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 .
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 1,3-13,15,16,18-23 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 the human mind and mathematical concepts..
Regarding claim 1, with the exception of the recitation of the limitations ‘at an anomaly detection system; a processor’, the claim recites mental processes – concepts performed in the human mind.
The limitations ‘detecting an event volume indicative of a volume of computing system events represented by the time series of metrics; comparing a representative value, representative of the metrics in the time window under analysis, to the dynamic anomaly detection threshold; detecting an anomaly in the operational characteristics of the computing system based on the comparison result signal; detecting feedback indicative of an accuracy in detecting the anomaly’ are mental processes performed in the human mind based on observation, evaluation, and/or judgment. The limitation ‘generating, in real-time, a dynamic anomaly detection threshold generator to generate a dynamic anomaly detection threshold that varies based on the event volume and based on distribution parameters characterizing a distribution of metric values over a historic time window that is larger than the time window under analysis, wherein the dynamic anomaly detection threshold is generated by identifying an absolute volume indicator by comparing the event volume to a volume constant, identifying a relative volume indicator by comparing the event volume to a historical volume level, and generating the dynamic anomaly detection threshold based on the absolute volume indicator and the relative volume indicator’ is math, as disclosed in the specification.
Step 2A: Prong two
This judicial exception is not integrated into a practical application because the additional elements ‘receiving a time series of metrics, each metric in the time series of metrics being indicative of a detected computing system event within a time window under analysis’ are merely adding insignificant extra-solution activity to the judicial exception (MPEP 2106.05(g)). The ‘receiving’ limitation is data gathering.
Step 2B
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 ‘at an anomaly detection system; using one or more processors of the anomaly detection system; using the one or more processors of the anomaly detection system; generating a comparison result signal, using the one or more processors of the anomaly detection system; generating, using the one or more processors of the anomaly detection system, an action signal; modifying, using the one or more processors of the anomaly detection system, by performing a machine learning scheme that modifies the dynamic anomaly detection threshold by adjusting one or more constants in a function used to generate the dynamic anomaly detection threshold based on the feedback, wherein the machine learning scheme is trained using feedback indicative of the accuracy of anomaly detection and remediation outcomes’ 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)). The modifies the threshold based on the feedback by a machine learning scheme is using a generic machine learning model and involves mathematical concepts.
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 ‘by reconfiguring resource allocation and automatically allocating additional computing resources in response to the detected anomaly’ is simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high-level of generality to the judicial exception (MPEP 2106.05(d)). The GB2389431A discloses - An example, the wide variations in demand for web-sites, for example an increased demand for information, or live video feed during major sporting events, has resulted in web-sites crashing as the systems administrator cannot establish the rate of change of requests quickly 30 enough in order to add resources quickly enough to cope with the fluctuations in demand. known solution to this problem is to massively over provide for the availability of data to users: to have much more data serving capacity than is normally needed. This is expensive and inefficient as at times of low data demand it results in large amounts of storage devices lying idle. High end disc arrays typically cost $300k per 5 Tera Byte (TB). The 5109486A discloses – in column 3, lines 36-45 - (31) In known data processing environments it is often necessary to add/remove resources (software or hardware types) to existing nodes. In addition, it is often necessary to add/remove nodes from the system. The connection between nodes may also become temporarily disrupted, this should not impact the correctness of the operation of the distributed service. Because of the interaction between nodes and resources of those nodes, it is essential that preexisting (remaining) nodes are notified of these additions (removals).
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 ‘in response to the detected anomaly, instantiating additional virtual machine capacity within a service region of the computing system and re-routing network traffic to the instantiated virtual machines using a load balancer that remediates the anomaly’ is simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high-level of generality to the judicial exception (MPEP 2106.05(d)). USPN 20100011368 - discloses in paragraph 0219 - When an application 501 is moved to a different physical location by my various known methods, such as virtual machine (VM) migration in order to realize load balancing, recovery from a failure, or the like, a partition (i.e., independent resources and services) used by the application 501 may be required to change physical location in storage platform 100 in accordance with the migration of the application 501.
