DETAILED ACTION
The application of Dang et al., for a “Reducing the amount of anomaly detection noise in a distributed computing environment” filed on May 10, 2024 has been examined. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . The information disclosure statement (IDS) submitted on July 7, 2025 has been considered.
Claims 1-20 are presented for examination.
Claims 1-20 are rejected under 35 USC § 101.
Claims 1-9 are rejected under 35 USC § 112.
Claims 1-7, 9-16, and 18-20 are rejected under 35 USC § 103.
Claims 8 and 17 are objected to while containing allowable matter.
Claim Rejections - 35 USC § 112
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 1-9 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 pre-AIA the applicant regards as the invention.
Claim 1, line 25, recites the limitation “the current ratio”. There is insufficient antecedent basis for this limitation in the claim. Claims 2-9 are rejected since they depend on claim 1.
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 1-20 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 in addition to mathematical relationships/calculations.
As per claim 1, with the exception of the recitation of the limitations “an entity executing via a distributed computing environment”, the limitations “calculating, based on the first health data, a historic center value indicating a health of the plurality of resources during the first period of time; calculating, based on the first health data, a spread value for the historic center value; establishing a first threshold associated with the historic center value based on a first multiple of the spread value, wherein the first threshold triggers a transition for the entity from a first health state to a second health state; establishing a second threshold associated with the historic center value based on a second multiple of the spread value, wherein the second threshold triggers a transition for the entity from the second health state back to the first health state” are directed to mathematical relationships/calculations (MPEP 2106.04(a)(2) I. A. and C.).
Further the limitations “determining, based on a first comparison of the current value to the first threshold at a first time during the second period of time, that the current value crosses the first threshold; providing, based on the determining that the current value crosses the first threshold, a first indication that the entity has transitioned from the first health state to the second health state; responsive to determining that the current ratio crosses the first threshold, determining, based on a second comparison of the current value to the second threshold at a second time during the second period of time that is after the first time, that the current value crosses the second threshold; and providing, based on the determining that the current value crosses the second threshold, a second indication that the entity has transitioned from the second health state back to the first health state” can be performed by a human mind or with the aid of pen and paper. (MPEP 2106.04(a)(2)).
Step 2A. This judicial exception is not integrated into a practical application because the additional element(s) “an entity executing via a distributed computing environment” is/are 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)).
The limitations of “receiving first health data corresponding to a plurality of resources upon which the entity depends, wherein the first health data includes historic values established based on whether a resource, of the plurality of resources, is healthy or unhealthy at a given time during a first period of time” and “continually receiving, during a second period of time, second health data corresponding to the plurality of resources, wherein the second health data includes a current value established based on whether the resource, of the plurality of resources, is healthy or unhealthy at a present time during the second period of time” are mere data gathering recited at a high level of generality, and thus are insignificant extra-solution activity (MPEP 2106.05(g).
Step 2B. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception. The additional element(s) “an entity executing via a distributed computing environment” does/do not provide significantly more than the recited 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)).
The limitations of “receiving first health data corresponding to a plurality of resources upon which the entity depends, wherein the first health data includes historic values established based on whether a resource, of the plurality of resources, is healthy or unhealthy at a given time during a first period of time” and “continually receiving, during a second period of time, second health data corresponding to the plurality of resources, wherein the second health data includes a current value established based on whether the resource, of the plurality of resources, is healthy or unhealthy at a present time during the second period of time” are mere data gathering recited at a high level of generality, and thus are insignificant extra-solution activity. These limitations amount to receiving or transmitting data over a network and are well-understood, routine, conventional activity (MPEP 2106.05(d)).
As for the limitations recited in claims 2-9, 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.
As per claim 10, with the exception of the recitation of the limitations “a processing system; and a computer readable storage medium storing instructions that, when executed by the processing system, cause the system to perform operations”, the rest of the limitations can be performed by a human mind or with the aid of pen and paper. (MPEP 2106.04(a)(2)) and/or are directed to mathematical relationships/calculations (MPEP 2106.04(a)(2) I. A. and C.). Please refer to analysis section for claim 1 for further details.
