Prosecution Insights
Last updated: May 29, 2026
Application No. 18/603,119

RESOLVING A TOPOLOGY OF A DYNAMIC NETWORK USING MACHINE LEARNING

Non-Final OA §102
Filed
Mar 12, 2024
Examiner
DOBSON, DANIEL G
Art Unit
2634
Tech Center
2600 — Communications
Assignee
Aalyria Technologies Inc.
OA Round
1 (Non-Final)
82%
Grant Probability
Favorable
1-2
OA Rounds
6m
Est. Remaining
89%
With Interview

Examiner Intelligence

Grants 82% — above average
82%
Career Allowance Rate
526 granted / 645 resolved
+19.6% vs TC avg
Moderate +7% lift
Without
With
+7.1%
Interview Lift
resolved cases with interview
Typical timeline
2y 8m
Avg Prosecution
12 currently pending
Career history
655
Total Applications
across all art units

Statute-Specific Performance

§101
2.4%
-37.6% vs TC avg
§103
73.3%
+33.3% vs TC avg
§102
12.5%
-27.5% vs TC avg
§112
6.1%
-33.9% vs TC avg
Black line = Tech Center average estimate • Based on career data from 645 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 . 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. Claim(s) 1,2,6,8-11, and 15-17 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by United States Patent 11,956,021 B1 to Rofougaran et al. Regarding Claim 1, Rofougaran discloses a method for resolving connections among nodes of a dynamic network based on network conditions (Col. 34, ll. 45-55, P2P free space networks is dynamically reconfigured based on network monitoring and performance data), the method comprising: determining connections among nodes of the dynamic network based on network conditions (Col. 35, ll. 40-60, processor (502) instructs the network to use a determined back-up path), wherein: the nodes comprise free-space optical communication nodes and the connections among the nodes are dynamically modifiable (Col. 35, ll. 55-65, route of free-space optical network is dynamically changed), and the connections among the nodes are determined by: providing, to a trained machine learning model, A) one or more network conditions relative to the nodes and B) a representation of a universe of potential connections among the nodes (Fig. 5, processor (502) is controlled by ML model (512) with network condition inputs (516,518) and potential connection inputs (514, 514A, 514B); and resolving, by the trained machine learning model, connections between pairs of the nodes, wherein the resolved connections define a first topology for the dynamic network (Fig. 5, processor (502) uses ML model (512) to determine the location and transmission angles of the backup path; Col. 36, ll. 50-67); and instructing at least a portion of the nodes to modify or initiate point-to-point connections according to the resolved connections between pairs of the nodes (Col. 48, ll. 45-55, processor (502) causes nodes to establish P2P free-space laser links between each pair of optical nodes), wherein: the instructing modifies the nodes to arrange the dynamic network according to the first topology (Fig. 12C, 1230, back-up optical path is selected from the determined options), and data is communicated through the dynamic network arranged according to the first topology (Col. 35, ll. 54-60, the back-up optical path becomes the communications route). Regarding Claim 2, Rofougaran discloses wherein the first topology for the dynamic network is arranged when the portion of the nodes are modified according to the instructing and another portion of nodes maintain previously established point-to-point connections (Fig. 6A, some nodes changes connection and some nodes stay the same when the obstruction only a portion of the network encounters a problem.) Regarding Claim 6, Rofougaran discloses wherein one or more of the nodes a comprised by satellites and the instructing the portion of the nodes to modify or initiate point-to-point connections causes movement of the one or more nodes (Col. 30, ll. 15-20, satellite nodes; Col. 34, ll. 18-33, nodes configured to move.) Regarding Claim 8, Rofougaran discloses wherein the network conditions relative to the nodes comprise environmental conditions (Fig. 5, sensor date (516,518) includes temperature data; Col. 24, ll. 34-38.) Regarding Claim 9, Rofougaran discloses wherein the modifiable connections among the nodes comprise free-space optical communication connections and radio frequency connections (Col. 4, ll. 2-9, hybrid photonic/RF connections.) Regarding Claim 10, Rofougaran discloses a computer-readable storage medium storing instructions that, when executed by a computing system, cause the computing system to perform a process for resolving connections among nodes of a dynamic network based on network conditions (Col. 48, ll. 55-Col. 49, ll. 1-20; processor running codes stored on a CRM; Col. 34, ll. 45-55, P2P free space networks is dynamically reconfigured based on network monitoring and performance data) the process comprising: determining connections among nodes of the dynamic network based on network conditions (Col. 35, ll. 40-60, processor (502) instructs the network to use a determined back-up path), wherein: the nodes comprise free-space optical communication nodes and the connections among the nodes are dynamically modifiable (Col. 35, ll. 55-65, route of free-space optical network is dynamically changed), and the connections among the nodes are determined by: providing, to a trained machine learning model, A) one or more network conditions relative to the nodes and B) a representation of a universe of potential connections among the nodes (Fig. 5, processor (502) is controlled by ML model (512) with network condition inputs (516,518) and potential connection