DETAILED ACTION
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
Applicant’s amendments to the claims, filed 1/2/2026, are accepted and appreciated by the examiner.
Response to Arguments
Applicant’s arguments filed 1/2/2026 have been fully considered. With respect to the 35 U.S.C.§101 Rejection, Applicant’s amendments recite a practical application and therefore the rejection has been withdrawn. With respect to the 35 U.S.C. §112(b) Rejection, Applicant’s amendments have addressed these issues and are therefore withdrawn. With regards to the 35 U.S.C. § 103 Rejection, Applicant amendments are addressed below.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, 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.
Claim(s) 1, 5-7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Chatterjee (US 2016/0087909 A1) in view of Barsness (US 2010/0257531 A1).
With respect to Claim 1 Chatterjee teaches A computer-implemented method performed by a data center management system, the method comprising: (See Abstract A method for scheduling cost efficient data center load distribution is described) predicting localized weather conditions for a location of a data center during a period of time; (See Para[0024] For example, information from different location data centers may be received containing renewable energy forecasts (R.sub.e(t)) 210, 220, and 230 for a desired time of task completion, ambient temperature forecasts (T.sub.i(t)) 211, 221, and 231, cooling forecasts (O.sub.i(t)) 212, 222, and 232. ) (See Para[0027] a given location individual data centers may rely on weather forecasts or wind predictions to create a renewable energy forecasts R.sub.e(t) 210, 220 and 230. Solar power forecasting may include implementation of the Sun's path, atmosphere's condition predicted using, for example, geostationary satellite imagery or numerical weather prediction model products, atmospheric light scattering process and the individual characteristics of the solar production to determine the amount of energy available for a given period. Similarly, the availability of wind power may be forecasted based on numerical weather prediction models. The satellite imagery and numerical weather prediction models may be obtained from governmental meteorological agencies such as the National Oceanic and Atmospheric Administration (NOAA). Information containing estimates of renewable energy production for a specific period may be sent to a workload scheduling device 110 in order to determine the individual data center's cost of operation for a specific period.) wherein predicting the localized weather conditions comprises predicting two or more of a temperature at the location, a measure of humidity at the location, or an amount of precipitation at the location (See Para[0024] ambient temperature forecasts (T.sub.i(t)) 211, 221, and 231, cooling forecasts (O.sub.i(t)) 212, 222, and 232. Examiner notes that Tsubi (t) is a function of time indicating that the ambient temperature forecasts depends on the time and is a value that may have various values over time) determining whether the localized weather conditions will degrade an operation of the data center during the period of time (See Para[0028] Temperature is a critical factor in data center operations and is rigorously maintained through temperature and humidity control. The temperature in a data center will naturally rise because the electrical power used heats the ambient air. Unless the heat is dissipated, the facility's ambient temperature will rise, resulting in electronic equipment malfunction or critical failure. By controlling the air temperature, the server components are kept within the manufacturer's specified temperature/humidity range.); obtaining computational workload information identifying one or more computational workloads scheduled for execution at the data center during the period of time; (See Para[0042] Based on the power consumption P.sub.i, workload scheduling device 110 may calculate the marginal energy cost in terms of a function of time and computational load) determining, based on the computational workload information, one or more priorities associated with the one or more computational workloads (See Para[0043] By calculating the marginal energy cost (MC.sup.i) workload scheduling device 110 may determine the lowest computational cost between all available data centers for the purpose of scheduling computational tasks, as described in more detail in FIG. 4.); and scheduling the one or more computational workloads for execution based on the one or more priorities and (See Para[0044] In step 305, workload scheduling device 110 assigns user workload tasks for completion to a data canter or a plurality of data centers with the lowest determined computational cost.) However Chatterjee is silent to the language of based on determining whether the localized weather conditions will degrade the operation of the data center. wherein scheduling the one or more computational workloads comprise: causing the one or more computational workloads to be executed based on the one or more priorities and based on determining whether the localized weather conditions will degrade the operation of the data center. Examiner notes it would have been obvious to one of ordinary skill in the art before the effective filing date to schedule based on determining whether the localized weather conditions will degrade the operation of the data center, because the scheduling takes into account a temperature forecast and cooling forecast. Chatterjee further teaches (See Para[0028] Temperature is a critical factor in data center operations and is rigorously maintained through temperature and humidity control. The temperature in a data center will naturally rise because the electrical power used heats the ambient air. Unless the heat is dissipated, the facility's ambient temperature will rise, resulting in electronic equipment malfunction or critical failure. By controlling the air temperature, the server components are kept within the manufacturer's specified temperature/humidity range.). Therefore in situations where the temperature is too high, the scheduling of Chatterjee would avoid equipment malfunction or critical failure.
