DETAILED ACTION
Status of the Application
The following is a non-Final Office Action. In response to Examiner's communication of September 12, 2025, Applicant, on December 11, 2025, amended claims 1 & 8. Claim 7 was previously canceled. Claims 1-6 & 8 are now pending in this application and have been rejected below.
The present application is being examined under the pre-AIA first to invent provisions. 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.
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on December 11, 2025 has been entered.
Response to Amendment
Applicant's amendments are not sufficient to overcome the 35 USC 101 rejections set forth in the previous action. Therefore, these rejections are updated in view of the amendments and maintained below.
Applicant's amendments render moot the prior art rejections set forth in the previous action. Therefore, new grounds for rejection necessitated by Applicant’s amendments are set forth below.
Response to Arguments - 35 USC § 101
Applicant’s arguments with respect to claims the 35 USC 101 rejections have been fully considered, but they are not persuasive.
Applicant argues that the claims transform the abstract idea into a specific technological implementation that provides concrete improvements to data center operations and cannot be performed through mental processes because the claim now recites that the processor "receives real-time renewable energy supply data for each data center candidate" and "calculates the score for each combination by applying a matching degree coefficient based on a correlation between the level of flexibility of power consumption amount control of each application program type candidate and a level of fluctuation in the characteristic of renewable energy supplied to each data center candidate,” this “is fundamentally different from the examiner's characterization of mental processes that could be performed with pen and paper,” “cannot be performed mentally,” the “claims are not directed to an abstract idea under Step 2A Prong 1 because they recite a specific technological solution to a technical problem in data center operation,” the “claims require storing and managing specific types of technical information (renewable energy characteristics of data centers and power consumption flexibility levels of application programs), “determining combinations based on these technical parameters, calculating scores using these technical characteristics, and selecting optimal combinations, “[t]his is not a mental process because the complexity of analyzing multiple data centers with varying renewable energy characteristics against multiple application types with different power consumption flexibility levels, and calculating matching scores for numerous combinations, cannot practically be performed mentally,” and “processing technical data about renewable energy supply characteristics and power consumption control flexibility … are inherently technological concepts tied to computer system operations and energy management.” Examiner respectfully disagrees.
Pursuant to 2019 Revised Patent Subject Matter Eligibility Guidance, in order to determine whether a claim is directed to an abstract idea, under Step 2A, we first (1) determine whether the claims recite limitations, individually or in combination, that fall within the enumerated subject matter groupings of abstract ideas (mathematical concepts, certain methods of organizing human activity, or mental processes), and (2) determine whether any additional elements beyond the recited abstract idea, individually and as an ordered combination, integrate the judicial exception into a practical application. 84 Fed. Reg. 52, 54-55. Next, if a claim (1) recites an abstract idea and (2) does not integrate that exception into a practical application, in order to determine whether the claim recites an “inventive concept,” under Step 2B, we then determine whether any of the additional elements beyond the recited abstract idea, individually and in combination, are significantly more than the abstract idea itself. 84 Fed. Reg. 56.
Under prong 1 of Step 2A, claim 1, and similarly claims 2-6 & 8, recites “stores data center candidate management information and application program type candidate management information, the data center candidate management information is used for managing information on a plurality of data center candidates, information on each data center candidate of the plurality of data center candidates indicates a characteristic of renewable energy supplied to each data center candidate, the application program type candidate management information is used for managing information on a plurality of application program type candidates, and application program type candidate management information comprise: (i) information on each application program type candidate of the plurality of application program type candidates indicates a characteristic of each application program type candidate; and (ii) a level of flexibility of power consumption amount control performed by each application program type candidate, and … receives real-time renewable energy supply data for each data center candidate, determines, with reference to the data center candidate management information and the application program type candidate management information, a plurality of combinations each including one or more data center candidates and one or more application program type candidates, determines, for each combination, a matching degree between a fluctuation characteristic of the renewable energy supplied to each data center candidate and the level of flexibility of power consumption amount control of each application program type candidate, … calculates a score for each combination by applying a matching degree coefficient based on a correlation between the level of flexibility of power consumption amount control of each application program type candidate and a level of fluctuation in the characteristic of renewable energy supplied to each data center candidate, and … selects the combination having a maximum total score for deployment and … based on the selected combination to optimize renewable energy utilization.”
Claims 1-6 & 8, in view of the claim limitations, recite the abstract idea of collecting information regarding data center candidate management information indicating renewable energy at the data centers and application program type candidate management information indicating a characteristic of each application program type, determining a plurality of combinations of data center candidates and application program type candidates based on the collected information, determining a matching degree between a fluctuation of the renewable energy and the level of flexibility of power consumption amount control of each application program type candidate, calculating a score for each of the combinations based on the determination, and selecting a combination from the combinations to present with the maximum the score.
A claim recites mental processes when the claim recites concepts performed in the human mind (including an observation, evaluation, judgment, opinion), wherein if the claim, under its broadest reasonable interpretation, covers the claim being practically performed in the mind but for the recitation of generic computer components, then the claim is in the mental process category. 84 Fed. Reg. 52 n.14. Here, as a whole, in view of the claim limitations, but for the computer components and systems performing the claimed functions, the broadest reasonable interpretation of the recited collecting information regarding data center candidate management information indicating renewable energy at the data centers and application program type candidate management information indicating a characteristic of each application program type, determining a plurality of combinations of data center candidates and application program type candidates based on the collected information, determining a matching degree between a fluctuation of the renewable energy and the level of flexibility of power consumption amount control of each application program type candidate, calculating a score for each of the combinations based on the determination, and selecting a combination from the combinations to present with the maximum the score could all be reasonably interpreted as a human observing information regarding data center candidate management information and application program type candidate management information to store the information mentally and/or with a pen and paper, a human mentally performing an evaluation and using judgment based on the information to determine combination of the data center candidates and program type candidates, a human mentally performing an evaluation and using judgment based on the information to determine a matching degree and calculate a score for each combination, and a human mentally comparing the scores to selected one of the combinations to present manually and/or using a pen and paper.
Specifically with respect to the recited receiving real time renewable energy supply information and calculating a score, these elements referred to by Applicant aims are similar to collecting of measurements collected in real time from a power grid, analyzing it, and displaying certain results of the collection and analysis, which was held to be abstract by the Court of Appeals for the Federal Circuit in Electric Power Group, LLC v. Alstom S.A., et al., No. 2015-1778 (Fed Cir. Aug. 1, 2016). Regardless of the alleged complexity, a human can analyze multiple data centers with varying renewable energy characteristics against multiple application types with different power consumption flexibility levels and calculating matching scores for numerous combinations. The complexity of the data and analysis does not make the claims an improvement to computer technology nor otherwise make the claims patent-eligible since “[a]ccelerating a process of analyzing … data when the increased speed comes solely from the capabilities of a general-purpose computer” is not sufficient to show an improvement in computer-functionality (MPEP 2106.05(a)) and “claiming the improved speed or efficiency inherent with applying the abstract idea on a computer" in not an improvement to computer technology nor otherwise integrate judicial exception into a practical application. MPEP 2106.05(f). Moreover, as in the claims at issue in Electric Power Group, the present claims are not focused on a specific improvement in computers or any other technology, but instead on certain independently abstract ideas (i.e., observing information, analyzing the information, and outputting the results) that simply invokes computers as tools to implement the abstract idea. Electric Power Group, LLC v. Alstom S.A., et al., No. 2015-1778, slip op. at 8 (Fed. Cir. Aug. 1, 2016); MPEP 2106.05(a).
Therefore, contrary to Applicant’s assertions, the claims, including the elements referred to by Applicant, recite mental processes. Accordingly, since the claims recite mental processes, the claims recite an abstract idea under the first prong of Step 2A.
Applicant argues that the claims integrate the judicial exception into a practical application under Prong Two of Step 2A because they provide a specific technological improvement to data center operations by enabling efficient utilization of renewable energy resources, the claims solve the technical problem of reducing surplus renewable energy in regions by matching data center candidates with appropriate application program types based on renewable energy characteristics and power consumption flexibility, this improves the functioning of data center systems by optimizing renewable energy usage and reducing load on power systems, the claimed system is not merely using generic computer components to automate a manual process, but rather implements a specific technical solution that could not exist without computer technology, as it requires real- time processing of renewable energy characteristics, power consumption flexibility levels, and complex scoring calculations across multiple combinations to achieve efficient renewable energy utilization in data centers. Examiner respectfully disagrees.
As noted above, after determining whether the claims recite limitations that fall within the enumerated abstract groupings in Prong 1 of Step 2A, Prong 2 of Step 2A asks whether any additional elements beyond the recited abstract idea, individually and as an ordered combination, integrate the judicial exception into a practical application. However, despite Applicant’s assertions, aside from the generically recited system comprising a processor and a data storage, each of the features referred to by Applicant of matching data center candidates with appropriate application program types based on renewable energy characteristics and power consumption flexibility, processing of renewable energy characteristics, power consumption flexibility levels, and complex scoring calculations across multiple combinations to achieve efficient renewable energy utilization in data centers are mental processes for the reasons detailed above under prong 1 of Step 2A, and thus, the features referred to by Applicant are not additional elements beyond the recited abstract idea, but rather, the features referred to by Applicant are part of and directed to the recited abstract idea identified in Prong 1 of Step 2A.
The claimed features are not necessarily rooted in computer technology because, for the reasons discussed above, all the argued features can be performed mentally and/or with a pen and paper without the use of computers. For example, a human can calculate a score for data centers and select a data center based on the score by mentally performing an evaluation of observed data and use mental judgement to select the data center with the highest score.
Mere automation of a manual process or a business method being applied on a general purpose computer is not sufficient to show an improvement in computers or other technology, and the claim must include more than mere instructions to perform the method on a generic component or machinery to qualify as an improvement to an existing technology. MPEP 2106.05(a). Simply requiring that the claims use generic computer components, such as the generically recited system comprising a processor and a data storage, to implement the recited abstract idea does not make the claims directed to an improvement in technology or otherwise transform the abstract idea into a patent eligible invention. As discussed above, each of the steps are mental processes that can be performed by a human observing data, performing evaluations of the observed the data, and using judgement to make selections based on the evaluations, and thus, implementing this with a system comprising a processor and a data storage amounts to nothing more than requiring that the abstract idea is implemented with generic computer components, which is not sufficient to integrate an abstract idea into a practical application. The complexity of the data and analysis does not make the claims an improvement to computer technology nor otherwise make the claims patent-eligible since “[a]ccelerating a process of analyzing … data when the increased speed comes solely from the capabilities of a general-purpose computer” is not sufficient to show an improvement in computer-functionality (MPEP 2106.05(a)) and “claiming the improved speed or efficiency inherent with applying the abstract idea on a computer" in not an improvement to computer technology nor otherwise integrate judicial exception into a practical application. MPEP 2106.05(f). Like in Electric Power Group, the claims are not focused on a specific improvement in computers, but on certain independently abstract ideas that simply use computers as tools. Electric Power Group, LLC v. Alstom S.A., et al., No. 2015-1778, slip op. at 8 (Fed. Cir. Aug. 1, 2016); MPEP 2106.05(a).
In the interest of compact prosecution and clarity, under the second prong of Step 2A, claim 1, and similarly claim 8, recites the additional elements beyond the recited abstract idea of “[a] data center management system comprising: a processor; and a data storage, wherein the data storage,” “automatically,” and “implements a configuration change to the data center and applications of the data center” in claim 1 and similarly claims 2-6 & 8; however, individually and when viewed as an ordered combination, and pursuant to the broadest reasonable interpretation, each of the additional elements are computing elements recited at high level of generality implementing the abstract idea on a computer (i.e. apply it), and thus, are no more than applying the abstract idea with generic computer components, which is not sufficient to integrate an abstract idea into a practical application. See MPEP 2106.05(f).
Applicant argues claim 1 further recites that the processor "automatically selects the combination having a maximum total score for deployment and implements a configuration change to the data center and applications of the data center based on the selected combination to optimize renewable energy utilization,” [t]his automatic selection for deployment to optimize renewable energy utilization transforms the abstract concept into a practical application that directly improves data center energy efficiency,” “[t]he claimed system does not merely present combinations to a user for manual consideration, but automatically selects the combination having a maximum total score for deployment and implements a configuration change to the data center and applications of the data center based on the selected combination to optimize renewable energy utilization.” Examiner respectfully disagrees.
As noted above, a human can mentally select the combination having a maximum total score for deployment by using judgement to decide a combination by comparing a total score, and thus, this limitation is a mental process and is part of the recited abstract idea. The specification does not describe “automatically” selecting or “implement[ing] a configuration change to the data center and applications of the data center” beyond selecting that can be performed mentally and generically and broadly deploying a selecting, and in view of the specification, these recitations are not an improvement in technology. The recitation of the additional elements beyond the recited abstract idea of “automatically” and “implements a configuration change to the data center and applications of the data center,” individually and when viewed as an ordered combination, and pursuant to the broadest reasonable interpretation, are computing elements recited at high level of generality implementing the abstract idea on a computer (i.e. apply it), and thus, are no more than applying the abstract idea with generic computer components, which is not sufficient to integrate an abstract idea into a practical application. See MPEP 2106.05(f). Further, the recitation of “automatically” and “implements a configuration change to the data center and applications of the data center” merely generally links the abstract idea to a technical environment.
Applicant argues the combination of receiving real-time renewable energy supply data, calculating scores by applying matching degree coefficients based on correlations between power consumption flexibility and energy fluctuation characteristics, and automatically selects the combination having a maximum total score for deployment and implements a configuration change to the data center and applications of the data center based on the selected combination to optimize renewable energy utilization, as recited by amended claim 1 integrates the abstract concept into a practical application that provides a concrete technological improvement, the amended claims address this technical problem by dynamically matching application workloads with data centers based on real-time renewable energy data and technical parameters of energy fluctuation and power consumption flexibility, the claims do not recite a mental process when they do not contain limitations that can practically be performed in the human mind, for instance when the human mind is not equipped to perform the claim limitations, and the human mind is not equipped to perform real-time data acquisition from power grid management systems, apply complex matching degree coefficients based on correlations between renewable energy fluctuation characteristics and application power consumption flexibility, and automatically deploy workloads to optimize renewable energy utilization across multiple data centers Examiner respectfully disagrees.
