In particular, FIG. 3A provides a representation 300 of a simple GUI rendered from an initial document provided by an e-commerce application, such as a front-end service executing on a webserver. For comparison, FIG. 3B provides a simplified object model 350 corresponding to the representation 300 generated from the initial document provided by the application. As illustrated in the representation 300, the dashed lines represent logical or structural elements defined in the document, but that are not visible upon rendering the document as a webpage, including a root element 304 and a body element 308. The spans displayed in the waterfall visualization 640 may be filtered based on one or more filter criteria. For example, GUI 600 may include icons associated with various types of spans or events, including all events 650, document load events 651, script error events 652, network error events 653, server request events 654, backend/resource events 655, user action events 656, and custom events 657. In response to a selection of a particular icon, the spans displayed in the waterfall visualization 640 may be filtered to remove spans not associated with the selected icon. Additionally, or alternatively, the spans currently displayed in the waterfall visualization 640 may be scoped to a particular region or portion of the user session. Agarwal further teaches, the span collector 115 may further be configured to process spans collected from the application 110 prior to export and/or storage. For example, the span collector 115 may modify one or more attributes or pieces of information comprising a span, place spans, metrics, and logs into batches, filter spans based on one or more metrics, apply one or more tags to the spans, and the like. Also, object models can be modified) and causing the simplified object model to be displayed to a monitoring computing device (see Agarwal, Col. 20, 26-35, Figs.3A, 3B, 10, Col. 21, 54-67, At block 910, an object model for the application GUI is accessed. As further described above, the object model may be an object-oriented representation of the structure and content of the document used by the user agent to display the application GUI, such as a DOM. After the object model has been generated by the user agent using the document, other components of the application, such as scripts, endpoints, and/or APIs executed by the user agent, may modify an updated copy of the object model.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of the Wie’s invention to include the teachings taught by Agarwal specifically providing a method wherein the query selects all objects of the object model that have a value of a telemetry parameter that satisfies a threshold condition in order to arrive at the claimed invention. The motivation for such combination would have been to provide methods for performing route optimization using real time traffic feedback and correlating the trends or patterns to the current conditions of the network determined by the streaming telemetry, thereby improving network performance. However, Wie-Agarwal does not explicitly disclose the simplified object model created from the object model.
But in the same field of endeavor, Telang discloses simplified model created from the object model and a set of filters (see Telang, Figs. 2-6, Col. 11, lines 23-55, As described earlier, the edge gateways 162a-162n are configured to capture the data (e.g. the telemetry data and the semantic model) from various assets in the facility. Further, the edge gateways 162a-162n are configured to provide at least one of: the data and a COM determined from the data, to the cloud 105. In some example embodiments, the cloud 105 can further process the data and/or the COM to create an extended object model (EOM) (simplified model created from the object model). An extended object model is representative of a data model which unifies several data ontologies, data relationships, and data hierarchies into a unified format. The EOM can be utilized for further data analytics and reporting one or more KPIs, contextual insights, performance, and operational insights of a facility. In some embodiments, the COM and/or the EOM may generate and/or suggest filter tags for the data. In other words, the COM and/or the EOM may ingest telemetry data and, using contextual information about the data (e.g. the semantic model), may assign filter tags to the data. The filter tags may accordingly be used to filter the potentially large amounts of data to desired granularity. In some embodiments, the COM and/or the EOM may assign geographic filter tags, filter tags identifying specific facilities, asset type filter tags, attribute filter tags, time series filter tags, or any other type of filter tags useful for sorting the data. For example, for a data element indicative of energy consumed by an individual boiler in a warehouse in Bangalore, the COM and/or the EOM may apply filter tags indicative of one or more of: the boiler, the system with which the boiler is associated, the warehouse, Bangalore, energy consumption, the sensor or meter used to detect the energy consumption, and the like. The COM and/or the EOM may assign filter tags to each data element ingested and/or maintained therein).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to have incorporated Telang’s of a system and method for constructing an object model that delineates spatial relationships between objects within a space and a system and method for presenting the object model via a graphical user interface with the system of Wie, Agarwal and Telang for the purpose of overcome difficulties in locating a target object for diagnostics.
However, Wie, Agarwal, and Telang does not explicitly discloses receiving a telemetry subscription from the monitoring computing device, the telemetry subscription comprising a selection of an object in the simplified object model.
But in the same field of endeavor, Musku discloses receiving a telemetry subscription from the monitoring computing device, the telemetry subscription comprising a selection of an object in the simplified object model a query against the object model and subscribing to telemetry data of the communication session matching the query and the object. (see Musku, teaches the selection of a target object and displaying a corresponding portion of the hierarchy, paras. 0098-0103).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to have incorporated Musku’s network management system that can subscribe to receive streaming telemetry data for traffic associated with one or more managed network entities (see Musku’s para. 0026) with Wie-Agarwal, and Telang for the purpose of providing an optimized route from a set of possible routes based upon metrics and further by providing a method wherein the query selects all objects of the object model that have a value of a telemetry parameter that satisfies a threshold condition in order to arrive at the claimed invention. The motivation for such combination would have been to provide methods for performing route optimization using real time traffic feedback and correlating the trends or patterns to the current conditions of the network determined by the streaming telemetry, thereby improving network performance.
