Prosecution Insights
Last updated: August 17, 2026
Application No. 18/358,719

Dynamic and QOS bandwidth aware load balancing in multi-path software defined wan area networks

Non-Final OA §103
Filed
Jul 25, 2023
Priority
Apr 07, 2023 — provisional 63/495,010
Examiner
CADORNA, CHRISTOPHER PALACA
Art Unit
2444
Tech Center
2400 — Computer Networks
Assignee
Cisco Technology Inc.
OA Round
3 (Non-Final)
66%
Grant Probability
Favorable
3-4
OA Rounds
2m
Est. Remaining
86%
With Interview

Examiner Intelligence

Grants 66% — above average
66%
Career Allowance Rate
156 granted / 235 resolved
+8.4% vs TC avg
Strong +20% interview lift
Without
With
+19.6%
Interview Lift
resolved cases with interview
Typical timeline
3y 3m
Avg Prosecution
20 currently pending
Career history
266
Total Applications
across all art units

Statute-Specific Performance

§101
10.6%
-29.4% vs TC avg
§103
54.1%
+14.1% vs TC avg
§102
14.5%
-25.5% vs TC avg
§112
19.7%
-20.3% vs TC avg
Black line = Tech Center average estimate • Based on career data from 235 resolved cases

Office Action

§103
Notice of Pre-AIA or AIA Status The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . Response to Arguments 1. Applicant's arguments have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument. Claim Rejections - 35 USC § 103 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. 2. Claims 1-4, 8-11, and 15-18 are rejected under 35 U.S.C. 103 as being unpatentable over Iyer et al. (US 20200259750 A1) in view of Muscariello et al. (US 20180103128 A1). Claim 1 Iyer teaches a method comprising: determining one or more metrics based on one or more Software-defined Wide Area Network (SDWAN) session level throughput and SDWAN session loss through one or more tunnels; (FIG. 3, block 306, ¶0052, determining whether the updated measurement of network bandwidth, i.e. a metric, is less than or greater than based on a stored network bandwidth measurement, i.e. a throughput, of an SD-WAN network) and generating a Quality of Service (QoS) SDWAN session level shape rate per tunnel based on the one or more metrics. (FIG. 3, ¶0052 and ¶0054, blocks 308 or 316, determining a new shaping rate based on the metric of the updated measurement being greater or not; Examiner interprets that the “shape rate per tunnel” as being the same as a shape rate for each tunnel, and therefore, as the shape rate is for a given connection, i.e. tunnel, the new shaping rate would be the shape rate per tunnel) However, Iyer does not explicitly each determining, from the QoS SDWAN session level shape rate, a per tunnel forwarding load-balance weight for each of the one or more tunnels; and dynamically adjusting the per tunnel forwarding load-balance weight for each of the one or more tunnels. From a related technology, Muscariello teaches determining, from the shape rate, a per tunnel forwarding load-balance weight for each of the one or more tunnels. (FIG. 16, ¶0256, computing from the shaping rate, forward load-balance weights for each of the queues, i.e. tunnels) and dynamically adjusting the per tunnel forwarding load-balance weight for each of the one or more tunnels. (¶0256-¶0257, wherein these weighs are calculated dynamically for each of the queues, i.e. tunnels) It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Iyer to incorporate the method of determining queue weights according to shaping rate as taught by Muscariello in order to more effectively manage network resources according to operating metrics. Claim 2 Iyer in view of Muscariello teaches Claim 1, and further teaches measuring the one or more metrics at a subsequent time after adjusting the SDWAN session level shape rate and the SDWAN forwarding load-balance weight; (Iyer, FIG. 3, ¶0047, wherein the measurement is part of an iterative flow process, as such is continually measured over time, i.e. after adjustment) and based on a change of the one or more metrics measured, further adjusting the SDWAN session level shape rate and the SDWAN forwarding load-balance weight in real-time. (Iyer, FIG. 3, ¶0052 and ¶0054, wherein the adjustments are based on updates, i.e. real time) Claim 3 Iyer in view of Muscariello teaches Claim 1, and further teaches determining that a first transport link has local Wide Area Network (WAN) (Iyer, FIG. 1, a regional WAN 150, ¶0041) QoS congestion based on the one or more metrics, (Iyer, FIG. 3, step 314, ¶0053, determining the bandwidth demand is greater than the current shaping rate, i.e. the link is having congestion) the first transport link having a first weight, monitored by a path monitor service; (Iyer, ¶0053, wherein shaping rate comprises a first weight, wherein the process comprises a path monitor service) determining that a second transport link is underutilized based on the one or more metrics (Iyer, FIG. 3, step 306, ¶0052, determining the bandwidth demand is lesser than the current shaping rate, i.e. the link is underutilized) monitored by the path monitor service, (See above) the second transport link having a second weight; (Iyer, ¶0053, wherein shaping rate comprises a second weight) dynamically adjusting the SDWAN forwarding load-balance weight for the first transport link and the second transport link by modifying the first weight and the second weight in accordance with the one or more metrics monitored by the path monitor service; (Iyer, FIG. 3, step 312 and 320, ¶0052-¶0054, adjusting the shaping rate based on the determined bandwidths and modifying the link shaper rates) and rerouting traffic from the first transport link to the second transport link based on QoS requirements. (Iyer, ¶0047, shaping traffic flow according the to process of FIG. 3, i.e. the adjusted weights/shaper rates) Claim 4 Iyer in view of Muscariello teaches Claim 1, and further teaches determining, at a first time, a first utilization of a first transport link and a second utilization of a second transport link (Iyer, FIG. 3, step 314, ¶0053, step 306, ¶0052, determining the bandwidth demand; FIG. 6, ¶0059, Examiner notes that the processes of FIG. 3 is performed across multiple transport links simultaneously) based