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 Arguments
Applicant’s arguments with respect to claim(s) 1, 8, and 15 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Claim Rejections - 35 USC § 103
2. 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.
3. Claims 1-3, 8-10, 15, and 16 are rejected under 35 U.S.C. 103 as being unpatentable over DASH et al. Pub. No. US2024/0394097 A1 (hereafter DASH) in view of Villella et al. Pub. No. US 2020/0218572 (hereafter Villella) and Karstens Pub. No. US 2012/0023500 A1.
4. Regarding claim 1, DASH teaches “A computer implemented method for gradually altering compute resources allocated to workloads in a cloud computing environment ([Abs] teaches a method for incremental autoscaling of a compute cluster. [0033] teaches of the gradual downscaling of a cluster, gracefully removing nodes to not disrupt tasks executing on the nodes), comprising: determining, by a number of processors, a … increment by which to alter a current allocation of at least one of a set of compute resources allocated to at least one of a set of workloads in the cloud computing environment during a selected period of time to incrementally switch the current allocation of the at least one of the set of compute resources allocated to the at least one of the set of workloads in the cloud computing environment from an original allocation to a target allocation; and switching, by the number of processors, incrementally … the current allocation from the original allocation to the target allocation during the selected period of time ([0030-0031] teaches upscaling or downscaling to achieve a target cluster size based on an estimated resource usage from the current resource usage, incrementing by nodes, and then using a command to add/remove the nodes. It also mentions that compute nodes may be added one at a time or a plurality at a time such that it represents incremental scaling. [0063] teaches of a configurable window for selecting a timeframe, wherein the length of the time frame determines the aggressiveness of scaling, such that a smaller time frame would represent scaling in smaller increments and longer time frames may result in larger increments).
DASH teaches of incremental autoscaling with the upscaling/downscaling of nodes to achieve a target cluster size for meeting an estimated resource demand based on the actual resource utilization [0030-0031]. DASH however, does not explicitly teach a fixed percentage per increment by which to alter the current allocation of resources.
Villella teaches a cumulative growth rate such that it teaches the limitation of a fixed percentage, “comprising: determining, by a number of processors, a fixed percentage per increment by which to alter a current allocation … and switching, by the number of processors, incrementally by the fixed percentage per increment the current allocation from the original allocation to the target allocation during the selected period of time ([0074-0079] teaches a cumulative growth rate from one adapted resource component to another adapted resource component over a time interval such that it would require the first adapted resource component to increment/decrement at that first fixed growth rate defined to attain the target resource component, being the second adapted resource component. Also see Figures 5A-5B, 6A-6B. Also, the graph shows a cumulative growth rate, such that it depends on the number of increments to determine what the fixed percentage was per increment (e.g. cumulative growth rate of 5% from 80000 to 84000 could have been 5 increments at 1% growth rate).”
It would have been obvious to a person of ordinary skill in the art before the effective
filing date to combine the teachings of Villella with the invention of DASH for providing a fixed percentage of growth/decay per increment when gradually altering compute resources. A person having ordinary skill in the art would have been motivated to make this combination for implementing finer increments at higher frequencies to reduce overhead costs [DASH 0036].
DASH teaches a configurable window which may determine the aggressiveness of the resource scaling that is to occur, however does not explicitly teach of the time window divided into time intervals corresponding to an increment of increments when that scaling occurs.
Villella teaches of time intervals for the dynamic resource allocation to take place such that it teaches the limitation “wherein the selected period of time is divided into a number of intervals, and wherein each time interval from the number of time intervals corresponds to an increments from the increments for switching the current allocation; and switching … the current allocation from the original allocation to the target allocation during the selected period of time, … ([0056] teaches a plurality of time intervals associated with adapted resources that require growing/decaying based on the growth rate. [0074-0079] teaches a growth rate for each predetermined time interval such that each time interval corresponds to a growth rate from the plurality of growth rates)”.
It would have been obvious to a person of ordinary skill in the art before the effective
filing date to combine the teachings of Villella with the invention of DASH for providing a time interval associated with an increment value for altering the compute resources. A person having ordinary skill in the art would have been motivated to make this combination to be able to define a rollout pattern over time for the resources such as a constant or variable rollout [Villella 0056]. Together, Villella in combination with DASH teach every limitation of the claimed invention. Since the teachings were analogous art known at the filing time of the invention, one of ordinary skill could have applied said teachings to achieve expected results.
The combination may not explicitly teach that the fixed percentage per increment remains constant for all time intervals during the selected period of time.
Karstens teaches a constant percentage per increment such that it teaches the limitation “wherein current allocation of the at least one of a set of compute resources allocated to at least one of a set of workloads in the cloud computing environment is adjusted based on the fixed percentage per increment for each increment, wherein the fixed percentage per increment remains constant for all time intervals from the number of time intervals during the selected period of time ([0030-0035] teaches a boost feature, wherein over a predetermined time interval, the boost can increase by a preset amount or percentage in a step wise manner until a maximum boost. It also teaches that the boost does not have to gradually scale up; it may increase normally such that it may remain constant until a threshold is reached. It also teaches of a static boost, being a preset amount or level of boost by which the boost may be increased after a time interval or each of a series of predetermined time intervals such that the same level of boost may be applied at each of a series of predetermined time intervals. