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 .
Status of Claims
Claims 1-19 are pending in this Office Action.
Drawings
The drawings are objected to because Figs. 1-7, 8G. The drawings are objected to as failing to comply with 37 CFR 1.84(p)(5) because they do not include the following reference numbers/signs. Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. The figure or figure number of an amended drawing should not be labeled as “amended.” If a drawing figure is to be canceled, the appropriate figure must be removed from the replacement sheet, and where necessary, the remaining figures must be renumbered and appropriate changes made to the brief description of the several views of the drawings for consistency. Additional replacement sheets may be necessary to show the renumbering of the remaining figures. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Independent Claim(s):
Step 1: Statutory Category. Claim(s) 1 is/are directed to statutory category of subject matter. The claim(s) does/do fall within at least one of the four categories of patent eligible subject matter because the claim(s) is/are directed to either a process, machine, manufacture, or composition of matter.
Step 2A: Prong One. Judicial Exception. Claim(s) 1 is/are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. The claim(s) are directed to abstract idea of determining one or more data producers for the data collection based at least on the received data producer profiles and the one or more requirements in the first message; collecting data from the determined one or more data producers; processing the collected data based on the one or more requirements in the first message, thereby generating a dataset comprising the processed data, as explained in detail below. The claim(s) do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional computer elements, which are recited at a high level of generality, provide conventional computer functions that do not add meaningful limits to practicing the abstract idea.
The independent claim(s) recites, in part, A method performed by a data collection enablement service (DCES) comprising: receiving data producer profiles of one or more data producers, wherein the data producer profiles comprise information associated with data generation or production capability of the one or more data producers; receiving a first message indicating a request for data collection, wherein the message comprises one or more requirements associated with the data collection; determining one or more data producers for the data collection based at least on the received data producer profiles and the one or more requirements in the first message; collecting data from the determined one or more data producers; processing the collected data based on the one or more requirements in the first message, thereby generating a dataset comprising the processed data; and storing the generated dataset in a repository in communication with the DCES. These steps describe the concept of determining one or more data producers for the data collection based at least on the received data producer profiles and the one or more requirements in the first message; collecting data from the determined one or more data producers; processing the collected data based on the one or more requirements in the first message, thereby generating a dataset comprising the processed data, which corresponds to concepts identified as abstract ideas by the courts, such as Collecting information, analyzing it, and displaying certain results of the collection and analysis (Electric Power Group; West View; SAP America). All of these concepts relate “An Idea ‘Of Itself’” in which “An idea standing alone such as an uninstantiated concept, plan or scheme, as well as a mental process (thinking) that “can be performed in the human mind, or by a human using a pen and paper.” The concept described in the claim(s) is/are not meaningfully different “An Idea ‘Of Itself’” found by the courts to be abstract ideas. As such, the description in the claim(s) of determining one or more data producers for the data collection based at least on the received data producer profiles and the one or more requirements in the first message; collecting data from the determined one or more data producers; processing the collected data based on the one or more requirements in the first message, thereby generating a dataset comprising the processed data is an abstract idea. Enfish, LLC v. Microsoft Corp. 822 F.3d 1327, 1335-36 (Fed. Cir. 2016) (“[T]he first step in the Alice inquiry in this case asks whether the focus of the claims [was] on the specific asserted improvement in computer capabilities … or, instead, on a process that qualifies as an ‘abstract idea’ for which computers are invoked merely as a tool.”) No such evidence exists on this record. Unlike Enfish, where the claims were focused on a specific improvement in how the computer functioned, the claim here merely uses the computer as a tool to perform the abstract concepts, and the claims are not rooted in technology and simply employs conventional techniques used by humans for determining one or more data producers for the data collection based at least on the received data producer profiles and the one or more requirements in the first message; collecting data from the determined one or more data producers; processing the collected data based on the one or more requirements in the first message, thereby generating a dataset comprising the processed data. The claim here is not similar to claimed patent’s innovative logical model for a computer database (p. 2-3), nor does the claim here have similar specific asserted improvement in computer capabilities (p. 7) as in the Enfish patent. Rather here, the claim is directed to automating the human behavior or task. (See Enfish Memo and Enfish v. Microsoft, May 2016). In addition, simply limiting the invention to a technological environment does “not make an abstract concept any less abstract under step one.” Intellectual Ventures I, 850 F.3d at 1340. Therefore, based on the similarity of the concept described in this claim to abstract ideas identified by the courts in the claim is directed to an abstract idea. For these reasons, afford are ineligible.