(See Para[0028] For example, the computational cost for location 1 data center where the outside temperature reaches 75 degrees Fahrenheit is much lower than location 3 data center with outside temperature of 90 degrees Fahrenheit. The 15 degree difference at location 3 data center may drive the computational cost significantly, and serve as a deciding factor in task scheduling, due to the air cooling system's additional use of energy to reach recommended standards for internal temperature and humidity.) Nevertheless Barsness teaches based on determining whether the localized weather conditions will degrade the operation of the data center. (See Para[0017]) wherein scheduling the one or more computational workloads comprise: causing the one or more computational workloads to be executed based on the one or more priorities and based on determining whether the localized weather conditions will degrade the operation of the data center (See Fig 3). It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Chatterjee causing the one or more computational workloads to be executed based on the one or more priorities and based on determining whether the localized weather conditions will degrade the operation of the data center such as that of Barsness. One of ordinary skill would have been motivated to modify Chatterjee because doing so would make sure the executed job plan runs smoothly without interruption. With respect to Claim 5 Chatterjee teaches The computer-implemented method of claim 1, wherein predicting the localized weather conditions comprises: predicting at least one of the temperature or the measure of humidity at the location of the data center; and (See Para[0024]) wherein the method further comprises: predicting an amount of energy to be used to decrease a data center temperature at the data center based on the at least one of the temperature or the measure of humidity; and (See Para[0024]) scheduling the one or more computational workloads to be executed by one or more computing nodes of the data center based on the amount of energy to be used to decrease a data center temperature of the data center. (See Para[0024]) With respect to Claim 6 Chatterjee teaches The computer-implemented method of claim 1, wherein predicting the localized weather conditions comprises: predicting at least one of a velocity of wind or the amount of precipitation at the location of the data center; and (See Para[0027]) wherein the method further comprises: predicting a continuity of power supplied to the data center based on the at least one of the velocity of wind or the amount of precipitation; and (See Para[0027]) scheduling the one or more computational workloads to be executed by one or more computing nodes of the data center based on the continuity of the power supplied to the data center. (See Fig 2) With respect to Claim 7 Chatterjee teaches The computer-implemented method of claim 1, wherein predicting the localized weather conditions comprises: predicting an amount of solar irradiance at the location of the data center; (See Para[0025])and wherein the method further comprises: predicting a continuity of power supplied to the data center based on the amount of solar irradiance; and (See Para[0025]) scheduling a computational workload to be executed by one or more computing nodes of the data center based on the continuity of power supplied to the data center. (See Fig 2)
Claim(s) 2-4, 8,9, 12-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Chatterjee (US 2016/0087909 A1) in view of Barsness (US 2010/0257531 A1) and Jackson (US 2014/0075222 A1). With respect to Claim 2 Chatterjee teaches The computer-implemented method of claim 1, wherein scheduling the one or more computational workloads comprise: determining that the localized weather will degrade the operation of the data center; (See Para[0044] In step 305, workload scheduling device 110 assigns user workload tasks for completion to a data canter or a plurality of data centers with the lowest determined computational cost.) (See Para[0028] Temperature is a critical factor in data center operations and is rigorously maintained through temperature and humidity control. The temperature in a data center will naturally rise because the electrical power used heats the ambient air. Unless the heat is dissipated, the facility's ambient temperature will rise, resulting in electronic equipment malfunction or critical failure. By controlling the air temperature, the server components are kept within the manufacturer's specified temperature/humidity range.). However Chatterjee is silent to the language of wherein determining the one or more priorities comprises: determining a first priority associated with a first computational workload of the one or more computational workloads; determining a second priority associated with a second computational workload of the one or more computational workloads, wherein the first priority exceeds the second priority; and causing the first computational workload to be executed during the period of time based on the first priority; and causing the second computational workload to be executed after the period of time based on the second priority. Nevertheless Jackson teaches wherein determining the one or more priorities comprises: determining a first priority associated with a first computational workload of the one or more computational workloads; (See Para[0024] Another benefit enables the system to take advantage of off-peak hours by automatically scheduling lower priority workload for processing during off-peak hours when energy costs are lower, while ensuring that QOS guarantees are met.) (See Para[0068] . Here, the system can prioritize "green" workload during the most expensive time-of-day periods. In this regard, the system analyzes the actual workload to determine the power consumption that will likely be needed in order to process