Prosecution Insights
Last updated: April 19, 2026
Application No. 17/974,718

ROUTING SELF-ORGANIZING NETWORKS USING APPLICATION QUALITY OF EXPERIENCE METRICS

Final Rejection §102
Filed
Oct 27, 2022
Examiner
KIM, CHONG G
Art Unit
2443
Tech Center
2400 — Computer Networks
Assignee
Cisco Technology Inc.
OA Round
3 (Final)
83%
Grant Probability
Favorable
4-5
OA Rounds
2y 11m
To Grant
87%
With Interview

Examiner Intelligence

Grants 83% — above average
83%
Career Allow Rate
352 granted / 424 resolved
+25.0% vs TC avg
Minimal +4% lift
Without
With
+4.2%
Interview Lift
resolved cases with interview
Typical timeline
2y 11m
Avg Prosecution
44 currently pending
Career history
468
Total Applications
across all art units

Statute-Specific Performance

§101
12.0%
-28.0% vs TC avg
§103
35.8%
-4.2% vs TC avg
§102
36.3%
-3.7% vs TC avg
§112
12.2%
-27.8% vs TC avg
Black line = Tech Center average estimate • Based on career data from 424 resolved cases

Office Action

§102
DETAILED ACTION Notice of Pre-AIA or AIA Status The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . Response to Amendment The Amendment filed on 11/12/2025 has been entered. Claims 1-20 remain pending in the application. Response to Arguments Applicant’s arguments on pages 6-9 with respect to claims 1, 11 and 20 have been considered but are moot upon a further consideration and a new ground of rejection made under 35 U.S.C. 102(a)(2) as being anticipated by Chatterjee (US PGPub 2017/0163422). Claim Rejections - 35 USC § 102 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)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention. Claims 1-20 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Chatterjee (US PGPub 2017/0163422). Regarding claims 1, 11 and 20, Chatterjee teaches a method (Chatterjee, see paragraph 0003, Systems and methods are provided that can enforce QoS across network elements for WebRTC communications) comprising: obtaining, by a device, physical link information of a group nodes associated with networking equipment in a network (Chatterjee, see paragraphs 0020 and 0030, The fourth illustrative system 400 comprises browser 101, network 110, edge servers 120A-120N, WebRTC applications 123A-123N, SDN controller 124, WebRTC media servers 360A-360N, and SDN networks 140A-140N. The Software Defined Network (SDN) controller 124 can be or may include any hardware coupled with software that can control various elements in the network 110B, such as the router(s) 130, a gateway, a media server, a communication device, and/or (e.g., a network resource) the like. The SDN 140 is a network that is defined where the higher level functionality is abstracted from the underlying systems), the physical link information including one or more paths between the group of nodes (Chatterjee, see paragraph 0032, The SDN controller 124 controls requests from the browser 101 to access the WebRTC media servers 360A-360N); receiving, at the device, quality of experience (QoE) metrics for an online application (Chatterjee, see paragraph 0032, he SDN controller 124 receives QoS information from each of the edge servers 120A-120N. The QoS information can include information, such as, capacity, bit rate, throughput, present traffic, jitter information, supported codecs, and/or the like), the QoE metrics including a first QoE metric associated with a first node of the group of nodes and a second QoE metric associated with a second node of the group of nodes (Chatterjee, see paragraph 0032, The QoS information may be gathered by the edge servers 120A-120N from various network elements, such as the routers 130, the gateway 250, the WebRTC media servers 360, the communication device 251, and/or the like); selecting, by the device, a path from the one or more paths and associated with the first node or the second node, wherein selecting the path is based at least in part on the first QoE metric and second QoE metric (Chatterjee, see paragraph 0032, The SDN controller 124 uses the received QoS information to determine a specific edge server 120 to send the request to. if the browser 101 makes a request from the United States to access the WebRTC media server 360, the request will be directed to the WebRTC media server 360 that is closest (e.g., in the United States). If the edge server 120 in the United States is heavily loaded (e.g., where taking the request would violate a Service Level Agreement (SLA)), the SDN controller 124 can send the request to a different edge server 120 (and a different WebRTC media server 360) that will be in compliance with the SLA); and causing, by the device, traffic associated with the online application to be sent via the path (Chatterjee, see paragraph 0032, the SDN controller 124 can send the request to a different edge server 120 (and a different WebRTC media server 360) that will be in compliance with the SLA). Regarding claims 2 and 12, Chatterjee teaches wherein the QoE metrics are indicative of satisfaction ratings provided by users of the online application (Chatterjee, see paragraph 0032, he SDN controller 124 receives QoS information from each of the edge servers 120A-120N. The QoS information can include information, such as, capacity, bit rate, throughput, present traffic, jitter information, supported codecs, and/or the like). Regarding claims 3 and 13, Chatterjee teaches wherein the device receives the QoE metrics from the online application via an application programming interface (API) of the online application (Chatterjee, see paragraph 0032, he SDN controller 124 receives QoS information from each of the edge servers 120A-120N. The QoS information can include information, such as, capacity, bit rate, throughput, present traffic, jitter information, supported codecs, and/or the like). Regarding claims 4 and 14, Chatterjee teaches wherein the device selects the path by using reinforcement learning with a reward function that seeks to maximize the QoE metrics from the online application (Chatterjee, see paragraph 0032, The SDN controller 124 uses the received QoS information to determine a specific edge server 120 to send the request to. if the browser 101 makes a request from