on the one or more metrics monitored by a path monitor service, wherein at least one of the first transport link and the second transport link is a dynamic link with variable transport bandwidth capacity; (Iyer, ¶0052-¶0054, wherein the transport link is dynamic and can have its bandwidth capacity adjusted) dynamically assigning a first weight for the first transport link and a second weight for the second transport link; (Iyer, FIG. 3, step 312 and 320, ¶0052-¶0054, adjusting the shaping rate based on the determined bandwidths and modifying the link shaper rates) determining, at a second time, (Iyer, ¶0047, wherein the process is iterative happening at recurrent different times) that a transport bandwidth capacity of the second transport link has increased; (Iyer, FIG. 3, step 306, ¶0052, determining the bandwidth demand is lesser than the current shaping rate, i.e. the link is underutilized) based on the determination, dynamically increasing the second weight and decreasing the first weight; (Iyer, FIG. 3, step 312, ¶0052-¶0054, adjusting the shaping rate based on the determined bandwidths and modifying the link shaper rates) and routing traffic along the first transport link in accordance with the first weight and the second transport link in accordance with the second weight. (Iyer, ¶0047, shaping traffic flow according the to process of FIG. 3, i.e. the adjusted weights/shaper rates) Claims 8-11 are taught by Iyer in view of Muscariello as described for Claims 1-4. Claims 15-18 are taught by Iyer in view of Muscariello as described for Claims 1-4. 3. Claims 5, 12, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Iyer et al. (US 20200259750 A1) in view of Muscariello et al. (US 20180103128 A1) and in further view of Khan et al. (US 20170279710 A1). Claim 5 Iyer in view of Muscariello teaches Claim 1, but does not explicitly teach adjusting the SDWAN forwarding load-balance weight for each of the one or more tunnels by a Transport Locator (TLOC) Session weight value, the TLOC session weight value based on the one or more metrics, wherein the one or more metrics include measured bandwidth capacity; and forwarding the TLOC session weight value to a SDWAN TLOC forwarding hashing table which dynamically distributes and load balances traffic flows over multiple tunnels based on available bandwidth. From a related technology, Khan adjusting a forwarding load-balance weight for each of the one or more tunnels by a Transport Locator (TLOC) Session weight value, the TLOC session weight value based on the one or more metrics wherein the one or more metrics include measured bandwidth capacity; (FIG. 6, ¶0101-¶0102, coming the TLOC value to a routing, i.e. forwarding hashing, table, ¶0040) and forwarding the TLOC session weight value to a SDWAN TLOC forwarding hashing table (FIG. 6, ¶0101-¶0102, coming the TLOC value to a routing, i.e. forwarding hashing, table, ¶0040) which dynamically distributes and load balances traffic flows over multiple tunnels based on available bandwidth. (Examiner notes that this is an intended use of the hashing table, the claim only covers forwarding the value, however, the hashing table has not been recited as a claim element nor it distributing traffic flows) It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Iyer to incorporate the teachings of Khan in order to adopt well-known load balancing techniques to improved network efficiency. Claim 12 and 19 are rejected by Iyer in view of Muscariello and Khan as described for Claim 5. 4. Claims 6-7, 13-14, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Iyer et al. (US 20200259750 A1) in view of Muscariello et al. (US 20180103128 A1) and in further view of Shanks et al. (US 20170180155 A1). Claim 6 Iyer in view of Muscariello teaches Claim 1, but does not explicitly teach wherein the one or more metrics are further determined based on multiple tunnel bandwidth usage and local WAN loss ratio. From a related technology, Shanks teaches one or more metrics are further determined based on multiple tunnel bandwidth usage and local WAN loss ratio. (¶0080, wherein one or more performance measures are based on bandwidth or packet drop rate) It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Iyer to incorporate the metrics determined by Shanks to more effectively analyze network resources to improve utilization. Claim 7 Iyer in view of Muscariello teaches Claim 1, but does not explicitly teach monitoring traffic throughput, Local/WAN drop ratio, and congestion state. (¶0080, wherein one or more performance measures are based on bandwidth, packet drop rate, and latency) It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of Iyer to incorporate the metrics determined by Shanks to more effectively analyze network resources to improve utilization. Claims 13-14 are taught by Iyer in view of Muscariello and Shanks as described for Claims 6-7. Claim 20 is taught by Iyer in view of Muscariello and Shanks as described for Claim 6. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to CHRISTOPHER PALACA CADORNA whose telephone number is (571)270-0584. The examiner can normally be reached M-F 10:00-7:00. 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, John Follansbee can be reached at (571) 272-3964. 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. /CHRISTOPHER P CADORNA/Examiner, Art Unit 2444 /JOHN A FOLLANSBEE/Supervisory Patent Examiner, Art Unit 2444
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Prosecution Timeline

Jul 25, 2023
Application Filed
Sep 03, 2025
Non-Final Rejection mailed — §103
Dec 03, 2025
Response Filed
Mar 27, 2026
Final Rejection mailed — §103
Jun 29, 2026
Request for Continued Examination
Jul 02, 2026
Response after Non-Final Action
Jul 17, 2026
Non-Final Rejection mailed — §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

3-4
Expected OA Rounds
66%
Grant Probability
86%
With Interview (+19.6%)
3y 3m (~2m remaining)
Median Time to Grant
High
PTA Risk
Based on 235 resolved cases by this examiner. Grant probability derived from career allowance rate.

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