that workload. Here, if a particular job or workload is anticipated not to utilize as much power as other workload, then the system can prioritize that workload during the most expensive time of day periods. As an example of prioritizing green workload, the system 304 can perform an analysis for the workload to identify that a particular workload will use a low amount of energy such that such workload can be processed during the most expensive time of day.) (See Para[0083] Preemption can revolve around the idea of terminating or suspending certain workloads (preemptees) to free up the allocated resources of these workloads and allow these resources to be re-assigned to other high priority workloads (preemptors)) determining a second priority associated with a second computational workload of the one or more computational workloads, (See Para[0024] and Para[0068] and [0083]) wherein the first priority exceeds the second priority; and (See Para[0024] and Para[0068] and [0083]) causing the first computational workload to be executed during the period of time based on the first priority; and (See Para[0024] and Para[0068] and [0083]) causing the second computational workload to be executed after the period of time based on the second priority. (See Para[0024] and Para[0068] and [0083])
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Chatterjee and execute according to the priority such as that of Jackson. One of ordinary skill would have been motivated to modify Chatterjee because, executing according to a priority would ensure important task are completed in a timely manner. With respect to Claim 3 Chatterjee is silent to the language of The computer-implemented method of claim 2, further comprising: determining a third priority associated with a third computational workload of the one or more computational workloads, wherein the second priority exceeds the third priority; and causing the third computational workload to be canceled during the period of time based on the third priority. Nevertheless Jackson teaches determining a third priority associated with a third computational workload of the one or more computational workloads, (See Para[0096]) wherein the second priority exceeds the third priority; and causing the third computational workload to be canceled during the period of time based on the third priority. (See Para[0096]) It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Chatterjee and cause the third computational workload to be canceled during the period of time based on the third priority such as that of Jackson. One of ordinary skill would have been motivated to modify Chatterjee because, canceling a task would allow for important task to be completed in a timely manner.
With respect to Claim 4 Chatterjee teaches The computer-implemented method of claim 2, wherein the data center is a first data center, and wherein causing the first computational workload to be executed during the period of time comprises: identifying a second data center; and causing the first computational workload to be executed during the period of time at the second data center. (See Para[0023] For example, one data center may initiate the user workload demand 105 and when another location with lower cost becomes available, the load transfer 130 may occur to a secondary location in order to minimize the computing cost.) and (see Claim 6) With respect to Claim 8 Chatterjee teaches A computer program product for managing computational workloads, the computer program product comprising: (See Fig 5) one or more non-transitory computer readable storage media, and program instructions collectively stored on the one or more non-transitory computer readable storage media, the program instructions comprising: (See Fig 5) program instructions to predict localized weather conditions for a location of a data center during a period of time; program instructions to determine that the localized weather conditions will degrade an operation of a portion of the data center during the period of time; (See Para[0024] For example, information from different location data centers may be received containing renewable energy forecasts (R.sub.e(t)) 210, 220, and 230 for a desired time of task completion, ambient temperature forecasts (T.sub.i(t)) 211, 221, and 231, cooling forecasts (O.sub.i(t)) 212, 222, and 232. ) (See Para[0027] a given location individual data centers may rely on weather forecasts or wind predictions to create a renewable energy forecasts R.sub.e(t) 210, 220 and 230. Solar power forecasting may include implementation of the Sun's path, atmosphere's condition predicted using, for example, geostationary satellite imagery or numerical weather prediction model products, atmospheric light scattering process and the individual characteristics of the solar production to determine the amount of energy available for a given period. Similarly, the availability of wind power may be forecasted based on numerical weather prediction models. The satellite imagery and numerical weather prediction models may be obtained from governmental meteorological agencies such as the National Oceanic and Atmospheric Administration (NOAA). Information containing estimates of renewable energy production for a specific period may be sent to a workload scheduling device 110 in order to determine the individual data center's cost of operation for a specific period.) wherein the localized weather conditions include two or more of a temperature at the location, a measure of humidity at the location, or an amount of precipitation at the location, and (See Para[0024] ambient temperature forecasts (T.sub.i(t)) 211, 221, and 231, cooling forecasts (O.sub.i(t)) 212, 222, and 232. Examiner notes that Tsubi (t) is a function of time indicating that the ambient temperature forecasts depends on the time and is a value that may have various values over time) wherein