DETAILED ACTION
Notice of 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 .
Claims 1-14 are pending and are rejected.
Information Disclosure Statement
The information disclosure statements (IDSs) filled on 12/12/2025 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements are being considered by the examiner.
Drawings
Drawings filled on 09/30/2024 are acceptable for the examination purpose.
Claim Objections
Claim(s) 1, 5 8 and 12 is/are objected to because of the following informalities:
Regarding claims 1 and 8, claims recite, serving the data center to be served that is redundant and sounds vague. Further, it is not clear what it means by to be served (happening in future), if data center is already being served (serving the data center now). This creates ambiguity as to whether “serving” is acted in the present or in the future.
Appropriate correction is required.
Regarding claims 1 and 8, claims recite, selecting, from among multiple different electrical power sources that include one or more electric utility sources, one or more electrical power sources for the data center corresponding to the future time. In this limitation, selection of electrical power sources “corresponding to the future time” is vague and it isn’t clear how the system makes a guess for selection of power sources that corresponds to the future time.
Applicant’s specification ¶22 describes, “so that the systems may select particular power sources and power-using devices in response to making a determination about what the system will need in order to operate in the near future,” such that it describes system makes a determination what power sources are needed in order to operate in the future.
However, claimed limitation describe vague statement of selection of power sources corresponding to the future time, thus it isn’t clear how system makes guess about what power sources the data center will need in order to operate in the near future.
Regarding claims 1 and 8, for the same reasons, the future time, in the limitation, selecting one or more cooling sources for the data center corresponding to the future time is not clear.
Examiner notes that the use of the phrase corresponding to the future time makes the meaning of the above describes limitations vague, because it infers that the system can guess what selection will happen at a guessed future time (vague).
Appropriate correction is required.
Regarding claims 1, 5 8 and 12, claims recite, in several places, computer data center and the computer data center. However, in other places in the claims it is referred to as data center and the data center which creates inconsistency throughout these claims and the other dependent claims. To maintain consistency, either of “computer data center” or “data center” should be used throughout the claims.
Appropriate correction is required.
Claim Rejections - 35 USC § 112
35 U.S.C. 112(a)
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.
Claims 1-15 rejected under 35 U.S.C. 112(a) 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 at the time the application was filed, had possession of the claimed invention.
Claims 1 and 8:
Claims recite the limitation, minimize an unfavorable result associated with operating the computer data center. The feature unfavorable result is not disclosed by the applicant’s specification. Specification doesn’t provide any clear and concise description what “results” are and what results are unfavorable and how these results being quantified as being unfavorable.
One of the ordinary skilled in the art will understand that there can be many results that are unfavorable to the associated with operating the computer data center. However, claim limitation or the specification doesn’t provide any clear and concise description of what results are unfavorable and how they are unfavorable associated with operating the computer data center.
Therefore, one of the ordinary skilled in the art, without undue experimentation, based on the description in the specification, will not understand what results are being unfavorable and how these results being quantified as being unfavorable so that the system can take action to minimize those results.
Appropriate correction is required.
Claims 6 and 13:
Claims recite the limitation, wherein the one or more cooling sources are selected based on physical parameters of multiple different candidate cooling sources, and operational parameters of the multiple different candidate cooling sources that were learned by a computer system over time. These features in combination with learned by a computer system over time is not disclosed by the applicant’s specification. Specification doesn’t provide any disclosure of a learning process where operational parameters of the multiple different candidate cooling sources were learned by a computer system and the algorithm to perform such learning.
Specification only describes, in
¶28: update and tweak model as part of learning process,
¶32: gather data on its actual performance compared to its expected performance, and may provide that data to a machine learning system as training data for updating a model that is used for making the determinations
¶59: the learning system 212 can determine whether the system 200 accurately maintained an appropriate state of the system 200… the learning system 212 may use such variance or lack of variance to update a model of the system 200.
