DETAILED ACTION
Response to Amendment
This Action is in response to Preliminary Amendment filed on 12/05/2023.
Claims 1-9, 12-18 have been amended. Claims 19-24 are cancelled and 25-26 are added.
Claims 1-18 and 25-26 are presented for examination. Claims 1 and 17 are independent.
Claims 1-18 and 25-26 remain pending in this application.
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 .
Information Disclosure Statement
The information disclosure statements (IDSs) submitted on 12/05/2023 and on 01/17/2025 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the IDSs are being considered by the examiner.
Domestic Benefit/ National Stage Information
This application is a 371 national stage application of PCT international application (# PCT/IN2021/050559) filed on 06/09/2021.
Specification
The lengthy specification has not been checked to the extent necessary to determine the presence of all possible minor errors. Applicant’s cooperation is requested in correcting any errors of which applicant may become aware in the specification.
Claim Objections
Claim(s) 1, 4, 6-7, 11, 17 and 26 are objected to because of the following informalities:
Claim 1 recites the limitation “the dimensioning forecast” in lines 9-10. There is insufficient antecedent basis for this limitation in the claim.
Claim 1 recites the limitation “the maximum bound of the dimensioning forecast” in lines 9-10. There is insufficient antecedent basis for this limitation in the claim. Claim 1 rather recites “a maximum bound of usage” in line 6.
Claim 4 recites the limitation “the occurrence” in line 6. There is insufficient antecedent basis for this limitation in the claim.
Claim 6 recites the limitation “the further dimensioning interval” in line 3. There is insufficient antecedent basis for this limitation in the claim.
Claim 6 recites the limitation “the value of the deviation threshold value” in lines 3-4. Examiner recommends amending it to recite “the value of the deviation threshold”.
Claim 7 recites “…using a machine learning model for at least one of to change… or to initiate” in lines 2-3. The limitation “for at least one of to” is confusing. Examiner recommends amending the claim to recite “…using a machine learning model either change… or to initiate” for better reading.
Claim 7 recites the limitation “the bounds” in lines 5-6. There is insufficient antecedent basis for this limitation in the claim.
Claim 11 recites the limitation “the future” in line 4. There is insufficient antecedent basis for this limitation in the claim.
Claim 17 recites similar limitations as recited in claim 1. Therefore, the claim objection, as set forth above, also applies to the claims.
Claim 17 recites the limitation “the orchestrator” in line 12. Examiner recommends amending it to recite “the underlying orchestrator” instead for proper antecedent basis.
Claim 26 recites similar limitations as recited in claim 4. Therefore, the claim objection, as set forth above, also applies to the claims.
Appropriate correction is required.
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 1-18 and 25-26 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 applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Independent claims 1 and 17 recite the limitations:
checking, on a periodic basis defined by the scaling interval of the underlying orchestrator, whether a measurement of actual usage of the at least one resource deviates from at least one of the minimum bound or the maximum bound by more than a deviation threshold value; and
performing a change to the value of the deviation threshold to a new value based on the checking.
Therefore, the claimed invention checks whether a measurement of actual usage of the at least one resource deviates from at least one of the minimum bound or the maximum bound by more than a deviation threshold value. However, it then recites updating the deviation threshold value based on the checking. As such, it is not clear whether the update happens if the actual usage deviates from min/max bound by more than a deviation threshold value, or if the update happens if the actual usage does not deviate from min/max bound by more than a deviation threshold value. For example, it is unclear what happens when actual usage deviates from min/max bound by more than a deviation threshold value, or when actual usage does not deviate from min/max bound by more than a deviation threshold value. It is also unclear when exactly to performing a change to the value of the deviation threshold to a new value.
Dependent claims 2-16, 18 and 25-26 depend upon rejected base claim, and do not individually remedy the deficiencies as set forth above. Therefore, claims 2-16, 18 and 25-26 are also rejected for the same reasons as set forth above, as same rationale applies to the claims.
Examiner’s Note: To properly overcome 112(b) rejection, examiner suggests incorporating limitations from dependent claims 2-4 into independent claims 1 and 17.
Claim Rejections - 35 USC § 103
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, 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 in the application indicating obviousness or nonobviousness.
