CTNF 18/591,365 CTNF 98979 Notice of Pre-AIA or AIA Status 07-03-aia AIA 15-10-aia The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA. Claims 1-20 are currently pending for examination. Claim Objections 07-29-01 AIA Claim 4, 11, and 18 are objected to because of the following informalities: Claims 4, 11, and 18 recite that “the activation power level is a dynamic value”, however, it is stated in claims 3, 10, and 17 that “the activation power level is a constant value”. It believed that this is a typographical error and that the applicant intended for claims 4, 11, and 18 to recite “the dynamic power level is a dynamic value” . Appropriate correction is required. Claim Rejections - 35 USC § 103 07-20-aia AIA 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. 07-21-aia AIA Claim s 1-2, 4-5, 8-9, 11-12, 15-16, and 18-19 rejected under 35 U.S.C. 103 as being unpatentable over Kim (US 20220329651 A1) in view of Tang (US 20170322241 A1) in further view of Duplys (US 20230367870 A1) . As per claim 1, Kim discloses: A computer-implemented method for deploying a workload in a Cloud computing system having a plurality of compute nodes (“an embodiment of the present invention may be implemented in a computer system including a computer-readable recording medium. For example, as illustrated in FIG. 7, the computer system may include one or more processors 710, memory 730, a user-interface input device 740, a user-interface output device 750, and storage 760, which communicate with each other via a bus 720. “, 0153 ; "The cluster scheduler 312 may serve to search for a suitable service node in which a service instance is to be deployed and to deploy the service instance therein when a request to deploy service instances is made. Here, the cluster scheduler 312 may search for the most suitable service node in consideration of resource requirements of the service instances, service quality requirements, priority, other constraints, and the like based on the resource utilization of each service node (the CPU usage rate or absolute CPU usage, the memory usage rate or absolute memory usage, the IO usage rate or absolute IO usage, and the like), stored in the database 313.", 0065 ; Examiner Note: a service instance equates to a workload) identifying resource utilization levels for processors and memory of each of the plurality of compute nodes; identifying characteristics of the workload to be deployed in Cloud computing system; identifying a plurality of locations in the Cloud computing system that are suitable for deployment of the workload based on the characteristics of the workload and the resource utilization levels for processors and memory of each of the plurality of compute nodes, wherein each of the plurality of locations is one of the plurality of compute nodes ("The cluster scheduler 312 may serve to search for a suitable service node in which a service instance is to be deployed and to deploy the service instance therein when a request to deploy service instances is made. Here, the cluster scheduler 312 may search for the most suitable service node in consideration of resource requirements of the service instances, service quality requirements, priority, other constraints, and the like based on the resource utilization of each service node (the CPU usage rate or absolute CPU usage, the memory usage rate or absolute memory usage , the IO usage rate or absolute IO usage, and the like), stored in the database 313.", 0065 ) Kim discloses the above limitations of claim 1, but does not explicitly disclose the calculation of an idle, activation, or dynamic power level for compute nodes. However, Tang discloses: calculating, for each of the plurality of compute nodes, an idle power level, an activation power level, and a dynamic power level ("A PMF can comprise a constant term and/or a plurality of variable terms. The constant term can indicate an idle or static power consumption of the server or group of servers. The plurality of variable terms can indicate a dynamic power consumption of the server or group of servers when the server or group of servers are running a specific workload. The constant term can be determined by measuring aggregate power changes upon turning one or more groups of idle servers off and on, and subsequently performing a least square minimization analysis by using the said aggregate power changes and the number of idle servers that were turned off and on as inputs. The variable terms can comprise coefficient values that are determined by measuring the aggregate power consumption of the datacenter at different time instants and the component states of servers in the datacenter at the corresponding time instants, and subsequently performing a least square minimization analysis by using the aggregate power consumption of the datacenter and the associated component states as inputs.", 0053 ; Examiner Note: the smallest variable term represents the lowest possible power while performing a workload and thus equates to an activation power level) deploying the workload on a first compute node, where the first compute node corresponds to one of the plurality of locations associated with a lowest estimated power consumption of the Cloud computing system (“For example, the power efficiency of different server types under the same workloads can be measured and used by to choose the most energy-conservative servers for performing similar workloads”, 0151 ; Examiner Note: as the measurements are for ‘similar’ workloads, they equate to estimations) It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of Kim (0065) with those of Tang (0053) in order to provide a method for selecting the