Step 2A: Prong Two. Practical Application. Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea - see MPEP 2106.05(f). Adding insignificant extra-solution activity to the judicial exception - see MPEP 2106.05(g). Generally linking the use of the judicial exception to a particular technological environment or field of use – see MPEP 2106.05(h).
Step 2B: Additional Elements Significantly More Then the Judicial Exception. The independent claim(s) do/does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements when considered both individually and as an ordered combination do not amount to significantly more than the abstract idea. The claim recites the additional limitations of a “data collection enablement service (DCES)” comprising: receiving data producer profiles of one or more data producers, wherein the data producer profiles comprise information associated with data generation or production capability of the one or more data producers; receiving a first message indicating a request for data collection, wherein the message comprises one or more requirements associated with the data collection; determining one or more data producers for the data collection based at least on the received data producer profiles and the one or more requirements in the first message; collecting data from the determined one or more data producers; processing the collected data based on the one or more requirements in the first message, thereby generating a dataset comprising the processed data; and storing the generated dataset in a repository in communication with the DCES. The “data collection enablement service (DCES)” is/are recited at a high level of generality and are recited as performing generic computer functions routinely used in computer applications. Generic computer components recited as performing generic computer functions that are well-understood, routine and conventional activities amount to no more than implementing the abstract idea with a computerized system. Next, “determining one or more data producers for the data collection based at least on the received data producer profiles and the one or more requirements in the first message; collecting data from the determined one or more data producers; processing the collected data based on the one or more requirements in the first message, thereby generating a dataset comprising the processed data” is stated at a high level of generality without tying it to an algorithm that would improve the functionality of the technology and its broadest reasonable interpretation comprises only determining one or more data producers for the data collection based at least on the received data producer profiles and the one or more requirements in the first message; collecting data from the determined one or more data producers; processing the collected data based on the one or more requirements in the first message, thereby generating a dataset comprising the processed data through the use of some unspecified generic computers and interface. The use of generic computer components for determining one or more data producers for the data collection based at least on the received data producer profiles and the one or more requirements in the first message; collecting data from the determined one or more data producers; processing the collected data based on the one or more requirements in the first message, thereby generating a dataset comprising the processed data through an unspecified interface does not impose any meaningful limit on the computer implementation of the abstract idea. These independent claims include insignificant pre-solution limitation(s) [receiving data producer profiles of one or more data producers, wherein the data producer profiles comprise information associated with data generation or production capability of the one or more data producers; receiving a first message indicating a request for data collection, wherein the message comprises one or more requirements associated with the data collection;] and post-solution limitation(s) [storing the generated dataset in a repository in communication with the DCES] that do not transform the patent-ineligible concept of an abstract idea to a patent-eligible concept even if they are performed using general purpose computer, as these pre-solution limitation(s) and post-solution limitation(s) add insignificant extrasolution activity to the judicial exception. Thus, taken alone, the additional elements do not amount to significantly more than the above-identified judicial exception (the abstract idea). Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation. Additionally, adding the words ‘‘apply it’’ (or an equivalent) with the judicial exception (i.e., applying the judicial exception to the networking), or mere instructions to implement an abstract idea on a computer or generally linking the use of the judicial exception to a particular technological environment or field of use (i.e., the networking) is also found to not be enough to qualify as significantly more.
Dependent Claim(s):
Step 1: Statutory Category. Claim(s) 2-19 is/are directed to statutory category of subject matter. The claim(s) does/do fall within at least one of the four categories of patent eligible subject matter because the claim(s) is/are directed to either a process, machine, manufacture, or composition of matter.
Step 2A: Judicial Exception. Claim(s) 2-19 is/are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. The claim(s) are directed to abstract idea of determining one or more data producers for the data collection based at least on the received data producer profiles and the one or more requirements in the first message; collecting data from the determined one or more data producers; processing the collected data based on the one or more requirements in the first message, thereby generating a dataset comprising the processed data with insignificant extrasolution activities, as explained in detail below. The claim(s) do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional computer elements, which are recited at a high level of generality, provide conventional computer functions that do not add meaningful limits to practicing the abstract idea.