However, specification provides no details regarding, what type of learning is used, what inputs constitutes operational parameters of the multiple different candidate cooling sources, what are the learned parameters and how they are feed back to the system. Since specification states in ¶31: The particular type of machine learning to be used, the data to be collected, and the manner in which the data is processed, may vary based on the particular application, the specification admits it lacks specific disclosure of that specific learning computer.
Therefore, one of the ordinary skilled in the art, without undue experimentation or undue burden, based on the description in the specification, will not be able to come up with the claimed learning and learning computer given the absence of disclosure of detailed algorithm for the learning process as described above.
Appropriate correction is required.
Dependent claims 2-7 and 9-14:
Based on their dependencies in claim 1, claims 2-7 are also rejected under 35 U.S.C. 112(a) for the same reasons.
Based on their dependencies in claim 8, claims 9-14 are also rejected under 35 U.S.C. 112(a) for the same reasons.
35 U.S.C. 112(b)
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
Claims 2-3 and 9-10 are rejected under 35 U.S.C. 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor regards as the invention.
-Unclear limitations and insufficient antecedent basis:
Claims 2 and 9:
Claims recite, the phrase, present expected compute for the data center associated with the future time is vague and unclear. It is unclear whether the claim refers to current/present expected compute or a future expected compute. These “present expected compute” and “present expected compute for the data center associated with the future time” contradicts each other. Therefore, the exact meaning of this limitation cannot be construed.
Appropriate correction is required.
Claims 3 and 10:
There is insufficient antecedent basis for the limitation the unfavorable parameter in the claim.
The corresponding parent independent claims 1/8 recite unfavorable result and not any unfavorable parameter. Specifically parent claims recite a parameter to minimize an unfavorable result that is not same as unfavorable parameter.
For the examination purpose, the above described limitation is construed as, the parameter to minimize the unfavorable result.
Appropriate correction is required.
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 (i.e., changing from AIA to pre-AIA ) 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.
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claim(s) 1-4, 7-11 and 14 is/are rejected under 35 U.S.C. 102(a)(1)/102(a)(2) as being anticipated by Kommula et al. (US20210195806A1; listed in the IDS dated 12/12/2025) [hereinafter KOMMULA].
Regarding claim 1:
KOMMULA discloses, A computer-implemented method for managing electrical and cooling supplies for a computer data center, the method comprising: [¶24: methods, apparatus and articles of manufacture disclosed herein optimize energy usage in data centers];
identifying, for a computer data center, an expected need for cooling and electrical power during a future time; [¶55: the climate controller 408 receives power utilization information from the power predictor 322 that identifies how much power to utilize at a future time to cool a server room 103 a-d during a future duration…
¶82: to deliver an amount of electrical power during the future duration to satisfy power requirements for running the climate control system 113 to cool the data center 102
¶25: mitigate problems associated with cooling multiple spaces in a data center and running multiple hardware resources in the data center….reduce inefficiencies related to identifying future power needs such as 1) ordering too much power for such future needs leading to unnecessarily spent capital,….reduce overly high temperatures known to adversely affect electrical properties of semiconductors.
Examiner notes the claim objections set forth in the current office action, and herein, the future time is construed as any future time for which a power or cooling need is being determined];
selecting, from among multiple different electrical power sources that include one or more electric utility sources, one or more electrical power sources for the data center corresponding to the future time; [¶82: the temperature predictor 1002 and the power utilization analyzer 1004 may determine that the total combined ambient temperature for the data center 102 is going to increase during a future duration….an increase in electrical power to cool the data center 102 is required….1006 configures the power supply station 1018 (e.g., power grid) to deliver an amount of electrical power during the future duration to satisfy power requirements for running the climate control system 113 to cool the data center 102];
selecting one or more cooling sources for the data center corresponding to the future time; and [¶86: the decision engine 106 and/or the power predictor 322 can predict the amount of heat that a physical server rack may generate based on the amount of power consumed by the physical server rack to execute its workloads,…the decision engine 106 and/or the power predictor 322 are capable of predicting a future temperature based on the predicted heat to be generated for a future duration based on a future predicted amount of workloads. This allows the decision engine 106 and/or the power predictor 322 to more accurately and efficiently operate the climate control system 113, and the physical server racks 202, 204,]
serving the data center to be served using the selected one or more electrical power sources and one or more selected cooling sources over a time corresponding to the future time, [¶91: The program 1300 begins at block 1302…predicts a number of workloads to be run on physical resources in a data center 102 at a future duration (block 1302)….At block 1312,…determines a climate control power utilization to adjust (e.g., cool) the combined ambient air temperature to satisfy an ambient air temperature threshold….
