DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Notice to Applicant
Claims 1-17 are pending.
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 1-17 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to a judicial exception (i.e. a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Step 1 – Statutory Categories of Invention:
Claims 1-17 are drawn to a method which is one of the statutory categories of invention.
Step 2A – Judicial Exception Analysis, Prong 1:
Independent claim 1 recites a method comprising the following:
performing ……..of one or more individual applications of the data center;
with an …..output…., generating an …..graph;
determining each component of each individual application of one or more individual applications of the data center, wherein a component comprises ……..of each individual application;
implementing a components mapping of each component of each individual application into the ……graph, wherein, with the ….graph, a plurality of components are represented as nodes and the connectivity between the nodes represented as edges, wherein based on a knowledge of the data-center environment, wherein each component is identified to correspond to each hardware component or each software component;
implementing a workload in the data center, wherein the workload comprises a set of one or more tasks which are performed over a time period towards a specific goal;
implementing a workload manager, wherein the workload manager executes the set of tasks in the workload, wherein a path of execution of the set of tasks is defined as the workflow; and
with the …., ….graph and Component Resource Utilization, calculating a carbon cost of individual workload in a data center of the workload to generate a carbon footprint calculation.
These steps amount to functions performable in the mind or with pen and paper and are only concepts relating to organizing or analyzing information in a way that can be performed mentally or is analogous to human mental work (MPEP § 2106.04(a)(2)(III)(B) citing the abstract idea grouping for mental processes with or without physical aid).
These steps also amount to a mathematical concept which includes mathematical relationships, mathematical formulas or equations, and mathematical calculations. The mathematical concept need not be expressed in mathematical symbols but not merely limitations that are based on or involve a mathematical concept (MPEP § 2106.04(a)(2)(I)(A) citing the abstract idea grouping for mathematical concepts for mathematical relationships).
Dependent claim 2 recites, in part, applying the carbon footprint calculation process as defined by a Green House Gas (GHG) Protocol.
Dependent claim 3 recites, in part, wherein the carbon footprint calculation is identified at the carbon footprint at the workload level.
Dependent claim 4 recites, in part, mapping the carbon footprint calculation process as defined by a Green House Gas (GHG) Protocol to an individual workload.
Dependent claim 5 recites, in part, wherein the carbon cost of the workload comprises an intrinsic carbon cost that comprises a summation of the difference of the carbon cost of the application when only the task is running on the application with the carbon cost of the application when no other tasks are running on the application and this is done for all the tasks of the workload running on all the different applications.
Dependent claim 6 recites, in part, wherein the carbon cost a carbon cost of the application when no tasks can be calculated.
Dependent claim 7 recites, in part, wherein the carbon cost of the application before running the task on the application is used.
Dependent claim 8 recites, in part, identifying the application used by each of these various tasks of the workload.
Dependent claim 9 recites, in part, identify what fraction of the application resource is consumed during the execution of the task as an extrinsic carbon footprint.
Dependent claim 10 recites, in part, wherein the fraction of the application resource is identified for a utilization when using a specified infrastructure or specified service.
Dependent claim 11 recites, in part, wherein the carbon footprint calculation is used to reduce an overall footprint in the data center.
Dependent claim 12 recites, in part, wherein the carbon footprint calculation is provided to a real-time monitoring tool for the application.
Dependent claim 13 recites, in part, wherein the step of calculating the cost of running the workload in the data center further comprises: calculating an extrinsic cost of running the workload in the data center.
Dependent claim 14 recites, in part, optimizing the high-cost workloads for lower cost.
Dependent claim 15 recites, in part, wherein the optimization of the high-cost workloads comprises re-architecting the high-cost workload.
Dependent claim 16 recites, in part, wherein the optimization of the high-cost workloads comprises rescheduling the high-cost workload.
Dependent claim 17 recites, in part, wherein the optimization of the high-cost workloads comprises deprioritizing the high-cost workload.
Each of these steps of the preceding dependent claims 2-17 only serve to further limit or specify the features of independent claim 1 accordingly, and hence are nonetheless directed towards fundamentally the same abstract idea as the independent claim and utilize the additional elements already analyzed in the expected manner.
Step 2A – Judicial Exception Analysis, Prong 2:
This judicial exception is not integrated into a practical application because the additional elements within the claims only amount to instructions to implement the judicial exception using a computer [MPEP 2106.05(f)].
Independent Claim 1 recites Application Discovery and Dependency Mapping (ADDM), an ADDM output, an ADDM graph, a hardware component, a software component. The specification defines Application Discovery and Dependency Mapping (ADDM) as the process of identifying the dependencies of individual components of the application (Example Embodiments in ¶ 0008), an ADDM output as from the ADDM (Example Embodiments in ¶ 0006), an ADDM graph as a graph with these individual components represented as nodes and the connectivity between the nodes represented as edges (Example Embodiments in ¶ 0008), a hardware component as servers, containers, virtual machines (Example Embodiments in ¶ 0046), a software component as software deployed on infrastructure (e.g. BareMetal, VMs) or Platform-as-a-Service (PaaS) offerings in the cloud such as, inter alia: Database, Cache, Serverless, Kubernetes, big data, Spark, streaming analytics, etc. (Example Embodiments in ¶ 0046). The use of the Application Discovery and Dependency Mapping (ADDM), an ADDM output, an ADDM graph, a hardware component, a software component are only recited as a tool to perform an existing process and only amounts to an instruction to implement the abstract idea using a computer (MPEP § 2106.05(f)(2) see case requiring the use of software to tailor information and provide it to the user on a generic computer within the “Other examples.. v.”).
