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 .
This communication is a Non-Final Office Action in response to Applicant’s request for continued examination, filed on March 19, 2026. This communication is also in response to a telephonic interview held with Applicant’s representative, Farhad Shir, to determine how to best expedite prosecution. See attached interview summary.
Claims 1-18 have been examined in this application.
No new information disclosure statement (IDS) has been filed.
Response to Arguments
Applicant’s arguments, filed on March 4, 2026, regarding claim objections and rejections under 35 U.S.C. 112 have been fully considered and are persuasive. Therefore, the objections and rejections are withdrawn.
Applicant’s arguments, pages 9-11, regarding claim rejections under 35 U.S.C. 101 have been fully considered but are not persuasive.
Applicant argues that the claims are directed to technical mechanisms of workload migration including partial migration without requirement of full data migration. Applicant also argues that the claims capture specific technical solutions linked to data center storage management, which cannot be carried out mentally. Applicant points to the Specification that discloses how this migration allows control over renewable energy and reducing overall carbon emissions. Applicant argues that the swapping of volume attribute workload cannot be done mentally. The claims require specific technical volume change designation between devices and redirecting data writes without full migration requirements. Therefore, Applicant argues that the alleged abstract idea is transformed to eligible subject matter because the claims capture a practical application that is based on the improvement of data center operations. Finally, Applicant cites case law and claims that said case law is analogous to the instant claims.
The Examiner respectfully disagrees. The claims are recited at a high level of generality, amounting to merely an abstract idea of designating workloads to different entities in response to analyzing data without significantly more. The abstract idea is found to be linked to mental processes and mathematical concepts. The claims require a calculation of a score or threshold of usage of energy and workload of a data center. This is clearly usage / based on a formula. Said formula can be carried out using a human mind and control of workload can be carried out by the human mind after calculation of the score as claimed. The claims are interpreted under the broadest reasonable interpretation to be directed to an entity that calculates data, determines other entities withing a group of entities that can carry out the workload, executes and control the migration of workload based on the calculated data and other data such as energy availability. These functions are generic computer function and nothing more. Contrary to Applicant’s arguments, the claims fail to provide any technical elements that would amount to a practical application. In fact, the additional elements present in the claims are recited at a high level of generality, capturing merely a device that is used to carry out the abstract idea; applying to abstract idea using the generic additional elements. These additional elements, argued technical elements, are carry out off-the-shelf basic computer functions such as analyzing or calculating data, generating data, and output a result. A technical solution is not deemed to be present as Applicant argues. The claimed server and is structure merely aid in applying to abstract idea. Also, said additional elements add insignificant extra-solution activity to the judicial exception; see MPEP 2106.05(g) and the use of the judicial exception is deemed as merely being linked to a particular technological environment or field of use; see MPEP 2106.05(h). Thus, the claims are deemed to be directed to the identified abstract idea above and further fail to include any additional elements that would amount to a practical application. The mental process abstract idea is in fact captured by the claims because aside from using the server or the additional elements, the claimed scope is in fact possible to be carried out by a human mind using pen-and-paper. Calculations are possible to be carried out by a human mind and pen-and-paper, likewise it is possible to determine how to manage the distribution of copies among data center based on the calculation and implementing the distribution without having to require the selected data center(s) to carry out the selected data file migration; not the entire full data migration. Applicant’s arguments directed to the cited case law are not relevant and they were not the basis of the rejection; rending the arguments moot.
The claims fail to amount to significantly more than the abstract idea. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements amount to merely instructions to apply the exception using generic computer components. The claim limitations do not improve another technology or technical field, improve the functioning of a computer itself, apply the abstract idea with, or by use of, a particular machine (not a generic computer, not adding the words "apply it" or words equivalent to "apply the abstract idea", not mere instructions to implement an abstract idea on a computer, adding insignificant extra solution activity to the judicial exception, generally linking the user of the judicial exception to a particular technological environment or field of use), effects a transformation or reduction of a particular article to a different state or thing, or adds meaningful limitations that amount to more than generally linking the use of the abstract idea to a particular technological environment. Mere instructions to apply an exception using generic computer components cannot provide an inventive concept.
The dependent claims do not include additional elements that integrate the abstract idea into a practical application or that provide significantly more than the abstract idea. The dependent claims fail to recite additional elements that would amount to a practical application or amount to significantly more than the judicial exception as discussed above. The dependent claims further describe the abstract idea.
The rejection is maintained.
Claim Objections
Claims 5, 11, and 17 are objected to because of the following informalities: the dependent claims recite “a standard deviation” which is already introduced in the independent claims; therefore, it’s not clear whether this is a new standard deviation of the sum or the same mathematical function as in the independent claims. Under prior art, it will be deemed as the same. Appropriate correction is required.