the localized weather conditions include weather conditions that are specific to an area corresponding to geographical boundaries of the data center; (See Para[0024] ambient temperature forecasts (T.sub.i(t)) 211, 221, and 231, cooling forecasts (O.sub.i(t)) 212, 222, and 232. Examiner notes that Tsubi (t) is a function of time indicating that the ambient temperature forecasts depends on the time and is a value that may have various values over time)center. However Chatterjee is silent to the language of program instructions to determine a first priority associated with a first computational workload of a plurality of computational workloads to be executed during the period of time; program instructions to determine a second priority associated with a second computational workload of the plurality of computational workloads; and program instructions to cause the first computational workload and the second computational workload to be executed based on the first priority, the second priority, and determining that the localized weather conditions will degrade the operation of a portion of the data center. (It would have been obvious to one of ordinary skill in the art before the effective filing date to schedule based on determining whether the localized weather conditions will degrade the operation of the data center, because the scheduling takes into account a temperature forecast and cooling forecast. Chatterjee further teaches (See Para[0028] Temperature is a critical factor in data center operations and is rigorously maintained through temperature and humidity control. The temperature in a data center will naturally rise because the electrical power used heats the ambient air. Unless the heat is dissipated, the facility's ambient temperature will rise, resulting in electronic equipment malfunction or critical failure. By controlling the air temperature, the server components are kept within the manufacturer's specified temperature/humidity range.). Therefore in situations where the temperature is too high, the scheduling of Chatterjee would avoid equipment malfunction or critical failure.
(See Para[0028] For example, the computational cost for location 1 data center where the outside temperature reaches 75 degrees Fahrenheit is much lower than location 3 data center with outside temperature of 90 degrees Fahrenheit. The 15 degree difference at location 3 data center may drive the computational cost significantly, and serve as a deciding factor in task scheduling, due to the air cooling system's additional use of energy to reach recommended standards for internal temperature and humidity.) Nevertheless Barsness teaches program instructions to cause the first computational workload and the second computational workload to be executed based on the first priority, the second priority, and determining that the localized weather conditions will degrade the operation of a portion of the data center. (See Fig 3). However Barsness is silent to the language of program instructions to determine a first priority associated with a first computational workload of a plurality of computational workloads to be executed during the period of time; program instructions to determine a second priority associated with a second computational workload of the plurality of computational workloads; and Nevertheless Jackson teaches program instructions to determine a first priority associated with a first computational workload of a plurality of computational workloads to be executed during the period of time; (See Para[0024] Another benefit enables the system to take advantage of off-peak hours by automatically scheduling lower priority workload for processing during off-peak hours when energy costs are lower, while ensuring that QOS guarantees are met.) (See Para[0068] Here the system can prioritize "green" workload during the most expensive time-of-day periods. In this regard, the system analyzes the actual workload to determine the power consumption that will likely be needed in order to process that workload. Here, if a particular job or workload is anticipated not to utilize as much power as other workload, then the system can prioritize that workload during the most expensive time of day periods. As an example of prioritizing green workload, the system 304 can perform an analysis for the workload to identify that a particular workload will use a low amount of energy such that such workload can be processed during the most expensive time of day.) (See Para[0083] Preemption can revolve around the idea of terminating or suspending certain workloads (preemptees) to free up the allocated resources of these workloads and allow these resources to be re-assigned to other high priority workloads (preemptors)) program instructions to determine a second priority associated with a second computational workload of the plurality of computational workloads; and (See Para[0024] and Para[0068] and [0083]) It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Chatterjee causing the one or more computational workloads to be executed based on the one or more priorities and based on determining whether the localized weather conditions will degrade the operation of the data center such as that of Barsness. One of ordinary skill would have been motivated to modify Chatterjee because doing so would make sure the executed job plan runs smoothly without interruption. It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Chatterjee and execute according to the priority such as that of Jackson. One of ordinary skill would have been motivated to modify Chatterjee because, executing according to a priority would ensure important task are completed in a timely manner. With respect to Claim 9 Chatterjee teaches The computer program product of claim 8, wherein the program instructions further comprise: program instructions to provide weather information, regarding