inputs (514, 514A, 514B); and resolving, by the trained machine learning model, connections between pairs of the nodes, wherein the resolved connections define a first topology for the dynamic network (Fig. 5, processor (502) uses ML model (512) to determine the location and transmission angles of the backup path; Col. 36, ll. 50-67); and instructing at least a portion of the nodes to modify or initiate point-to-point connections according to the resolved connections between pairs of the nodes (Col. 48, ll. 45-55, processor (502) causes nodes to establish P2P free-space laser links between each pair of optical nodes), wherein: the instructing modifies the nodes to arrange the dynamic network according to the first topology (Fig. 12C, 1230, back-up optical path is selected from the determined options), and data is communicated through the dynamic network arranged according to the first topology (Col. 35, ll. 54-60, the back-up optical path becomes the communications route). Regarding Claim 11, Rofougaran discloses wherein the modifiable connections among the nodes comprise free-space optical communication connections and/or radio frequency connections, the resolved connections comprise connections between pairs of nodes, and the connections that the portion of nodes are instructed to modify or initiate comprise point-to-point connections (Col. 4, ll. 2-9, hybrid photonic/RF connections; Col. 48, ll. 45-55, processor (502) causes nodes to establish P2P free-space laser links between each pair of optical nodes). Regarding Claim 15, Rofougaran discloses wherein one or more of the nodes a comprised by satellites and the instructing the portion of the nodes to modify or initiate point-to-point connections causes movement of the one or more nodes (Col. 30, ll. 15-20, satellite nodes; Col. 34, ll. 18-33, nodes configured to move.) Regarding Claim 16, Rofougaran discloses a computing system for resolving connections among nodes of a dynamic network based on network conditions (Col. 34, ll. 45-55, P2P free space networks is dynamically reconfigured based on network monitoring and performance data), the computing system comprising: one or more processors (Fig. 5, processor (502)); and one or more memories storing instructions that, when executed by the one or more processors Col. 48, ll. 55-Col. 49, ll. 1-20; processor running codes stored on a CRM), cause the computing system to perform a process comprising: determining connections among nodes of the dynamic network based on network conditions (Col. 35, ll. 40-60, processor (502) instructs the network to use a determined back-up path), wherein: the nodes comprise free-space optical communication nodes and the connections among the nodes are dynamically modifiable (Col. 35, ll. 55-65, route of free-space optical network is dynamically changed), and the connections among the nodes are determined by: providing, to a trained machine learning model, A) one or more network conditions relative to the nodes and B) a representation of a universe of potential connections among the nodes (Fig. 5, processor (502) is controlled by ML model (512) with network condition inputs (516,518) and potential connection inputs (514, 514A, 514B); and resolving, by the trained machine learning model, connections between pairs of the nodes, wherein the resolved connections define a first topology for the dynamic network (Fig. 5, processor (502) uses ML model (512) to determine the location and transmission angles of the backup path; Col. 36, ll. 50-67); and instructing at least a portion of the nodes to modify or initiate point-to-point connections according to the resolved connections between pairs of the nodes (Col. 48, ll. 45-55, processor (502) causes nodes to establish P2P free-space laser links between each pair of optical nodes), wherein: the instructing modifies the nodes to arrange the dynamic network according to the first topology (Fig. 12C, 1230, back-up optical path is selected from the determined options), and data is communicated through the dynamic network arranged according to the first topology (Col. 35, ll. 54-60, the back-up optical path becomes the communications route). Regarding Claim 17, Rofougaran discloses wherein the modifiable connections among the nodes comprise free-space optical communication connections and/or radio frequency connections, the resolved connections comprise connections between pairs of nodes, and the connections that the portion of nodes are instructed to modify or initiate comprise point-to-point connections (Col. 4, ll. 2-9, hybrid photonic/RF connections; Col. 48, ll. 45-55, processor (502) causes nodes to establish P2P free-space laser links between each pair of optical nodes). Allowable Subject Matter Claims 3-5,7,12-14,18-20 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to DANIEL G DOBSON whose telephone number is (571)272-9781. The examiner can normally be reached M-F 8-5 EST. 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, Kenneth Vanderpuye can be reached at 5712723078. 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. /DANIEL G DOBSON/ Primary Examiner, Art Unit 2634 05/02/2026
Read full office action

Prosecution Timeline

Mar 12, 2024
Application Filed
May 06, 2026
Non-Final Rejection mailed — §102 (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

1-2
Expected OA Rounds
82%
Grant Probability
89%
With Interview (+7.1%)
2y 8m (~6m remaining)
Median Time to Grant
Low
PTA Risk
Based on 645 resolved cases by this examiner. Grant probability derived from career allowance rate.

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