Claim(s) 1, 9, 11-14 and 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Bacus et al. (hereinafter, Bacus, US 10193822 B1) in view of TOEROE et al. (hereinafter, TOEROE, WO 2020095232 A1) in view of Cormode et al. (hereinafter, Cormode, US 20070286071 A1).
Regarding claim 1, Bacus discloses a method performed by a network node for adaptive dimensioning and provisioning at least one resource of a cloud-based infrastructure of a telecommunications network (see Abstract; predict a future volume of messages that will be received and processed by the message processing service. Based upon the prediction, resources, in the form of computing resources, are allocated to the message processing service. Reactive auto-scaling of the resources can also be used in conjunction with predictive auto-scaling; also see Col.3: lines 57-62; the resources for the message processing service comprise stateless event-driven compute services. An example of such stateless event-driven compute services is the LAMBDA serverless compute service available from AWS), the method comprising:
dimensioning, to obtain a forecast of, a minimum bound of usage of the at least one resource and a maximum bound of usage of the at least one resource for a dimensioning interval based on an amount of data available (see Col.2: line 58 - Col.3: line 9; Based upon the analysis, future increases in message volume can be predicted to provide forecasts for a period of time, e.g., a day; Additionally, message volumes generally rise and fall during the day, and commonly follow a saw-tooth pattern from day-to-day. Thus, in configurations, upper and lower bounds for message processing during the day for the message processing service can be determined using predictive auto-scaling), wherein the dimensioning interval is greater than a scaling interval of an underlying orchestrator (see Col.2: line 58 - Col.3: line 9; Based upon the analysis, future increases in message volume can be predicted to provide forecasts for a period of time, e.g., a day; also see Col.7: lines 4-12; an additional check is made by the resource management service 114 against the next day's predicted peak message volume in order to determine if the next day's predicted peak message volume would put the resources of the message processing service 106 in excess of the upper (or lower) bound of the resource utilization allocated to the message processing service 106. If so, the message processing service 106 can be adjusted by the resource management service 114 to compensate; examiner articulates that it is obvious that the dimensioning interval is greater than a scaling interval of an underlying orchestrator because if forecasts is predicted for a period of time, e.g., a day, it would not be useful to take same amount to time to perform the predictive auto-scaling and be able to adjust the resource to compensate peak resource requirement for the next day; therefore, the time to scale, i.e., “a scaling interval of an underlying orchestrator” would obviously need to be smaller than the forecast period of time, i.e., “the dimensioning interval”);
provisioning of the at least one resource when the maximum bound of the dimensioning forecast exceeds current resources of the cloud-based infrastructure (see Col.2: line 58 - Col.9: line 2; Based upon the upper and lower bounds and predicted message volume, the resources provided for the message processing service can be scaled a day or more in advance in order to accommodate the available provisioning horizon or forecast temporal granularity. More particularly, for predictive auto-scaling, the current capacity of resources used by the message processing service is compared against the next day's message volume forecast. If the forecast message volume is calculated to exceed the upper (or lower) bound of resource utilization, then the resources allocated to the message processing service can be scaled to compensate);
checking, on a periodic basis defined by the scaling interval of the underlying orchestrator, whether a measurement of actual usage of the at least one resource deviates from at least one of the minimum bound or the maximum bound by more than a deviation threshold value (see Col.5: lines 4-33; the message prediction service 112 can be utilized to predict a volume of messages for peak and/or low points of message volume during the period of time, e.g. peak and/or low points of message volumes on an hourly basis during the period of time; The health check service 116 also monitors utilization of resources of the message processing service 106 in order to ensure that the resources are not being “over-utilized” and thus, the message processing service 106 cannot keep up with the volume of messages being generated by the message production service; examiner articulates monitoring (i.e., “checking”) on a periodic basis is obvious in order to ensure that the resources are not being over-utilized).
Bacus does not explicitly disclose the method being orchestrator and cloud infrastructure agnostic, and performing a change to the value of the deviation threshold to a new value based on the checking.