¶82: configures the power supply station 1018 (e.g., power grid) to deliver an amount of electrical power during the future duration to satisfy power requirements for running the climate control system 113 to cool the data center 102 in response to the increase in temperature...
¶86: the decision engine 106 and/or the power predictor 322 are capable of predicting a future temperature based on the predicted heat to be generated for a future duration based on a future predicted amount of workloads. This allows the decision engine 106 and/or the power predictor 322 to more accurately and efficiently operate the climate control system 113, and the physical server racks 202, 204, as well as more accurately and efficiently interact with the power supply station 1018.
Examiner notes the claim objections set forth in the current office action.];
wherein selecting the one or more electrical power sources and one or more cooling sources comprises applying a parameter to minimize an unfavorable result associated with operating the computer data center. [¶91: At block 1312,…determines a climate control power utilization to adjust (e.g., cool) the combined ambient air temperature to satisfy an ambient air temperature threshold….
¶82: configures the power supply station 1018 (e.g., power grid) to deliver an amount of electrical power during the future duration to satisfy power requirements for running the climate control system 113 to cool the data center 102 in response to the increase in temperature...
¶86: This allows the decision engine 106 and/or the power predictor 322 to more accurately and efficiently operate the climate control system 113, and the physical server racks 202, 204, as well as more accurately and efficiently interact with the power supply station 1018.
Examiner notes the claim rejections under 35 USC 112(a).
Examiner notes that applying a parameter to minimize an unfavorable result associated with operating data center is broad and means that applying or controlling any parameter in order to minimize any unfavorable result/condition.
As such, as described above, KOMMULA discloses, minimizing temperature increase or power consumption (efficiency) in the data center by applying a parameter such as adjusting ambient temperature to meet a threshold or controlling amount of power to satisfy power requirement efficiently].
Regarding claim 2:
KOMMULA further discloses, wherein the expected need for cooling and electrical power for the data center is identified as a function of present expected compute for the data center associated with the future time. [¶81: The example power predictor 322 is provided with the example power utilization analyzer 1004 to determine a predicted total data center power utilization for the future duration based on a computing power utilization and a climate control power utilization…
¶82: the temperature predictor 1002 and the power utilization analyzer 1004 may determine that the total combined ambient temperature for the data center 102 is going to increase during a future duration (e.g., 2 days into the future, 1 week into the future, one month into the future, one year into the future, etc.). As such, an increase in electrical power to cool the data center 102 is required. The example power manager 1006 configures the power supply station 1018 (e.g., power grid) to deliver an amount of electrical power during the future duration to satisfy power requirements for running the climate control system 113 to cool the data center 102 in response to the increase in temperature.
Examiner notes the 35 USC 112(b) rejections set forth in the current office action. Since the exact meaning of the claim cannot be determined, the plain meaning of the limitations are applied eliminating the contradiction between the present/current and future expected compute.
In broadest reasonable interpretation, the plain meaning of claim 2 is construed as, expected cooling and power need for the data center is as a function of future expected compute (e.g.; expected power use/increase/decrease in future).].
