DETAILED ACTION
This action is in response to an amendment filed on October 7, 2025 for the application of Hwang et al., for a “Machine learning classification of object store workloads” filed on March 4, 2022. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claims 1-12 and 15-20 are pending in the application.
Claims 13-14 have been cancelled.
Claims 1, 8, and 16 have been amended.
Claims 1-12 and 15-20 are rejected under 35 USC § 101.
Specification
The disclosure is objected to because of the following informalities: In view of the amendments filed on October 7, 2025, the title of the invention is not descriptive. A new title is required that is clearly indicative of the invention to which the claims are directed.
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 1-12 and 15-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim(s) recite(s) mental processes-concepts performed in human mind.
Claim 1 recites abstract ideas:
an access component that accesses a resource utilization descriptor representing how a workload of a data store consumes resources of the data store, wherein the resource utilization descriptor indicates at least one of a computer processing unit utilization level of the data store that is caused by the workload, a temporary computer memory utilization level of the data store that is caused by the workload, a permanent computer memory utilization level of the data store that is caused by the workload, or a network bandwidth utilization level of the data store that is caused by the workload, wherein the resource utilization descriptor includes metrics pertaining to counter manager objects, platform characteristics associated with the data store and environmental metrics corresponds to data analysis steps recited at high level of generality such that they could be performed in the human mind, which are mental processes. The broadest reasonable interpretation of the limitations in light of the specification encompasses analyzing data values/trends/patterns ([0062]).
a model component that generates, via execution of a machine learning model, a classification label based on the resource utilization descriptor, wherein the model component feeds the resource utilization descriptor as input to the machine learning model, wherein the machine learning model produces as output the classification label, and wherein the classification label characterizes the workload of the data store is directed to generating a classification label which is considered a mental process of assigning labels to data. Using a machine learning model is directed to generic computer components recited at a high-level of generality such that they amount to nothing more than mere instructions to apply the exception using generic computer components (MPEP 2106.05(f)).
an execution component that performs one or more electronic actions based on the classification label, wherein the one or more electronic actions include generating and electronically transmitting a recommendation that indicates that the workload could be successfully transplanted to a particular data store that is different than the data store and suggests that such transplantation be carried out when the classification label indicates that the workload represented by the resource utilization descriptor can be successfully transplanted to the particular data store and wherein the one or more electronic actions include generating and electronically transmitting a different recommendation that indicates that the workload could not be successfully transplanted to the particular data store and suggests that such transplantation not be carried out when the classification label indicates that the workload represented by the resource utilization descriptor cannot be successfully transplanted to the particular data store corresponds to data analysis steps recited at high level of generality such that they could be performed in the human mind, which are mental processes. Analyzing resource utilization data to infer possibility of a successful workload transfer and making a recommendation/suggestion as to whether the workload transfer would/would not be successful is a mental process. The broadest reasonable interpretation of the limitations in light of the specification encompasses recommendations of a suggestion ([0096] and [0119]-[0120]).
Claim 1 does not recite additional elements that integrate the judicial exceptions into practical application.
a processor that executes computer-executable components stored in a non-transitory computer-readable memory amounts to mere instructions to implement the abstract ideas on a computer, which is mere instructions to apply the exception using generic computer components (MPEP 2106.05(f)).
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements are mere instructions to implement an abstract idea or other exception on a computer and in this case generic computer components (MPEP 2106.05(f)).
As for the limitations recited in claims 2-7, when considering each of the claims as a whole these additional elements do not integrate the exception into a practical application, using one or more of the considerations laid out by the Supreme Court and the Federal Circuit. The additional elements do not reflect an improvement in the functioning of a computer, or an improvement to other technology or technical field. The additional elements do not implement a judicial exception with, or use a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim. The additional element do not apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception.
Claims 8-12 and 15 recite a computer-implemented method of claims 1-7’s system. Therefore, claims 8-12 and 15 are rejected on the same grounds as claims 1-7.
Claim 8 does not recite additional elements that integrate the judicial exceptions into practical application.
a device operatively coupled to a processor amounts to mere instructions to implement the abstract ideas on a computer, which is mere instructions to apply the exception using generic computer components (MPEP 2106.05(f)).
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements are mere instructions to implement an abstract idea or other exception on a computer and in this case generic computer components (MPEP 2106.05(f)).