WO 2012120557 A1 - If the communication characteristics including the communication target and traffic of the newly added virtual machine are not known in advance, a new MAC address is assigned to the newly added virtual machine so that the network load is balanced.
USPN 20140189441A1 - discloses in paragraph 0061In this case, in conventional control of virtual machine placement, if the load on the physical server 51 in the chassis 50 is lower than that on the physical server 61 and the physical server 51 has more free processing capacity than the physical server 61, the virtual machines m3 and m4 would be migrated to the physical server 51 in the chassis 50 for load balancing.
USPN 8959173B1 - discloses in column 4, lines 6-17 - Conventional Server virtualization products may have developed the capability to execute migrations of virtual machines, the underlying storage, or both to address load balancing and high availability requirements with certain limitations. Typically, however there are limitations on the maximum physical separation between the various migration components. Typical implementations limit this distance to within a site. Current approaches do not usually allow site to site separation of shared, coherent resources. Moreover, conventional solutions usually require disruptive failover (i.e. failure of one site to transfer the processes to the back-up site), merged SANs, and do not work with heterogeneous products.
Regarding claim 3, the limitation ‘wherein detecting an anomaly comprises: accessing anomaly detection criteria; and applying the anomaly detection criteria to the comparison result to determine whether an anomaly is detected’ are mental processes performed in the human mind based on observation, evaluation, and/or judgment.
Regarding claim 4, the limitation ‘wherein the anomaly detection criteria comprise persistence criteria and wherein detecting an anomaly comprises: identifying a persistence time period over which the anomaly persisted; comparing the persistence time period to the persistence criteria; and detecting the anomaly when the persistence time period meets the persistence criteria’ are mental processes performed in the human mind based on observation, evaluation, and/or judgment.
Regarding claim 5, the limitation ‘further comprising: detecting an anomaly severity level based on a persistence of the anomaly indicated by the comparison of the persistence time period to the persistence criteria’ are mental processes performed in the human mind based on observation, evaluation, and/or judgment.
Regarding claim 6, the limitation ‘wherein generating an action signal comprises: generating the actions signal based on the detected anomaly severity level’ 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)).
Regarding claim 7, the limitation ‘wherein applying a dynamic anomaly detection threshold generator to generate a dynamic anomaly detection threshold comprises: applying a dynamic anomaly detection threshold generator to generate a dynamic anomaly detection threshold that decreases as the event volume decreases, and increases as the event volume increases’ 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)).
Regarding claim 8, the limitation ‘wherein comparing a representative value, representative of the metrics in the time window under analysis, to the dynamic anomaly detection threshold to obtain a comparison result signal comprises dividing the time window under analysis into a plurality of temporal segments, and wherein detecting an event volume comprises: selecting a temporal segment; and detecting an event volume in the selected temporal segment’ are mental processes performed in the human mind based on observation, evaluation, and/or judgment as well as mathematical concepts.
Regarding claim 9, the limitation ‘wherein applying the anomaly detection threshold generator comprises: applying the dynamic anomaly detection threshold generator to generate a dynamic anomaly detection threshold for the selected temporal segment that varies based on the event volume in the selected temporal segment and based on distribution parameters characterizing a distribution of metric values over the historic time window that is larger than the selected temporal segment’ 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)) and mathematical concepts.
Regarding claim 10, the limitation ‘wherein comparing comprises :generating the representative value as representative of the metric values in the selected temporal segment; and comparing the representative value to the dynamic anomaly detection threshold for the selected temporal segment’ are mental processes performed in the human mind based on observation, evaluation, and/or judgment as well as mathematical concepts.