The dependent claim(s) recites, in part, 2. The method of claim 1, wherein the DCES provides the data collection service in a cellular/3GPP network. 3. The method of claim 1, wherein the data collection service resides in a 3GPP service layer. 4. The method of claim 1, wherein the data collection service comprises a data analytics service. 5. The method of claim 1, wherein the data producer profiles are received via a discovery procedure. 6. The method of claim 1, wherein the data producer profiles further comprise data freshness information of the data provided by a respective data producer. 7. The method of claim 1, wherein the data producer profiles further comprise a data generation/collection rate or a data collection schedule supported by a respective data producer. 8. The method of claim 1, wherein the first message comprises a data analytics request. 9. The method of claim 1, wherein the one or more requirements in the first message comprise filter criteria of data producers. 10. The method of claim 1, wherein the one or more data producers comprise a service layer entity. 11. The method of claim 1, wherein the one or more data producers comprise a 3GPP service layer entity. 12. The method of claim 1, wherein the one or more data producers comprise an edge enabler layer entity. 13. The method of claim 1, wherein the one or more data producers comprise a data repository entity. 14. The method of claim 1, further comprising: examining previously generated datasets to identify a dataset that satisfy the one or more requirements in the first message. 15. The method of claim 1, wherein the processing of data comprises correlating data from multiple data producers, wherein the data from multiple data producers is of a same type with different data granularities. 16. The method of claim 1, wherein the processing of data further comprises combining or aggregating data from multiple data producers. 17. The method of claim 1, wherein the processing of data comprises modifying or tailoring data from a previously generated dataset to satisfy the one or more requirements in the first message. 18. The method of claim 1, further comprising transmitting a second message in response to the first message, wherein the second message comprises an identifier of the repository storing the generated dataset. 19. The method of claim 1, further comprising maintaining the information associated with the generated dataset. These steps describe the concept of determining one or more data producers for the data collection based at least on the received data producer profiles and the one or more requirements in the first message; collecting data from the determined one or more data producers; processing the collected data based on the one or more requirements in the first message, thereby generating a dataset comprising the processed data with insignificant extrasolution activities, which corresponds to concepts identified as abstract ideas by the courts, such as Collecting information, analyzing it, and displaying certain results of the collection and analysis (Electric Power Group; West View; SAP America). All of these concepts relate “An Idea ‘Of Itself’” in which “An idea standing alone such as an uninstantiated concept, plan or scheme, as well as a mental process (thinking) that “can be performed in the human mind, or by a human using a pen and paper.” The concept described in the claim(s) is/are not meaningfully different “An Idea ‘Of Itself’” found by the courts to be abstract ideas. As such, the description in the claim(s) determining one or more data producers for the data collection based at least on the received data producer profiles and the one or more requirements in the first message; collecting data from the determined one or more data producers; processing the collected data based on the one or more requirements in the first message, thereby generating a dataset comprising the processed data with insignificant extrasolution activities is an abstract idea. Enfish, LLC v. Microsoft Corp. 822 F.3d 1327, 1335-36 (Fed. Cir. 2016) (“[T]he first step in the Alice inquiry in this case asks whether the focus of the claims [was] on the specific asserted improvement in computer capabilities … or, instead, on a process that qualifies as an ‘abstract idea’ for which computers are invoked merely as a tool.”) No such evidence exists on this record. Unlike Enfish, where the claims were focused on a specific improvement in how the computer functioned, the claim here merely uses the computer as a tool to perform the abstract concepts, and the claims are not rooted in technology and simply employs conventional techniques used by humans for determining one or more data producers for the data collection based at least on the received data producer profiles and the one or more requirements in the first message; collecting data from the determined one or more data producers; processing the collected data based on the one or more requirements in the first message, thereby generating a dataset comprising the processed data with insignificant extrasolution activities. The claim here is not similar to claimed patent’s innovative logical model for a computer database (p. 2-3), nor does the claim here have similar specific asserted improvement in computer capabilities (p. 7) as in the Enfish patent. Rather here, the claim is directed to automating the human behavior or task. (See Enfish Memo and Enfish v. Microsoft, May 2016). In addition, simply limiting the invention to a technological environment does “not make an abstract concept any less abstract under step one.” Intellectual Ventures I, 850 F.3d at 1340. Therefore, based on the similarity of the concept described in this claim to abstract ideas identified by the courts in the claim is directed to an abstract idea. For these reasons, afford are ineligible.
