DETAILED ACTION
This communication is responsive to Amendment filed 10/30/2025.
Claims 1-20 are pending in this application. Claims 1, 11, and 20 are independent claims. In Amendment, claims 1, 6, 8, 11, 16, 18 and 20 are amended. This Office Action is made final.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim(s) does/do not fall within at least one of the four categories of patent eligible subject matter because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Claim(s) 1, 11, and 20 is/are method, apparatus, and medium respectively directed to an abstract idea under the mental process wherein the limitation “using…to estimate an energy consumption….in the computer network” can be mentally done in human mind with pen and paper given the data information of the particular entity power consumption in the network by observation, evaluation, and judgment as required under Prong I step 2A. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because all other limitations in these independent claims including limitations “one or more network interfaces….when executed configured to”; “obtain…computer network”; “obtain computer network”; and “train … the energy consumption information” and “by the device” are considered as additional elements under Prong II step 2A, however these additional elements are either well known components of computer system/network or pre-activity solution for gathering/collecting data or merely computer instruction as “apply it” using generic computing equipment to perform abstract idea wherein all of these additional elements either individually or in combination are insignificant amount to the judicial exception and does not integrate into the practical application. In addition, these additional elements are either well known components of computer system/network or pre-activity solution for gathering/collecting data or merely computer instruction as “apply it” using generic computing equipment to perform abstract idea wherein all of these additional elements either individually or in combination are insignificant amount to the judicial exception as identified in MPEP 2106.05(d)/(f).
Re claims 2-10 and 12-19, these claims are similarly rejected as depending on claims 1 and 11 respectfully. In addition, these claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception as evidently seen in MPEP 2106.05.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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.
(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 1-3, 5-9, 11-13, and 15-20 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Engelberg et al. (U.S. 2023/0021961 A1).
Re claim 1, Engelberg discloses in Figures 1-6 a method (e.g. abstract) comprising: obtaining, by a device, telemetry data regarding a plurality of entities in a computer network (e.g. Figure 2 with component 222 and paragraph [0054]); obtaining, by the device, energy consumption information for the plurality of entities in the computer network (e.g. Figure 2 with component 224 and paragraph [0033 and 0054]); training, by the device, a machine learning model to estimate energy consumption by an entity in the computer network, based on the telemetry data and the energy consumption information (e.g. Figures 3-5 and paragraphs [0034 and 0037]); and using, by the device, the machine learning model to estimate an energy consumption for a digital twin of a particular entity in the computer network, to assess an estimated change in energy consumption by the particular entity were a certain action performed in the computer network (e.g. Figures 3-5 and paragraphs [0033-0036]).
Re claim 2, Engelberg discloses in Figures 1-6 the certain action is performed in the computer network, when the estimated change in energy consumption indicates a decrease in energy consumption and a performance metric of the computer network is predicted to remain at an acceptable level (e.g. paragraphs [0005 and 0039-0040 and 0052]).
Re claim 3, Engelberg discloses in Figures 1-6 providing, by the device and to a user interface, an indication of energy consumed by one or more entities in the computer network that is estimated using the machine learning model (e.g. Figure 1, paragraphs [0019 and 0063]).
Re claim 5, Engelberg discloses in Figures 1-6 the energy consumption information is obtained at different granularities for the plurality of entities (e.g. Figures 4-5 and paragraphs [0046-0047]).
Re claim 6, Engelberg discloses in Figures 1-6 the telemetry data is indicative of traffic characteristics of network traffic flowing through a port or interface of the particular entity in the plurality of entities or through the particular entity as a whole (e.g. Figure 1 and paragraphs [0019-0021 and 0033]).
Re claim 7, Engelberg discloses in Figures 1-6 the network traffic is associated with a particular application accessed via the computer network (e.g. Figure 1 and paragraph [0021]).
Re claim 8, Engelberg discloses in Figures 1-6 using active learning to increase performance of the machine learning model for a combination of values of the telemetry data and the energy consumption information for which there is high uncertainty (e.g. paragraphs [0034-0037] as part of training ML).
Re claim 9, Engelberg discloses in Figures 1-6 the telemetry data is indicative of a hardware or software configuration of one of the plurality of entities (e.g. paragraph [0054]).
Re claim 11, it is an apparatus claim having similar limitations as cited in claim 1. Thus, claim 11 is also rejected under the same rationale as cited in the rejection of claim 1 above.
Re claim 12, it is an apparatus claim having similar limitations as cited in claim 2. Thus, claim 12 is also rejected under the same rationale as cited in the rejection of claim 2 above.
Re claim 13, it is an apparatus claim having similar limitations as cited in claim 3. Thus, claim 13 is also rejected under the same rationale as cited in the rejection of claim 3 above.
Re claim 15, it is an apparatus claim having similar limitations as cited in claim 5. Thus, claim 15 is also rejected under the same rationale as cited in the rejection of claim 5 above.
Re claim 16, it is an apparatus claim having similar limitations as cited in claim 6. Thus, claim 16 is also rejected under the same rationale as cited in the rejection of claim 6 above.
Re claim 17, it is an apparatus claim having similar limitations as cited in claim 7. Thus, claim 17 is also rejected under the same rationale as cited in the rejection of claim 7 above.
Re claim 18, it is an apparatus claim having similar limitations as cited in claim 8. Thus, claim 18 is also rejected under the same rationale as cited in the rejection of claim 8 above.
Re claim 19, it is an apparatus claim having similar limitations as cited in claim 9. Thus, claim 19 is also rejected under the same rationale as cited in the rejection of claim 9 above.