However, in an analogous art, TOEROE discloses method performed by a network node for adaptive dimensioning and provisioning at least one resource of a cloud-based infrastructure (see Abstract; method and network node are provided for dimensioning a network service (NS)... for use for instantiating the dimensioned NS), the method being orchestrator and cloud infrastructure agnostic (see [0035]; deploying and managing an NS instance of a generic Network Service Descriptor (NSD); also see [0041]; Such an NSD is not tailored towards any specific non-functional requirements (NFRs)), the method being orchestrator and cloud infrastructure agnostic (see [0035]; deploying and managing an NS instance of a generic Network Service Descriptor (NSD); also see [0041]; Such an NSD is not tailored towards any specific non-functional requirements (NFRs)).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the teachings of TOEROE with Bacus so that the method is orchestrator and cloud infrastructure agnostic.
One of ordinary skill in the art would have been motivated so that deployment parameters can be added to the deployment flavor of the NSD, and the NS can be scaled based on different levels of capacity spanning (TOEROE: [0035]).
Bacus (modified by TOEROE) does not explicitly disclose performing a change to the value of the deviation threshold to a new value based on the checking.
However, in an analogous art, Cormode discloses checking, on a periodic basis defined by the scaling interval of the underlying orchestrator, whether a measurement deviates by more than a deviation threshold value (see [0069]; in the adaptive threshold scheme, the coordinator adaptively sets the thresholds of the monitoring nodes 104 every time there is a threshold violation in a node; In other words, the coordinator not only receives the threshold violations from the monitoring nodes, but also reacts to them by sending new thresholds back); and
performing a change to the value of the deviation threshold to a new value based on the checking (see [0069]; in the adaptive threshold scheme, the coordinator adaptively sets the thresholds of the monitoring nodes 104 every time there is a threshold violation in a node; In other words, the coordinator not only receives the threshold violations from the monitoring nodes, but also reacts to them by sending new thresholds back).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the teachings of Cormode with Bacus and TOEROE to perform a change to the value of the deviation threshold to a new value based on the checking.
One of ordinary skill in the art would have been motivated to set thresholds based on more information about each site and, hence, to try to reduce the number of threshold violations based on a complete history of past violations (Cormode: [0069]).
Regarding claim 9, Bacus (modified by TOEROE and Cormode) discloses the method of claim 1, as set forth above. In addition, Bacus further discloses wherein the amount of data available is in a range from a minimum amount of data to a maximum amount of data (see Col.6: lines 30-34; the message prediction service 112 evaluates a history of message throughput for the message processing service 106. The history of message throughput, as well as other data and metrics can be provided by a metrics data store 118. Based upon the analysis, future increases in message volume can be predicted in order to provide forecasts for a period of time, e.g., a day).
Regarding claim 11, Bacus (modified by TOEROE and Cormode) discloses the method of claim 9, as set forth above. In addition, Bacus further discloses wherein the maximum amount of data comprises at least one of streaming data from the telecommunications network, historical data from the telecommunications network, features derived from historical data from the telecommunications network, and data on new services or new subscribers for the future for the telecommunications network (see Col.6: lines 30-34; the message prediction service 112 evaluates a history of message throughput for the message processing service 106. The history of message throughput, as well as other data and metrics can be provided by a metrics data store 118. Based upon the analysis, future increases in message volume can be predicted in order to provide forecasts for a period of time, e.g., a day).
Regarding claim 12, Bacus (modified by TOEROE and Cormode) discloses the method of claim 1, as set forth above. In addition, Bacus further discloses wherein the at least one resource comprises at least one of a virtual network function(VNF), a unit of VNFs, a processor, or a memory (see Col.5: lines 47-54; also see Col.6: lines 50-59; the resources can be scaled a day or more in advance in order to accommodate predicted volumes of messages. The resource management service 114 can adjust resources for the message processing service 106 up or down from current resource allocations for the message processing service 106. Additionally, the resource management service 114 can adjust characteristics of the resources. For example, speeds of processing, writing and/or reading by resources can be automatically increased or decreased by the resource management service 114).
