DETAILED ACTION
Notice of Pre-AIA or AIA Status
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Continued Examination Under 37 CFR 1.114
2. A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 01/23/2026 has been entered.
Status of Claims
3. Claims 1-20 are pending wherein claims 1, 16, and 19 are in independent form.
4. Claims 1, 3, 16, and 19 have been amended.
Response to Arguments
5. Applicant's arguments filed on 01/23/2026 have been fully considered but they are not persuasive. The reasons set forth below.
6. On page 9 of the remarks, applicant argues, “3GPP does not disclose "receive, from an analytics consumer, a subscription request for load analytics for an edge node, the subscription request comprising an analytics consumer identifier, an analytics event identifier, and filter information for an analytics event" as recited in amended claim 1. Thus, 3GPP does not anticipate, teach or suggest all features of amended claim 1.”
In response, examiner respectfully disagrees because:
3GPP discloses that a consumer (i.e., a requesting server) sends a data analytics request to ADAES and the data analytics request might be a subscription request (Pg. 24, step 1, “The requesting server sends a data analytics 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 as defined in Table 6.3.1.3-2”). The subscription request includes requester ID, Information filter along with other information (Table 6.3.1.3-2, Pg. 29).Therefore, 3GPP teaches that the subscription request comprises an analytics consumer identifier (requester ID), an analytics event identifier (analytics event ID included in the subscription request), and filter information for an analytics event (information filter, Table 6.3.1.3-2, Pg. 29) (Pg. 24, step 1, Pg. 29, Table 6.3.1.3-2, Fig. 6.4.1-1, Step 1, Pg. 32).
Claim Rejections - 35 USC § 102
7. The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
8. Claims 19-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by 3GPP (3GPP TR 23.700-36, Study on Application Data Analytics Enablement Service, hereinafter referred to as 3GPP).
Re claim 19, 3GPP teaches computer-implemented method for providing edge load analytics (Pg. 31, Section 6.4-Support for edge load analytics), the computer- implemented method comprising:
(i) receiving, from an analytics consumer, a subscription request for load analytics for an edge node by an application data analytics enablement server (ADAES) (analytics subscription request received from consumer, step 1, Fig. 6.4.1-1), the subscription request comprising an analytics consumer identifier (requester ID), an analytics event identifier (analytics event ID included in the subscription request), and filter information for an analytics event (information filter, Table 6.3.1.3-2, Pg. 29; Step 1, Pg. 32 –"the time validity and area of the request, the required confidence level, whether offline and/or online analytics are needed”) (Pg. 24, step 1, Pg. 29, Table 6.3.1.3-2, Fig. 6.4.1-1, Step 1, Pg. 32). (Fig. 6.4.1-1, Step 1, Pg. 32);
(ii) determining, by the ADAES, a mapping of the analytics event identifier to at least one of a list of data collection event identifiers and a list of data producer identifiers (determining a mapping of analytics ID to data collection IDs, or data producer IDs) (Fig. 6.4.1-1, Step 3, Pg. 32);
(iii) transmitting, by the ADAES, a data collection subscription request to the data producers identified by the list of data producer identifiers (data collection subscription request, Step 4, Fig. 6.4.1-1), wherein the data collection subscription request comprises data collection requirements (requirement for data collection) and at least one of the analytics event identifier, the list of data producer identifiers, or the respective data collection event identifier (data collection subscription request includes Data Collection event ID and/or the analytics event ID) (Fig. 6.4.1-1, Step 4, Pg. 32-33), wherein the data collection requirements comprises a reporting frequency (Pg. 21, step 4a, Pg. 36, line 1-3, The ADAES sends a subscription request to the ADAEC #1 with the analytics event ID and the configuration of the reporting required (e.g., periodic, based on threshold or event). Such request also includes the application QoS attributes to be analyzed (latency, jitter, PER,..)”) and an abstraction level of the data (time validity, area of request, required confidence level, Step 4, Pg. 32-33);
(iv) receiving data, by the ADAES, from the data producers, the received data corresponding to the at least one of the analytics event identifier and the respective data collection event identifier (receiving data based on the based on the analytics/data collection event ID) (Fig. 6.4.1-1, steps 6-8, Pg. 32-33), the reporting frequency indicates whether the data is received once or periodically based on a threshold (Pg. 19, step 8b, “The ADAES may receive also data (periodically or if a threshold is reached based on configuration) from the application of the UE within the ongoing session (via ADAEC). Such data can be about the RTT, average/peak throughput, jitter, QoE measurements (MOS, stalling events, stalling ratios, etc), QoS profile load, VAL server load, etc.”; Pg. 33, step 8, “The Data Producer send the data to the ADAES (based on step 7 measurements or analytics), 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%)”. Pg. 36, line 1-3, “The ADAES sends a subscription request to the ADAEC #1 with the analytics event ID and the configuration of the reporting required (e.g., periodic, based on threshold or event);
(v) deriving edge load analytics for the edge node from the received data corresponding to the subscription request, wherein the edge load analytics indicate at least one of statistics and a prediction of the load for the edge node (deriving edge analytics including stats or prediction based on the subscription request) (Fig. 6.4.1-1, step 9, Pg. 32-33); and
(vi) transmitting the derived edge load analytics to the analytics consumer (sending edge analytics to the consumer) (Fig. 6.4.1-1, step 10, Pg. 32-33).