the localized weather conditions, to a building management system of the data center, (See Fig 2) wherein the weather information includes information identifying weather conditions at the data center, and (See Fig 2) However Chatterjee is silent to the language of wherein the weather information is provided to the building management system to cause the building management system to control a data center temperature, of the data center, based on the weather information. Nevertheless Jackson teaches wherein the weather information is provided to the building management system to cause the building management system to control a data center temperature, of the data center, based on the weather information. (See Para[0056] [0067]) It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Chatterjee wherein the weather information is provided to the building management system to cause the building management system to control a data center temperature, of the data center, based on the weather information such as that of Jackson. One of ordinary skill would have been motivated to modify Chatterjee, because controlling the temperature would efficiently manage the computing environment and would avoid failure. With respect to Claim 12 Chatterjee is silent to the language of The computer program product of claim 8, wherein the program instructions to schedule the first computational workload and the second computational workload include: program instructions to determine an operational cost associated with executing the first computational workload and the second computational workload during the period of time; program instructions to determine that the operational cost satisfies a cost threshold; program instructions to cause the first computational workload to be executed during the period of time based on a first priority associated with the first computational workload; and program instructions to cause the second computational workload after the period of time based on determining that the operational cost satisfies the cost threshold and based on the second priority associated with the second computational workload. Nevertheless Jackson teaches wherein the program instructions to schedule the first computational workload and the second computational workload include: program instructions to determine an operational cost associated with executing the first computational workload and the second computational workload during the period of time; (See Para[0024] Another benefit enables the system to take advantage of off-peak hours by automatically scheduling lower priority workload for processing during off-peak hours when energy costs are lower, while ensuring that QOS guarantees are met.) (See Para[0068] . Here, the system can prioritize "green" workload during the most expensive time-of-day periods. In this regard, the system analyzes the actual workload to determine the power consumption that will likely be needed in order to process that workload. Here, if a particular job or workload is anticipated not to utilize as much power as other workload, then the system can prioritize that workload during the most expensive time of day periods. As an example of prioritizing green workload, the system 304 can perform an analysis for the workload to identify that a particular workload will use a low amount of energy such that such workload can be processed during the most expensive time of day.) (See Para[0083] Preemption can revolve around the idea of terminating or suspending certain workloads (preemptees) to free up the allocated resources of these workloads and allow these resources to be re-assigned to other high priority workloads (preemptors)) program instructions to determine that the operational cost satisfies a cost threshold; program instructions to cause the first computational workload to be executed during the period of time based on a first priority associated with the first computational workload; and (See Para[0024] and Para[0068] and [0083]) program instructions to cause the second computational workload after the period of time based on determining that the operational cost satisfies the cost threshold and based on the second priority associated with the second computational workload. (See Para[0024] and Para[0068] and [0083]) It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Chatterjee and execute according to the priority such as that of Jackson. One of ordinary skill would have been motivated to modify Chatterjee because, executing according to a priority would ensure important task are completed in a timely manner. With respect to Claim 13 Chatterjee teaches The computer program product of claim 8, wherein the program instructions further include: program instructions to predict an amount of power to be generated by a source of renewable energy based on the localized weather conditions (See [0024]); and program instructions to adjust an amount of energy consumption based on the amount of power to be generated by the source of renewable energy. (See Para[0024]) With respect to Claim 14 Chatterjee teaches The computer program product of claim 8, wherein the portion of the data center is a first portion, and wherein the program instructions further include: program instructions to determine that an operation of a second portion of the data center during the period of time will not be disrupted by the local weather conditions; and (See Fig 2) cause the first computational workload to be executed by one or more computing nodes of the second portion of the data center during the period of time based on determining that the localized weather conditions will not disrupt the operation of the second portion of the data center. (See Fig 2) With respect to Claim 15 Chatterjee teaches A system comprising: a data center (See Fig 2) including a plurality of computing nodes; and a data center management