Regarding claim 3:
KOMMULA further discloses, wherein the unfavorable parameter comprises one or more of electricity cost, carbon generation, ambient noise, data center availability, and equipment wear. [¶23: Examples disclosed herein may be used to significantly lower costs associated with cooling operations of a data center by consolidating workload operations to fewer physical spaces or fewer server rooms of the data center during times of lower demand for resources….also useful for more accurately predicting future energy requirements by maintaining ambient operating temperatures of the server rooms at sufficiently cool temperatures to prevent overheating of hardware resources and to provide hardware resources with operating environment temperatures that will promote high computing performance.
Examiner notes the 35 USC 112(b) rejections set forth in the current office action.
As described above, KOMMULA discloses, unfavorable parameter/result comprises electricity cost].
Regarding claim 4:
KOMMULA further discloses, wherein the selection of an electrical power source corresponding to the future time
depends on cost terms in one or more service level power agreements with one or more suppliers of grid power. [¶76: data centers may attempt to identify future power needs in order to lock in price rates early for future power needs…. ordering too much power for such future needs leads to unnecessarily spent capital, and ordering too little power may lead to paying significantly increased prices to order instant on-demand power as needed for unforeseen spikes and excess energy needs…
¶81: the climate control power utilization is based on a power utilization corresponding to adjusting or conditioning the combined ambient air temperature of the data center 102 to satisfy an ambient air temperature threshold (e.g., 50 degrees, 60 degrees, 70 degrees, etc.)… the power utilization analyzer 1004 receives power utilization information from the power grid interface 1012, which interacts with an electrical power utility company that supplies electrical power to the data center 102].
Regarding claim 7:
KOMMULA further discloses, determining an energy-minimizing timing of operating the data center, and selecting the one or more electrical power sources and the one or more cooling sources as a function of the energy-minimizing timing. [¶23: Examples disclosed herein may be used to significantly lower costs associated with cooling operations of a data center by consolidating workload operations to fewer physical spaces or fewer server rooms of the data center during times of lower demand for resources…
¶31: At time (T1), the migrator 114 migrates the virtual machines 104 of rooms 103 b-d to room 103 a based on the processes carried out by the decision engine 106. As such, the physical server racks in rooms 103 b-d are no longer executing any workloads and can be placed in a low-power mode to reduce the amount of power required to cool the physical server racks in rooms 103 b-d. In some examples, the number of workloads in rooms 103 b-d are only decreased (e.g., if there is not sufficient resource capacity in room 103 a to execute all workloads), but such decreasing of workloads still allows decreasing power consumption needed to cool rooms 103 b-d due to fewer hardware resources generating heat.].
Regarding claim 8:
KOMMULA discloses, A device containing one or more tangible, non-transitory machine-readable storage media that store instructions that, when executed by one or more computer processors, perform operations comprising: [¶24: methods, apparatus and articles of manufacture disclosed herein optimize energy usage in data centers…
¶62: the processor 912 shown in the example processor platform 900 discussed below in connection with FIG. 9. The program may be embodied in software stored on a non-transitory computer readable storage medium];
identifying, for a computer data center, an expected need for cooling and electrical power during a future time; [¶55: the climate controller 408 receives power utilization information from the power predictor 322 that identifies how much power to utilize at a future time to cool a server room 103 a-d during a future duration…
¶82: to deliver an amount of electrical power during the future duration to satisfy power requirements for running the climate control system 113 to cool the data center 102
¶25: mitigate problems associated with cooling multiple spaces in a data center and running multiple hardware resources in the data center….reduce inefficiencies related to identifying future power needs such as 1) ordering too much power for such future needs leading to unnecessarily spent capital,….reduce overly high temperatures known to adversely affect electrical properties of semiconductors.