Re claim 20, 3GPP teaches to generate a trigger event indicating a predicted overload (predicting EDN high load condition) and an action, wherein the action comprises at least one of migration of the edge node to a different edge data network (EDN), or a pro-active edge application server (EAS) reselection for a target user equipment (UE) or a group of UEs (triggering an EAS relocation to a different platform) (Section 6.4.1-Solution description, Pg. 31, Line 1-9, Fig. 6.4.1-1, steps 9-10, Pg. 32-33, Pg. 34, Line 9-10).
Claim Rejections - 35 USC § 103
9. 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.
10. Claims 1-18 are rejected under 35 U.S.C. 103 as being unpatentable over 3GPP (3GPP TR 23.700-36, Study on Application Data Analytics Enablement Service, hereinafter referred to as 3GPP) in view of Liu et al (WO 2023220030 A1, hereinafter referred to as Liu).
Re claim 1, 3GPP teaches an apparatus (ADAES, Fig. 6.4.1-1, Pg. 32) to:
(i) receive, from an analytics consumer, a subscription request for load analytics for an edge node (analytics subscription request received from consumer, step 1, Fig. 6.4.1-1), the subscription request comprising an analytics consumer identifier (requester ID), an analytics event identifier (analytics event ID included in the subscription request), and filter information for an analytics event (information filter, Table 6.3.1.3-2, Pg. 29; Step 1, Pg. 32 –"the time validity and area of the request, the required confidence level, whether offline and/or online analytics are needed”) (Pg. 24, step 1, Pg. 29, Table 6.3.1.3-2, Fig. 6.4.1-1, Step 1, Pg. 32). (Fig. 6.4.1-1, Step 1, Pg. 32);
(ii) determine a mapping of the analytics event identifier to at least one of a list of data collection event identifiers or a list of data producer identifiers (determining a mapping of analytics ID to data collection IDs, and data producer IDs) (Fig. 6.4.1-1, Step 3, Pg. 32);
(iii) transmit a data collection subscription request to the data producers identified by the list of data producer identifiers (data collection subscription request, Step 4, Fig. 6.4.1-1), wherein the data collection subscription request comprises data collection requirements (requirement for data collection) and at least one of the analytics event identifier, the list of data producer identifiers, or the respective data collection event identifier (data collection subscription request includes Data Collection event ID and/or the analytics event ID) (Fig. 6.4.1-1, Step 4, Pg. 32-33); wherein the data collection requirements comprises a reporting frequency (Pg. 21, step 4a, Pg. 36, line 1-3, The ADAES sends a subscription request to the ADAEC #1 with the analytics event ID and the configuration of the reporting required (e.g., periodic, based on threshold or event). Such request also includes the application QoS attributes to be analyzed (latency, jitter, PER,..)”) and an abstraction level of the data (time validity, area of request, required confidence level, Step 4, Pg. 32-33);
(iv) receive data from the data producers, the received data corresponding to the analytics event identifier or the respective data collection event identifier (receiving data based on the based on the analytics/data collection event ID) (Fig. 6.4.1-1, steps 6-8, Pg. 32-33), the reporting frequency indicates whether the data is received once or periodically based on a threshold (Pg. 19, step 8b, “The ADAES may receive also data (periodically or if a threshold is reached based on configuration) from the application of the UE within the ongoing session (via ADAEC). Such data can be about the RTT, average/peak throughput, jitter, QoE measurements (MOS, stalling events, stalling ratios, etc), QoS profile load, VAL server load, etc.”; Pg. 33, step 8, “The Data Producer send the data to the ADAES (based on step 7 measurements or analytics), 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%)”. Pg. 36, line 1-3, “The ADAES sends a subscription request to the ADAEC #1 with the analytics event ID and the configuration of the reporting required (e.g., periodic, based on threshold or event);
