Prosecution Insights
Last updated: October 23, 2026
Application No. 18/822,878

SYSTEM FOR NETWORK CONGESTION CONTROL

Non-Final OA §102§112
Filed
Sep 03, 2024
Examiner
BLAIR, DOUGLAS B
Art Unit
2454
Tech Center
2400 — Computer Networks
Assignee
Mellanox Technologies Ltd.
OA Round
2 (Non-Final)
72%
Grant Probability
Favorable
2-3
OA Rounds
1y 9m
Est. Remaining
80%
With Interview

Examiner Intelligence

Grants 72% — above average
72%
Career Allowance Rate
469 granted / 647 resolved
+14.5% vs TC avg
Moderate +8% lift
Without
With
+7.9%
Interview Lift
resolved cases with interview
Typical timeline
3y 11m
Avg Prosecution
43 currently pending
Career history
705
Total Applications
across all art units

Statute-Specific Performance

§101
10.5%
-29.5% vs TC avg
§103
34.1%
-5.9% vs TC avg
§102
21.5%
-18.5% vs TC avg
§112
27.8%
-12.2% vs TC avg
Black line = Tech Center average estimate • Based on career data from 647 resolved cases

Office Action

§102 §112
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 Arguments Applicant's arguments filed 7/2/2026 have been fully considered but they are not persuasive. The applicant’s amendments have overcome the rejections based on 35 USC sections 101, 112(b), and 102(a)(1). However, after further search and consideration the applicant’s amended claim language was found to be unpatentable over the Ismailsheriff reference that had been applied to claims 4 and 16 in the previous office action. Additionally, the Examiner found that although the applicant removed the term behavioral policy from the claims, the applicant is still claiming the machine learning model whose algorithm is not sufficiently described in order carry out the determining of actions to execute. The applicant has not disclosed a manner of determining that does not require the use of a machine learning model and the applicant has not disclosed sufficient details regarding their machine learning model. Claim Rejections - 35 USC § 112 The following is a quotation of the first paragraph of 35 U.S.C. 112(a): (a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention. The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112: The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention. Claims 1, 3-5, 7-13, 15-18, and 20 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention. Claims 1, 13, and 18 feature the following limitations: determine, using the intelligent agent, having the captured congestion indicators as input actions to be executed by the processor in response to the captured congestion indicators to change the congestion state of the network environment; and execute the actions to adjust sending rates of one or more of the plurality of NICs. Section 2163.03(V) of the MPEP states: V. ORIGINAL CLAIM NOT SUFFICIENTLY DESCRIBED While there is a presumption that an adequate written description of the claimed invention is present in the specification as filed. In re Wertheim, 541 F.2d 257, 262, 191 USPQ 90, 96 (CCPA 1976), a question as to whether a specification provides an adequate written description may arise in the context of an original claim. An original claim may lack written description support when (1) the claim defines the invention in functional language specifying a desired result but the disclosure fails to sufficiently identify how the function is performed or the result is achieved or (2) a broad genus claim is presented but the disclosure only describes a narrow species with no evidence that the genus is contemplated. See Ariad Pharms., Inc. v. Eli Lilly & Co., 598 F.3d 1336, 1349-50 (Fed. Cir. 2010) (en banc). The written description requirement is not necessarily met when the claim language appears in ipsis verbis in the specification. "Even if a claim is supported by the specification, the language of the specification, to the extent possible, must describe the claimed invention so that one skilled in the art can recognize what is claimed. The appearance of mere indistinct words in a specification or a claim, even an original claim, does not necessarily satisfy that requirement."Enzo Biochem, Inc. v. Gen-Probe, Inc., 323 F.3d 956, 968, 63 USPQ2d 1609, 1616 (Fed. Cir. 2002). The applicant’s disclosure does not describe how to perform the function of using an intelligent agent to determine actions in response to captured congestion indicators. The applicant’s intelligent agent is using machine learning to implement a behavioral policy but the applicant has not actually disclosed any technology related to machine learning for performing the functions claimed. Section 2161.01(I) of the MPEP states the following: When examining computer-implemented functional claims, examiners should determine whether the specification discloses the computer and the algorithm (e.g., the necessary steps and/or flowcharts) that perform the claimed function in sufficient detail such that one of ordinary skill in the art can reasonably conclude that the inventor possessed the claimed subject matter at the time of filing. An algorithm is defined, for example, as "a finite sequence of steps for solving a logical or mathematical problem or performing a task." Microsoft Computer Dictionary (5th ed., 2002). Applicant may "express that algorithm in any understandable terms including as a mathematical formula, in prose, or as a flow chart, or in any other manner that provides sufficient structure." Finisar Corp. v. DirecTV Grp., Inc., 523 F.3d 1323, 1340, 86 USPQ2d 1609, 1623 (Fed. Cir. 2008) (internal citation omitted). It is not enough that one skilled in the art could write a program to achieve the claimed function because the specification must explain how the inventor intends to achieve the claimed function to satisfy the written description requirement. See, e.g., Vasudevan Software, Inc. v. MicroStrategy, Inc., 782 F.3d 671, 681-683, 114 USPQ2d 1349, 1356, 1357 (Fed. Cir. 2015) (reversing and remanding the district court’s grant of summary judgment of invalidity for lack of adequate written description where there were genuine issues of material fact regarding "whether the specification show[ed] possession by the inventor of how accessing disparate databases is achieved"). If the specification does not provide a disclosure of the computer and algorithm in