system configured to (See Fig 2): predict localized weather conditions for a location of the data center during a period of time; determine that the localized weather conditions will degrade an operation of the data center during the period of time; (See Para[0024] For example, information from different location data centers may be received containing renewable energy forecasts (R.sub.e(t)) 210, 220, and 230 for a desired time of task completion, ambient temperature forecasts (T.sub.i(t)) 211, 221, and 231, cooling forecasts (O.sub.i(t)) 212, 222, and 232. ) (See Para[0027] a given location individual data centers may rely on weather forecasts or wind predictions to create a renewable energy forecasts R.sub.e(t) 210, 220 and 230. Solar power forecasting may include implementation of the Sun's path, atmosphere's condition predicted using, for example, geostationary satellite imagery or numerical weather prediction model products, atmospheric light scattering process and the individual characteristics of the solar production to determine the amount of energy available for a given period. Similarly, the availability of wind power may be forecasted based on numerical weather prediction models. The satellite imagery and numerical weather prediction models may be obtained from governmental meteorological agencies such as the National Oceanic and Atmospheric Administration (NOAA). Information containing estimates of renewable energy production for a specific period may be sent to a workload scheduling device 110 in order to determine the individual data center's cost of operation for a specific period.) wherein the localized weather conditions include two or more of a temperature at the location, a measure of humidity at the location or an amount of precipitation at the location; (See Para[0024] ambient temperature forecasts (T.sub.i(t)) 211, 221, and 231, cooling forecasts (O.sub.i(t)) 212, 222, and 232. Examiner notes that Tsubi (t) is a function of time indicating that the ambient temperature forecasts depends on the time and is a value that may have various values over time) and determining that the localized weather conditions will degrade the operation of the data center. (See Para[0044] In step 305, workload scheduling device 110 assigns user workload tasks for completion to a data canter or a plurality of data centers with the lowest determined computational cost.) However Chatterjee is silent to the language of including a plurality of computing nodes determine a first priority associated with a first computational workload of a plurality of computational workloads to be executed during the period of time; determine a second priority associated with a second computational workload of the plurality of computational workloads; and cause the first computational workload and the second computational workload be executed based on the first priority, the second priority, Nevertheless Barsness teaches cause the first computational workload and the second computational workload be executed based on the first priority, the second priority, (See Fig 3) However Barsness is silent to the language of including a plurality of computing nodes determine a first priority associated with a first computational workload of a plurality of computational workloads to be executed during the period of time; determine a second priority associated with a second computational workload of the plurality of computational workloads; and Nevertheless Jackson teaches including a plurality of computing nodes (See Para[0009]) determine a first priority associated with a first computational workload of a plurality of computational workloads to be executed during the period of time; (See Para[0024] Another benefit enables the system to take advantage of off-peak hours by automatically scheduling lower priority workload for processing during off-peak hours when energy costs are lower, while ensuring that QOS guarantees are met.) (See Para[0068] Here the system can prioritize "green" workload during the most expensive time-of-day periods. In this regard, the system analyzes the actual workload to determine the power consumption that will likely be needed in order to process that workload. Here, if a particular job or workload is anticipated not to utilize as much power as other workload, then the system can prioritize that workload during the most expensive time of day periods. As an example of prioritizing green workload, the system 304 can perform an analysis for the workload to identify that a particular workload will use a low amount of energy such that such workload can be processed during the most expensive time of day.) (See Para[0083] Preemption can revolve around the idea of terminating or suspending certain workloads (preemptees) to free up the allocated resources of these workloads and allow these resources to be re-assigned to other high priority workloads (preemptors)) determine a second priority associated with a second computational workload of the plurality of computational workloads; and (See Para[0024] and Para[0068] and [0083]) It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Chatterjee causing the one or more computational workloads to be executed based on the one or more priorities and based on determining whether the localized weather conditions will degrade the operation of the data center such as that of Barsness. One of ordinary skill would have been motivated to modify Chatterjee because doing so would make sure the executed job plan runs smoothly without interruption. It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Chatterjee and execute according to the priority such as that of Jackson. One of ordinary skill would have been motivated to modify Chatterjee because, executing according to a priority would ensure important task are completed in a timely manner. With respect to Claim 16 Chatterjee is silent to