(v) derive edge load analytics for the edge node from the received data corresponding to the subscription request, wherein the edge load analytics indicate at least one of statistics and a prediction of the load for the edge node (deriving edge analytics including stats or prediction based on the subscription request) (Fig. 6.4.1-1, step 9, Pg. 32-33); and
(vi) transmit the derived edge load analytics to the analytics consumer (sending edge analytics to the consumer) (Fig. 6.4.1-1, step 10, Pg. 32-33).
3GPP does not explicitly disclose that the apparatus comprises at least one memory; and at least one processor coupled with the at least one memory.
Liu teaches that the apparatus comprises at least one memory (RAM, ROM); and at least one processor (processor) coupled with the at least one memory (Fig. 8F, Par 0006, Par 01540156).
It would have been obvious to one of ordinary skill in the art before the filing date of the invention to modify the apparatus disclosed by 3GPP by including at least one memory; and at least one processor coupled with the at least one memory, as taught by Liu for the purpose of optimizing the efficiency of the data collection process along with managing and coordinating the data collection requests, as taught by Liu (Par 0005).
Re claim 2, 3GPP teaches that the edge node is an edge data network (EDN), an edge enabler server (EES), or an edge application server (EAS) (EDN, EES, EAS) (Fig. 6.4.1-1, Steps 1-10, Pg. 32-33, Section 6.4.2 - Corresponding Analytics API, Pg. 33-34).
Re claim 3, 3GPP teaches that the subscription request further comprises at least one of: an analytics type of the analytics event, a destination EAS identifier identifying a destination EAS associated with the subscription request, a destination EES identifier identifying a destination EES associated with the subscription request, data network name (DNN) information associated with the subscription request, data network access identifier (DNAI) information associated with the subscription request, a preferred confidence level for a prediction, a geographical area associated with the subscription request, a service area associated with the subscription request , or a time validity indication of the subscription request (Fig. 6.4.1-1, Pg. 32, Step 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.”).
Re claim 4, 3GPP teaches that the analytics type of the analytics event indicates whether the analytics event concerns a prediction or a statistics (Fig. 6.4.1-1, Pg. 32, Step 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.”) (Fig. 6.4.1-1, steps 9-10, Pg. 32-33, Pg. 34, Line 9-10).
Re claim 5, 3GPP teaches to transmit a subscription response as an acknowledgement to the analytics consumer (Subscription response, step 2, Fig. 6.4.1-1, Pg. 32).
Re claim 6, 3GPP teaches that the mapping is preconfigured by an operation administration and maintenance (OAM) function (Fig. 6.4.1-1, step 3, Pg. 32 “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”).
Re claim 7, 3GPP teaches that the data collection subscription request further comprises at least one of: an apparatus server identifier, a destination EAS identifier identifying a destination EAS associated with the subscription request, a destination EES identifier identifying a destination EES associated with the subscription request, a data network name (DNN) information associated with the subscription request, a data network access identifier (DNAI) information associated with the subscription request, a preferred confidence level for prediction, a geographical area associated with the subscription request, a service area associated with the subscription request, or a time validity indication of the subscription request (Fig. 6.4.1-1, step 4, Pg. 32 - “The ADAES sends a subscription request to the Data Producers (EASs onboarded to EDN, EESs, SEALDD server, RNIS, N6 endpoint at EDN, NWDAF, OAM) with the respective Data Collection Event ID and the requirement for data collection. This message includes the Data Collection event ID and/or the analytics event ID, the ADAES ID, the time validity and area of the request, the required confidence level etc.”).
