Prosecution Insights
Last updated: April 19, 2026
Application No. 18/692,724

METHOD FOR ALIGNING QUALITY OF SERVICE IN MOBILE NETWORK AND EDGE CLOUD

Final Rejection §103
Filed
Mar 15, 2024
Examiner
NGUYEN, QUANG N
Art Unit
2441
Tech Center
2400 — Computer Networks
Assignee
Telefonaktiebolaget Lm Ericsson (Publ)
OA Round
3 (Final)
88%
Grant Probability
Favorable
4-5
OA Rounds
2y 4m
To Grant
99%
With Interview

Examiner Intelligence

Grants 88% — above average
88%
Career Allow Rate
450 granted / 513 resolved
+29.7% vs TC avg
Strong +17% interview lift
Without
With
+17.1%
Interview Lift
resolved cases with interview
Typical timeline
2y 4m
Avg Prosecution
27 currently pending
Career history
540
Total Applications
across all art units

Statute-Specific Performance

§101
11.0%
-29.0% vs TC avg
§103
36.6%
-3.4% vs TC avg
§102
21.5%
-18.5% vs TC avg
§112
8.4%
-31.6% vs TC avg
Black line = Tech Center average estimate • Based on career data from 513 resolved cases

Office Action

§103
Detailed Action 1. This Office Action is responsive to the Response After Final Action filed 01/13/2026. Claims 1-20 are pending for examination. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . Claim Rejections - 35 USC § 103 2. 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. 3. Claims 1-3, 5-12, 14-17 and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Maciocco et al. (US 2021/0014133 A1), in view of Abhigyan et al. (US 2022/0174485 A1), and further in view of Wu et al. (US 2015/0103670 A1) hereinafter “Maciocco”, “Abhigyan” and “Wu” correspondingly. 4. As to claim 1, Maciocco teaches a method by one or more computing devices to configure an edge cloud to meet end-to-end (E2E) performance targets for microservices-based applications, the method comprising: obtaining cloud-side service information, cloud-side resource usage information, and cloud-side performance information associated with the application (Maciocco, [0034]); determining microservice instances of a microservice chain in the edge cloud that can be used to meet the cloud-side performance target for the application based on the cloud-side service information, the cloud-side resource usage information, and the cloud-side performance information (Maciocco, [0034]); determining cloud-side QoS parameters for the microservice instances based on the cloud-side performance target and knowledge regarding a performance associated with the cloud-side QoS parameters (Maciocco, [0035]); determining a resource configuration for the microservice instances based on the cloud-side performance target for the application, the cloud-side service information, the cloud-side resource usage information, and the cloud-side performance information (Maciocco, [0035]); and configuring the edge cloud to implement the microservice instances including applying the cloud-side QoS parameters and the resource configuration to the microservice instances (Maciocco, [0053]). Maciocco does not explicitly teach “obtaining network-side information for a mobile network that is communicatively coupled to an edge cloud, wherein the network-side information comprises performance information associated with a microservices-based application that is implemented over the edge cloud and the mobile network”. In an analogous art, Abhigyan discloses that network API service 158 collects low-level network data representing latency and bandwidth within access network 220A, core network 230A, gateway 230J and edge cloud location 240J … The collected low-level network data is analyzed and/or synthesized to produce the application-level network data corresponding to the end-to-end bandwidth and/or end-to-end latency between UE device and various edge cloud locations (i.e., between UE device and various edge cloud devices/applications) (Abhigyan, [0092-0093] and [0115]). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing data of the claimed invention to incorporate the feature of “obtaining network-side information for a mobile network that is communicatively coupled to an edge cloud, wherein the network-side information comprises network-side quality of service (QoS) control information and performance information associated with a microservices-based application that is implemented over the edge cloud and the mobile network”, as disclosed by Abhigyan, into the teachings of Maciocco to enable the edge cloud platform to select and edge location to instantiate an application server (Abhigyan, [0115]). Maciocco-Abhigyan does not explicitly teach “obtaining the network-side information comprises network-side quality of service (QoS) control information” and “determining a cloud-side performance target for the application based on an E2E performance target for the application, the network-side QoS control information, and the network-side performance information”. In an analogous art, Wu discloses obtaining the network-side information comprises network-side quality of service (QoS) control information associated with a microservices-based application that is implemented over the edge cloud and the mobile network (i.e., an obtaining module 610 configured to obtain initial quality of service QoS information of a user equipment in a mobile network); and determining a cloud-side performance target for the application based on an E2E performance target for the application, the network-side QoS control information, and the network-side performance information (i.e., a determining module 620 configured to determine, according to the initial QoS information, to request the mobile network to increase a QoS level of the user equipment) (Wu, [0048] and [0187]). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing data of the claimed invention to incorporate the teachings of Wu, into Maciocco-Abhiyan to achieve “obtaining the network-side information comprises network-side quality of service (QoS) control information” and “determining a cloud-side performance target for the application based on an E2E performance target for the application, the network-side QoS control information, and the network-side performance information” to allow the system to request the mobile network to increase the QoS level of the user equipment when the initial QoS information does not meet the QoS demand of a service (Wu, [0088]). 