sufficient detail to demonstrate to one of ordinary skill in the art that the inventor possessed the invention a rejection under 35 U.S.C. 112(a) or pre-AIA 35 U.S.C. 112, first paragraph, for lack of written description must be made. In this case, the applicant provides a general reference to machine learning techniques that could be used to carry out the invention in paragraphs 50-54 but those of ordinary skill in the art would recognize that the reference to a general technique of using a “deep neural network” and using “algorithms like policy gradients or Q-learning” is not a disclosure of any actual machine learning algorithm sufficient to meet the written description requirements as defined by section 2161.01(I) of the MPEP. Those of ordinary skill would recognize the need for actual details of managing policy gradients or Q-learning techniques in order to provide meaningful feedback to a deep neutral network. Such a solution would require a sophistication for how the deep neural network would be configured and implemented and how the policy gradients and Q-learning techniques would be oriented and weighted. Paragraph 58 alleges that the “claims are intended to cover such variations and modifications as would occur to those skilled in the art” but does not provide any evidence for such conclusions. Paragraph 74 references a training phase and provides a description of the purpose of the training phase but does not provide any actual technical details about how the model is trained. It is very clear from the reading the disclosure that the applicant makes no contribution to the technical art of machine learning yet the entire implementation of the policy is dependent upon machine learning. Section 2162 of the MPEP states: To obtain a valid patent, a patent application must contain a full and clear description of the invention for which a patent is sought in the manner prescribed by 35 U.S.C. 112(a) or pre-AIA 35 U.S.C. 112, first paragraph. The requirement for an adequate written description ensures that the public receives something in return for the exclusionary rights that are granted to the inventor by a patent. The grant of a patent helps to foster and enhance the development and disclosure of new ideas and the advancement of scientific knowledge. Upon the grant of a patent in the U.S., information contained in the patent becomes a part of the information available to the public for further research and development, subject only to the patentee’s right to exclude others during the life of the patent In this case the public would only receive guidance to use generalized machine learning techniques in order to solve the claimed problem of implementing a policy comprises of specific actions to mitigate congestion. Those of ordinary skill would recognize that machine learning exists but they would also recognize that implementing machine learning techniques to solve specific problems requires specific technical solutions that are not detailed in the applicant’s disclosure. 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)(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. Claim(s) 1, 3, 4, 13, 15, 16, 18, and 20 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by U.S. Patent Number 10,873,533 to Ismailsheriff et al. As to claim 1, Ismailsheriff teaches a system for network congestion control, the system comprising a processor and a memory configured to: deploy, using the processor and the memory, an intelligent agent (network controller) in communication with one or more network devices in a network environment (paragraph 30, lines 34-54), wherein the one or more network devices comprise a plurality of network interface cards (NICs) (col. 53, lines 10-32); capture, using the processor and the memory, congestion indicators representing a congestion state of the network environment, wherein the congestion indicators comprise at least telemetry information generated by the one or more network devices in the network environment (step 504 in Figure 5); determine, using the intelligent agent having the captured congestion indicators as input, actions to be executed by the processor in response to the captured congestion indicators to change the congestion state of the network environment (step 508 in Figure 5); and execute the actions to adjust sending rates of one or more of the plurality of NICs (col. 40, line 36-col. 41, line 47). As to claim 3, see col. 40, line 36-col. 47, line 47. As to claim 4, see col. 27, lined 3-43. As to claims 13, 15, and 16, they are rejected for the same reasoning as claims 1, 3, and 4. As to claims 18 and 20, they are rejected for the same reasoning as claims 1 and 3. Claims Not Rejected With Prior Art Claims 5, 7-12, and 17 are not rejected with prior art. The details of the reward functions were not found to be suggested in the prior art in the context of the preceding claims. These claims are not indicated as allowable because the independent claims are rejected under 35 USC section 112(a) for lacking written description support and thus the dependent claims are also rejected as such. 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 DOUGLAS B BLAIR whose telephone number is (571)272-3893. The examiner can normally be reached Monday-Friday 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, Glenton Burgess can be reached at 571-272-3949. 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. /DOUGLAS B BLAIR/ Primary Examiner, Art Unit 2454
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Prosecution Timeline

Sep 03, 2024
Application Filed
Mar 24, 2026
Non-Final Rejection mailed — §102, §112
Jun 25, 2026
Applicant Interview (Telephonic)
Jun 29, 2026
Examiner Interview Summary
Jul 02, 2026
Response Filed
Jul 22, 2026
Final Rejection mailed — §102, §112
Oct 12, 2026
Response after Non-Final Action

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

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Prosecution Projections

2-3
Expected OA Rounds
72%
Grant Probability
80%
With Interview (+7.9%)
3y 11m (~1y 9m remaining)
Median Time to Grant
Moderate
PTA Risk
Based on 647 resolved cases by this examiner. Grant probability derived from career allowance rate.

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