Regarding claim 11, the limitation ‘wherein detecting an anomaly comprises: identifying the temporal segment as an anomalous segment based on the comparison of the representative value to the dynamic anomaly detection threshold for the selected temporal segment’ are mental processes performed in the human mind based on observation, evaluation, and/or judgment.
Regarding claim 12, the limitation ‘wherein detecting an anomaly comprises: detecting the anomaly based on a number of the temporal segments in the window under analysis are anomalous segments’ is a mental process performed in the human mind based on observation, evaluation, and/or judgment.
Regarding claim 13, the claim recites mental processes – concepts performed in the human mind and mathematical concepts.
The limitations ‘identifying an event volume indicative of a volume of computing system events represented by the time series of metrics in the time window under analysis; comparing a representative value, representative of the metrics in the time window under analysis, to the dynamic anomaly detection threshold; if the representative value meets the dynamic anomaly detection threshold, determining a persistence value by detecting a time period over which the representative value meets the dynamic anomaly detection threshold; identifying an anomaly in the operational characteristics of the computing system based on the comparison result signal and the persistence value’ are mental processes performed in the human mind based on observation, evaluation, and/or judgment. The limitation ‘generating a dynamic anomaly detection threshold that varies based on the event volume and based on distribution parameters characterizing a distribution of metric values over a historic time window that is larger than the time window under analysis, wherein the dynamic anomaly detection threshold is generated by identifying an absolute volume indicator by comparing the event volume to a volume constant, identifying a relative volume indicator by comparing the event volume to a historical volume level, and generating the dynamic anomaly detection threshold based on the absolute volume indicator and the relative volume indicator’ is math, as disclosed in the specification.
Step 2A: Prong two
This judicial exception is not integrated into a practical application because the additional elements ‘receiving a time series of metrics, each metric in the time series of metrics being indicative of a detected computing system event within a time window under analysis’ are merely adding insignificant extra-solution activity to the judicial exception (MPEP 2106.05(g)). The ‘receiving’ limitation is data gathering. The ‘controlling’ limitation per the specification is directed to performing remediation steps to correct anomalous operational characteristics.
Step 2B
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 ‘generating a comparison result signal, the comparison result signal indicative of whether the representative value meets the dynamic anomaly detection threshold; generating an action signal; modifying the dynamic anomaly detection threshold by adjusting one or more constants in a function used to generate the dynamic anomaly detection threshold, wherein the machine learning scheme is trained using feedback of the accuracy of anomaly detection and remediation outcomes’ 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 modifies the threshold based on the feedback by a machine learning scheme is using a generic machine learning model and involves mathematical concepts.
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 ‘by reconfiguring resource allocation and automatically allocating additional computing resources in response to the detected anomaly’ is simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high-level of generality to the judicial exception (MPEP 2106.05(d)). The GB2389431A discloses - An example, the wide variations in demand for web-sites, for example an increased demand for information, or live video feed during major sporting events, has resulted in web-sites crashing as the systems administrator cannot establish the rate of change of requests quickly 30 enough in order to add resources quickly enough to cope with the fluctuations in demand. known solution to this problem is to massively over provide for the availability of data to users: to have much more data serving capacity than is normally needed. This is expensive and inefficient as at times of low data demand it results in large amounts of storage devices lying idle. High end disc arrays typically cost $300k per 5 Tera Byte (TB). The 5109486A discloses – in column 3, lines 36-45 - (31) In known data processing environments it is often necessary to add/remove resources (software or hardware types) to existing nodes. In addition, it is often necessary to add/remove nodes from the system. The connection between nodes may also become temporarily disrupted, this should not impact the correctness of the operation of the distributed service. Because of the interaction between nodes and resources of those nodes, it is essential that preexisting (remaining) nodes are notified of these additions (removals).