most energy-conservative servers/nodes to execute a workload (Tang, [0151]). Kim in view of Tang discloses the above limitations of claim 1, but does not disclose the estimation of power consumption through simulation. However, Duplys discloses: calculating, for each of the plurality of locations based on a simulated deployment of the workload at a corresponding location, an estimated power consumption of the Cloud computing system; ("Since the software running on the first computing node is known to a manufacturer, simulators can be used to predict selected digital and physical properties of the first computing node. For example, an instruction set stimulator can be used to predict the register values, and power simulator can be used to predict power consumption of the first computing node based on the knowledge of the input, internal state, and the software executed by the first computing node", 0042) It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of Kim (0065) and Tang (0053) with those of Duplys (0042) in order to provide the cloud computing system with the ability to perform relatively complex analyses at the same time as requiring the transmission of relatively small amounts of data between the monitored device and a monitoring intrusion detection and prevention system, thereby providing an effective method for intrusion detection and prevention (Duplys [0039]). As per claim 2, Kim in view of Tang in further view of Duplys fully discloses the limitations of claim 1. Furthermore , Tang discloses: the idle power level is an amount of power used by a compute node in a standby state during which no workloads are being executed by the compute node ("The constant term can indicate an idle or static power consumption of the server or group of servers", 0053 ; “Moreover, the overall power consumption of a server f(s) can be broken down into two parts: idle power (or static power) and dynamic power. The former is considered as a baseline power supplied to maintain a server system in an idle state, while the latter is an additional power consumption for running specific workloads on the server system”, 0077 ) As per claim 4, Kim in view of Tang in further view of Duplys fully discloses the limitations of claim 1. Furthermore , Tang discloses: the dynamic power level is an amount of power used by a compute node in an active state during which at least one workload is being executed by the compute node and wherein the activation power level is a dynamic value that is dependent upon the resource utilization levels for processors and memory of the compute node (“Moreover, the overall power consumption of a server f(s) can be broken down into two parts: idle power (or static power) and dynamic power. The former is considered as a baseline power supplied to maintain a server system in an idle state, while the latter is an additional power consumption for running specific workloads on the server system”, 0077 As per claim 5, Kim in view of Tang in further view of Duplys fully discloses the limitations of claim 1. Furthermore , Tang discloses: the idle power level, the activation power level, and the dynamic power level for each of the plurality of compute nodes is calculated by based on a power consumption of each of the plurality of compute nodes during a standby state and during active states with varying resource utilization levels. ("Referring to FIG. 12, aggregate power consumption of the IT infrastructure of the datacenter is collected by aggregate power collector 1230 via a UPS 1240 interface and a power monitoring proxy. An arbitrary sampling interval can be set. The sampling interval can be, for example, 2 seconds. Besides the UPS 1240, the datacenter is further equipped with 6 Power Data Management Modules (PDMMs) 1250 as part of PDUs, each of which can provide power measuring at the rack-level at the sampling interval.", 0114 ; “ The constant term can be determined by measuring aggregate power changes upon turning one or more groups of idle servers off and on, and subsequently performing a least square minimization analysis by using the said aggregate power changes and the number of idle servers that were turned off and on as inputs. The variable terms can comprise coefficient values that are determined by measuring the aggregate power consumption of the datacenter at different time instants and the component states of servers in the datacenter at the corresponding time instants, and subsequently performing a least square minimization analysis by using the aggregate power consumption of the datacenter and the associated component states as inputs.”, 0053) As per claim 8, it is a ‘system having a memory having computer readable instructions’ (see Kim, [0153]) claim with substantially the same limitations as claim 1, and as such it is rejected for substantially the same reasons. As per claim 9, it is a ‘system having a memory having computer readable instructions’ (see Kim, [0153]) claim with substantially the same limitations as claim 2, and as such it is rejected for substantially the same reasons. As per claim 11, it is a ‘system having a memory having computer readable instructions’ (see Kim, [0153]) claim with substantially the same limitations as claim 4, and as such it is rejected for substantially the same reasons. As per claim 12, it is a ‘system having a memory having computer readable instructions’ (see Kim, [0153]) claim with substantially the same limitations as claim 5, and as such it is rejected for substantially the same reasons. As per claim 15, it is a ‘computer program product’ (see Kim, [0153]) claim with substantially the same limitations as claim 1, and as such it is rejected for substantially the same reasons. As per claim 16, it is a ‘computer program product’ (see Kim, [0153]) claim with substantially the same limitations as claim 2, and as such it is rejected for substantially the same reasons. As per claim 18, it is a ‘computer program product’ (see Kim, [0153]) claim with substantially the same limitations as claim 4, and as such it is rejected for substantially the same reasons. As per claim 19, it is a ‘computer program product’ (see Kim, [0153]) claim with substantially the same limitations as claim 5, and as such it is rejected for substantially the same reasons . 