Re claim 20, it is a medium claim having similar limitations as cited in claim 1. Thus, claim 20 is also rejected under the same rationale as cited in the rejection of claim 1 above.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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 4 and 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Engelberg et al. (U.S. 2023/0021961 A1) in view of Chen (U.S. 2016/0277266 A1).
Re claim 4, Engelberg fails to disclose in Figures 1-6 the certain action comprises shutting down an interface on a switch in the computer network or routing traffic in the computer network via a different path. However, Chen discloses the certain action comprises shutting down an interface on a switch in the computer network or routing traffic in the computer network via a different path (e.g. paragraph [0038 and 0067]). Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of claimed invention to add the certain action comprises shutting down an interface on a switch in the computer network or routing traffic in the computer network via a different path as conceptually seen in Chen’s invention into Engelberg et al.’s invention because it would enable to reduce the energy consumption by shutdown the component.
Re claim 14, it is an apparatus claim having similar limitations as cited in claim 4. Thus, claim 14 is also rejected under the same rationale as cited in the rejection of claim 4 above.
Claim 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Engelberg et al. (U.S. 2023/0021961 A1) in view of Kannan et al. (U.S. 2023/0205591 A1).
Re claim 10, Engelberg fails to disclose in Figures 1-6 the energy consumption information includes a rack-level energy consumption measurement for a portion of the plurality of entities that share a common rack. However, Kannan et al. disclose in Figures the energy consumption information includes a rack-level energy consumption measurement for a portion of the plurality of entities that share a common rack (e.g. abstract, Figures 9-11 and paragraphs [0106 and 0358]). Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of claimed invention to add the energy consumption information includes a rack-level energy consumption measurement for a portion of the plurality of entities that share a common rack as conceptually seen in Kannan et al.’s invention into Engelberg et al.’s invention because it would enable to manage and optimize power distribution across the rack system.
Response to Arguments
Applicant's arguments filed 10/30/2025 have been fully considered but they are not persuasive.
The applicant argues in pages 10-11 for claims rejected under 35 USC 101 as directing to an abstract idea under the mental process, particularly the independent claims 1, 11, and 20 that the recited claim language is not a mathematical concept, a method of organizing human activity or a mental process but instead of a mechanism for automatically and dynamically assessing an estimated change in energy consumption by the entity.
The examiner respectfully submits that the independent claim is broadly claiming to estimate the energy consumption for a digital twin of a particular entity in the computer network in order to assess an estimate change in energy consumption by the particular entity were a certain action performed. This limitation itself is merely and broadly claiming to estimate the energy consumption of device/component if certain action performed which clearly can be done by any ordinary skill in the art to review/monitor/observe the energy consumption data and then perform an analysis/computation/evaluation by means of mathematical or logical operations in order to determine the energy consumption. For example, the ones can review previous power consumption of certain component and predict/estimate the energy/power consumption based on the historical data. In addition, the alleged limitations in the remark including the detail do not exist in the current claimed language. Therefore, the abstract idea limitation identified in Prong I step 2A is maintained.
The applicant argues in pages 12-13 for claims that the additional elements under Prong II step 2A claiming the detail as listed in the remark including how and when to use a machine LM to estimate energy consumption for a digital twin of a particular entity in a computer network.
The examiner respectfully submits that the detail including how and when to use a machine LM to estimate energy consumption for a digital twin of a particular entity in a computer network is not in neither the claim, nor it is listed/explained in the remark. The claim is merely and broadly claiming the machine ML is trained and used to estimate energy consumption. Nothing in the claim would detail how and when to use the machine LM to model/estimate the energy consumption for a digital twin of a particular entity in a computer network. Therefore, the rejection as directing an abstract idea under mental process is maintained.
The applicant argues in pages 14-15 for independent claims that the cited reference fail to disclose obtaining telemetry data as listed in the remark which can be seen in specification page 26 lines 12 – page 27 line 5.
The examiner respectfully submits that the detail of how to obtain the telemetry data and what would be the telemetry data as seen in the specification are not recited in the claim. The claim is merely claiming to obtain the telemetry data. Under the BRI, any data obtained from the entity is considered as telemetry data. The examiner does not consider any specific example from the specification into the claim. Therefore, the reference is reasonably disclose the claimed limitation of obtaining telemetry data from the entity over the network as claimed.
The applicant argues in page 15 for claim 6 that the reference does not teach the telemetry data is indicative of traffic characteristics of network flowing.
The examiner respectfully submits that the cited reference does reasonably disclose the claimed limitations under BRI wherein the telemetry data is collected from the sensors of the entity that are on the network. Thus, the telemetry is either directly/indirectly associated/indicative of traffic/communication of certain ports as power consumption to provide the service.
The applicant argues in page 11 for claim 5 that the reference does not teach the energy consumption information is obtained at different granularities.
The examiner respectfully submits that this limitation can be reasonably seen in the reference wherein each of entity associated with different level of the network topology. Thus, estimation of energy consumption of each of the entity would be associated with different level of granularities at broad level.
The applicant argues in page 11 for claim 8 that reference does not teach using active learning to increase performance of the machine ML.
The examiner respectfully submits that the citation clearly indicate that the machine ML is performed/trained over multiple iterations with each iteration adjusting one or more parameters of the ML model wherein the further iteration would increase the performance of the machine ML in term of predicting/estimating.
Conclusion
THIS ACTION IS MADE FINAL. 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 PHUOC H NGUYEN whose telephone number is (571)272-3919. The examiner can normally be reached M-F: 7:30 am -3:30 pm.
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/PHUOC H NGUYEN/Primary Examiner, Art Unit 2451