The dependent claims do not recite any additional elements.
The above claims, as a whole, are therefore directed to an abstract idea.
Step 2B – Additional Elements that Amount to Significantly More:
The present claims do not include additional elements that are sufficient to amount to more than the abstract idea because the additional elements or combination of elements amount to no more than a recitation of instructions to implement the abstract idea on a computer.
Independent Claim 1 recites Application Discovery and Dependency Mapping (ADDM), an ADDM output, an ADDM graph, a hardware component, a software component. Each of these elements is only recited as a tool for performing steps of the abstract idea, such as use of the Application Discovery and Dependency Mapping (ADDM), an ADDM output, an ADDM graph, a hardware component, a software component to store, analyze, and process data. These additional elements therefore only amount to mere instructions to perform the abstract idea using a computer and are not sufficient to amount to significantly more than the abstract idea (MPEP 2016.05(f) see for additional guidance on the “mere instructions to apply an exception”).
Each additional element under Step 2A, Prong 2 is analyzed in light of the specification’s explanation of the additional element’s structure. The claimed invention’s additional elements do not have sufficient structure in the specification to be considered a not well-understood, routine, and conventional use of generic computer components. Note that the specification can support the conventionality of generic computer components if “the additional elements are sufficiently well-known that the specification does not need to describe the particulars of such additional elements to satisfy 35 U.S.C. § 112(a)” (Berkheimer in III. Impact on Examination Procedure, A. Formulating Rejections, 1. on p. 3).
Thus, taken alone, the additional elements do not amount to significantly more than the above-identified judicial exception. Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. Their collective functions merely provide conventional computer implementation.
Claims 1-17 are therefore rejected under 35 U.S.C. § 101 as being directed to non-statutory subject matter.
Subject Matter Free of the Prior Art
7. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure (see Conclusion) failed to teach the following limitations:
performing Application Discovery and Dependency Mapping (ADDM) of one or more individual applications of the data center;
with an ADDM output from the ADDM, generating an ADDM graph;
determining each component of each individual application of one or more individual applications of the data center, wherein a component comprises a hardware component or a software component of each individual application;
implementing a components mapping of each component of each individual application into the ADDM graph, wherein, with the ADDM graph, a plurality of components are represented as nodes and the connectivity between the nodes represented as edges, wherein based on a knowledge of the data-center environment, wherein each component is identified to correspond to each hardware component or each software component;
implementing a workload in the data center, wherein the workload comprises a set of one or more tasks which are performed over a time period towards a specific goal;
implementing a workload manager, wherein the workload manager executes the set of tasks in the workload, wherein a path of execution of the set of tasks is defined as the workflow; and
with the ADDM, ADDM graph and Component Resource Utilization, calculating a carbon cost of individual workload in a data center of the workload to generate a carbon footprint calculation.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
DATABASE CONFIGURATION ANALYSIS (US 20070174335 A1) teaches a plurality of queries may be sampled from a representative workload using statistical inference to compute the probability of correctly selecting one of a plurality of evaluation configurations. The probability of correctly selecting may determine which and/or how many queries to sample, and/or may be compared to a target probability threshold to determine if more queries must be sampled. The configuration from the plurality of configurations with the lowest estimated cost of executing the representative workload may be determined based on the probability of selecting correctly. Estimator variance may be reduced through a stratified sampling scheme that leverages commonality, such as an average cost of execution, between queries based on query templates. The applicability of the Central Limit Theorem may be verified and used to determine which and/or how many queries to sample.
SYSTEM AND METHOD FOR COMPUTERIZED PREDICTIVE PERFORMANCE ANALYSIS OF NATURAL LANGUAGE (US 20180025303 A1) teaches behavior assessment or performance prediction, comprising: acquiring a video stream of an interviewee responding to a set of interview prompts or a corpus of documents of a subject; analyzing at least the semantic content of the video stream or corpus; statistically processing, with at least one automated processor, the semantic content according to a correspondence of the interviewee's response or subject's corpus to a set of classified exemplar responses, and a context, to classify the interviewee or subject with respect to the context; and generating at least one output selectively dependent on the classification of the interviewee or subject.
Workload placement based on carbon emissions (US 12086650 B2) teaches Workload placement based on carbon emissions, including: calculating, for each execution environment of a plurality of execution environments, a carbon emission cost associated with a workload; selecting, based on each carbon emission cost for the plurality of execution environments, a target execution environment; and executing the workload on the target execution environment.
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/AMBER A MISIASZEK/Primary Examiner, Art Unit 3682