Prosecution Insights
Last updated: October 02, 2026
Application No. 18/807,573

METHODS AND SYSTEMS FOR SUSTAINABLY OPERATING COMPUTER NETWORK EQUIPMENT

Non-Final OA §103
Filed
Aug 16, 2024
Examiner
PATEL, CHIRAG R
Art Unit
2454
Tech Center
2400 — Computer Networks
Assignee
Saudi Arabian Oil Company
OA Round
2 (Non-Final)
87%
Grant Probability
Favorable
2-3
OA Rounds
8m
Est. Remaining
99%
With Interview

Examiner Intelligence

Grants 87% — above average
87%
Career Allowance Rate
625 granted / 717 resolved
+29.2% vs TC avg
Strong +16% interview lift
Without
With
+15.6%
Interview Lift
resolved cases with interview
Typical timeline
2y 10m
Avg Prosecution
17 currently pending
Career history
732
Total Applications
across all art units

Statute-Specific Performance

§101
11.2%
-28.8% vs TC avg
§103
55.0%
+15.0% vs TC avg
§102
18.8%
-21.2% vs TC avg
§112
5.2%
-34.8% vs TC avg
Black line = Tech Center average estimate • Based on career data from 717 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 . 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. Claims 1-3 and 11-13 are rejected under 35 U.S.C. 103 as being unpatentable over Menon et al. – hereinafter Menon (US 2024/0403895) in view of Catalano et al. – hereinafter Catalano (US 20250317386) Menon discloses obtaining facility data from a computer network facility housing the computer and the plurality of computer network devices, the facility data comprising a facility temperature;([0046] In addition to the components described above, internet-of-things (IoT) devices 44 may be distributed throughout the upstream system 12, the midstream system 14, and the downstream system 16 and may collect information, perform analysis on data, send data related to a respective component or parameters (e.g., temperature, flow) of a component to a computing system or the like; [0094] Referring now to FIG. 4, at block 172, the sustainability platform system 72 may receive enterprise facility data and enterprise production data. ) storing the device data and the facility data in a system database; ([0056]; In some embodiments, the reports 92, the metadata regarding the reports 92, instructions regarding the preparation or formatting of the reports 92 may also be stored in a database or data storage for access by the sustainability platform system 72.) processing, by a sustainability module communicatively coupled to the system database, the device data and the facility data stored in the system database to generate using a sustainability module resulting in a computer network metrics summary, wherein the processing comprises analyzing the device data together with the facility data to determine power usage characteristics of the plurality of computer network devices within the computer network facility,([0074] The combined heat and power (CHP) system 126 may perform analysis to determine methods for reusing emissions such as carbon dioxide to increase efficiency. For instance, heat can be recaptured during a portion of a process and the heat can be applied to a heat exchanger to produce energy or perform some other function using the heat recaptured from performing another process within the enterprise. As such, the CHP system 126 may request image data and infrastructure or design data for facilities of the enterprise from the sustainability platform system 72 to identify process components that may produce heat or power that may be recaptured and recycled for other functions within the enterprise. In any case, the CHP system 126 may help the sustainability platform system 72 determine action plans 90 that improve energy efficiency and reduce facility carbon emissions.) wherein the computer network, metrics summary comprises at least a portion of the processed device data and the processed facility data. ([0097] In some embodiments, the facility data may include energy usage data including an amount of energy (e.g., electricity, gas, kilowatt hours) consumed within the building 56 over a period of time. In addition, the energy usage data may include measurements from energy sensors and other IoT devices that may be within the building 56, smart meters associated with the building 56, and the like ; [0104]; As such, the IoT data may represent real time data regarding current operational and consumption parameters for devices within a structure of the enterprise, equipment used within the enterprise, and the like. ) updating the system data using the computer network metrics summary ([152] If the simulated action plan 90 of block 236 is determined to have acceptable sustainability variables (e.g., at block 268), the action plan 90 may be sent to the enterprise system, as in block 240. As should be appreciated, when implemented, the new action plan 90 changes the sustainability model to an updated sustainability model.) transmitting the computer network metrics summary from the sustainability module to a user interface ([0134] In some embodiments, the action plans 90 may be stored in the sustainability database 94 for analysis or retrieval at another time. In this way, the sustainability platform system 72 may evaluate action plans 90 prior to sending the sustainability model to engineering workflow systems 78 to identify recommendations more efficiently if the respective action plans 90 are applicable.; [0139] In some embodiments, the sustainability platform system 72 may receive multiple sustainability variable datasets for optimization and may identify multiple engineering workflow systems 78 to coordinate with to determine action plans 90. By evaluating each sustainability variable data in isolation, the sustainability platform system 72 may identify solutions in parallel and present action plans 90 that optimize for different sustainability variables to provide a user more context to select the generated action plans 90. determining, via the user interface, a sustainability adjustment of the computer and the plurality of computer network device based, at least in part, on the computer network metrics summary; ([0169]; As with the other datasets received at blocks 292-300, if the change in sustainability parameters is greater than some threshold, the sustainability platform system 72 may identify abatement technologies, updated action plans 90, or the like to provide an immediate remedy. In some embodiments, the user input data may include adjustments to the action plan 90, thereby allowing manual additions or subtractions of parts of the action plan 90 to enable user control to counter the undesired sustainability parameters) Menon fails to disclose