Step 2B: Additional Elements Significantly More Then the Judicial Exception. The dependent claim(s) do/does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements when considered both individually and as an ordered combination do not amount to significantly more than the abstract idea. The claim recites the additional limitations of a “data collection enablement service (DCES)” for 2. The method of claim 1, wherein the DCES provides the data collection service in a cellular/3GPP network. 3. The method of claim 1, wherein the data collection service resides in a 3GPP service layer. 4. The method of claim 1, wherein the data collection service comprises a data analytics service. 5. The method of claim 1, wherein the data producer profiles are received via a discovery procedure. 6. The method of claim 1, wherein the data producer profiles further comprise data freshness information of the data provided by a respective data producer. 7. The method of claim 1, wherein the data producer profiles further comprise a data generation/collection rate or a data collection schedule supported by a respective data producer. 8. The method of claim 1, wherein the first message comprises a data analytics request. 9. The method of claim 1, wherein the one or more requirements in the first message comprise filter criteria of data producers. 10. The method of claim 1, wherein the one or more data producers comprise a service layer entity. 11. The method of claim 1, wherein the one or more data producers comprise a 3GPP service layer entity. 12. The method of claim 1, wherein the one or more data producers comprise an edge enabler layer entity. 13. The method of claim 1, wherein the one or more data producers comprise a data repository entity. 14. The method of claim 1, further comprising: examining previously generated datasets to identify a dataset that satisfy the one or more requirements in the first message. 15. The method of claim 1, wherein the processing of data comprises correlating data from multiple data producers, wherein the data from multiple data producers is of a same type with different data granularities. 16. The method of claim 1, wherein the processing of data further comprises combining or aggregating data from multiple data producers. 17. The method of claim 1, wherein the processing of data comprises modifying or tailoring data from a previously generated dataset to satisfy the one or more requirements in the first message. 18. The method of claim 1, further comprising transmitting a second message in response to the first message, wherein the second message comprises an identifier of the repository storing the generated dataset. 19. The method of claim 1, further comprising maintaining the information associated with the generated dataset. The “data collection enablement service (DCES)” is/are recited at a high level of generality and are recited as performing generic computer functions routinely used in computer applications. Generic computer components recited as performing generic computer functions that are well-understood, routine and conventional activities amount to no more than implementing the abstract idea with a computerized system. Next, “determining one or more data producers for the data collection based at least on the received data producer profiles and the one or more requirements in the first message; collecting data from the determined one or more data producers; processing the collected data based on the one or more requirements in the first message, thereby generating a dataset comprising the processed data with insignificant extrasolution activities” is stated at a high level of generality without tying it to an algorithm that would improve the functionality of the technology and its broadest reasonable interpretation comprises only determining one or more data producers for the data collection based at least on the received data producer profiles and the one or more requirements in the first message; collecting data from the determined one or more data producers; processing the collected data based on the one or more requirements in the first message, thereby generating a dataset comprising the processed data with insignificant extrasolution activities through the use of some unspecified generic computers and interface. The use of generic computer components for determining one or more data producers for the data collection based at least on the received data producer profiles and the one or more requirements in the first message; collecting data from the determined one or more data producers; processing the collected data based on the one or more requirements in the first message, thereby generating a dataset comprising the processed data with insignificant extrasolution activities through an unspecified interface does not impose any meaningful limit on the computer implementation of the abstract idea. These dependent claims include insignificant pre-solution limitation(s) and post-solution limitation(s) that do not transform the patent-ineligible concept of an abstract idea to a patent-eligible concept even if they are performed using general purpose computer, as these pre-solution limitation(s) and post-solution limitation(s) add insignificant extrasolution activity to the judicial exception. Thus, taken alone, the additional elements do not amount to significantly more than the above-identified judicial exception (the abstract idea). Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation. Additionally, adding the words ‘‘apply it’’ (or an equivalent) with the judicial exception (i.e., applying the judicial exception to the networking), or mere instructions to implement an abstract idea on a computer or generally linking the use of the judicial exception to a particular technological environment or field of use (i.e., the networking) is also found to not be enough to qualify as significantly more.
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.
Claim(s) 1, 2, 4, 8-10, 12, 13, 15, 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over 3GPP (TR 23.700-36, V0.2.0, 2022-04, Release 18, provided in the IDS) in view of Amini (US 20100293301).
1. 3GPP TR 23.700-36 teaches:
A method performed by a data collection enablement service (DCES) comprising: – on pages 6-24 (Figure 6.4.1-1 illustrates the procedure where the edge analytics are performed based on data collected from the EDN (EAS and/or EES, edge database or networking stack at EDN side). Figure 6.4.1-1: ADAES support for edge analytics.)
receiving a first message indicating a request for data collection, wherein the message comprises one or more requirements associated with the data collection; – on pages 6-24 (Pre-conditions: 1. ADAES has discovered the APIs to access the edge services at EDN. Figure 6.4.1-1 illustrates the procedure where the edge analytics are performed based on data collected from the EDN (EAS and/or EES, edge database or networking stack at EDN side). EDN are data sources. 1. The consumer of the ADAES analytics service sends a subscription request to ADAES and provides the analytics event ID e.g. edge performance prediction or stats, the DNN / DNAI, the time validity and area of the request, the required confidence level, whether offline and/or online analytics are needed etc.)