As noted above, despite Applicant’s assertions to the contrary, like the mental process of receiving of measurements collected in real time from a power grid, analyzing the collected information, and displaying certain results of the collection and analysis that is held to be an abstract idea by the Court of Appeals for the Federal Circuit in Electric Power Group, a human can mentally receive real-time renewable energy supply data, calculate scores by applying matching degree coefficients based on correlations between power consumption flexibility and energy fluctuation characteristics, and select the combination having a maximum total score for deployment by a human observing information regarding energy supply data, evaluating the information to calculate scores, and using judgement to select a combination by comparing the scores, and thus, these elements referred to by Applicant do indeed recite a mental process. Similar to the claims at issue in Electric Power Group, the present claims are not focused on a specific improvement in computers or any other technology, but instead on certain independently abstract ideas (i.e., observing information, analyzing the information, and outputting the results) that simply invokes computers as tools to implement the abstract idea. Electric Power Group, LLC v. Alstom S.A., et al., No. 2015-1778, slip op. at 8 (Fed. Cir. Aug. 1, 2016); MPEP 2106.05(a).
The complexity of the data and analysis does not make the claims an improvement to computer technology nor otherwise make the claims patent-eligible since “[a]ccelerating a process of analyzing … data when the increased speed comes solely from the capabilities of a general-purpose computer” is not sufficient to show an improvement in computer-functionality (MPEP 2106.05(a)) and “claiming the improved speed or efficiency inherent with applying the abstract idea on a computer" in not an improvement to computer technology nor otherwise integrate judicial exception into a practical application. MPEP 2106.05(f).
The recitation of the additional elements beyond the recited abstract idea of “automatically” and “implements a configuration change to the data center and applications of the data center,” individually and when viewed as an ordered combination, and pursuant to the broadest reasonable interpretation, are computing elements recited at high level of generality implementing the abstract idea on a computer (i.e. apply it), and thus, are no more than applying the abstract idea with generic computer components, which is not sufficient to integrate an abstract idea into a practical application. See MPEP 2106.05(f). Further, the recitation of “automatically” and “implements a configuration change to the data center and applications of the data center” merely generally links the abstract idea to a technical environment.
Response to Arguments - Prior Art
Applicant’s arguments with respect to claims the prior art rejections have been fully considered, but they are now moot in view of new grounds for rejection necessitated by Applicant’s amendments.
Claim Rejections - 35 USC § 112, First Paragraph
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1-6 & 8 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for pre-AIA the inventor(s), at the time the application was filed, had possession of the claimed invention.
Claim 1, and similarly claim 8, recites “receives real-time renewable energy supply data for each data center candidate” and “automatically selects the combination having a maximum total score for deployment and implements a configuration change to the data center and applications of the data center based on the selected combination to optimize renewable energy utilization.” However, Applicant’s specification does not in expressly or inherently require that the received renewable energy supply data is “real time” nor require that the selecting combination having a maximum total score results in implementing “a configuration change to the data center and applications of the data center based on the selected combination to optimize renewable energy utilization,” as the claims require.
In order to satisfy the written description requirement, each claim limitation must be expressly or inherently supported by the disclosure. MPEP 2163 (emphasis added). “The 'written description' requirement implements the principle that a patent must describe the technology that is sought to be patented; the requirement serves both to satisfy the inventor's obligation to disclose the technologic knowledge upon which the patent is based, and to demonstrate that the patentee was in possession of the invention that is claimed.” Capon v. Eshhar, 76 USPQ2d 1078, 1084 (Fed. Cir. 2005). Further, the written description requirement promotes the progress of the useful arts by ensuring that patentees adequately describe their inventions in their patent specifications in exchange for the right to exclude others from practicing the invention for the duration of the patent's term. See MPEP 2163 (emphasis added).
For claims directed toward computer-implemented functions, like the presently claimed invention, “[i]f the specification does not provide a disclosure of the computer and algorithm in sufficient detail to demonstrate to one of ordinary skill in the art that the inventor possessed the invention including how to program the disclosed computer to perform the claimed function, a rejection under 35 U.S.C. 112(a) or pre-AIA 35 U.S.C. 112, first paragraph, for lack of written description must be made.” MPEP 2161.01 (emphasis added). It is not enough that one skilled in the art could write a program to achieve the claimed function because the written description requirement requires that the specification explains how the inventor intends to achieve the claimed function. Examining Claims for Compliance with 35 USC 112(a) - PowerPoint of Computer Based Training, Slides 20 & 21, (emphasis added) available at http://www.uspto.gov/ sites/default/files/documents/uspto_112a_ part1_17aug2015.pptx. The ability of one skilled in the art to make and use the claimed invention does not satisfy the written description requirement if details of how the function is to be performed are not disclosed. Id. at Slide 20.
With respect to the recitation of “receives real-time renewable energy supply data for each data center candidate” and “automatically selects the combination having a maximum total score for deployment and implements a configuration change to the data center and applications of the data center based on the selected combination to optimize renewable energy utilization,” nothing in the Specification expressly or inherently requires the received renewable energy supply data is “real time” nor require that the selecting combination having a maximum total score results in implementing “a configuration change to the data center and applications of the data center based on the selected combination to optimize renewable energy utilization,” as the claims require.
Specifically regarding the recitation of “receives real-time renewable energy supply data for each data center candidate,” as noted by Applicant in their remarks dated November 10, 2025, the specification discloses “the virtual zero emission computing planning server 110 acquires information on a renewable energy power generation source and information on a power generation amount of the renewable energy power generation source from the power transmission and distribution grid and renewable energy power generation source management server 105”; however, this portion of the Specification relied upon by Applicant and/or any other portion of the Specification do not expressly or inherently require that the energy supply data is received in real time, as required by the claims.
Further, with respect to the recitation of “automatically selects the combination having a maximum total score for deployment and implements a configuration change to the data center and applications of the data center based on the selected combination to optimize renewable energy utilization,” while, as relied upon by Applicant, when discussing an embodiment depicted in fig. 20A-20C, the Specification discloses in Step S45 “the DC and app type selection program 232 selects a combination having a maximum total score,” the Specification does not require that the invention implements “a configuration change to the data center and applications of the data center” based on the selected combination to optimize renewable energy utilization in this or any other embodiment. This embodiment which selects the combination having a maximum score never is implemented or deployed by the invention, but rather this embodiment ends after “calculate[ing] the expected application profit of the app type and stor[ing] the expected app profit in the expected app profit column 406 of the selected app type and expected amount table 248” in Step S51.