Regarding claim 13, Bacus (modified by TOEROE and Cormode) discloses the method of claim 1, as set forth above. In addition, Bacus further discloses wherein the deviation threshold value is a value defining a maximum allowed deviation under the minimum bound of usage of the at least one resource and a maximum allowed deviation over the maximum bound of usage of the at least one resource for the dimensioning interval (see Col.2: line 58 - Col.9: line 2; Based upon the upper and lower bounds and predicted message volume, the resources provided for the message processing service can be scaled a day or more in advance in order to accommodate the available provisioning horizon or forecast temporal granularity. More particularly, for predictive auto-scaling, the current capacity of resources used by the message processing service is compared against the next day's message volume forecast. If the forecast message volume is calculated to exceed the upper (or lower) bound of resource utilization, then the resources allocated to the message processing service can be scaled to compensate).
Regarding claim 14, Bacus (modified by TOEROE and Cormode) discloses the method of claim 1, as set forth above. In addition, TOEROE further discloses wherein the provisioning meets or maintains a quality of service, QoS, level for the telecommunications network (see [0041]; NSD designed to satisfy these three requirements (FR, AR, and SAPR) is a generic NSD, as it provides no specific information on the performance or the Quality of Service (QoS) of the network service; also see [0063] and [00167]; The NS dimensioning method extends the VNF interface element with the QoS and functional characteristics of the VNF interface; also see [00124]- [00126] and [00174]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the teachings of TOEROE with Bacus and Cormode so that the provisioning meets or maintains a quality of service, QoS, level for the telecommunications network.
One of ordinary skill in the art would have been motivated so that deployment parameters can be added to the deployment flavor of the NSD, and the NS can be scaled based on different levels of capacity spanning (TOEROE: [0035]).
As for Claim 17, the claims list all the same elements of claim 1, but in a network node (see Bacus: Fig.7:700) comprising: processing circuitry (see Bacus: Fig.7:704), and memory (see Bacus: Fig.7:708-710 and 714-718) that includes instructions (see Bacus Col.14: lines 16-57) to carry out the steps of claim 1, rather than the method form. Therefore, the supporting rationale of the rejection to claim 1 applies equally as well to claim 17.
Claim(s) 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Bacus et al. (hereinafter, Bacus, US 10193822 B1) in view of TOEROE et al. (hereinafter, TOEROE, WO 2020095232 A1) in view of Cormode et al. (hereinafter, Cormode, US 20070286071 A1) in view of ZETTERBLAD et al. (hereinafter, ZETTERBLAD, WO 2008004955 A2).
Regarding claim 10, Bacus (modified by TOEROE and Cormode) discloses the method of claim 9, as set forth above. In addition, Bacus further discloses wherein the minimum amount of data comprises network traffic metrics when deploying a specific service (see Col.6: lines 30-34; the message prediction service 112 evaluates a history of message throughput for the message processing service 106. The history of message throughput, as well as other data and metrics can be provided by a metrics data store 118. Based upon the analysis, future increases in message volume can be predicted in order to provide forecasts for a period of time, e.g., a day).
Bacus (modified by TOEROE and Cormode) does not explicitly disclose minimum amount of data comprises a number of subscribers.
However, in an analogous art, ZETTERBLAD discloses wherein the minimum amount of data comprises a number of subscribers (see Abstract; the costumer data at least comprises the parameter number of subscribers).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the teachings of ZETTERBLAD with Bacus, TOEROE and Cormode so that the minimum amount of data comprises a number of subscribers.
One of ordinary skill in the art would have been motivated to supply some minimum basic input parameters (ZETTERBLAD: see page 5, line 31).
Allowable Subject Matter
Claims 2-8, 15-16, 18 and 25-26 would be allowable if rewritten to overcome the rejection(s) under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), 2nd paragraph, set forth in this Office action and to include all of the limitations of the base claim and any intervening claims.
Additional References
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Baughman et al. (US 10361924 B2) forecasts computer resources demand.
Xiang (US 9806975 B2) teaches managing capacity in a virtualized network.
Chou et al. (US 11303501 B2) discloses method to dynamically change connectivity of VNF and PNF instances in New Radio (NR) networks.
XIANG et al. (US 20150365352 A1) manages virtualization capacity by creating virtual network function (NF), where parameters are capacity indications relative to service capacity.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SANDARVA KHANAL whose telephone number is (571)272-8107. The examiner can normally be reached MON-FRI, 0800-1700.
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) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Kamal B Divecha can be reached at 571-272-5863. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/SANDARVA KHANAL/Primary Examiner, Art Unit 2453
Prosecution Insights