transmitting network data between a computer and a plurality of computer network devices; applying the sustainability adjustment to the computer and the plurality of computer network devices to change a transmission of the network data between the computer and the plurality of computer network devices; wherein applying the sustainability adjust optimizes the power usage of the plurality of computer network devices within the computer network facility. Catalano discloses transmitting network data between a computer and a plurality of computer network devices; ([0002]; The packet is then transmitted using the path to the next device.) applying the sustainability adjustment to the computer and the plurality of computer network devices to change a transmission of the network data between the computer and the plurality of computer network devices ( [0013]; As the packet traverses the path, the header can be updated with the energy demand of each hop such that the energy demand of the ‘green’ path can be compared to the energy demand based on a standard routing policy. This improves the infrastructure by allowing the customer and the operator of the infrastructure to determine whether sustainability targets are being met) wherein applying the sustainability adjustment optimizes the power usage of the plurality of computer network devices within the computer network facility ( [0019]; For example, in selecting a path to a next device in route to the endpoint, a device will be associated with a more favorable sustainability metric if the device has a lower energy demand, for example, by employing power conservation mechanisms or otherwise being more energy efficient, if the device is located in a data center that is managed to meet sustainability goals, if the device operates from a power grid or source that utilizes renewable energy, and so on. ) It would have been obvious before the earliest effective filing date for the teachings of Menon to be modified to include a sustainability module to adjust the computer for the routing according to the facility and the device data. This would have been advantageous for the network to reduce the carbon foot and environmental impacts. (Catalano, [0001]) As per claim 2, Menon / Catalano disclose the method of claim 1. Catalano discloses wherein the sustainability adjustment changes an operation of the computer network facility. ( [0013]; As the packet traverses the path, the header can be updated with the energy demand of each hop such that the energy demand of the ‘green’ path can be compared to the energy demand based on a standard routing policy. This improves the infrastructure by allowing the customer and the operator of the infrastructure to determine whether sustainability targets are being met) As per claim 3, Menon / Catalano disclose the method of claim 2. Catalano discloses wherein the sustainability adjustment changes the transmission of the network data between the computer and the plurality of computer network devices while maintaining a communication link between the computer and at least one of the plurality of computer network devices. ([0049; some implementations, a sustainability metric 507 associated with a path to a device is based on the energy demand of the link between the first device 550 and the next device 550, 551, 553) As per claim 11, please see the discussion under claim 1 as similar logic applies. As per claim 12, please see the discussion under claim 2 as similar logic applies. As per claim 13, please see the discussion under claim 3 as similar logic applies. Claims 4-7, 9-10, 14-17 and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Menon(US 2024/0403895) /Catalano (US 20250317386) further in view of Jain (US 2025/0023807) As per claim 4, Menon/ Catalano disclose the method of claim 1. Menon / Catalano fails to disclose wherein processing the device data and the facility data using the sustainability module comprises creating a device profile for each of the plurality of computer network devices, resulting in a plurality of device profiles Jain discloses wherein processing the device data and the facility data using the sustainability module comprises creating a device profile for each of the plurality of computer network devices, resulting in a plurality of device profiles. ( [0106] In still further embodiments, the process 700 may refresh the list of subscribing network nodes (block 760). Periodically, the control plane can update its list of subscribed network nodes to ensure that it is always up to date with the current participants in the energy efficiency service.) It would have been obvious before the earliest effective filing date of the invention for the combined teachings of Menon / Catalano to be modified so that the sustainability module creates a device profile of each network device. This would have been advantageous because it have reduced energy cost and carbon footprint on the network infrastructure. (Jain, [0003]) As per claim 5, Menon / Catalano / Jain disclose the method of claim 4. Menon discloses wherein the device profile of each of the plurality of computer network devices comprises a record of past power usage of the computer network device. ([0107]; The drilling activity workflow may include planning of rig activities for proposing a drilling plan accounting for the well profile, well activities, emission forecasts, and the like. As such, the enterprise production data may also include the real-time monitoring of emissions from rig activities, such as power consumption by controllers (e.g., PLCs) and fuel consumption based on data from flow meters. In some embodiments, GHG sensors may be positioned at various locations.) As per claim 6, Menon / Catalano / Jain disclose the method of claim 4. Catalano discloses wherein processing the device data and the facility data using the sustainability module further comprises creating a plurality of routing profiles for the transmission of network data between the computer and the plurality of computer network devices. ([0013]; a packet is provided with a sustainability header that enables the setting of a sustainability policy used for routing the packet within the infrastructure ; [0038] Each switch 302, 304, 306 also includes a routing table 330. The routing table 330 includes, among other elements, an IP address and/or port of a next hop for each route to each destination endpoint address in the fabric 308.) It would have been obvious before the earliest effective filing date for the combined teachings of Menon / Jain to be further modified so that