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 ‘in response to the detected anomaly, instantiating additional virtual machine capacity within a service region of the computing system and re-routing network traffic to the instantiated virtual machines using a load balancer that remediates the anomaly’ is simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high-level of generality to the judicial exception (MPEP 2106.05(d)). USPN 20100011368 - discloses in paragraph 0219 - When an application 501 is moved to a different physical location by my various known methods, such as virtual machine (VM) migration in order to realize load balancing, recovery from a failure, or the like, a partition (i.e., independent resources and services) used by the application 501 may be required to change physical location in storage platform 100 in accordance with the migration of the application 501.
WO 2012120557 A1 - If the communication characteristics including the communication target and traffic of the newly added virtual machine are not known in advance, a new MAC address is assigned to the newly added virtual machine so that the network load is balanced.
USPN 20140189441A1 - discloses in paragraph 0061In this case, in conventional control of virtual machine placement, if the load on the physical server 51 in the chassis 50 is lower than that on the physical server 61 and the physical server 51 has more free processing capacity than the physical server 61, the virtual machines m3 and m4 would be migrated to the physical server 51 in the chassis 50 for load balancing.
USPN 8959173B1 - discloses in column 4, lines 6-17 - Conventional Server virtualization products may have developed the capability to execute migrations of virtual machines, the underlying storage, or both to address load balancing and high availability requirements with certain limitations. Typically, however there are limitations on the maximum physical separation between the various migration components. Typical implementations limit this distance to within a site. Current approaches do not usually allow site to site separation of shared, coherent resources. Moreover, conventional solutions usually require disruptive failover (i.e. failure of one site to transfer the processes to the back-up site), merged SANs, and do not work with heterogeneous products.
Regarding claim 15, the limitation ‘wherein applying a dynamic anomaly detection threshold generator to generate a dynamic anomaly detection threshold comprises: applying a dynamic anomaly detection threshold generator to generate a dynamic anomaly detection threshold that decreases, as the event volume in the time window under analysis decreases, and increases, as the event volume in the window under analysis increases’ 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)).
Regarding claim 16, with the exception of the recitation of the limitations ‘communication system; volume detector component; dynamic anomaly detection threshold generator; threshold comparison system; anomaly detector; a feedback system; machine learning system’, the claim recites mental processes – concepts performed in the human mind and mathematical concepts.
The limitations ‘identifies an event volume indicative of a volume of computing system events represented by the time series of metrics in the time window under analysis; compares a representative value, representative of the metrics in the time window under analysis, to the dynamic anomaly detection threshold to obtain a comparison result signal indicative of whether the representative value meets the dynamic anomaly detection threshold; detects an anomaly in the operational characteristics of the computing system based on the comparison result signal’ are mental processes performed in the human mind based on observation, evaluation, and/or judgment. The limitation ‘generates a dynamic anomaly detection threshold that varies based on the event volume and based on distribution parameters characterizing a distribution of metric values over a historic time window that is larger than the time window under analysis, wherein the dynamic anomaly detection threshold is generated by identifying an absolute volume indicator by comparing the event volume to a volume constant, identifying a relative volume indicator by comparing the event volume to a historical volume level, and generating the dynamic anomaly detection threshold based on the absolute volume indicator and the relative volume indicator’ is math, as disclosed in the specification.
Step 2A: Prong two
This judicial exception is not integrated into a practical application because the additional elements ‘receives a time series of metrics, each metric in the time series of metrics being indicative of a detected computing system event within a time window under analysis; receives the event volume; receives the comparison result signal; generates an action signal to control a portion of the computing system based on the identified anomaly’ are merely adding insignificant extra-solution activity to the judicial exception (MPEP 2106.05(g)). The ‘receiving’ limitation is data gathering. The ‘generates’ limitation per the specification is directed to performing remediation steps to correct anomalous operational characteristics.
Step 2B
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 ‘communication system; volume detector component; dynamic anomaly detection threshold generator; threshold comparison system; anomaly detector; a feedback system; machine learning system; modifies, using the one or more processors of the anomaly detection system, by performing a machine learning scheme that modifies the dynamic anomaly detection threshold by adjusting one or more constants in a function used to generate the dynamic anomaly detection threshold based on the feedback’ 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)). The modifies the threshold based on the feedback by a machine learning scheme is using a generic machine learning model and involves mathematical concepts.