As per claims 11-17 and 18-20, please refer to analysis section for claims 1-9.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102 of this title, 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.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-7, 9-16, and 18-20 are rejected under 35 U.S.C. 103 as being unpatentable over BahenaTapia et al. (U.S. PGPUB 20200364607) in view of Dhot et al. (U.S. PGPUB 20250086083).
As per claims 1, 10, and 18, BahenaTapia discloses a method/a system comprising a processing system; and a computer readable storage medium storing instructions that, when executed by the processing system ([0141]) for reducing noise in health determination for an entity ([0037], “may reduce false positives caused by measurement drift”) executing via a distributed computing environment ([0028], anomaly detection in cloud systems), comprising:
receiving first health data corresponding to a plurality of resources upon which the entity depends ([0045], “Agents 114a-j comprise hardware and/or software logic for capturing time-series measurements from a corresponding target (or set of targets) and sending these metrics to data collector 120.”), wherein the first health data includes historic values ([0050], “historical values”) established based on whether a resource, of the plurality of resources, is healthy or unhealthy at a given time during a first period of time ([0047], “Anomaly detection services 130 includes logic for training models that represent the behavior of a set of time-series data and evaluating the models to detect anomalous behavior”);
calculating, based on the first health data, a historic center value indicating a health of the plurality of resources during the first period of time ([0047], “Anomaly detection services 130 includes logic for training models that represent the behavior of a set of time-series data and evaluating the models to detect anomalous behavior”) and ([0051], “The set of a t-digest structures may summarize the training data into a small list of structures referred to as centroids, which are much smaller than the overall training dataset”);
calculating, based on the first health data, a spread value for the historic center value ([0100], “a cumulative sum (CUSUM) control chart is used to determine whether a deviation is statistically significant. A CUSUM control chart is a model that may be trained to model (a) the expected mean and standard deviation of a time-series signal; (b) the size of a shift from the historical mean and standard deviation; and (c) a control limit or threshold (e.g., five standard deviations) for classifying the time-series as statistically significant.”);
establishing a first threshold associated with the historic center value, wherein the first threshold triggers a transition for the entity from a first health state to a second health state; establishing a second threshold associated with the historic center value, wherein the second threshold triggers a transition for the entity from the second health state back to the first health state ([0052], “The order statistics may then be converted to corresponding quantile probabilities including a lower quantile probability quantile denoted LQ and an upper quantile probability denoted UQ. These quantile probabilities represent the upper and lower probabilities for a tolerance interval covering a prescribed proportion of values for the particular metric within a prescribed confidence level. Techniques for computing these values are described further below. In some embodiments, quantile probability estimator 204 queries quantile estimator 202 for the corresponding quantiles, which may be determined as a function of the sliding window of t-digest structures. These quantiles may be used as the lower and upper limits in the trained anomaly detection model.”);
continually receiving, during a second period of time, second health data corresponding to the plurality of resources, wherein the second health data includes a current value established based on whether the resource, of the plurality of resources, is healthy or unhealthy at a present time during the second period of time ([0102], “The process may stream or periodically receive time-series data generated by targets 112a-i for evaluation. The process may be repeated for remaining data points in the received time-series dataset and/or as new time-series data is received to continue evaluating resource behavior within the computing environment.”);
BahenaTapia fails to explicitly disclose establishing a first threshold associated with the historic center value based on a first multiple of the spread value.
Dhot of analogous art teaches:
establishing a first threshold associated with the historic center value based on a first multiple of the spread value ([0030], “The system then takes the average of the activity in the past weeks, and sets a threshold based on the average and a buffer.”);
establishing a second threshold associated with the historic center value based on a second multiple of the spread value ([0030]) and ([0033], “compute respective threshold baselines for each the plurality of metrics based on one or more past instances of the time segment”);
determining, based on a first comparison of the current value to the first threshold at a first time during the second period of time, that the current value crosses the first threshold ([0030], “When the current activity rises above (or below) the threshold”);
providing, based on the determining that the current value crosses the first threshold, a first indication that the entity has transitioned from the first health state to the second health state ([0030], “When the current activity rises above (or below) the threshold, an alert can be triggered and a notification can be sent to one or more user devices 150”);
responsive to determining that the current ratio crosses the first threshold, determining, based on a second comparison of the current value to the second threshold at a second time during the second period of time that is after the first time, that the current value crosses the second threshold ([0029]-[0033]); and
providing, based on the determining that the current value crosses the second threshold, a second indication ([0030], “When the current activity rises above (or below) the threshold, an alert can be triggered and a notification can be sent to one or more user devices 150”) that the entity has transitioned from the second health state back to the first health state ([0028], “This historical baselining and comparison can facilitate identifying anomalous activity”).