Re claim 8, 3GPP teaches that the data collection requirements include at least one of: a data format or an accuracy level of the data (“the required confidence level”) (Fig. 6.4.1-1, step 4, Pg. 32 - “The ADAES sends a subscription request to the Data Producers (EASs onboarded to EDN, EESs, SEALDD server, RNIS, N6 endpoint at EDN, NWDAF, OAM) with the respective Data Collection Event ID and the requirement for data collection. This message includes the Data Collection event ID and/or the analytics event ID, the ADAES ID, the time validity and area of the request, the required confidence level etc.”).
Re claim 9, 3GPP teaches to receive a data collection subscription response from the data producers, the data collection subscription response being a positive or negative acknowledgement (Fig. 6.4.1-1, step 5, Pg. 32-33-- “The Data Producer(s) sends a subscription response as an ACK to the ADAES”).
Re claim 10, 3GPP teaches to receive offline data from an analytical data repository (receiving offline data) (Fig. 6.4.1-1, step 6, Pg. 32-33).
Re claim 11, 3GPP teaches that the received data comprises at least one of: load Statistics in terms of numbers of EAS or EES connections for a given area or time window, statistics regarding an average edge computational resource usage, a resource ratio based on a total resource availability of an EDN, an EDN overload indication, a high load indication event, and a probability of EAS and EES unavailability due to high load (Section 6.4.1-Solution description, Pg. 31, Line 1-9, Fig. 6.4.1-1, steps 6-10, Pg. 32-33, Section 6.4.2 - Corresponding Analytics API, Pg. 33-34).
Re claim 12, 3GPP teaches that the received data includes a given time or area of interest (data analytics for a given area/time) (Fig. 6.4.1-1, steps 6-10, Pg. 32-33, Section 6.4.2 - Corresponding Analytics API, Pg. 33-34).
Re claim 13, 3GPP teaches to receive real-time collected data from the data producers (Fig. 6.4.1-1, steps 7-8, Pg. 32-33).
Re claim 14, 3GPP teaches that the real-time collected data comprises at least one of: load statistics in terms of numbers of EAS or EES connections for a given area or time window, statistics regarding an average edge computational resource usage, a resource ratio based on a total resource availability of an EDN, an EDN overload indication, a high load indication event, or a probability of EAS and EES unavailability due to high load (Section 6.4.1-Solution description, Pg. 31, Line 1-9, Fig. 6.4.1-1, steps 9-10, Pg. 32-33, Section 6.4.2 - Corresponding Analytics API, Pg. 33-34).
Re claim 15, 3GPP teaches that the data producers comprise at least one of: an edge application server (EAS) providing at least one of computational resource load per EAS and a number of connections of the EAS; an edge enabler server (EES) providing at least one of computational resource load per EES and a number of connections of the EES; an N6 endpoint providing an N6 load; an OAM function providing at least one of computational resource load per EAS and a number of connections of the EAS; an OAM function providing at least one of computational resource load per EES and a number of connections of the EES; a service enabler architecture layer data delivery server (SEALDD) providing N6 load measurements and a SEALDD computational resource load; at least one of a 5G core (5GC) and a network data analytics function (NWDAF) providing data network performance analytics; a management domain analytics service (MDAS) providing load analytics per data network access identifier (DNAI); and a multi-access edge computing (MEC) platform service such as a radio network information service (RNIS) providing per cell average radio conditions and a load for all cells within an edge data network (EDN) (Fig. 6.4.1-1, steps 6-10, Pg. 32-33, Section 6.4.2 - Corresponding Analytics API, Pg. 33-34).