Further, in a separate embodiment relied upon by Applicant as supporting that the claim limitation reciting “implements a configuration change to the data center and applications of the data center,” fig. 18 of the Specification discloses the “app deployment program 271 determines, as an execution data center and execution time of the app workload, a data center and a time zone in which a renewable energy supply amount is large, based on the predicted renewable energy amount per hour indicated by the renewable energy amount prediction table 281,” and “deploys the requested app workload to the data center 160 as the determined deployment destination” in Step S114. However, even this embodiment, which is different from the embodiment that selects the combination with a maximum score, fails to disclose “a configuration change to the data center and applications of the data center.” Simply disclosing “deploy[ing] the requested app workload to the data center 160 as the determined deployment destination” does not necessarily require “a configuration change to the data center and applications of the data center,” as required by the claims. Moreover, this embodiment disclosing of deployment a workload is not based on “based on the selected combination” nor “to optimize renewable energy utilization,” as recited in the amended claim.
Applicant’s amendments requiring the supply data is received in “real time” and that the claimed implementing includes “a configuration change to the data center and applications of the data center” insert requirements into the claimed invention for which the Specification is silent, and therefore, are neither expressly nor inherently disclosed in the Specification. Furthermore, the disclosure of the Specification relied upon as support for the claimed “implementing” discussing deploying a workload is separate embodiment from the embodiment “select[ing] a combination having a maximum total score,” and thus, Applicant’s amendment requiring the implementing is based on based on the selected combination has combined separate embodiments in such a manner that is not supported by Specification.
For the reasons set forth above, the Specification does not inherently nor expressly support “receives real-time renewable energy supply data for each data center candidate” nor “automatically selects the combination having a maximum total score for deployment and implements a configuration change to the data center and applications of the data center based on the selected combination to optimize renewable energy utilization,” as required by the claims.
Claims 2-6 depend on claim 1 and do not cure the aforementioned deficiencies, and thus, these claims are rejected for the reasons set forth above.
Claim Rejections - 35 USC § 112, Second Paragraph
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.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-6 & 8 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claims 1 & 8 recite “the combination having a maximum total score.” The term “maximum” is a relative term which renders the claim indefinite. The term “maximum” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. It is not clear whether “a maximum total score” is a particular predefined score that is a maximum or whether a combination having a maximum total score is selected by determining a combination having a “highest” score.
Claims 1 & 8 recite “the combination having a maximum total score.” However, the claims previously refer to a “score,” not a “total score.” Accordingly, it is not clear what total score is being referred to here, and thus, how to select such a combination.
Claims 1 & 8 recite “the combination having a maximum total score.” Previously the claims recite “a plurality of combinations” and “each combination.” It is not clear whether “the combination refers to one of “the plurality of combinations,” one combination of the recitation of “each combination,” or introduces a new combination because the claims do not previously introduce “a combination” individually. Moreover, there is insufficient antecedent basis for “the combination” in this limitation in the claim.
Claims 1 & 8 recite “implements a configuration change to the data center.” Previously the claims recite “a plurality of data center candidates” and “each data center candidate.” The claims never previously introduce a “data center” that is not a “candidate.” Further, it is unclear whether “the data center” refers to one data center of the “plurality of data center candidates,” one of data center of “each data center candidate, or introduce a new “data center.” Moreover, there is insufficient antecedent basis for “the combination” in this limitation in the claim.
Claim 1 recites “determines, for each combination, a matching degree between a fluctuation characteristic of the renewable energy supplied to each data center candidate and the level of flexibility of power consumption amount control of each application program type candidate” and then in the next limitation recites again “determines, for each combination, a matching degree between a fluctuation characteristic of the renewable energy supplied to each data center candidate and the level of flexibility of power consumption amount control of each application program type candidate.” It appears these are identical limitations, and thus, it is not clear how these limitations further narrow the claimed invention.
Claims 2-6 depend on claim 1 and do not cure the aforementioned deficiencies, and thus, these claims are rejected for the reasons set forth above.
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 1-6 & 8 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Under prong 1 of Step 2A, claim 1, and similarly claims 2-6 & 8, recites “stores data center candidate management information and application program type candidate management information, the data center candidate management information is used for managing information on a plurality of data center candidates, information on each data center candidate of the plurality of data center candidates indicates a characteristic of renewable energy supplied to each data center candidate, the application program type candidate management information is used for managing information on a plurality of application program type candidates, and application program type candidate management information comprise: (i) information on each application program type candidate of the plurality of application program type candidates indicates a characteristic of each application program type candidate; and (ii) a level of flexibility of power consumption amount control performed by each application program type candidate, and … receives real-time renewable energy supply data for each data center candidate, determines, with reference to the data center candidate management information and the application program type candidate management information, a plurality of combinations each including one or more data center candidates and one or more application program type candidates, determines, for each combination, a matching degree between a fluctuation characteristic of the renewable energy supplied to each data center candidate and the level of flexibility of power consumption amount control of each application program type candidate, … calculates a score for each combination by applying a matching degree coefficient based on a correlation between the level of flexibility of power consumption amount control of each application program type candidate and a level of fluctuation in the characteristic of renewable energy supplied to each data center candidate, and … selects the combination having a maximum total score for deployment and … based on the selected combination to optimize renewable energy utilization.” Claims 1-6 & 8, in view of the claim limitations, recite the abstract idea of collecting information regarding data center candidate management information indicating renewable energy at the data centers and application program type candidate management information indicating a characteristic of each application program type, determining a plurality of combinations of data center candidates and application program type candidates based on the collected information, determining a matching degree between a fluctuation of the renewable energy and the level of flexibility of power consumption amount control of each application program type candidate, calculating a score for each of the combinations based on the determination, and selecting a combination from the combinations to present with the maximum the score.
As a whole, in view of the claim limitations, but for the computer components and systems performing the claimed functions, the broadest reasonable interpretation of the recited collecting information regarding data center candidate management information indicating renewable energy at the data centers and application program type candidate management information indicating a characteristic of each application program type, determining a plurality of combinations of data center candidates and application program type candidates based on the collected information, determining a matching degree between a fluctuation of the renewable energy and the level of flexibility of power consumption amount control of each application program type candidate, calculating a score for each of the combinations based on the determination, and selecting a combination from the combinations to present with the maximum the score could all be reasonably interpreted as a human observing information regarding data center candidate management information and application program type candidate management information to store the information mentally and/or with a pen and paper, a human mentally performing an evaluation and using judgment based on the information to determine combination of the data center candidates and program type candidates, a human mentally performing an evaluation and using judgment based on the information to determine a matching degree and a score for each combination, and a human mentally comparing the scores to selected one of the combinations to present manually and/or using a pen and paper; therefore, the claims recite mental processes. Further, with respect to the dependent claims, aside from the additional elements beyond the recited abstract idea addressed below under the second prong of Step 2A and 2B, the limitations of dependent claims 2-6, recite similar further abstract limitations to those discussed above that narrow the abstract idea recited in the independent claims because, aside from the generic computer components and systems performing the claimed functions the limitations of claims recite mental processes that can be practically performed mentally by observing, evaluating, and judging information mentally and/or with a pen and paper. Accordingly, since the claims recite mental processes, the claims recite an abstract idea under the first prong of Step 2A.