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 1-18 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter.
Claims 1-18 fall within at least one of the four categories of patent eligible subject matter (process, machine, manufacture, or composition of matter).
Claims 1-18 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea of managing migration of workloads between data centers based on manipulation of data without significantly more.
The abstract idea is categorized under mathematical concepts and mental processes, including mathematical relationships, formulas and calculations, and concepts performed in the human mind including observation, evaluation, judgement, and opinion and performing said mental concepts using pen and paper. A human can utilize a paper and pen to record workload or power usage between other users or entities. When a certain threshold of workload or power usage is reached, the user can determine which other entity can carry over the workload or has not reached the threshold power usage and delegate that other entity to handle some of the workload. The score is recited at a high level, therefore, it is something that can be determined using basic formular/equations or mental analysis. The determination of workload among entities is something that can be done mentally, visually, and analyzed mentally and a determination based on the entity usage and workload can be made. Likewise, the claims capture basic formulas used to calculate a score for each data center and based on the score determine how to distribute the copies among the data centers without exceeding thresholds or mathematical limits. The additional elements, as will be discussed later, merely apply the abstract idea or automate the abstract idea.
Claim 7 recites, in pertinent part:
A workload control method for controlling migration of workloads between a first data center and one or more second data centers by a data center management… [entity], wherein the first data center and one or more second data centers are among a plurality of data centers, and wherein the migration is controlled based on renewable energy supply at the data centers, comprising:
calculating… a complementary score of each of the plurality of data centers based on information of time-series data of past renewable energy supply at the each of the plurality of data centers,
determining… one or more second data centers among the one or more second data centers as destination data centers for creation of remote copies to one or more volumes by selecting, in order of the complementary score, from the plurality of data centers having a remote copy pair count that has not reached a threshold; and
executing… creation of the remote copies to the one or more second data centers; and
controlling… migration of the workloads between the first data center and the one or more second data centers by swapping volume attributes in response to renewable energy supply at the first data center falling below a threshold, wherein the swapping of volume attributes comprises changing a volume designation from secondary to primary at a second data center storage device and from primary to secondary at the first data center storage device, thereby redirecting application data writes to the second data center without requiring full data migration, to control use of renewable energy in executing workloads and reduce carbon emissions from the plurality of data centers.
The judicial exception is not integrated into a practical application. The claims recite the following additional elements: a processor, a data center management server, and a non-transitory computer readable medium, storing instructions, when executed by a processor of a data center management server. The additional elements are recited at a high level of generality, wherein the claims merely amount to an abstract idea that is implemented using generic computers, performing generic computer functions such as calculating data, analyzing data, determining an outcome and causing an output based on the determination. Each of the additional elements / limitations are no more than mere instructions to apply the exception using generic computer components or a generic device. Accordingly, even in combination, the additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements amount to merely instructions to apply the exception using generic computer components. The claim limitations do not improve another technology or technical field, improve the functioning of a computer itself, apply the abstract idea with, or by use of, a particular machine (not a generic computer, not adding the words "apply it" or words equivalent to "apply the abstract idea", not mere instructions to implement an abstract idea on a computer, adding insignificant extra solution activity to the judicial exception, generally linking the user of the judicial exception to a particular technological environment or field of use), effects a transformation or reduction of a particular article to a different state or thing, or adds meaningful limitations that amount to more than generally linking the use of the abstract idea to a particular technological environment. Mere instructions to apply an exception using generic computer components cannot provide an inventive concept.
The dependent claims do not include additional elements that integrate the abstract idea into a practical application or that provide significantly more than the abstract idea. The dependent claims fail to recite additional elements that would amount to a practical application or amount to significantly more than the judicial exception as discussed above. The dependent claims further describe the abstract idea.
The claims are not patent eligible.