Examiner notes the claim objections set forth in the current office action, and herein, the future time is construed as any future time for which a power or cooling need is being determined];
selecting, from among multiple different electrical power sources that include one or more electric utility sources, one or more electrical power sources for the data center corresponding to the future time; [¶82: the temperature predictor 1002 and the power utilization analyzer 1004 may determine that the total combined ambient temperature for the data center 102 is going to increase during a future duration….an increase in electrical power to cool the data center 102 is required….1006 configures the power supply station 1018 (e.g., power grid) to deliver an amount of electrical power during the future duration to satisfy power requirements for running the climate control system 113 to cool the data center 102];
selecting one or more cooling sources for the data center corresponding to the future time; and [¶86: the decision engine 106 and/or the power predictor 322 can predict the amount of heat that a physical server rack may generate based on the amount of power consumed by the physical server rack to execute its workloads,…the decision engine 106 and/or the power predictor 322 are capable of predicting a future temperature based on the predicted heat to be generated for a future duration based on a future predicted amount of workloads. This allows the decision engine 106 and/or the power predictor 322 to more accurately and efficiently operate the climate control system 113, and the physical server racks 202, 204,]
serving the data center to be served using the selected one or more electrical power sources and one or more selected cooling sources over a time corresponding to the future time, [¶91: The program 1300 begins at block 1302…predicts a number of workloads to be run on physical resources in a data center 102 at a future duration (block 1302)….At block 1312,…determines a climate control power utilization to adjust (e.g., cool) the combined ambient air temperature to satisfy an ambient air temperature threshold….
¶82: configures the power supply station 1018 (e.g., power grid) to deliver an amount of electrical power during the future duration to satisfy power requirements for running the climate control system 113 to cool the data center 102 in response to the increase in temperature...
¶86: the decision engine 106 and/or the power predictor 322 are capable of predicting a future temperature based on the predicted heat to be generated for a future duration based on a future predicted amount of workloads. This allows the decision engine 106 and/or the power predictor 322 to more accurately and efficiently operate the climate control system 113, and the physical server racks 202, 204, as well as more accurately and efficiently interact with the power supply station 1018.
Examiner notes the claim objections set forth in the current office action.];
wherein selecting the one or more electrical power sources and one or more cooling sources comprises applying a parameter to minimize an unfavorable result associated with operating the computer data center. [¶91: At block 1312,…determines a climate control power utilization to adjust (e.g., cool) the combined ambient air temperature to satisfy an ambient air temperature threshold….
¶82: configures the power supply station 1018 (e.g., power grid) to deliver an amount of electrical power during the future duration to satisfy power requirements for running the climate control system 113 to cool the data center 102 in response to the increase in temperature...
¶86: This allows the decision engine 106 and/or the power predictor 322 to more accurately and efficiently operate the climate control system 113, and the physical server racks 202, 204, as well as more accurately and efficiently interact with the power supply station 1018.
Examiner notes the claim rejections under 35 USC 112(a).
Examiner notes that applying a parameter to minimize an unfavorable result associated with operating data center is broad and means that applying or controlling any parameter in order to minimize any unfavorable result/condition.
As such, as described above, KOMMULA discloses, minimizing temperature increase or power consumption (efficiency) in the data center by applying a parameter such as adjusting ambient temperature to meet a threshold or controlling amount of power to satisfy power requirement efficiently].
Regarding claim 9:
KOMMULA further discloses, wherein the expected need for cooling and electrical power for the data center is identified as a function of present expected compute for the data center associated with the future time. [¶81: The example power predictor 322 is provided with the example power utilization analyzer 1004 to determine a predicted total data center power utilization for the future duration based on a computing power utilization and a climate control power utilization…
¶82: the temperature predictor 1002 and the power utilization analyzer 1004 may determine that the total combined ambient temperature for the data center 102 is going to increase during a future duration (e.g., 2 days into the future, 1 week into the future, one month into the future, one year into the future, etc.). As such, an increase in electrical power to cool the data center 102 is required. The example power manager 1006 configures the power supply station 1018 (e.g., power grid) to deliver an amount of electrical power during the future duration to satisfy power requirements for running the climate control system 113 to cool the data center 102 in response to the increase in temperature.
Examiner notes the 35 USC 112(b) rejections set forth in the current office action. Since the exact meaning of the claim cannot be determined, the plain meaning of the limitations are applied eliminating the contradiction between the present/current and future expected compute.