This judicial exception is not integrated into a practical application under the second prong of Step 2A. In particular, the claims recite the additional elements beyond the recited abstract idea of “[a] data center management system comprising: a processor; and a data storage, wherein the data storage,” “automatically,” and “implements a configuration change to the data center and applications of the data center” in claim 1, and similarly in claims 2-6, and further, “[a] method for managing a data center by a system, the method comprising: by the system,” “automatically,” and “implements a configuration change to the data center and applications of the data center” in claim 8; however, individually and when viewed as an ordered combination, and pursuant to the broadest reasonable interpretation, each of the additional elements are computing elements recited at high level of generality implementing the abstract idea on a computer (i.e. apply it), and thus, are no more than applying the abstract idea with generic computer components. Further, these elements generally link the abstract idea to a field of use. Moreover, aside from the aforementioned additional elements, the remaining elements of dependent claims 2-6 do not integrate the abstract idea into a practical application because these claims merely recite further limitations that provide no more than simply narrowing the recited abstract idea.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception under Step 2B. As noted above, the aforementioned additional elements beyond the recited abstract idea, as an order combination, are no more than mere instructions to implement the idea using generic computer components (i.e. apply it), and further, generally link the abstract idea to a field of use, which is not sufficient to amount to significantly more than an abstract idea; therefore, the additional elements are not sufficient to amount to significantly more than an abstract idea. Additionally, these recitations as an ordered combination, simply append the abstract idea to recitations of generic computer structure performing generic computer functions that are well-understood, routine, and conventional in the field as evinced by Applicant’s specification at p. 62 (describing each of the above configurations, functions, and the like may be implemented by software when a processor interprets and executes a program for implementing each function). Furthermore, as an ordered combination, these elements amount to generic computer components performing repetitive calculations, receiving or transmitting data over a network, electronic record keeping, storing and retrieving information in memory, and presenting offers, which, as held by the courts, are well-understood, routine, and conventional. See MPEP 2106.05(d); July 2015 Update, p. 7. Moreover, aside from the aforementioned additional elements, the remaining elements of dependent claims 2-6 do not transform the recited abstract idea into a patent eligible invention because these claims merely recite further limitations that provide no more than simply narrowing the recited abstract idea.
Looking at these limitations as an ordered combination adds nothing additional that is sufficient to amount to significantly more than the recited abstract idea because they simply provide instructions to use a generic arrangement of generic computer components and recitations of generic computer structure that perform well-understood, routine, and conventional computer functions that are used to “apply” the recited abstract idea. Thus, the elements of the claims, considered both individually and as an ordered combination, are not sufficient to ensure that the claims as a whole amount to significantly more than the abstract idea itself. Since there are no limitations in these claims that transform the exception into a patent eligible application such that these claims amount to significantly more than the exception itself, claims 1-6 & 8 are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
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, 2, 4-6, & 8 are rejected under 35 U.S.C. 103 as being unpatentable over Herb, et al. (US 20230017632 A1), hereinafter Herb, in view of Liang, et al., (CN 113394812 A) hereinafter Liang.
Regarding claim 1, Herb discloses a data center management system comprising ([0024], [0077]-[0078], [0082]):
a processor ([0024], [0077]-[0078], [0082]); and
a data storage, wherein the data storage stores ([0086], some or all of the system data structures may be stored (e.g., as structured data) on a computer-accessible medium or a portable article to be read by an appropriate drive, various embodiments may further include storing data implemented in accordance with the foregoing description upon a computer-accessible medium, [0030]-[0032], each data center may store the data (or a version thereof) upon which the operations are performed and tasks of a distributed application, [0038]-[0040], the process obtains environmental-impact-related values such as a conversion weight, price, energy distribution mixture, or the like from an API of a government, utility, or private database) data center candidate management information and application program type candidate management information,
the data center candidate management information is used for managing information on a plurality of data center candidates ([0030]-[0032], a process for tracking and responding to resource consumption of the process 300 includes obtaining a set of workload tasks of an application, like a distributed application, a set of performance criteria, as indicated by block 302, wherein each data center may store the data (or a version thereof) upon which the operations are performed and tasks of a distributed application, wherein the set of performance criteria may include one or more various requirements for target application performance, such as a latency, bandwidth, time-to-first byte, data geofencing, network throughput, availability, measure of central tendency of a response time (e.g., an average application response time), a count of the application instances, a request rate capacity, [0038]-[0040], to determine environmental impact scores of a set of possible task distribution of the set of candidate computing resources, step 310 obtains environmental-impact values such a conversion value representing an amount of carbon footprint (or carbon emissions) per kilowatt-hour, an energy consumption value and the conversion weight, energy distribution mixture, or the like from an API of a government, utility, or private database, or the like, e.g., a web request to an API of a third-party service, where the request may include a location of a data center, an electric power consumption value, or energy source type),
information on each data center candidate of the plurality of data center candidates indicates a characteristic of renewable energy supplied to each data center candidate ([0038]-[0040], to determine environmental impact scores of a set of possible task distribution of the set of candidate computing resources, step 310 obtains environmental-impact values such a conversion value representing an amount of carbon footprint (or carbon emissions) per kilowatt-hour, an energy consumption value and the conversion weight, energy distribution mixture, or the like from an API of a government, utility, or private database, or the like, e.g., a web request to an API of a third-party service, where the request may include a location of a data center, an electric power consumption value, or energy source type, [0025], the obtained environmental impact values, used to determine impact scores, include a rate and a unit type e.g., 30 kilograms of carbon dioxide gas emitted per kilojoule by the power source of a computing resource, unit types, such as energy (e.g., joules) used over time (e.g., seconds), watts (joules/second) or kilowatts per hour, and embodiments may assign categorical values indicating an energy source type, such as “solar” or “coal”, [0051], criteria used to filter out schedules include values indicating how computing resources are allocated or network paths are selected, e.g., requires a set of all data centers in a region must use at least 50% renewable energy, and an update to the policy requires the set of all data centers in a region must use at least 25% renewable energy, and some embodiments adjust a set of weights of the computing resources of the first and second regions to favor the use data centers that draw power from renewable energy sources),
the application program type candidate management information is used for managing information on a plurality of application program type candidates, and application program type candidate management information comprise: (i) information on each application program type candidate of the plurality of application program type candidates indicates a characteristic of each application program type candidate ([0030]-[0032], a process for tracking and responding to resource consumption of the process 300 includes obtaining a set of workload tasks of an application, like a distributed application, a set of performance criteria, as indicated by block 302, wherein each data center may store the data (or a version thereof) upon which the operations are performed and tasks of a distributed application, wherein the set of performance criteria may include one or more various requirements for target application performance, such as a latency, bandwidth, time-to-first byte, data geofencing, network throughput, availability, measure of central tendency of a response time (e.g., an average application response time), a count of the application instances, a request rate capacity); and (ii) a level of flexibility of power consumption amount control performed by each application program type candidate ([0038]-[0040], to determine environmental impact scores of a set of possible task distribution of the set of candidate computing resources, step 310 obtains environmental-impact values such a conversion value representing an amount of carbon footprint (or carbon emissions) per kilowatt-hour, an energy consumption value and the conversion weight, energy distribution mixture, or a request may include a location of a data center, an electric power consumption value, or energy source type, [0025], the obtained environmental impact values, used to determine impact scores, include a rate and a unit type e.g., 30 kilograms of carbon dioxide gas emitted per kilojoule by the power source of a computing resource, unit types, such as energy (e.g., joules) used over time (e.g., seconds), watts (joules/second) or kilowatts per hour, and embodiments may assign categorical values indicating an energy source type, such as “solar” or “coal”, [0051], policy include values indicating how computing resources are allocated or network paths are selected, e.g., first policy requiring all data centers in a region use at least 50% renewable energy, and an update to the policy requiring all data centers in a region use at least 25% renewable energy, embodiments adjust a set of weights of the computing resources to favor data centers that draw power from renewable energy sources), and