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 ‘by reconfiguring resource allocation and automatically allocating additional computing resources in response to the detected anomaly’ is simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high-level of generality to the judicial exception (MPEP 2106.05(d)). The GB2389431A discloses - An example, the wide variations in demand for web-sites, for example an increased demand for information, or live video feed during major sporting events, has resulted in web-sites crashing as the systems administrator cannot establish the rate of change of requests quickly 30 enough in order to add resources quickly enough to cope with the fluctuations in demand. known solution to this problem is to massively over provide for the availability of data to users: to have much more data serving capacity than is normally needed. This is expensive and inefficient as at times of low data demand it results in large amounts of storage devices lying idle. High end disc arrays typically cost $300k per 5 Tera Byte (TB). The 5109486A discloses – in column 3, lines 36-45 - (31) In known data processing environments it is often necessary to add/remove resources (software or hardware types) to existing nodes. In addition, it is often necessary to add/remove nodes from the system. The connection between nodes may also become temporarily disrupted, this should not impact the correctness of the operation of the distributed service. Because of the interaction between nodes and resources of those nodes, it is essential that preexisting (remaining) nodes are notified of these additions (removals).
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 ‘in response to the detected anomaly, instantiating additional virtual machine capacity within a service region of the computing system and re-routing network traffic to the instantiated virtual machines using a load balancer that remediates the anomaly’ is simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high-level of generality to the judicial exception (MPEP 2106.05(d)). USPN 20100011368 - discloses in paragraph 0219 - When an application 501 is moved to a different physical location by my various known methods, such as virtual machine (VM) migration in order to realize load balancing, recovery from a failure, or the like, a partition (i.e., independent resources and services) used by the application 501 may be required to change physical location in storage platform 100 in accordance with the migration of the application 501.
WO 2012120557 A1 - If the communication characteristics including the communication target and traffic of the newly added virtual machine are not known in advance, a new MAC address is assigned to the newly added virtual machine so that the network load is balanced.
USPN 20140189441A1 - discloses in paragraph 0061In this case, in conventional control of virtual machine placement, if the load on the physical server 51 in the chassis 50 is lower than that on the physical server 61 and the physical server 51 has more free processing capacity than the physical server 61, the virtual machines m3 and m4 would be migrated to the physical server 51 in the chassis 50 for load balancing.
USPN 8959173B1 - discloses in column 4, lines 6-17 - Conventional Server virtualization products may have developed the capability to execute migrations of virtual machines, the underlying storage, or both to address load balancing and high availability requirements with certain limitations. Typically, however there are limitations on the maximum physical separation between the various migration components. Typical implementations limit this distance to within a site. Current approaches do not usually allow site to site separation of shared, coherent resources. Moreover, conventional solutions usually require disruptive failover (i.e. failure of one site to transfer the processes to the back-up site), merged SANs, and do not work with heterogeneous products.
Regarding claim 18, the limitation ‘wherein the dynamic anomaly detection threshold generator comprises: an absolute comparison value identifier that identifies a volume constant; a historical volume comparison value identifier that identifies a historical volume level; and a function application component that compares the event volume to the volume constant to obtain an absolute volume indicator and that compares the event volume to the historical volume level to obtain a relative volume indicator and that generates the dynamic anomaly detection threshold using a function that decreases, as the event volume in the time window under analysis decreases, and increases, as the event volume in the window under analysis increases, based on the absolute volume indicator and the relative volume indicator’ 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)).
Regarding claim 19, the limitation ‘wherein the anomaly detector comprises: an anomaly detection criteria comparison system that detects a time period over which the representative value meets the dynamic anomaly detection threshold, to obtain a persistence value, and identifies an anomaly in the operational characteristics of the computing system based on the comparison result signal and the persistence value’ 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)).