In broadest reasonable interpretation, the plain meaning of claim 2 is construed as, expected cooling and power need for the data center is as a function of future expected compute (e.g.; expected power use/increase/decrease in future).].
Regarding claim 10:
KOMMULA further discloses, wherein the unfavorable parameter comprises one or more of electricity cost, carbon generation, ambient noise, data center availability, and equipment wear. [¶23: Examples disclosed herein may be used to significantly lower costs associated with cooling operations of a data center by consolidating workload operations to fewer physical spaces or fewer server rooms of the data center during times of lower demand for resources….also useful for more accurately predicting future energy requirements by maintaining ambient operating temperatures of the server rooms at sufficiently cool temperatures to prevent overheating of hardware resources and to provide hardware resources with operating environment temperatures that will promote high computing performance.
Examiner notes the 35 USC 112(b) rejections set forth in the current office action.
As described above, KOMMULA discloses, unfavorable parameter/result comprises electricity cost].
Regarding claim 11:
KOMMULA further discloses, wherein the selection of an electrical power source corresponding to the future time
depends on cost terms in one or more service level power agreements with one or more suppliers of grid power. [¶76: data centers may attempt to identify future power needs in order to lock in price rates early for future power needs…. ordering too much power for such future needs leads to unnecessarily spent capital, and ordering too little power may lead to paying significantly increased prices to order instant on-demand power as needed for unforeseen spikes and excess energy needs…
¶81: the climate control power utilization is based on a power utilization corresponding to adjusting or conditioning the combined ambient air temperature of the data center 102 to satisfy an ambient air temperature threshold (e.g., 50 degrees, 60 degrees, 70 degrees, etc.)… the power utilization analyzer 1004 receives power utilization information from the power grid interface 1012, which interacts with an electrical power utility company that supplies electrical power to the data center 102].
Regarding claim 14:
KOMMULA further discloses, determining an energy-minimizing timing of operating the data center, and selecting the one or more electrical power sources and the one or more cooling sources as a function of the energy-minimizing timing. [¶23: Examples disclosed herein may be used to significantly lower costs associated with cooling operations of a data center by consolidating workload operations to fewer physical spaces or fewer server rooms of the data center during times of lower demand for resources…
¶31: At time (T1), the migrator 114 migrates the virtual machines 104 of rooms 103 b-d to room 103 a based on the processes carried out by the decision engine 106. As such, the physical server racks in rooms 103 b-d are no longer executing any workloads and can be placed in a low-power mode to reduce the amount of power required to cool the physical server racks in rooms 103 b-d. In some examples, the number of workloads in rooms 103 b-d are only decreased (e.g., if there is not sufficient resource capacity in room 103 a to execute all workloads), but such decreasing of workloads still allows decreasing power consumption needed to cool rooms 103 b-d due to fewer hardware resources generating heat.].
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 (i.e., changing from AIA to pre-AIA ) 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 filling 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.
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
Determining the scope and contents of the prior art.
Ascertaining the differences between the prior art and the claims at issue.
Resolving the level of ordinary skill in the pertinent art.
Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 5 and 12 is/are rejected under 35 U.S.C. 103 as being unpatentable over KOMMULA, and further in view of Jackson (US20130024710A1) [hereinafter Jackson].
Regarding claim 5:
KOMMULA discloses, The computer-implemented method of claim 1, but doesn’t explicitly discloses, and
JACKSON discloses, in response to identifying the expected need, delaying an amount of compute by the computer data center so that the compute is performed during a period of lower cost for electrical power. [¶22: enables the system to take advantage of off-peak hours by automatically scheduling lower priority workload for processing during off-peak hours when energy costs are lower…
¶47: intelligent policy involves a time of day based power consumption….if the most costly consumption period during a day is between 9:00 am and 12 noon,…less critical workload may be processed for example, during a lunch period from 12-1 pm or later in the middle of the night in which less expensive power costs are available…Thus, the system 304 may provide a normal costing factor associated with using the compute resources.