the processor:
receives real-time renewable energy supply data for each data center candidate ([0034], process 300 includes obtaining telemetry values indicating the utilization of a set of candidate data centers usable to execute workload tasks in block 304, indicating processor, memory, data plane, control plane, input output (I/O), memory usage at data centers, a computing resource capability to satisfy a set of performance criteria, energy consumption value of the computing resource, predict a future value thereof, [0032], requirements of target applications include requiring operations obtain a result is performed within a time threshold, an average application response time be satisfied),
determines, with reference to the data center candidate management information and the application program type candidate management information, a plurality of combinations each including one or more data center candidates and one or more application program type candidates ([0031], different distributions of workload tasks may characterize or otherwise indicate different workload task distribution schedules, and embodiments may generate a plurality of workload task distribution schedules, [0034], [0038], [0041]-[0042], [0045], process 300 includes obtaining telemetry values indicating the utilization of a set of candidate data centers usable to execute workload tasks in block 304, predicting or determining a set of environmental impact scores such as a carbon footprint amount, electrical energy consumption value, a noise generation value, a water use value, a pollutant generation value, or the like based on a set of possible workload task distribution schedules of the set of candidate computing resources in block 310 for members of a set of candidate computing resources of a workload task distribution schedule from obtained environmental-impact-related values such as a conversion weight, price, energy distribution mixture, and determining measures of computing performance for members of the set of candidate computing resources in block 314 such as a total amount of memory to be allocated by the two data centers, an average response time, a total number of flops to be performed by the two data centers, or the like),
determines, for each combination, … a fluctuation characteristic of the renewable energy supplied to each data center candidate and the level of flexibility of power consumption amount control of each application program type candidate,
determines, for each combination, … a fluctuation characteristic of the renewable energy supplied to each data center candidate ([0038]-[0040], based on environmental-impact-related values such as the conversion value representing an amount of carbon footprint (other carbon emissions) per kilowatt-hour, or energy source type of a candidate computing resource, block 310 predicts/determines a set of environmental impact scores, such as a carbon footprint amount, electrical energy consumption value, of a set of possible workload task distribution of the set of candidate computing resources, [0025], the obtained environmental impact values, used to determine impact scores, include categorical values indicating an energy source type, such as “solar” or “coal” (i.e. energy source type of the candidate computing resource, such as solar or coal, is a fluctuation characteristic of the renewable energy supplied to each data center candidate)) and the level of flexibility of power consumption amount control of each application program type candidate ([0049], [0051], embodiments above may weigh environmental impact scores by one or more weighting factors of a policy, e.g., the policy requires that a set of all data centers in a region must use at least 50%, 25% renewable energy (i.e. a policy requiring a percentage of renewable energy is a level of flexibility of an application candidate)),
calculates a score for each combination by applying a … coefficient based on a correlation between the level of flexibility of power consumption amount control of each application program type candidate ([0038]-[0040], block 310 predicts/determines a set of environmental impact scores, such as a carbon footprint amount, electrical energy consumption value, of a set of possible workload task distribution of the set of candidate computing resources based on environmental-impact-related values such as the conversion value representing an amount of carbon footprints, an electric power consumption value, or energy source type, [0025], the obtained environmental impact values, used to determine impact scores, assign categorical values indicating an energy source type, such as “solar” or “coal”) and a level of fluctuation in the characteristic of renewable energy supplied to each data center candidate ([0048]-[0049], [0051], block 318 determines a workload task distribution schedule of the set of candidate computing resources based on the environmental impact scores and the computing performance measures including determining a plurality of workload distribution values by, after computing the performance measures and environmental impact scores, weigh the scores by weighting factors of a policy, multiply the performance scores and the environmental impact scores by a weighting factor, and resulting in the weighted sum used as a workload distribution value of the first workload task distribution schedule, and repeat these weighted sum operations to determine a plurality of weighted sums as workload distribution values of a plurality of the workload distributions, and embodiments may weigh scores by weighting factors of a policy, including how computing resources are allocated or how network paths are selected, e.g., a first policy requires all data centers in a first region use at least 50% renewable energy, 25% renewable energy, and some embodiments adjust weights to favor the use data centers that draw power from renewable energy sources), and
automatically selects the combination having a maximum total score for deployment ([0048]-[0050], process 300 determines a workload task distribution schedule including members of the set of candidate computing resources based on the set of environmental impact scores and the set of computing performance measures in block 318 by determining a plurality of workload distribution values based on performance scores and an environmental impact scores and then selecting a maximum or minimum value of the plurality of workload distribution values e.g., after the operation results in the weighted sum used as a workload distribution value of the first workload task distribution schedule and is repeated to determine a plurality of other weighted sums as workload distribution values of a plurality of other workload distributions, such as a second workload distribution value, and then the workload distribution values are compared to select, e.g., the first workload task distribution schedule to use for orchestration based on a determination the workload distribution value satisfies a selection criterion) and implements a configuration change to the data center and applications of the data center based on the selected combination to optimize renewable energy utilizations ([0057], process 300 orchestrates a workload to execute the distributed application based on the workload task distribution schedule in block 322 by distributing the a workload into a plurality of workload tasks amongst a set of candidate computing resources, an orchestration system may containerize a workload into a set of pods of a Kubernetes system, where different containers may be distributed across different geographically-separated computing resources to execute workload tasks to be performed by the container, some embodiments may reduce the amount of computing resource being used by a data center by removing containers from the data center, may scale the computing resources assigned to performing a set of workload tasks using a VM instance. may scale a workload at a data center by increasing the number of VM instances in order to satisfy a workload task schedule indicating that the data center is to be assigned an increased number of tasks).
While Herb discloses all of the above, including determines, for each combination, … a fluctuation characteristic of the renewable energy supplied to each data center candidate and the level of flexibility of power consumption amount control of each application program type candidate,
calculates a score for each combination by applying a … coefficient based on a correlation between the level of flexibility of power consumption amount control of each application program type candidate and a level of fluctuation in the characteristic of renewable energy supplied to each data center candidate (as above), Herb does not necessarily expressly require the following remaining limitations, which however are taught by further teachings in Liang.