Regarding claim 2, Wie-Agarwal, Telang and Musku is applied as disclosed in claim 1 examined above. Furthermore, Wie teaches a method wherein the query selects an object from the object model, the object comprises one of: a texture, a mesh, a virtual object, a set of vertices, an animation, a lighting node, a pencil, a whiteboard, an object depicted on a whiteboard, a model of a user, a canvas, an eraser, documents, graphs, or shared content (see [0070]: In the context of a virtual area, an “object” is any type of discrete element in a virtual area that may be usefully treated separately from the geometry of the virtual area. Exemplary objects include doors, portals, windows, view screens, and speakerphone. An object typically has attributes or properties that are separate and distinct from the attributes and properties of the virtual area. An “avatar” is an object that represents a communicant in a virtual area (i.e. a model of a user)).
Regarding claim 4, Wie-Agarwal, Telang and Musku discloses the limitations of claim 1 as examined above. Furthermore, Wie teaches a method wherein the telemetry data comprises one or more of: jitter measurements, rendering performance, packet loss, or buffer size (see at least [0450]: measuring the rendering latency (i.e. rendering performance)).
Regarding claim 5, Wie-Agarwal, Telang and Musku are applied as disclosed in claim 1 examined above. The Wie reference further teaches a method wherein the query selects all objects of the object model within a prespecified distance from a particular object of the object model within the three-dimensional graphical representation (see Wie, [0107]: proximity policy rule).
Regarding claim 6, Wie-Agarwal, Telang and Musku discloses wherein the query selects all objects of the object model that have a value of a telemetry parameter that satisfies a threshold condition (see Musku, [0134]: In other embodiments, one or more policies can be defined for selecting the managed network entities for route optimization. For example, the network management system can include policy functions (e.g., the policy functions 208) for selecting the managed network entities for the route optimization based on access control policies (e.g., via the access control policies tool 334), IP addresses (e.g., via the IP-based access control policies tool 336), QoS policies (e.g., via the application policies tool 338), and so forth; see also [0147]: In some embodiments, these processes may be preceded by a triggering event, such as the network management system detecting that one or more current metrics (e.g., packet loss, bit rate, throughput, delay, availability, jitter, etc.) for the traffic fail to satisfy various thresholds. As another example, the network management system may predict that network performance will fall below the various thresholds based on trends or patterns discovered by an analytics or assurance engine processing historical traffic data and correlating the trends or patterns to the current conditions of the network determined by the streaming telemetry).
Regarding claim 7, Wie-Agarwal, Telang and Musku discloses the limitations of claim 1 as examined above. The Wie reference teaches a method comprising generating an object model of the communication session, the object model comprising objects representing data about elements of the three-dimensional graphical representation and the communication session and object links between the elements of the three-dimensional graphical representation. However, the Wie-Agarwal references does not explicitly teach a method wherein the object model is generated from log file data.
In the same field of endeavor, Musku teaches a method in accordance with the present invention, the method wherein the object model is generated from log file data (see [0137] Model-driven telemetry can provide a mechanism to stream data from a model-driven telemetry-capable device to a destination. In some embodiments, telemetry can use a subscription model to identify information sources and destinations. Model-driven telemetry can replace the need for the periodic polling of network devices; instead, a continuous request for information to be delivered to a subscriber can be established upon the network device. Then, either periodically, or as objects change, a subscribed set of data model objects (e.g., Yet Another Next Generation (YANG) data models) can be streamed to that subscriber).
Claim 8 list all the same elements of claim 1, but in computing device form rather than method form. Therefore, the supporting rationale of the rejection to claim 1 applies equally as well to claim 8. Furthermore, regarding the claim limitations of a processor (para. 0053); a memory (paras. 0015, 0053), the memory storing instructions, which when executed by the processor.
Regarding claims 9 and 16, they teach the same limitations as claim 2 examined above. Therefore, the same rationale of rejection is applied.
Regarding claims 11 and 18, they teach the same limitations as claim 4 examined above. Therefore, the same rationale of rejection is applied.
Regarding claims 12 and 19, they teach the same limitations as claim 5 examined above. Therefore, the same rationale of rejection is applied.
Regarding claims 13 and 20, they teach the same limitations as claim 6 examined above. Therefore, the same rationale of rejection is applied.
Regarding claim 14, it teaches the same limitations as claim 7 examined above. Therefore, the same rationale of rejection is applied.
Claim 15 list all the same elements of claim 1, but in non-transitory machine-readable storage medium form rather than method form. Therefore, the supporting rationale of the rejection to claim 1 applies equally as well to claim 15. Furthermore, regarding the claim limitation of a non-transitory computer readable storage medium (see Van Wie, paras.0015 and 0057).
Citation of Prior Art
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US Patent No. 12469226 B1: Fig. 6, update the 3D representation of the objects based on receiving additional object content.
US PG PUB 20200202634 A1: Fig. 10, steps 1002 thru 1014, Fig. 11, The system comprises data processing units, and a computer-readable medium that has encoded computer-executable instructions to cause the one or more data processing units to receive input data which indicates a position for a content object to be displayed in association with an object rendered on computing devices of a communication session.
Conclusion
THIS ACTION IS MADE FINAL. 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 WILLIAM C VAUGHN JR whose telephone number is (571)272-3922. The examiner can normally be reached Monday-Friday, 8:30am-5:00pm.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, William C Vaughn, Jr can be reached at 571-272-3922. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/WILLIAM C VAUGHN JR/Supervisory Patent Examiner, Art Unit 2481
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