Examiner notes that, as described above, JACKSON discloses, shifting the loads via schedule to a time when the power cost is lower.]
Therefore, it would have been obvious to one of ordinary skill in the art before the filling date of the claimed invention to have combined the capability of delaying an amount of compute by the computer data center so that the compute is performed during a period of lower cost for electrical power in response to identifying the expected need in order to save energy cost by utilizing load shifting to off-peak hours based on need taught by Jackson with the method taught by KOMMULA as discussed above in order to have reasonable expectation of success such as to save energy cost by utilizing load shifting to off-peak hours based on need [Jackson, ¶47: workload may be processed for example, during a lunch period from 12-1 pm or later in the middle of the night in which less expensive power costs are available].
Regarding claim 12:
KOMMULA discloses, The computer-implemented method of claim 8, but doesn’t explicitly discloses, and
JACKSON discloses, in response to identifying the expected need, delaying an amount of compute by the computer data center so that the compute is performed during a period of lower cost for electrical power. [¶22: enables the system to take advantage of off-peak hours by automatically scheduling lower priority workload for processing during off-peak hours when energy costs are lower…
¶47: intelligent policy involves a time of day based power consumption….if the most costly consumption period during a day is between 9:00 am and 12 noon,…less critical workload may be processed for example, during a lunch period from 12-1 pm or later in the middle of the night in which less expensive power costs are available…Thus, the system 304 may provide a normal costing factor associated with using the compute resources.
Examiner notes that, as described above, JACKSON discloses, shifting the loads via schedule to a time when the power cost is lower.]
Therefore, it would have been obvious to one of ordinary skill in the art before the filling date of the claimed invention to have combined the above described teachings of Jackson with the method taught by KOMMULA for the same reasons as described above in claim 5.
Claim(s) 6 and 13 is/are rejected under 35 U.S.C. 103 as being unpatentable over KOMMULA, and further in view of Evans (US20180204116A1) [hereinafter Evans].
Regarding claim 6:
KOMMULA discloses, The computer-implemented method of claim 1, but doesn’t explicitly discloses, and
Evans discloses, wherein the one or more cooling sources are selected based on physical parameters of multiple different candidate cooling sources, and operational parameters of the multiple different candidate cooling sources that were learned by a computer system over time. [¶23: The efficiency management system (100) can train an ensemble of machine learning models (132A-132N)…to predict the resource efficiency of the data center (104) if particular data center settings are adopted…
¶24: each machine learning model (132A-132N)… configured through training to receive a state input characterizing the current state of the data center (104) and a data center setting slate that defines a combination of possible data center settings and to process the state input and the data center setting slate to generate an efficiency score that characterizes a predicted resource efficiency…
¶19: system (100) can take in, as input, state data (140) representing the current state of the data center (104). This state data (140) can come from sensor readings of sensors… may include data such as temperatures, power, pump speeds, and set points…
¶22: Once the efficiency management system (100) determines the data center settings (120) that will make the data center (104) more efficient,..provides the updated data center settings (120) to the control system (102)…if the efficiency management system (100) determines that an additional cooling tower should be turned on in the data center (104),…provide the updated data center settings (120)…to the control system (102), which automatically adopts the settings…
¶35: To efficiently control the cooling system, the efficiency management system (100) may construct different potential setting slates that include…a number of cooling units running…
¶36: one setting slate may include the following values:…10 as the number of cooling units running.
Examiner notes the 35 USC 112(a) rejections set forth in this office action.].
Therefore, it would have been obvious to one of ordinary skill in the art before the filling date of the claimed invention to have combined the capability of selecting the one or more cooling sources based on physical parameters of multiple different candidate cooling sources, and operational parameters of the multiple different candidate cooling sources that were learned by a computer system over time in order to increase the cooling efficiency of the data center by making best selection of cooling control based on learning from operational parameters for efficient cooling taught by Evans with the method taught by KOMMULA as discussed above in order to have reasonable expectation of success such as to increase the cooling efficiency of the data center by making best selection of cooling control based on learning from operational parameters for efficient cooling [Evans, ¶35: To efficiently control the cooling system, the efficiency management system (100) may construct different potential setting slates that include…a number of cooling units running].