determining one or more data producers for the data collection based at least on the received data producer profiles and the one or more requirements in the first message; – on pages 6-24 (3. The ADAES maps the analytics event ID to a list of data collection event identifiers, and optionally a list of data producer IDs. Such mapping may be preconfigured by OAM or may be configured at ADAES based on the analytics event ID.)
collecting data from the determined one or more data producers; – on pages 6-24 (6. The ADAES based on subscription, may receive offline stats/data on the edge DN load based on the analytics/data collection event ID. Such offline data can be per EDN or per DNAI or per EAS/EES load statistics and edge computational resource utilization stats for a given time and area of interest. One example can be the load in terms of number of EAS or EES connections for a given area or time window, or the average edge computational resource usage or usage ratio based on the EDN total resource availability, EDN overload/high load indication events, probability of EAS/EES unavailability due to high load, etc 8. The Data Producer send the data to the ADAES, where the data correspond to the data collection ID or the analytics event ID for which the ADAES subscribed. Such data can be provided one time or periodically or based on a threshold (e.g., load >X%).)
processing the collected data based on the one or more requirements in the first message, thereby generating a dataset comprising the processed data; and – on pages 6-24 (9. The ADAES derives edge analytics on EDN / DNAI load or per EES/EAS load, based on the analytics ID and type of request. Such analytics can be stats or prediction for a given area/time and based on the event type for a given network configuration. Such analytics can be for example a predicted load indication for the EDN or for an EES or EAS (e.g. 50% load or medium /high load), a predictive load in terms of number of EAS or EES connections for a given area or time window, or the predicted computational resource usage or usage ratio based on the EDN total resource availability, EDN overload/high load indication events, probability of EAS/EES unavailability due to high load.)
3GPP TR 23.700-36 does not explicitly teach:
receiving data producer profiles of one or more data producers, wherein the data producer profiles comprise information associated with data generation or production capability of the one or more data producers; storing the generated dataset in a repository in communication with the DCES.
However, Amini teaches:
receiving data producer profiles of one or more data producers, – in paragraphs [0008]-[0101] (Step 1102 includes receiving a data producer profile for each of a plurality of output ports within a software application to be executed on one or more processors, wherein the application comprises a plurality of components that each comprise an output port that produces a data stream and an input port that consumes a data stream)
wherein the data producer profiles comprise information associated with data generation or production capability of the one or more data producers; – in paragraphs [0008]-[0101] (Each data producer profile describes a characteristic of the data produced by the corresponding output port.)
storing the generated dataset in a repository in communication with the DCES. – in paragraphs [0008]-[0101] (The data flow manager can also act as a reliable store for the various data objects associated with dynamic application composition.)
It would have been obvious for one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify 3GPP TR 23.700-36 with Amini to include receiving data producer profiles of one or more data producers, wherein the data producer profiles comprise information associated with data generation or production capability of the one or more data producers; storing the generated dataset in a repository in communication with the DCES, as taught by 3GPP TR 23.700-36, on pages 6-24, to provide a tool for the operator to help optimizing the service offering by predicting events related to the network or slice or UE conditions.
2. The method of claim 1, – refer to the indicated claim for reference(s).
3GPP TR 23.700-36 teaches:
wherein the DCES provides the data collection service in a cellular/3GPP network. – on pages 6-24 (The aspects of the study include the investigation of application data analytics services to optimize the application service operation, edge/cloud analytics enablement, data collection aspects per identified application data analytics service, coordination of data collection from multiple sources and unified exposure of data analytics to the vertical/ASP. The study takes into consideration the work done for data analytics in 3GPP TS 23.288 [2] and 3GPP TS 28.104 [3] and other related work outside 3GPP.)
4. The method of claim 1, – refer to the indicated claim for reference(s).
3GPP TR 23.700-36 teaches:
wherein the data collection service comprises a data analytics service. – on pages 6-24 (The application data analytics enablement layer needs to be capable of receiving data from different data producers and prepare the data to be used for deriving analytics. Such data can be measurements or analytics from the 5GS (5GC, OAM), the applications of the VAL UEs, other application enablers etc.)
8. The method of claim 1, – refer to the indicated claim for reference(s).
3GPP TR 23.700-36 teaches:
wherein the first message comprises a data analytics request. – on pages 6-24 (The requesting server sends a request to the serving ADAE server to initiate data analytics, using either a one-time request or a subscription request. The request may specify the type of data analytics and the requirements/ preferences of the required analytics.)
