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 .
Response to Amendment
In view of Applicant's amendments, the objection to the claims is withdrawn except those
addressed below.
The amendment integrates the abstract idea into a practical application by imposing a meaningful limit on the abstract idea. In view of Applicant's amendments, the rejection under 35 USC § 101 is withdrawn.
Claim Objections
Claim 18 is objected to because of the following informalities:
Claim 18, line 2, before “performance drift”, --the-- should be inserted.
Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1-20 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Claims 1, 8, and 15 recite collecting end-user network level metrics for a target end-user outside of the monitoring points.
The specification recites (see para [0036], [0037], and [0040]):
At this step, data processing program 150 may utilize an exemplary network level metric data collection module 320 configured to collect network level metric data from accessible data logs 315 associated with a target cloud-based service. In embodiments, network level metrics may include, for example, packets sent on a connection, packets received on a connection, bytes sent on a connection, bytes received on a connection, retransmitted bytes on a connection, lost bytes on a connection, round trip response time (RTT) on a connection, delays between connection establishment request and connection establishment response packet, among others.
The second dataset collected by data processing program 150 at step 202 includes end-user performance data from one or more monitoring services. As discussed above, monitoring services typically utilize a set number of monitoring points ( or sites) to obtain precise end-user performance data for each individual monitoring point. In embodiments, end-user performance data from one or more monitoring services may include data related to the response time observed at the cloud-based service, the time taken to download a given file, the latency between a request and when the entire response is rendered, the lag at which a movie can be played, the maximum, minimum or average amount of buffer that is occupied, the choppiness of an audio clip, among other examples.
In embodiments, exemplary trained prediction models that are trained using curated training datasets generated by data processing program 150 may be configured to determine y=f(xl ... xn) for any given user of the target cloud-based service where y = end-user performance and xl ... xn represents network level metrics observable at the cloud side of the target cloud-based service, for example, in the connection logs for a given cloud-based service.
The specification recites collecting network level metric data from accessible data logs associated with a target cloud-based service and collecting end-user performance data from one or more monitoring services. However, the specification does not disclose collecting end-user network level metrics for a target end-user outside of the monitoring points. Thus, the specification does not support “collecting end-user network level metrics for a target end-user outside of the monitoring points”.
Claims 1, 8, and 15 recite predicting, using the trained machine learning prediction model, an end-user performance of the target cloud-based service for the target end-user based on the end-user network level metrics.
The specification recites (see para [0036], [0037], [0040], and [0044]):
At this step, data processing program 150 may utilize an exemplary network level metric data collection module 320 configured to collect network level metric data from accessible data logs 315 associated with a target cloud-based service. In embodiments, network level metrics may include, for example, packets sent on a connection, packets received on a connection, bytes sent on a connection, bytes received on a connection, retransmitted bytes on a connection, lost bytes on a connection, round trip response time (RTT) on a connection, delays between connection establishment request and connection establishment response packet, among others.
The second dataset collected by data processing program 150 at step 202 includes end-user performance data from one or more monitoring services. As discussed above, monitoring services typically utilize a set number of monitoring points ( or sites) to obtain precise end-user performance data for each individual monitoring point. In embodiments, end-user performance data from one or more monitoring services may include data related to the response time observed at the cloud-based service, the time taken to download a given file, the latency between a request and when the entire response is rendered, the lag at which a movie can be played, the maximum, minimum or average amount of buffer that is occupied, the choppiness of an audio clip, among other examples.
Accordingly, a model for predicting end-user performance for a target cloud-based service is obtained that leverages data from both the network level metrics for the cloud-based service, as well as the end-user performance data from associated monitoring service data based on a set of monitoring sites/points.
It may be appreciated that data processing program 150 has thus provided for improved estimating of end-user performance of cloud-based services by collecting data from both network level metrics as well as performance data from monitoring services to generate a curated training data set that may be used to train a machine learning prediction model such that it may predict end-user performance for a target cloud-based service for all users of the cloud-based service.
The specification recites predicting end-user performance for a target cloud-based service by training a machine learning model using network level metrics for the cloud-based service and end-user performance data. However, the specification does not disclose predicting end-user performance for a target cloud-based service by training a machine learning model using end-user network level metrics. Thus, the specification does not support “predicting, using the trained machine learning prediction model, an end-user performance of the target cloud-based service for the target end-user based on the end-user network level metrics”.
Claims 2-7, 9-14, and 16-20 depend on the rejected claims and inherit the same issues.
Response to Arguments
The prior art rejection is withdrawn because references Albasheir (U.S. Patent Application Publication No. US 20210349747 A1), Agarwal (U.S. Patent Application Publication No. US 20240205127 A1), Marcus (U.S. Patent Application Publication No. US 20160162779 A1), Borkar (U.S. Patent Application Publication No. US 20200162471 A1), Vicat-Blanc (U.S. Patent Publication No. US 9762471 B1), and Evans (U.S. Patent Publication No. US 9449042 B1) do not teach or suggest “collecting end-user network level metrics for a target end-user outside of the monitoring points". However, the amendment appears to cite new matter. See rejection under 112(a).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
D (U.S. Patent Application Publication No. US 20230185668 A1) discloses “A remote collector may refer to a service/program that is installed in an additional cluster node (e.g., a virtual machine). The remote collector may allow the monitoring tool (e.g., vROps Manager) to gather objects into the remote collector's inventory for monitoring purposes. The remote collectors collect the data from the endpoints and then forward the data to the management node that executes the monitoring tool. For example, remote collectors may be deployed at remote location sites while the monitoring tool may be deployed at a primary location” (D, para [0012]).
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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.
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/S.S.N./Examiner, Art Unit 2192
/S. Sough/SPE, Art Unit 2192
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