Liang teaches determines, for each combination, a matching degree between a fluctuation characteristic of the renewable energy supplied to each … candidate and the level of flexibility of power consumption amount control of each application program type candidate (pp. 1-2, the invention provides a method for calculating the matching degree between the output of the new energy field and the electricity load, including: … based on the new energy field output time series and the corresponding power load time series, which includes: determining the model distance between the output of the new energy field and the power load based on the time series of the output of the new energy field and its corresponding power load, p. 11, an example implementation calculates the daily matching degree between the load curve of a certain prefecture-level city and the output of a local distributed photovoltaic station),
calculates a score for each combination by applying a matching degree coefficient based on a correlation between the level of flexibility of power consumption amount control of each application program type candidate and a level of fluctuation in the characteristic of renewable energy supplied to each … candidate (p. 2, wherein model distance is used to calculate the trend matching degree between the output of the new energy field and the electricity load, p. 11, wherein an example calculates the daily matching degree between the load curve of a certain prefecture-level city and the output of a local distributed photovoltaic station).
Herb and Liang are analogous fields of invention because both address the problem of determining allocation of resources based on power consumption and energy supply. At the time the invention was effectively filed, it would have been obvious to one of ordinary skill in the art to include in the system of Herb the ability to determine, for each combination, a matching degree between a fluctuation characteristic of the renewable energy supplied to each candidate and the level of flexibility of power consumption amount control of each application program type candidate and calculate a score for each combination by applying a matching degree coefficient based on a correlation between the level of flexibility of power consumption amount control of each application program type candidate and a level of fluctuation in the characteristic of renewable energy supplied to each candidate, as taught by Liang, since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the combination would produce the predictable results of determining, for each combination, a matching degree between a fluctuation characteristic of the renewable energy supplied to each data center candidate and the level of flexibility of power consumption amount control of each application program type candidate and calculating a score for each combination by applying a matching degree coefficient based on a correlation between the level of flexibility of power consumption amount control of each application program type candidate and a level of fluctuation in the characteristic of renewable energy supplied to each data center candidate, as claimed. Further, it would have been obvious to one of ordinary skill in the art to have modified Herb with the aforementioned teachings of Liang in order to produce the added benefit of solve problems of present technologies to improve the matching output of energy stations and electric loads by accounting for trend of change of the energy stations and electric loads and find the best match. p. 1.
Regarding claim 2, the combined teachings of Herb and Liang teaches the data center management system according to claim 1 (as above). Further, Herb discloses wherein a condition for selecting the combination by the processor is that renewable energy supplied to the one or more data center candidates is equal to or greater than a threshold designated by a user ([0040], a policy includes criteria used to filter out schedules other values indicating how computing resources are allocated or how network paths are selected, e.g., a first update to a policy that requires that a set of all data centers in a first region must use at least 50% renewable energy and a second update to the policy that requires that the set of all data centers in a second region must use at least 25% renewable energy, and some embodiments adjust a set of weights of the computing resources of the first and second regions to favor the use data centers that draw power from renewable energy sources).
Regarding claim 4, the combined teachings of Herb and Liang teaches the data center management system according to claim 1 (as above). Further, Herb discloses wherein the information on each data center candidate of the plurality of data center candidates indicates information on performance of each data center candidate, the information on each application program type candidate of the plurality of application program type candidates indicates information on requested performance of each application program type candidate, and the processor determines the score based on the information on the performance of the data center candidate and the information on the requested performance of the application program type candidate ([0034], [0038], [0041]-[0042], [0045]-[0046], process 300 includes obtaining telemetry values indicating the utilization of a set of candidate data centers usable to execute workload tasks in block 304, and determining measures of computing performance for members of the set of candidate computing resources for use in a workload task distribution schedule in block 314 such as a total amount of memory to be allocated by the two data centers, an average response time, a total number of flops to be performed by the two data centers, or the like, e.g., embodiments may sum a set of known values and compare the sum to a performance criterion, e.g., some embodiments may sum the available memory of a first data center and a second data center for use as a computing performance measure, then determine whether the sum of the available memory satisfies a memory threshold of a performance criterion (e.g., by being greater than the memory threshold), and in response, some embodiments select the first and second data centers for use in a workload task distribution schedule, [0048], operations of the process 300 determining a workload task distribution schedule including members of the set of candidate computing resources based on the set of environmental impact scores and the set of computing performance measures, as indicated for block 318 using a set of selection criteria to determine a workload task distribution schedule, e.g., embodiments determine a workload task distribution schedule by first determining a plurality of workload distribution values based on performance scores, and then selecting a maximum or minimum value of the plurality of workload distribution values, wherein after computing the performance measures, weigh the scores by one or more weighting factors of a policy, multiply a performance score by a weighting factor, this operation results in the weighted sum used as a workload distribution value of the first workload task distribution schedule, and repeat these weighted sum operations to determine a plurality of other weighted sums as workload distribution values of a plurality of other workload distributions, such as a second workload distribution value).
Regarding claim 5, the combined teachings of Herb and Liang teaches the data center management system according to claim 1 (as above). Further, Herb discloses wherein the information on each data center candidate of the plurality of data center candidates indicates priority of each data center candidate, and the processor determines the score based on the priority ([0049], in some embodiments the orchestration system determines a workload task distribution schedule by first determining a plurality of workload distribution values based on performance scores and an environmental impact scores and then selecting a maximum or minimum value of the plurality of workload distribution values, [0050], the weights or other values of a policy indicating how computing resources are allocated or how network paths are selected provide a prioritization scheme, e.g., some embodiments may multiply a performance score of 0.8 by a weighting factor of 0.25 and an environmental impact score of 0.4 by a weighting factor of 0.75 to receive the weighted performance score of 0.2 and 0.3, respectively, which results in a weighted sum of 0.5 as a workload distribution value of the first workload task distribution schedule, and embodiments may repeat these weighted sum operations to determine a plurality of other weighted sums as workload distribution values of a plurality of other workload distributions, such as a second workload distribution value of 0.9 for a second workload task distribution schedule, embodiments may then compare the workload distribution values and determine that the first workload distribution value is less than any other value of the plurality of workload distribution values, and in response, embodiments may select the first workload task distribution schedule to use for orchestration based on a determination the workload distribution value satisfies a selection criterion when the workload distribution value is a minimum value in a set of other workload distribution values).
Regarding claim 6, the combined teachings of Herb and Liang teaches the data center management system according to claim 1 (as above). Further, Herb discloses wherein the processor determines the score based on a relation between ranges of power generation sources configured to supply renewable energy to each of the one or more data center candidates ([0025], some embodiments may assign categorical values, indicating an energy source type, such as “solar” or “coal,” and then use the environmental impact values obtained from the energy data server 205 to determine a first environmental impact score 216 and a second environmental impact score 226 for the first containerized computing resource 210 and the second containerized computing resource 220, respectively, [0040], a policy includes criteria used to filter out schedules other values indicating how computing resources are allocated or how network paths are selected, e.g., a first update to a policy that requires that a set of all data centers in a first region must use at least 50% renewable energy and a second update to the policy that requires that the set of all data centers in a second region must use at least 25% renewable energy, and some embodiments adjust a set of weights of the computing resources of the first and second regions to favor the use data centers that draw power from renewable energy sources).