07-21-aia AIA Claim s 3, 10, and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Kim (US 20220329651 A1) in view of Tang (US 20170322241 A1) in further view of Duplys (US 20230367870 A1) in further view of Bodas (US 20160187906 A1) . As per claim 3, Kim in view of Tang in further view of Duplys fully discloses the limitations of claim 1, but does not explicitly disclose the activation power level being a minimum power used by a node executing at least one workload. However, Bodas discloses: the activation power level is a minimum amount of power used by a compute node in an active state during which at least one workload is being executed by the compute node and wherein the activation power level is a constant value that does not vary based on the resource utilization levels for processors and memory of the compute node ("At the facility level, the facility power manager (FPM) 130 may accommodate requirements for facility power variations per time (e.g., per minute and per hour), and maintain the power consumption at the facility 102 between a minimum power consumption and a maximum power consumption. Such a range may be based on the allocation of power by the utility company or provider, or by a facility manager (e.g., human administrator).", 0036 ; "FIG. 7 is a bar chart 700 comparing power consumption of two example compute jobs 702 and 704, or the same compute job at different times, executing on a compute node 108 in a distributed computing system 106. The desired range or band for the node 108 power is from a minimum power 708 to a maximum power 710. The first compute job 702 executes within the desired band. In contrast, the second compute job 704 executes below the desired minimum power 708 for the node 108. However, with implementation of the aforementioned power balloon application 622, the power of node 108 when executing the second job 704 may be increased to at or above the minimum power 708 level, as indicated by the added power 706, to within the desired power band.", 0062 ; Examiner Note: the minimum power for the node equates to the activation power level, as it is a constant minimum which does not vary based on utilization) It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of Kim (0065), Tang (0053), and Duplys (0042) with those of Bodas (0062) in order to provide the cloud computing system with green mechanisms that improve system-wide reliability (Bodas, [0055]). As per claim 10, it is a ‘system having a memory having computer readable instructions’ (see Kim, [0153]) claim with substantially the same limitations as claim 3, and as such it is rejected for substantially the same reasons. As per claim 17, it is a ‘computer program product’ (see Kim, [0153]) claim with substantially the same limitations as claim 3, and as such it is rejected for substantially the same reasons . 07-21-aia AIA Claim s 6, 13, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Kim (US 20220329651 A1) in view of Tang (US 20170322241 A1) in further view of Duplys (US 20230367870 A1) in further view of Hedge (US 20240023014 A1) . As per claim 6, Kim in view of Tang in further view of Duplys fully discloses the limitations of claim 1, but does not explicitly disclose the estimated power consumption of the Cloud computing system being calculated as a sum of idle power level, activation power level, and dynamic power level. However, Hedge discloses: the estimated power consumption of the Cloud computing system is calculated as a sum of: the idle power level of each of the plurality of the compute nodes operating in a standby state; the activation power level of each of the plurality of the compute nodes operating in an active state; and the dynamic power level of each of the plurality of the compute nodes operating in a standby state (Examiner Note: the dynamic power level of a node operating in a standby state would be equivalent to the idle power of the node operating in a standby state) ("FIG. 4 depicts a device 400 comprising a processor 402 configured to determine a static power consumption estimate based on configuration parameters of modem subcomponents of a wireless modem 404; determine a dynamic power consumption estimate based on a sum of, for each corresponding active power amplifier of the wireless modem 404, a predefined power offset associated with a current reported power level for the corresponding active power amplifier and a maximum transmit power of a predefined range associated with the current reported power level; and combine the static power consumption estimate and the dynamic power consumption estimate as a total estimate of the power consumption of the wireless modem. The processor of the device may be further configured to control a maximum power supplied to the wireless modem based on the total estimate of the power consumption.", 0055 ; Examiner Note: the static power consumption corresponds to idle power level and the power offset associated with a current reported power level corresponds to an activation power level) It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of Kim (0065), Tang (0053), and Duplys (0042) with those of Hedge (0055) in order to provide the system with an improved methodology for power consumption estimation for a given real-time use case (Hedge, [0033]) As per claim 13, it is a ‘system having a memory having computer readable instructions’ (see Kim, [0153]) claim with substantially the same limitations as claim 6, and as such it is rejected for substantially the same reasons. As per claim 20, it is a ‘computer program product’ (see Kim, [0153]) claim with substantially the same limitations as claim 6, and as such it is rejected for substantially the same reasons . 