the device and facility data creates a plurality of routing profiles in a routing table. This would have been advantageous for the network to reduce the carbon foot and environmental impacts. (Catalano, [0001]) As per claim 7, Menon / Jain/ Catalano disclose the method of claim 6. Catalano discloses wherein each of the plurality of routing profiles defines a network data transmission pathway for the transmission of network data between the computer and the plurality of computer network devices based, at least in part, on the device data and the facility data. [0019] As used herein, ‘sustainability’ refers to environmental and ecological sustainability and the capacity to promote so-called ‘green’ initiatives such as energy, resource, and ecological conservation and mitigation against water pollution, air pollution, fossil-fuel depletion, ozone depletion, climate change, and so on.; [0020] In accordance with aspects of the present disclosure, a fabric switch or other fabric device includes a sustainability module that makes routing decisions based on sustainability metrics.) As per claim 9, Menon / Catalono / Jain disclose the method of claim 7. Catalano discloses wherein the computer network metrics summary is created based on the plurality of device profiles and the plurality of routing profiles and the sustainability adjustment is applied to the computer and the plurality of computer network devices automatically. ([0020] In accordance with aspects of the present disclosure, a fabric switch or other fabric device includes a sustainability module that makes routing decisions based on sustainability metrics. In some examples, the sustainability module identifies a sustainability policy associated with a packet from a header of the packet. The sustainability module selects a path to a next device along a route to a destination endpoint, or a next hop, based on a sustainability metric associated with the path and the sustainability policy. ) As per claim 10, Menon / Catalano / Jain disclose the method of claim 1. Jain discloses wherein the sustainability module comprises an anomaly detector configured to determine an anomaly based on the device data and the facility data and report the anomaly to the user interface. ([0089] In a number of embodiments, the process 500 can collect network data relating to end-to-end paths (block 520). The control plane may gather real-time data about the network's topology, traffic patterns, and the number of connected devices. In certain embodiments, the control plane may use this network condition data to analyze the current state of the network and identify potential areas or opportunities for energy optimization, such as, but not limited to, underutilized devices or network segment) As per claim 14, please see the discussion under claim 4 as similar logic applies. As per claim 15, please see the discussion under claim 5 as similar logic applies. As per claim 16, please see the discussion under claim 6 as similar logic applies. As per claim 17, please see the discussion under claim 7 as similar logic applies. As per claim 19, please see the discussion under claim 9 as similar logic applies. As per claim 20, please see the discussion under claim 10 as similar logic applies. Claim 8 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Menon (US 2024/0403895) / Jain (US 2025/0023807) / Catalano (US 20250317386) further in view of Kommula et al. – hereinafter Kommula (US 2025/0088427) As per claim 8, Menon / Jain / Catalano disclose the method of claim 6. The combined teachings of Menon / Jain / Catalano fail to disclose wherein the sustainability module comprises a smart engine that uses at least one machine learning model to process the device data and the facility data. Kommula discloses wherein the sustainability module comprises a smart engine that uses at least one machine learning model to process the device data and the facility data.. ([2382] In embodiments, artificial intelligence modules 17904 may include and/or provide access to a neural network module 17914. In embodiments, the neural network module 17914 is configured to train, deploy, and/or leverage artificial neural networks (or “neural networks”) on behalf of an intelligence service client 17936. It is noted that in the description, the term machine learning model may include neural networks, and as such, the neural network module 17914 may be part of the machine learning module 17912. ) It would have been obvious before the earliest effective filing date for the combined teachings of Menon / Jain / Catalano to be further modified so that the device and facility data is processed by the smart engine of the neural networks. This would have advantageous to meet the green energy goals from the service level agreements. (Kommula, [0004]) As per claim 18, please see the discussion under claim 8 as similar logic applies. Response to Arguments Applicant’s arguments with respect to claims 1-20 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. 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 theexaminer should be directed to Chirag R Patel whose telephone number is (571)272-7966. The examiner can normally be reached on Monday to Friday from 9:00AM to 6:00PM. If attempts to reach the examiner by telephone are unsuccessful, theexaminer's supervisor, Glenton Burgess, can be reached on 571-272-3949. The fax phone number for the organization where this application or proceedingis assigned is 571-273-8300. Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status informationfor published applications may be obtained from either Private PAIR or PublicPAIR. Status information for unpublished applications is available throughPrivate PAIR only. For more information about the PAIR system, seehttp://pairdirect.uspto.gov. Should you have questions on access to the PrivatePAIR system, contact the Electronic Business Center (EBC) at 866-217-9197(toll free). /Chirag R Patel/ Primary Examiner, Art Unit 2454
Read full office action

Prosecution Timeline

Aug 16, 2024
Application Filed
Feb 17, 2026
Non-Final Rejection mailed — §103
Apr 28, 2026
Response Filed
Jul 07, 2026
Final Rejection mailed — §103
Sep 01, 2026
Response after Non-Final Action

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Prosecution Projections

2-3
Expected OA Rounds
87%
Grant Probability
99%
With Interview (+15.6%)
2y 10m (~8m remaining)
Median Time to Grant
Moderate
PTA Risk
Based on 717 resolved cases by this examiner. Grant probability derived from career allowance rate.

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