Regarding claim 13:
KOMMULA discloses, The computer-implemented method of claim 8, but doesn’t explicitly discloses, and
Evans discloses, wherein the one or more cooling sources are selected based on physical parameters of multiple different candidate cooling sources, and operational parameters of the multiple different candidate cooling sources that were learned by a computer system over time. [¶23: The efficiency management system (100) can train an ensemble of machine learning models (132A-132N)…to predict the resource efficiency of the data center (104) if particular data center settings are adopted…
¶24: each machine learning model (132A-132N)… configured through training to receive a state input characterizing the current state of the data center (104) and a data center setting slate that defines a combination of possible data center settings and to process the state input and the data center setting slate to generate an efficiency score that characterizes a predicted resource efficiency…
¶19: system (100) can take in, as input, state data (140) representing the current state of the data center (104). This state data (140) can come from sensor readings of sensors… may include data such as temperatures, power, pump speeds, and set points…
¶22: Once the efficiency management system (100) determines the data center settings (120) that will make the data center (104) more efficient,..provides the updated data center settings (120) to the control system (102)…if the efficiency management system (100) determines that an additional cooling tower should be turned on in the data center (104),…provide the updated data center settings (120)…to the control system (102), which automatically adopts the settings…
¶35: To efficiently control the cooling system, the efficiency management system (100) may construct different potential setting slates that include…a number of cooling units running…
¶36: one setting slate may include the following values:…10 as the number of cooling units running.
Examiner notes the 35 USC 112(a) rejections set forth in this office action.].
Therefore, it would have been obvious to one of ordinary skill in the art before the filling date of the claimed invention to have combined the above described teachings of Evans with the system taught by KOMMULA as discussed above for the same reasons as described above in claim 6.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure is listed in the PTO-892 Notice of Reference Cited document.
Bernat et al. (US20230273839A1) - Methods and apparatus to balance and coordinate power and cooling systems for compute components
¶126: resource prediction circuitry 1710 determines resource usage predictions based on the cooling resource usage data, the power resource usage data, and previous resource usage data.
¶154: The example cooling budget circuitry 1850 generates a resource budget based on total cooling resources, the resource usage predictions, and the cooling resource allocation information. Such a resource budget may be referred to as a cooling budget. The cooling budget specifies available cooling resources at a given time. The example cooling budget circuitry 1850 allocates a portion of the total cooling resources for future use based on the resource usage predictions. In some examples, the cooling budget circuitry 1850 allocates a relatively large portion of the total cooling resources to prepare for predictions of relatively high resource usage. In such examples, the cooling budget circuitry 1850 allocates a relatively small portion of the total cooling resources to prepare for predictions of relatively low resource usage.
Chatterjee et al. (US20160087909A1) - Scheduling cost efficient datacenter load distribution:
¶3: system for scheduling cost efficient data center load distribution. A computer receives a task to be performed by computing resources within a set of data centers. The computer further identifies all available data centers to perform the task. Lowest cost task schedule is determined from the available data centers. The computer further schedules the task to be completed at the cheapest available data center.
Ahuja (US20180024578A1) - Technologies for predicting power usage of a data center:
¶46: variables may be inputted to the software on a continuing basis comprising a measured angular position of the drill string at a surface position…and/or azimuth and inclination taken at the nonmagnetic measurement portion….then outputs an adjusted angular position, an adjusted sliding mode drill string tension, and an adjusted mud flow rate to maintain a tool face of the bit wherein a projected direction of drilling may be determined utilizing the distance between the bit and the nonmagnetic measurement portion of the bottom hole assembly and the desired trajectory.
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/M.S./
Patent Examiner,
Art Unit 2116
Prosecution Insights