Regarding claim 8, this claim is substantially similar to claim 1, and thus, claim 8 is rejected for the reasons set forth above regarding claim 1. While claim 8 is directed to a method, Zarakas discloses a method as claimed. [0077], [0092].
Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over Herb, et al. (US 20230017632 A1), hereinafter Herb, in view of Liang, et al., (CN 113394812 A) hereinafter Liang, and in further view of Reineke, et al., (US 20230237398 A1) hereinafter Reineke.
Regarding claim 3, the combined teachings of Herb and Liang teaches the data center management system according to claim 1 (as above). Further, while Herb discloses all of the above and wherein the information on each application program type candidate of the plurality of application program type candidates includes information on a … of the application program type candidate ([0032], the set of performance criteria may include one or more various requirements for target application performance, such as a latency, bandwidth, time-to-first byte, data geofencing, network throughput, availability, measure of central tendency of a response time (e.g., an average application response time), a count of the application instances, a request rate capacity, or the like, e.g., the set of performance criteria may include a requirement an average application response time be satisfied that represents a response time for an application executing on a set of client computing devices in communication with a data center, and enforcing the performance criterion may cause the selection of a subset of data centers to execute an application workload that will satisfy the average application response time some embodiments may have a plurality of performance criteria, e.g., some embodiments include a first criterion requiring that operations to obtain a result is performed within a time threshold and a second criterion that a request-response latency between a set of client computing devices in communication with an application and any data center used to execute the application is less than a latency threshold), the processor determines a predicted … value of the combination to be presented based on the information on the profit ([0045], [0047]-[0048], process 300 determines measures of computing performance for members of the set of candidate computing resources in block 314 using subsets of the candidate computing resources described above when determining measures of computing performance, e.g., the measure may include as a total amount of memory to be allocated by the two data centers, an average response time, a total number of flops to be performed by the two data centers, e.g., embodiments may predict that implementing a workload distribution causing the distribution of a set of workload tasks will take 8 minutes to complete, and then determine a workload task distribution schedule including members of the set of candidate computing resources based on the set of computing performance measures in block 318, wherein a set of selection criteria may be used to determine a workload task distribution schedule), and information on a renewable energy supply amount of one or more data center candidates of the combination to be presented and the predicted … value are included in information on the combination to be presented ([0025], some embodiments may assign categorical values, indicating an energy source type, such as “solar” or “coal,” and then use the environmental impact values obtained from the energy data server 205 to determine a first environmental impact score 216 and a second environmental impact score 226 for the first containerized computing resource 210 and the second containerized computing resource 220, respectively, [0038], [0040], [0043], the process 300 predicts or otherwise determines a set of environmental impact scores based on a set of possible workload task distribution schedules associated with the set of candidate computing resources in block 310, a policy includes criteria used to filter out schedules other values indicating how computing resources are allocated or how network paths are selected, e.g., a first update to a policy that requires that a set of all data centers in a first region must use at least 50% renewable energy and a second update to the policy that requires that the set of all data centers in a second region must use at least 25% renewable energy, and some embodiments adjust a set of weights associated with the computing resources of the first and second regions to favor the use data centers that draw power from renewable energy sources, some embodiments may obtain metrics indicating that a data center or other computing resource may obtain power from a plurality of energy source types, and in some embodiments, each respective data center of a set of data centers may be assigned a respective score representing an environmental impact, e.g., a first data center may obtain power from a solar plant and from a natural gas plant, where the two generators may have different carbon footprint scores, [0048], operations of the process 300 determining a workload task distribution schedule including members of the set of candidate computing resources based on the set of environmental impact scores and the set of computing performance measures, as indicated for block 318 using a set of selection criteria to determine a workload task distribution schedule), Herb does not appear to expressly disclose all the remaining elements of the following limitation, which however, are taught by further teachings in Reineke.
Reineke teaches wherein the information on each application program type candidate of the plurality of application program type candidates includes information on a profit of the application program type candidate ([0121], [0124], at step 850 the data center monitoring and management console 118 provides a user with information regarding quantification (e.g., monetization) of the particular infrastructure configuration based upon the particular data center infrastructure utilization unit, wherein the quantification of the particular infrastructure configuration based upon the particular data center infrastructure utilization unit can also include representation of a profit generated based upon the quantification of the particular infrastructure configuration based upon the particular data center infrastructure utilization unit), the processor determines a predicted profit value of the combination to be presented based on the information on the profit, and information on a renewable energy supply amount of one or more data center candidates of the combination to be presented ([0101], [0111], [0115], e.g., a customer can set organizational value as sustainability, to use solar power, e.g., with a particular customer a sustainable value preference is to use solar power, the recommendation engine 414 matches the type of power that is in the infrastructure available, a particular data center location (XYZ) might be primarily solar-powered (thus meeting the customer's primary value), and a customer might choose to use a cluster which is includes a new form factor called “ServerClusterGreen” which is made out of recycled materials, thus meeting a secondary sustainability goal of the customer as well, and the recommendation is presented to the customer in a transparent manner so the customer could continue with the recommendation or select a different choice, the data center monitoring and management console UI may be implemented to provide a user with the ability to select (i.e., to identify) one or more organizational values (see e.g., FIG. 6B), and the data center monitoring and management console UI may be implemented to provide a user with one or more infrastructure recommendations (see e.g., FIG. 6D), wherein the recommendations include an indication of how the recommendation aligns with one or more of the organizational values identified as important to the organization) and the predicted profit value are included in information on the combination to be presented ([0121], [0124], the data center monitoring and management console UI may be implemented to provide a user with a quantification of a particular infrastructure configuration based upon the particular data center infrastructure utilization unit (see e.g., FIG. 9D), e.g., the quantification of the particular infrastructure configuration based upon the particular data center infrastructure utilization unit can also include representation of a simulated profit).
Herb and Reineke are analogous fields of invention because both address the problem of determining allocation of computing tasks based on sustainability, computing resource availability, and performance. At the time the invention was effectively filed, it would have been obvious to one of ordinary skill in the art to include in the system of Herb the ability for the information on each application program type candidate of the plurality of application program type candidates to include information on a profit of the application program type candidate, the arithmetic device to determine a predicted profit value of the combination to be presented based on the information on the profit, and information on a renewable energy supply amount of one or more data center candidates of the combination to be presented and the predicted profit value are included in information on the combination to be presented, as taught by Reineke, since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the combination would produce the predictable results of the information on each application program type candidate of the plurality of application program type candidates including information on a profit of the application program type candidate, the arithmetic device determining a predicted profit value of the combination to be presented based on the information on the profit, and information on a renewable energy supply amount of one or more data center candidates of the combination being presented and the predicted profit value are included in information on the combination being presented, as claimed. Further, it would have been obvious to one of ordinary skill in the art to have modified Herb with the aforementioned teachings of Reineke in order to produce the added benefit of improving monitoring and management of data center assets. [0022].
Conclusion
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CHARLES GUILIANO
Primary Examiner
Art Unit 3623
/CHARLES GUILIANO/Primary Examiner, Art Unit 3623