Regarding claim 20, the limitation ‘wherein the action signal generator comprises: an alert generator that generates an alert based on the detected anomaly’ 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)) and merely adding insignificant extra-solution activity to the judicial exception (MPEP 2106.05(g)).
Regarding claim 21, the limitation ‘wherein generating the dynamic anomaly detection threshold comprises: calculating the absolute volume indicator by comparing the event volume to the volume constant using a first exponential decay function; calculating the relative volume indicator by comparing the event volume to the historical volume level using a second exponential decay function; and combining the absolute volume indicator and the relative volume indicator in the function that decreases as the event volume decreases, and increases as the event volume increases’ is a mathematical concept.
Regarding claim 22, the limitation ‘wherein generating the dynamic anomaly detection threshold comprises: calculating the absolute volume indicator by comparing the event volume to the volume constant using a first exponential decay function; calculating the relative volume indicator by comparing the event volume to the historical volume level using a second exponential decay function; and combining the absolute volume indicator and the relative volume indicator in the function that decreases as the event volume decreases, and increases as the event volume increases’ is a mathematical concept.
Regarding claim 23, the limitation ‘wherein generating the dynamic anomaly detection threshold comprises: calculating the absolute volume indicator by comparing the event volume to the volume constant using a first exponential decay function; calculating the relative volume indicator by comparing the event volume to the historical volume level using a second exponential decay function; and combining the absolute volume indicator and the relative volume indicator in the function that decreases as the event volume decreases, and increases as the event volume increases’ is a mathematical concept.
Claim Objections
Claim 13 is objected to because of the following informalities: The limitation ‘modifying the dynamic anomaly detection threshold by adjusting one or more constants in a function used to generate the dynamic anomaly detection threshold, wherein the machine learning scheme is trained using feedback of the accuracy of anomaly detection and remediation outcomes’ Should be: ‘modifying by performing a machine learning scheme that modifies the dynamic anomaly detection threshold by adjusting one or more constants in a function used to generate the dynamic anomaly detection threshold based on the feedback, wherein the machine learning scheme is trained using feedback indicative of the accuracy of anomaly detection and remediation outcomes’. Appropriate correction is required.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: ‘communication system’ in claim 16; ‘volume detector component’ in claim 16; ‘dynamic anomaly detection threshold generator’ in claim 16; ‘threshold comparison system’ in claim 16; ‘anomaly detector’ in claim 16; ‘action signal generator’ in claim 16; ‘feedback system’ in claims 16,17; ‘machine learning system’ in claims 16,17; ‘function application component’ in claim 18; ‘absolute comparison value identifier’ in claim 18; ‘historical volume comparison value identifier’ in claim 18; ‘anomaly detection criteria comparison system’ in claim 19; ‘alert generator’ in claim 20.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Response to Arguments
Applicant's arguments and amendments filed 10/29/2025 have been fully considered. Concerning Applicant’s arguments on the 101 – abstract idea rejection, the limitations argued in the arguments section on page 11-15 are not viewed to be improvements to the technology operation of computers in this case. The threshold is determined by mathematical concepts and mental processes. The threshold is then used to compare metrics to the threshold which is generically tied to a processor. There is no firm details of how the comparison is being performed by the processor except by some sort of comparison result signal. Then an anomaly is detected by tying it generically to a processor with no details of how the detecting is performed. The rest of the limitations are well-understood, routine, and conventional, detecting feedback, and generically using a machine learning scheme for training and modifying the threshold. A human can perform particular limitations in real-time with the aid of a computer. The limitations pertaining to virtual machines are well-understood, routine, conventional.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Yolanda L Wilson whose telephone number is (571)272-3653. The examiner can normally be reached M-F (7:30 am - 4 pm).
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/Yolanda L Wilson/Primary Examiner, Art Unit 2113