9. The method of claim 1, – refer to the indicated claim for reference(s).
3GPP TR 23.700-36 teaches:
wherein the one or more requirements in the first message comprise filter criteria of data producers. – on pages 6-24 (The requesting server sends a request to the serving ADAE server to initiate data analytics, using either a one-time request or a subscription request. The request may specify the type of data analytics and the requirements/ preferences of the required analytics.)
10. The method of claim 1, – refer to the indicated claim for reference(s).
3GPP TR 23.700-36 teaches:
wherein the one or more data producers comprise a service layer entity. – on pages 6-24 (The collected client-side input data is sent to the ADAE server from other functions external to the service layer (e.g. NWDAF, OAM): The ADAE server may collect input data and/or request for analytics service from other analytics functions in the system, such as NWDAF or OAM. For example, the ADAE server may collect input data from 5GC via monitoring events or via interactions with NWDAF, receive input data from OAM system, receive analytics result from NWDAF by subscription, etc.)
12. The method of claim 1, – refer to the indicated claim for reference(s).
3GPP TR 23.700-36 teaches:
wherein the one or more data producers comprise an edge enabler layer entity. – on pages 6-24 (For application QoS related analytics, such data can be potentially derived by the OAM, monitoring of network QoS by 5GC, subscribing and receiving QoS and network analytics from NWDAF, performance data from the application server, QoS data from enabler layer client-server sessions, etc.)
13. The method of claim 1, – refer to the indicated claim for reference(s).
Amini teaches:
wherein the one or more data producers comprise a data repository entity. – in paragraphs [0008]-[0101] (The data flow manager can also act as a reliable store for the various data objects associated with dynamic application composition.)
15. The method of claim 1, – refer to the indicated claim for reference(s).
3GPP TR 23.700-36 teaches:
wherein the processing of data comprises correlating data from multiple data producers, wherein the data from multiple data producers is of a same type with different data granularities. – on pages 6-24 (The ADAES abstracts or correlates the data based on the analytics event and the data collection configuration. Such correlation can be filtering of data for the same metrics but with different granularities or be combining/aggregating the data of segments of the end-to-end path (end to end is between VAL client and server). The outcome is an abstracted/correlated/filtered set of data.)
16. The method of claim 1, – refer to the indicated claim for reference(s).
3GPP TR 23.700-36 teaches:
wherein the processing of data further comprises combining or aggregating data from multiple data producers. – on pages 6-24 (The ADAES abstracts or correlates the data based on the analytics event and the data collection configuration. Such correlation can be filtering of data for the same metrics but with different granularities or be combining/aggregating the data of segments of the end-to-end path (end to end is between VAL client and server). The outcome is an abstracted/correlated/filtered set of data.)
Claim(s) 3, 7, 11 is/are rejected under 35 U.S.C. 103 as being unpatentable over 3GPP (TR 23.700-36, V0.2.0, 2022-04, Release 18, provided in the IDS) in view of Amini (US 20100293301), and further in view of Li ‘746 (US 20180159746).
3. The method of claim 1, – refer to the indicated claim for reference(s).
Combination of 3GPP TR 23.700-36 and Amini does not explicitly teach:
wherein the data collection service resides in a 3GPP service layer.
However, Li ‘746 teaches:
wherein the data collection service resides in a 3GPP service layer. – in paragraphs [0016]-[0207] (The DC can collect real-time data from input sources at service layer (e.g., other existing CSFs). Whether embodied in a DSCL, GSCL, or NSCL of the ETSI M2M architecture, in a Service Capability Server (SCS) of the 3GPP MTC architecture, in a CSF or CSE of the oneM2M architecture, or in some other node of a network, an instance of the service layer may be implemented as a logical entity (e.g., software, computer-executable instructions, and the like) executing either on one or more standalone nodes in the network, including servers, computers, and other computing devices or nodes, or as part of one or more existing nodes.)
It would have been obvious for one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify 3GPP TR 23.700-36 and Amini with Li ‘746 to include wherein the data collection service resides in a 3GPP service layer, as taught by Li ‘746, in paragraphs [0001]-[0015], to enable service layer instances to provide value-added services to network applications, device applications as well as to the network nodes themselves.
7. The method of claim 1, – refer to the indicated claim for reference(s).
Combination of 3GPP TR 23.700-36 and Amini does not explicitly teach:
wherein the data producer profiles further comprise a data generation/collection rate or a data collection schedule supported by a respective data producer.