the language of The system of claim 15, wherein, to schedule the first computational workload and the second computational workload, the data center management system is further configured to: cause, using a machine learning model, the first computational workload to be executed during the period of time based on the first priority; and cause, using the machine learning model, the second computational workload to be executed after the period of time based on the second priority. Nevertheless Jackson teaches cause, using a machine learning model, the first computational workload to be executed during the period of time based on the first priority; and (See Para[0061],[0087]) cause, using the machine learning model, the second computational workload to be executed after the period of time based on the second priority. (See Para[0061],[0087]) With respect to Claim 17 Chatterjee teaches The system of claim 16, wherein the data center is a first data center, and wherein, to cause the first computational workload to be executed during the period of time, the data center management system is further configured to: identify a second data center; and (See Para[0002]) causing the first computational workload to be executed during the period of time at the second data center, wherein the first data center is a first cloud instance and the second data center is a second cloud instance.(See Para[0002]) With respect to Claim 18 Chatterjee is silent to the language of The system of claim 16, wherein the data center management system is further configured to: determine a third priority associated with a third computational workload of the plurality of computational workloads, wherein the second priority exceeds the third priority; and cause the third computational workload to be canceled during the period of time based on the third priority. Nevertheless Jackson teaches wherein the data center management system is further configured to: determine a third priority associated with a third computational workload of the plurality of computational workloads, (See Para[0096]) wherein the second priority exceeds the third priority; and cause the third computational workload to be canceled during the period of time based on the third priority. (See Para[0096]) It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Chatterjee and cause the third computational workload to be canceled during the period of time based on the third priority such as that of Jackson. One of ordinary skill would have been motivated to modify Chatterjee because, canceling a task would allow for important task to be completed in a timely manner.
With respect to Claim 19 Chatterjee is silent to the language of The system of claim 16, wherein, to cause the first computational workload to be executed during the period of time, the data center management system is further configured to: determine one or more of a service level agreement associated with the first computation workload or a quality of service associated with the first computation workload; and cause the first computational workload to be executed during the period of time based on the one or more of the service level agreement or the quality of service. Nevertheless Jackson teaches wherein, to cause the first computational workload to be executed during the period of time, the data center management system is further configured to: determine one or more of a service level agreement associated with the first computation workload or a quality of service associated with the first computation workload; and (See Para[0018],[0024], [0105]) cause the first computational workload to be executed during the period of time based on the one or more of the service level agreement or the quality of service. (See Para[0018],[0024], [0105]) It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Chatterjee and cause the first computational workload to be executed during the period of time based on the one or more of the service level agreement or the quality of service such as that of Jackson. One of ordinary skill would have been motivated to modify Chatterjee because executing based on a service level agreement would make sure the agreement is kept and improve satisfaction. With respect to Claim 20 Chatterjee teaches The system of claim 16, wherein the data center management system is further configured to: provide weather information, regarding the localized weather conditions, to a building management system of the data center, (See Fig 2) However Chatterjee is silent to the language of wherein the weather information is provided to the building management system to cause the building management system to control a data center temperature, of the data center, based on the weather information. Nevertheless Jackson teaches wherein the weather information is provided to the building management system to cause the building management system to control a data center temperature, of the data center, based on the weather information. (See Para[0056] [0067]) It would have been obvious to one of ordinary skill in the art before the effective filing date to modify Chatterjee wherein the weather information is provided to the building management system to cause the building management system to control a data center temperature, of the data center, based on the weather information such as that of Jackson. One of ordinary skill would have been motivated to modify Chatterjee, because controlling the temperature would efficiently manage the computing environment and would avoid failure.
Allowable Subject Matter
Claims 10, 11 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
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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YOSHIHISA . ISHIZUKA
Examiner
Art Unit 2857
/YOSHIHISA ISHIZUKA/Primary Examiner, Art Unit 2857
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