Claims 11-12 recite the limitations of a resource of the data store that is being underutilized/overutilized and transmitting a suggestion that utilization of such resource be increased/decreased. These limitations are directed to adding/removing/balancing resources, which has been recognized by the courts as being well-understood, routine, and conventional functions (MPEP 2106.05(d)). The following prior arts are examples of well-understood, routine, and conventional functions of adding/removing/balancing resources:
Adamson et al. (U.S. PGPUB 20190129779) discloses various remedies for resource overutilization and resource underutilization ([0039]-[0042]).
Kaminski et al. (U.S. PGPUB 20150365309) discloses load balancing for resource overutilization and resource underutilization ([0109]).
Claims 16-20 recite a computer program product of claims 1-7’s system. Therefore, claims 8-16 are rejected on the same grounds as claims 1-7.
Claim 16 does not recite additional elements that integrate the judicial exceptions into practical application.
A computer program product for facilitating machine learning classification of workloads of a data store so as to support provision of tailored warnings or recommendations regarding the data store, the computer program product comprising a non-transitory computer-readable memory having program instructions embodied therewith, the program instructions executable by a processor to cause the processor amounts to mere instructions to implement the abstract ideas on a computer, which is mere instructions to apply the exception using generic computer components (MPEP 2106.05(f)).
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements are mere instructions to implement an abstract idea or other exception on a computer and in this case generic computer components (MPEP 2106.05(f)).
For the reasons stated above, claims 1-12 and 15-20 are not patent eligible.
Claim Rejections - 35 USC § 103
In view of the applicant’s amendments, the previous rejection of claims 1-20 has been withdrawn.
Reasons for allowance
The following is an examiner’s statement of reasons for allowance:
After a complete search of all the relevant prior art the examiner has determined the claims are in condition for allowance. The following limitations when viewed in combination with the remainder of the claim as a whole place this application in condition for allowance.
As per independent claims 1, 8, and 16, the examiner finds the novel and non obvious feature of claims, when read as whole to be a model component that generates, via execution of a machine learning model, a classification label based on the resource utilization descriptor, wherein the model component feeds the resource utilization descriptor as input to the machine learning model, wherein the machine learning model produces as output the classification label, and wherein the classification label characterizes the workload of the data store; and an execution component that performs one or more electronic actions based on the classification label, wherein the one or more electronic actions include generating and electronically transmitting a recommendation that indicates that the workload could be successfully transplanted to a particular data store that is different than the data store and suggests that such transplantation be carried out when the classification label indicates that the workload represented by the resource utilization descriptor can be successfully transplanted to the particular data store and wherein the one or more electronic actions include generating and electronically transmitting a different recommendation that indicates that the workload could not be successfully transplanted to the particular data store and suggests that such transplantation not be carried out when the classification label indicates that the workload represented by the resource utilization descriptor cannot be successfully transplanted to the particular data store.
The closest prior art is Adamson et al. (U.S. PGPUB 20190129779), which was cited in the previous office action mailed on June 9, 2025.
Adamson teaches transmitting a recommendation that indicates that the workload could be successfully transplanted to a particular data store that is different than the data store and suggests that such transplantation be carried out when the classification label indicates that the workload represented by the resource utilization descriptor can be successfully transplanted to the particular data store ([0041]-[0045]).
However, Adamson fails to teach the above limitations as recited in claims 1, 8, and 16.
Therefore, the prior art does not teach the claimed invention as recited in independent claims 1, 8, and 16. Claims 2-7, 9-12, 15, and 17-20 are allowed because the claims are dependent upon independent claims 1, 8, and 16.
Any comments considered necessary by applicant must be submitted no later than the payment of the issue fee and, to avoid processing delays, should preferably accompany the issue fee. Such submissions should be clearly labeled “Comments on Statement of Reasons for Allowance.”
Response to Arguments
With respect to the 35 U.S.C. 101 rejections, applicant argues that amendments discussed during an interview on August 5, 2025 overcome the 35 U.S.C. 101 rejections. The Examiner respectfully disagrees and would like to point out that during the interview no agreement was reached regarding the proposed amendments overcoming the 35 U.S.C. 101 rejections.
Examiner further notes that various sections of the applicant’s specifications disclose generating recommendations of a suggestion of a remedial action (see paragraphs [0096] and [0119]-[0120]). Making a suggestion is a mental process. Please refer to the 35 U.S.C. 101 rejection analysis section for claims 1-12 and 15-20.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Elmira Mehrmanesh whose telephone number is (571)272-5531. The examiner can normally be reached on M-F from 10-6.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Bryce Bonzo, can be reached at telephone number (571) 272-3655. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/Elmira Mehrmanesh/
Primary Examiner, Art Unit 2113
Prosecution Insights