However, Li ‘746 teaches:
wherein the data producer profiles further comprise a data generation/collection rate or a data collection schedule supported by a respective data producer. – in paragraphs [0016]-[0207] (Interested Data, e.g., what type of data of the interested node that DC 904 intends to collect from the source, e.g., the session log data of CSE-1 (i.e. the interested node), which could be collected from the aforementioned session management CSF (as a source). Message Format, i.e., the format to be used for data exchange. Policy in terms of desirable data reporting frequency, duration, priority, and the minimum accepted QoS requirement if the desirable values in the initial policy cannot be satisfied.)
It would have been obvious for one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify 3GPP TR 23.700-36 and Amini with Li ‘746 to include wherein the data producer profiles further comprise a data generation/collection rate or a data collection schedule supported by a respective data producer, as taught by Li ‘746, in paragraphs [0001]-[0015], to enable service layer instances to provide value-added services to network applications, device applications as well as to the network nodes themselves.
11. The method of claim 1, – refer to the indicated claim for reference(s).
Combination of 3GPP TR 23.700-36 and Amini does not explicitly teach:
wherein the one or more data producers comprise a 3GPP service layer entity.
However, Li ‘746 teaches:
wherein the one or more data producers comprise a 3GPP service layer entity. – in paragraphs [0016]-[0207] (The DC can collect real-time data from input sources at service layer (e.g., other existing CSFs). The Third Generation Partnership Project (3GPP) has also defined an architecture for machine-type communications (MTC). In that architecture, the service layer, and the service capabilities it provides, are implemented as part of a Service Capability Server (SCS).)
It would have been obvious for one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify 3GPP TR 23.700-36 and Amini with Li ‘746 to include wherein the one or more data producers comprise a 3GPP service layer entity, as taught by Li ‘746, in paragraphs [0001]-[0015], to enable service layer instances to provide value-added services to network applications, device applications as well as to the network nodes themselves.
Claim(s) 5 is/are rejected under 35 U.S.C. 103 as being unpatentable over 3GPP (TR 23.700-36, V0.2.0, 2022-04, Release 18, provided in the IDS) in view of Amini (US 20100293301), and further in view of Li ‘388 (US 20220060388).
5. The method of claim 1, – refer to the indicated claim for reference(s).
Combination of 3GPP TR 23.700-36 and Amini does not explicitly teach:
wherein the data producer profiles are received via a discovery procedure.
However, Li ‘388 teaches:
wherein the data producer profiles are received via a discovery procedure. – in paragraphs [0005]-[0205] (The service discovery request may further carry indication information for requesting to obtain an NF profile.)
It would have been obvious for one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify 3GPP TR 23.700-36 and Amini with Li ‘388 to include wherein the data producer profiles are received via a discovery procedure, as taught by Li ‘388, in paragraphs [0002]-[0005], to resolve a problem of how a consumer of a network data analytics service finds a suitable NWDAF and requests a required data analytics result from the NWDAF when a plurality of NWDAF instances are deployed in a network.
Claim(s) 6, 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over 3GPP (TR 23.700-36, V0.2.0, 2022-04, Release 18, provided in the IDS) in view of Amini (US 20100293301), and further in view of Han (US 20230269141).
6. The method of claim 1, – refer to the indicated claim for reference(s).
Combination of 3GPP TR 23.700-36 and Amini does not explicitly teach:
wherein the data producer profiles further comprise data freshness information of the data provided by a respective data producer.
However, Han teaches:
wherein the data producer profiles further comprise data freshness information of the data provided by a respective data producer. – in paragraphs [0012]-[0174] (As a method for maintaining the freshness of analytics information, the network function may require that the network analytics information be collected within a specific time range or be generated based on valid information within the specific time range, through freshness-related information (e.g., fresh time range).)
It would have been obvious for one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify 3GPP TR 23.700-36 and Amini with Han to include wherein the data producer profiles further comprise data freshness information of the data provided by a respective data producer, as taught by Han, in paragraphs [0002]-[0011], to provide network analytics information for management of a wireless communication network and to efficiently manage radio resources and devices to reduce costs or power required for network management or to minimize interference.
14. The method of claim 1, – refer to the indicated claim for reference(s).
Combination of 3GPP TR 23.700-36 and Amini does not explicitly teach:
further comprising: examining previously generated datasets to identify a dataset that satisfy the one or more requirements in the first message.