All of the claimed elements were known in BahenaTapia and Dhot and could have been combined by known methods with no change in their respective functions. It therefore would have been obvious to a person of ordinary skill in the art before the time of effective filing language to combine their anomaly detection methods. One would be motivated to make this combination since Dhot’s threshold calculation is a mere variation of BahenaTapia’s threshold calculation.
As per claims 2 and 11, Dhot discloses the historic center value comprises a historic average ratio established based on a number of unhealthy resources and a number of total resources ([0030]-[0032]).
As per claims 3 and 12, Dhot discloses the historic center value comprises an average absolute number of unhealthy resources ([0030]-[0032]).
As per claims 4 and 13, BahenaTapia discloses the first period of time comprises a sliding predefined recent time window ([0031], “The techniques further allow for quantile values to be estimated over a sliding window of streamed data”).
As per claims 5 and 14, Dhot discloses the first period of time reflects a periodic time unit to account for seasonality ([0030]-[0031]).
As per claims 6, 15, and 20, Dhot discloses the first threshold and the second threshold are established based on a sensitivity input from an owner of the entity ([0035], “the command instruction may cause the baseline to change, or reset and be recalculated, or silence further notifications”).
As per claims 7 and 16, BahenaTapia discloses the first indication and the second indication include real-world timing information associated with a first transition from the first health state to the second health state and a second transition from the second health state back to the first health state ([0108], “The interactive visualization may include a graph of time-series data that displays information about the detected anomalies. Example information may include, but is not limited, the time the anomaly was first detected, the magnitude and duration of the anomaly”).
As per claim 9, Dhot discloses establishing a third threshold associated with the historic center value based on a third multiple of the spread value, wherein the third threshold triggers a transition for the entity from the second health state to a third health state ([0030], “The system then takes the average of the activity in the past weeks, and sets a threshold based on the average and a buffer.”);
establishing a fourth threshold associated with the historic center value based on a fourth multiple of the spread value, wherein the fourth threshold triggers a transition for the entity from the third health state back to the second health state ([0033], “compute respective threshold baselines for each the plurality of metrics based on one or more past instances of the time segment”);
determining, based on a third comparison of the current value to the third threshold at a third time between the first time and the second time, that the current value crosses the third threshold; providing, based on the determining that the current value crosses the third threshold, a third indication ([0030], “When the current activity rises above (or below) the threshold, an alert can be triggered and a notification can be sent to one or more user devices 150”) that the entity has transitioned from the second health state to the third health state ([0028], “This historical baselining and comparison can facilitate identifying anomalous activity”);
determining, based on a fourth comparison of the current value to the fourth threshold at a fourth time that is after the third time and before the second time, that the current value crosses the fourth threshold; and providing, based on the determining that the current value crosses the fourth threshold, a fourth indication ([0030], “When the current activity rises above (or below) the threshold, an alert can be triggered and a notification can be sent to one or more user devices 150”) that the entity has transitioned from the third health state back to the second health state ([0028], “This historical baselining and comparison can facilitate identifying anomalous activity”).
As per claim 19, please refer to the analysis sections of claims 2-3.
Allowable Subject Matter
Claims 8 and 17 objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims and if rewritten to overcome the U.S.C. 101 rejections.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. See included PTO-892.
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.
Information regarding the status of an application may be obtained from Patent Center. Status information for published applications may be obtained from Patent Center. Status information for unpublished applications is available through Patent Center for authorized users only. Should you have questions about access to Patent Center, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free).
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) Form at https://www.uspto.gov/patents/uspto-automated- interview-request-air-form.
/Elmira Mehrmanesh/
Primary Examiner, Art Unit 2113