McGuire teaches all of the following limitations A workload control method for controlling migration of workloads between a first data center and one or more second data centers by a data center management server, wherein the first data center and one or more second data centers are among a plurality of data centers, and wherein the migration is controlled based on renewable energy supply at the data centers, comprising: (determining and optimizing work output from various data centers based on renewable energy consumption to optimize carbon emission) [Abstract, Paragraphs 0011-0012 and Figure 2]:
calculating, by the data center management server, a complementary score of each of the plurality of data centers … (determine “threshold score” and maximize usage of renewable energy by distributing workloads based on a calculated score using previous historical usage data among a plurality of other data) [Paragraphs 0012, 0026-0033 and Claims 1-6],
determining, by the data center management server, one or more second data centers among the one or more second data centers as destination data centers for creation of remote copies to one or more volumes by selecting, in order of the complementary score based on the complementary score, from the plurality of data centers having a remote copy pair count that has not reached a threshold [Paragraphs 0012, 0031-0040 and Claims 1-6]; and
execute, by the data center management server, the creation of the remote copies to the one or more second data centers (replicate the work in other data centers) [Paragraphs 0037-0040 and Claims 1-7]; and
controlling, by the data center management server, migration of the workloads between the first data center and the one or more second data centers by swapping volume attributes between primary and secondary volumes in response to renewable energy supply at the first data center falling below a threshold, wherein the swapping of volume attributes comprises changing a volume destination from secondary to primary at a second data center storage device and from primary to secondary at the first data center storage device, thereby redirecting application data writes to the second data center without requiring full data migration, to control use of renewable energy in executing workloads and reduce carbon emissions from the plurality of data centers (the movement of data or migration of workload is done in order to optimize renewable energy consumption between all data centers in response to the calculated and determined output of data used by the data centers) [Paragraphs 0037-0040 and Claims 1-7].
McGuire does not disclose performing said calculation based on a standard deviation of a sum of: time-series data of past renewable energy supply at the each of the plurality of data centers and time-series data of past renewable energy supply at the first data center and McGuire also does not explicitly disclose swapping volume attributes between primary and secondary volumes in response to renewable energy supply at the first data center falling below a threshold, wherein the swapping of volume attributes comprises changing a volume destination from secondary to primary at a second data center storage device and from primary to secondary at the first data center storage device, thereby redirecting application data writes to the second data center without requiring full data migration.
Chinese Patent Application Publication CN 120069245 to Sun et al. (Sun) teaches at least the use of the well settled standard deviation analysis of determining how to optimize distribution. Sun discloses: “Specifically, when defining the fuzzy membership standard, firstly the overall trend characteristic parameter is divided into three types of core dimensions, load fluctuation (by standard deviation membership function is divided into " stable, medium, violent ") , period regularity (adopting trapezoidal membership function to distinguish " strong period, weak period, irregular ") and trend direction (using S type membership function to describe three states of descending, stable and ascending); For block trend characteristic parameters, spatial heterogeneity (Gaussian membership function quantization "uniformity, gradient, mutation" distribution), load concentration (triangular membership function evaluation "dispersion, general, aggregation") is established. and conduction delay (judging " instant, lag, blocking " based on half-Lingnan type function) the fuzzy standard.
specifically, when analyzing the future total energy consumption trend and the abnormal value of the block energy consumption trend, using the three-level abnormal detecting mechanism based on matching fuzzy clustering algorithm, performing membership degree matching on the real-time energy consumption data stream and the pre-stored clustering template library, calculating the standardized distance of each data point relative to the nearest clustering centre, for the overall trend, when the membership degree of the continuous 3 period data point is less than 0.3 and the Euclidean distance exceeds two times of standard deviation, judging that the system is abnormal and marked as red alarm, aiming at the block-level data, combining the spatial correlation detection, when the energy consumption deviation degree of the single block exceeds the three times quartile distance of the average value of the adjacent block, even if the requirement of the clustering membership degree is satisfied, it is marked as the orange spatial abnormality. For the block-level trend, the spatial compensation algorithm is used, the dynamic weight re-balance is performed in the prediction abnormal area, the redundancy capacity of the adjacent block is preferably scheduled to perform local compensation, after optimization, the effect evaluation is performed through the three-dimensional verification system, the sliding window mean square error is used in the time dimension to check the prediction deviation improvement degree, the space dimension calculates the inter-block load similarity index, the system dimension verifies whether the voltage fluctuation rate of the key node of the power grid reaches the standard, finally generates the adjusting amplitude, the optimization report of the energy-saving benefit and the stability coefficient, and the digital twin platform performs 72-hour deducing verification, ensuring that the optimization strategy meets the short-term precision and long-term sustainability requirement at the same time. Specifically, the overall energy consumption trend characteristic is extracted, the historical baseline parameter calculates the average energy consumption value, the standard deviation and the daily ratio fluctuation rate (such as + 8 %) of the same type period in the past 30 days, as the reference anchor point of the trend prediction, capturing the slope of the current energy consumption curve (such as rising by 2kW/h per minute), peak value offset (advanced/delayed time length than historical average value) and load mutation point (such as suddenly increased by 10 % within 5 minutes), for short-term trend fine adjustment, fusion temperature, humidity and other environmental parameters (such as temperature per litre of 1 °C resulting in air conditioner energy consumption + 5 %) and real-time feedback data of construction personnel density, block energy consumption trend characteristic extracting space differentiation parameter, according to functional area (such as office area, data centre, The energy consumption ratio (such as 40 % of the total amount of the data center) and the energy consumption intensity per unit area (such as 0.8 kW/h/m2 of the office area) are respectively counted by the illumination area), and the cluster characteristics of the device are as follows: identifying the high associated device group in the same block (such as air conditioner + fresh air system cooperative energy consumption), recording the linkage energy consumption fluctuation range (such as + 15 %), time section sensitivity mark, such as data centre at night still keeps 90 % load, but office area night load is only 10 %.”