5. As to claim 2, Maciocco-Abhigyan-Wu teaches the method of claim 1, wherein the mobile network is a 4G mobile network or a 5G mobile network (Maciocco, [0045] and [0049]). 6. As to claim 3, Maciocco-Abhigyan-Wu teaches the method of claim 1, wherein the network-side QoS control information and the network-side performance information is obtained from network functions of the mobile network exposing network information (Maciocco, [0072-0073]). 7. As to claim 5, Maciocco-Abhigyan-Wu teaches the method of claim 1, wherein the network-side performance information includes information regarding latency or throughput associated with the application in the mobile network (Maciocco, [0043]). 8. As to claim 6, Maciocco-Abhigyan-Wu teaches the method of claim 1, wherein the cloud-side service information includes information regarding microservice chains of the application in the edge cloud (Maciocco, [0033]). 9. As to claim 7, Maciocco-Abhigyan-Wu teaches the method of claim 6, wherein the cloud-side resource usage information includes information regarding resource usage of microservice instances of the microservice chains (Maciocco, [0033]). 10. As to claim 8, Maciocco-Abhigyan-Wu teaches the method of claim 6, wherein the cloud-side performance information includes information regarding latency or throughput associated with microservice instances of the microservice chains (Maciocco, [0033]). 11. As to claim 9, Maciocco-Abhigyan-Wu teaches the method of claim 1, wherein the cloud-side QoS parameters that are applied to the microservice instances includes parameters related to scheduling, scaling, and traffic optimization (Maciocco, [0034], [0040], [0072] and [0083]). 12. As to claim 10, Maciocco-Abhigyan-Wu teaches the method of claim 1, wherein applying the resource configuration to the microservice instances includes one or more of changing a number of replicas of a microservice instance, changing an amount of resources allocated to a microservice instance, and configuring a traffic routing policy for a microservice (Maciocco, [0065-0066]). 13. As to claim 11, Maciocco-Abhigyan-Wu teaches the method of claim 1, wherein the microservice instances span across a plurality of edge clusters (Maciocco, [0065-0066]). 14. As to claims 12, 14-17 and 19-20, claims 12, 14-17 and 19-20 are corresponding set of non-transitory machine-readable media and computing device claims that recite similar limitations as of method claims 1-3 and 5-11 and do not contain any additional limitations with respect to novelty and/or inventive steps; therefore, they are rejected under the same rationale. 15. Claims 4, 13 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Maciocco-Abhigyan-Wu, in view of XIN et al. (US 2020/0229199 A1), hereinafter “XIN”. 16. As to claim 4, Maciocco-Abhigyan-Wu teaches the method of claim 1, wherein the mobile network is a 5G mobile network (Maciocco, [0052]), but does not explicitly teach “wherein the network-side QoS control information includes a QoS indicator or an allocation and retention priority (ARP) value associated with the application in the mobile network”. In an analogous art, XIN teaches that for a first communication network is a 5G network, the first QoS parameter includes at least one of a QI, a session aggregate maximum bit rate (AMBR), and an allocation retention priority (ARP) that correspond to a default QoS flow3 (i.e., the network-side QoS control information includes a QoS indicator or an allocation and retention priority (ARP) value associated with the application in the mobile network) (XIN, [0012]). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the feature of “the network-side QoS control information includes a QoS indicator or an allocation and retention priority (ARP) value associated with the application in the mobile network”, as disclosed by XIN, into the teachings of Maciocco-Abhigyan-Wu to allow a network-side network element in the first communications network removes, while releasing the first QoS parameter that corresponds to an SDF of the first communications network, the second QoS parameter that corresponds to the SDF of the second communications network to ensure that a communication resource is not occupied and interworking between the first and second communications networks can be smoothly performed, thereby improving network resource utilization (XIN, [0007]). 17. As to claims 13 and 18, claims 13 and 18 are corresponding set of non-transitory machine-readable media and computing device claims that recite similar limitations as of method claims 4 and 8 and does not contain any additional limitations with respect to novelty and/or inventive steps; therefore, they are rejected under the same rationale. Response to Arguments 18. Applicant’s arguments with respect to claims 1, 12 and 17 have been considered but are moot because of the new ground of rejection. Conclusion 19. Applicant's amendment (submitted on 11/04/2025) necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a). A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action. 20. Further references of interest are cited on Form PTO-892, which is an attachment to this Office Action. 21. Any inquiry concerning this communication or earlier communications from the examiner should be directed to QUANG N NGUYEN whose telephone number is (571) 272-3886. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s SPE, Wing Chan, can be reached at (571) 272-7493. The fax phone number for the organization is (571) 273-8300. Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /QUANG N NGUYEN/Primary Examiner, Art Unit 2441
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Prosecution Timeline

Mar 15, 2024
Application Filed
Jul 30, 2025
Non-Final Rejection — §103
Nov 04, 2025
Response Filed
Nov 11, 2025
Final Rejection — §103
Jan 13, 2026
Response after Non-Final Action
Jan 16, 2026
Final Rejection — §103 (current)

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

4-5
Expected OA Rounds
88%
Grant Probability
99%
With Interview (+17.1%)
2y 4m
Median Time to Grant
High
PTA Risk
Based on 513 resolved cases by this examiner. Grant probability derived from career allow rate.

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