07-21-aia AIA Claim s 7 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Kim (US 20220329651 A1) in view of Tang (US 20170322241 A1) in further view of Duplys (US 20230367870 A1) in further view of Szewczyk (US 20110264418 A1) . As per claim 7, Kim in view of Tang in further view of Duplys fully discloses the limitations of claim 1, but does not explicitly disclose evenly dividing the activation power level of the first compute node among workloads being processed by the first compute node to calculate a power consumption of a workload. However, Szewczyk discloses: calculating a power consumption of the workload by: evenly dividing the activation power level of the first compute node among workloads being processed by the first compute node; and apportioning the dynamic power level among the workloads being processed by the first compute node based on the resource utilization levels of each of the workloads being processed by the first compute node. ("It is noted that the aforementioned power model can be represented as having a fixed electrical consumption component and a variable electrical consumption component. For example, the aforementioned power model can be represented by the following formula: P=C1+C2+ . . . CN+F1(util1)+F2(util2)+ . . . FN(utilN) wherein P represents the electrical consumption of the asset. C1+C2+CN represent the aggregate fixed power consumption of the entire asset based on the fixed power consumption of its individual components . These individual constants can be combined and represented as single constant. F1(util1)+F2(util2)+FN(utilN) represent the aggregate variable power consumption of the asset based on the variable power consumption of its individual components. ", 0053 ; Examiner Note: an asset equates to a node, and a component equates to a workload. C1-CN represent the even divisions of activation power, and F1-FN represent the portions of the dynamic power level based on resource utilization levels (util1-utilN). Rearranging this equation would provide an equation which provides the power consumption of a workload) It would have been obvious to one of ordinary skill in the art, before the effective filing date, to combine the teachings of Kim (0065), Tang (0053), and Duplys (0042) with those of Szewczyk (0053) in order to beneficially allow for the measurement of electrical values within a node without the need for any physical meters (Szewczyk, [0066]). As per claim 14, it is a ‘system having a memory having computer readable instructions’ (see Kim, [0153]) claim with substantially the same limitations as claim 7, and as such it is rejected for substantially the same reasons . Conclusion 07-96 AIA The prior art made of record and not relied upon is considered pertinent to applicant's disclosure : Hiregoudar (US 20240069614 A1) – discloses various mechanisms and workflows that can utilize power and/or carbon footprint-based metrics to manage storage unit usage and/or configuration. In some example configurations, storage system management mechanisms collect power consumption for storage units (e.g., individual drives, storage shelfs, nodes, clusters) and can utilize the power consumption information with other storage unit characteristics to generate power and carbon footprint metrics. Grimshaw (US 12099873 B2) – discloses a system and method for receiving a user request for an application to be executed by a computing system associated with a data center, wherein the application includes a plurality of tasks, and wherein the request includes an estimated execution time corresponding to an estimated amount of real-world time that the tasks will be actively running on the computing system to fully execute the application. Any inquiry concerning this communication or earlier communications from the examiner should be directed to ROSS MICHAEL VINCENT whose telephone number is (703)756-1408. The examiner can normally be reached Mon-Fri 8:30AM-5:30PM. 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, April Blair can be reached at (571) 270-1014. 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. /R.M.V./ Examiner, Art Unit 2196 /APRIL Y BLAIR/Supervisory Patent Examiner, Art Unit 2196 Application/Control Number: 18/591,365 Page 2 Art Unit: 2196 Application/Control Number: 18/591,365 Page 3 Art Unit: 2196 Application/Control Number: 18/591,365 Page 4 Art Unit: 2196 Application/Control Number: 18/591,365 Page 5 Art Unit: 2196 Application/Control Number: 18/591,365 Page 6 Art Unit: 2196 Application/Control Number: 18/591,365 Page 7 Art Unit: 2196 Application/Control Number: 18/591,365 Page 8 Art Unit: 2196 Application/Control Number: 18/591,365 Page 9 Art Unit: 2196 Application/Control Number: 18/591,365 Page 10 Art Unit: 2196 Application/Control Number: 18/591,365 Page 11 Art Unit: 2196 Application/Control Number: 18/591,365 Page 12 Art Unit: 2196 Application/Control Number: 18/591,365 Page 13 Art Unit: 2196 Application/Control Number: 18/591,365 Page 14 Art Unit: 2196
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