However, Sun fails to cure the second elements that is not disclosed explicitly by McGuire and further that the standard deviation calculated also includes the first data center data as well. The teaching of swapping volume attributes between primary and secondary volumes in response to renewable energy supply at the first data center falling below a threshold, wherein the swapping of volume attributes comprises changing a volume destination from secondary to primary at a second data center storage device and from primary to secondary at the first data center storage device, thereby redirecting application data writes to the second data center without requiring full data migration could be taught by another reference. However, such a reference is not found to explicitly recite such limitation and if used would destroy the combination of the references at least to McGuire in view of Sun.
As a result, the claimed scope as a whole is deemed novel over prior art.
Additional References
Examiner has provided multiple additional references which teach the claimed scope of what the Applicant deems as their invention. The additional art teaches solely or in combination the claimed scope.
For instance, Examiner points to the additional reference, PGPUB 2021/0342185, to Naidu et al. which teaches relocation of workloads across data centers of a data center system are described. A target for the data center system for power cost reduction or carbon footprint reduction or both is received. Power source information pertaining to power sources that power data centers of the data center system is also received. A workload to be relocated is identified based on characteristics of the workload, the power source information, and the target. The present subject matter relates to relocation of workloads across data centers, such as across datacenters belonging to an organization. The present subject matter facilitates reduction of cost expenditure and carbon footprint of the data centers. In accordance with an example implementation, a data center system may include a plurality of data centers, such as a first data center and a second data center. The data center system may be managed or owned by an organization. The data centers of the data center system may be powered by different power sources. For example, the first data center may be powered by a thermal power plant and the second data center may be powered by a solar farm. Further, a cost incurred per unit of power consumed may be different for the first data center and the second data center. The organization owning or managing the data center system may have targets pertaining to power consumption of the data center system. The targets may include, for example, a power cost reduction target, which indicates an amount by which power cost of the data center system is to be reduced. For example, the power cost reduction target may indicate that the power cost in the current year should be 20% less than that in the previous year. The power cost reduction target may also be referred to as total cost of ownership (TCO) reduction target, as power cost impacts TCO of a data center. The targets may also include a carbon footprint reduction target, which indicates an amount by which the carbon footprint of the data center system is to be reduced. In an example, power source information of the data center system may be received. The power source information may indicate, for example, a first cost incurred for obtaining power for the first data center, a second cost incurred for obtaining power for the second data center, and type of power sources that power the first data center and the second data center. A type of a power source may provide an indication of a carbon footprint generated by the power source for generating a unit of electric energy. For instance, the type of the power source may indicate whether the power source is renewable or non-renewable, and a source or a fuel (e.g., coal, natural gas, or wind) used by the power source for generating the power. Based on the targets and the power source information, it may be determined that a workload is to be relocated from the first data center to the second data center. For example, if the second cost is less than the first cost, or if the power source powering the second data center has a lesser carbon footprint than that powering the first data center, it may be determined that a workload from the first data center is to be relocated to the second data center, to achieve the targets.
The present subject matter facilitates reducing TCO and carbon footprint of an organization having a data center system. By analyzing targets of an organization, cost information, and characteristics of workloads, the present subject matter identifies the workloads that are to be relocated to achieve the targets. Therefore, techniques of the present subject matter can be utilized to achieve quantitative targets, such as a target to achieve 20% reduction of TCO as compared to previous year. Further, the switching of a power source from which the power for a data center is obtained also helps achieving the targets. Thus, the present subject matter facilitates making decisions regarding switching of power sources and relocation of workloads to achieve the targets. See Figures 1-6 and related text.
See also, PGPUB 2024/0104478 to Ozawa et al. which teaches reducing a power surplus of fluctuating renewable energy. Data center candidate management information indicates a characteristic of renewable energy supplied to each data center candidate. Application program type candidate management information indicates a characteristic of each application program type candidate. The system 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 a score of each combination based on a characteristic of renewable energy supplied to each of the one or more data center candidates and a characteristic of each of the one or more application program type candidates, and selects, based on the score, a combination to be presented.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure is listed on for PTO-892.
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Sincerely,
/EL MEHDI OUSSIR/Primary Examiner, Art Unit 3699
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