However, Han teaches:
further comprising: examining previously generated datasets to identify a dataset that satisfy the one or more requirements in the first message. – in paragraphs [0012]-[0174] (As a method for maintaining the freshness of analytics information, the network function may require that the network analytics information be collected within a specific time range or be generated based on valid information within the specific time range, through freshness-related information (e.g., fresh time range).)
It would have been obvious for one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify 3GPP TR 23.700-36 and Amini with Han to include further comprising: examining previously generated datasets to identify a dataset that satisfy the one or more requirements in the first message, as taught by Han, in paragraphs [0002]-[0011], to provide network analytics information for management of a wireless communication network and to efficiently manage radio resources and devices to reduce costs or power required for network management or to minimize interference.
Claim(s) 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over 3GPP (TR 23.700-36, V0.2.0, 2022-04, Release 18, provided in the IDS) in view of Amini (US 20100293301), and further in view of Kim (US 20220046436).
17. The method of claim 1, – refer to the indicated claim for reference(s).
Combination of 3GPP TR 23.700-36 and Amini does not explicitly teach:
wherein the processing of data comprises modifying or tailoring data from a previously generated dataset to satisfy the one or more requirements in the first message.
However, Kim teaches:
wherein the processing of data comprises modifying or tailoring data from a previously generated dataset to satisfy the one or more requirements in the first message. – in paragraphs [0018]-[0077] (SDN 308 can use the parameter in the payload 310 to generate a modified data structure, referred to herein as a RAN file 312, which can comprise a file or other data structure having properties which meet syntax and other requirements for a particular EMS, such as EMS 233 or EMS 237 in FIG. 2.)
It would have been obvious for one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify 3GPP TR 23.700-36 and Amini with Kim to include wherein the processing of data comprises modifying or tailoring data from a previously generated dataset to satisfy the one or more requirements in the first message, as taught by Kim, in paragraphs [0002]-[0017], to automate deployment of parameters from network automation platforms to EMS and RAN devices.
Claim(s) 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over 3GPP (TR 23.700-36, V0.2.0, 2022-04, Release 18, provided in the IDS) in view of Amini (US 20100293301), and further in view of Jerichow (US 20230275810).
18. The method of claim 1, – refer to the indicated claim for reference(s).
Combination of 3GPP TR 23.700-36 and Amini does not explicitly teach:
further comprising transmitting a second message in response to the first message, wherein the second message comprises an identifier of the repository storing the generated dataset.
However, Jerichow teaches:
further comprising transmitting a second message in response to the first message, wherein the second message comprises an identifier of the repository storing the generated dataset. – in paragraphs [0036]-[0160] (The device is caused to send the at least one of the request for the access token or the request for the service by: sending the request for the service to a service communication proxy or the second network function; and the device is caused to generate the log by: generating the log comprising at least one of: an identifier of the first network function, an identifier of the second network function, an identifier of the service, a timestamp associated with the request for the service, validity of an access token obtained from a network repository function to access the service, an identifier of the network repository function, or an indication whether the service is provided by the second network function.)
It would have been obvious for one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify 3GPP TR 23.700-36 and Amini with Jerichow to include further comprising transmitting a second message in response to the first message, wherein the second message comprises an identifier of the repository storing the generated dataset, as taught by Jerichow, in paragraphs [0001]-[0035], to provide a mechanism to trace the activities of the consumer, the producer and/or the NRF.
Claim(s) 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over 3GPP (TR 23.700-36, V0.2.0, 2022-04, Release 18, provided in the IDS) in view of Amini (US 20100293301), and further in view of Di Girolamo (US 20200244741).
19. The method of claim 1, – refer to the indicated claim for reference(s).
Combination of 3GPP TR 23.700-36 and Amini does not explicitly teach:
further comprising maintaining the information associated with the generated dataset.
However, Di Girolamo teaches:
further comprising maintaining the information associated with the generated dataset. – in paragraphs [0053]-[0466] (Server maintains information that links the data together (see, for example, FIG. 9).)
It would have been obvious for one of ordinary skill in the art, before the effective filing date of the claimed invention, to modify 3GPP TR 23.700-36 and Amini with Di Girolamo to include further comprising maintaining the information associated with the generated dataset, as taught by Di Girolamo, in paragraphs [0002]-[0053], to store their data, have their data readily available to Data Consumers, and provide value added services that operate on the stored data.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MUHAMMAD RAZA whose telephone number is (571)272-7734. The examiner can normally be reached Monday-Friday, 7:00 A.M.-5:00 P.M..
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/MUHAMMAD RAZA/Primary Examiner, Art Unit 2449