Re claim 16, 3GPP teaches an apparatus (ADAES, Fig. 6.4.1-1, Pg. 32) for utilizing edge load analytics for optimizing edge service performance, the apparatus causes to:
(i) send a subscription request for edge load analytics to an edge analytics producer (data collection subscription request, Step 4, Fig. 6.4.1-1, Pg. 32-33), the subscription request indicating an analytics event identifier (analytics event ID included in the subscription request) (Fig. 6.4.1-1, Step 1, Pg. 32);
(ii) receive a determined mapping of the analytics event identifier to at least one of a list of data collection event identifiers or a list of data producer identifiers (determining a mapping of analytics ID to data collection IDs, and data producer IDs) (Fig. 6.4.1-1, Step 3, Pg. 32);
(iii) receive a data collection subscription request to the data producers identified by the list of data producer identifiers (data collection subscription request, Step 4, Fig. 6.4.1-1), wherein the data collection subscription request comprises data collection requirements (requirement for data collection) and at least one of the analytics event identifier, the list of data producer identifiers, or the respective data collection event identifier (data collection subscription request includes Data Collection event ID and/or the analytics event ID) (Fig. 6.4.1-1, Step 4, Pg. 32-33), wherein the data collection requirements comprises a reporting frequency (Pg. 21, step 4a, Pg. 36, line 1-3, The ADAES sends a subscription request to the ADAEC #1 with the analytics event ID and the configuration of the reporting required (e.g., periodic, based on threshold or event). Such request also includes the application QoS attributes to be analyzed (latency, jitter, PER,..)”) and an abstraction level of the data (time validity, area of request, required confidence level, Step 4, Pg. 32-33), the reporting frequency indicates whether the data is received once or periodically based on a threshold (Pg. 19, step 8b, “The ADAES may receive also data (periodically or if a threshold is reached based on configuration) from the application of the UE within the ongoing session (via ADAEC). Such data can be about the RTT, average/peak throughput, jitter, QoE measurements (MOS, stalling events, stalling ratios, etc), QoS profile load, VAL server load, etc.”; Pg. 33, step 8, “The Data Producer send the data to the ADAES (based on step 7 measurements or analytics), 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%)”. Pg. 36, line 1-3, “The ADAES sends a subscription request to the ADAEC #1 with the analytics event ID and the configuration of the reporting required (e.g., periodic, based on threshold or event);
(iv) receive derived edge load analytics from the edge analytics producer (receiving data from the data producers) (Fig. 6.4.1-1, steps 6-8, Pg. 32-33); and
(v) generate a trigger event indicating a predicted overload and an action based on the derived edge load analytics (overload prediction and recommended action) (Section 6.4.1-Solution description, Pg. 31, Line 1-9, Fig. 6.4.1-1, steps 9-10, Pg. 32-33, Pg. 34, Line 9-10).
3GPP does not explicitly disclose that the apparatus comprises one or more processors configured to execute computer- readable instructions.
Liu teaches that that the apparatus (DCES) comprises one or more processors configured to execute computer- readable instructions (Fig. 8F, Par 0006, Par 0154).
It would have been obvious to one of ordinary skill in the art before the filing date of the invention to modify the apparatus disclosed by 3GPP by including one or more processors configured to execute computer- readable instructions, as taught by Liu for the purpose of optimizing the efficiency of the data collection process along with managing and coordinating the data collection requests, as taught by Liu (Par 0005).
Re claim 17, 3GPP teaches that the action comprises at least one of a migration of an edge node to a different edge data network (EDN) and a pro-active edge application server (EAS) reselection for a target user equipment (UE) or a group of UEs (triggering an EAS relocation to a different platform) (Section 6.4.1-Solution description, Pg. 31, Line 1-9, Fig. 6.4.1-1, steps 9-10, Pg. 32-33, Pg. 34, Line 9-10).
Re claim 18, 3GPP teaches that the apparatus comprises at least one of an edge enabler server (EES), an edge application server (EAS), or an analytics consumer (EES, EAS, Consumer) (Section 6.4.1-Solution description, Pg. 31, Line 1-9, Fig. 6.4.1-1, steps 1-10, Pg. 32-33, Section 6.4.2 - Corresponding Analytics API, Pg. 33-34).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to HARUN UR R CHOWDHURY whose telephone number is (571)270-3895. The examiner can normally be reached Monday-Friday 9AM-5PM.
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/HARUN CHOWDHURY/ Examiner, Art Unit 2473
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