the United States to access the WebRTC media server 360, the request will be directed to the WebRTC media server 360 that is closest (e.g., in the United States). If the edge server 120 in the United States is heavily loaded (e.g., where taking the request would violate a Service Level Agreement (SLA)), the SDN controller 124 can send the request to a different edge server 120 (and a different WebRTC media server 360) that will be in compliance with the SLA). Regarding claims 5 and 15, Chatterjee teaches further comprising: computing an updated path for the traffic associated with the online application in response to a detected trigger (Chatterjee, see paragraph 0051, the SDN controller 124, WebRTC application 123, and/or edge server 120/320 determines if the closest edge server 120/320 meets the QoS of the tenant in step 604). Regarding claims 6 and 16, Chatterjee teaches wherein the detected trigger indicates a threshold percentage of traffic in the network having unacceptable QoE metrics (Chatterjee, see paragraph 0032, The SDN controller 124 uses the received QoS information to determine a specific edge server 120 to send the request to. if the browser 101 makes a request from the United States to access the WebRTC media server 360, the request will be directed to the WebRTC media server 360 that is closest (e.g., in the United States). If the edge server 120 in the United States is heavily loaded (e.g., where taking the request would violate a Service Level Agreement (SLA)), the SDN controller 124 can send the request to a different edge server 120 (and a different WebRTC media server 360) that will be in compliance with the SLA). Regarding claims 7 and 17, Chatterjee teaches wherein the detected trigger indicates a change in a traffic matrix (Chatterjee, see paragraph 0032, The SDN controller 124 uses the received QoS information to determine a specific edge server 120 to send the request to. if the browser 101 makes a request from the United States to access the WebRTC media server 360, the request will be directed to the WebRTC media server 360 that is closest (e.g., in the United States). If the edge server 120 in the United States is heavily loaded (e.g., where taking the request would violate a Service Level Agreement (SLA)), the SDN controller 124 can send the request to a different edge server 120 (and a different WebRTC media server 360) that will be in compliance with the SLA). Regarding claims 8 and 18, Chatterjee teaches wherein the detected trigger indicates a routing topology change reported by a particular one of the networking equipment (Chatterjee, see paragraphs 0020 and 0030, The fourth illustrative system 400 comprises browser 101, network 110, edge servers 120A-120N, WebRTC applications 123A-123N, SDN controller 124, WebRTC media servers 360A-360N, and SDN networks 140A-140N. The Software Defined Network (SDN) controller 124 can be or may include any hardware coupled with software that can control various elements in the network 110B, such as the router(s) 130, a gateway, a media server, a communication device, and/or (e.g., a network resource) the like. The SDN 140 is a network that is defined where the higher level functionality is abstracted from the underlying systems). Regarding claims 9 and 19, Chatterjee teaches wherein the path is configured in an underlay of a software-defined network (SDN) (Chatterjee, see paragraphs 0020 and 0030, The fourth illustrative system 400 comprises browser 101, network 110, edge servers 120A-120N, WebRTC applications 123A-123N, SDN controller 124, WebRTC media servers 360A-360N, and SDN networks 140A-140N. The Software Defined Network (SDN) controller 124 can be or may include any hardware coupled with software that can control various elements in the network 110B, such as the router(s) 130, a gateway, a media server, a communication device, and/or (e.g., a network resource) the like. The SDN 140 is a network that is defined where the higher level functionality is abstracted from the underlying systems). Regarding claim 10, Chatterjee teaches wherein the networking equipment comprises a plurality of routers (Chatterjee, see paragraphs 0020 and 0030, The fourth illustrative system 400 comprises browser 101, network 110, edge servers 120A-120N, WebRTC applications 123A-123N, SDN controller 124, WebRTC media servers 360A-360N, and SDN networks 140A-140N. The Software Defined Network (SDN) controller 124 can be or may include any hardware coupled with software that can control various elements in the network 110B, such as the router(s) 130, a gateway, a media server, a communication device, and/or (e.g., a network resource) the like. The SDN 140 is a network that is defined where the higher level functionality is abstracted from the underlying systems). Conclusion Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a). A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action. Any inquiry concerning this communication or earlier communications from the examiner should be directed to CHONG G KIM whose telephone number is (571)270-0619. The examiner can normally be reached Mon-Fri @ 9am - 5pm. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Nicholas R. Taylor can be reached at 571-272-3889. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /CHONG G KIM/Examiner, Art Unit 2443 /NICHOLAS R TAYLOR/Supervisory Patent Examiner, Art Unit 2443
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Prosecution Timeline

Oct 27, 2022
Application Filed
Feb 06, 2025
Non-Final Rejection — §102
May 12, 2025
Response Filed
Aug 06, 2025
Non-Final Rejection — §102
Oct 31, 2025
Interview Requested
Nov 10, 2025
Applicant Interview (Telephonic)
Nov 10, 2025
Examiner Interview Summary
Nov 12, 2025
Response Filed
Jan 27, 2026
Final Rejection — §102
Apr 10, 2026
Interview Requested

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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
83%
Grant Probability
87%
With Interview (+4.2%)
2y 11m
Median Time to Grant
High
PTA Risk
Based on 424 resolved cases by this examiner. Grant probability derived from career allow rate.

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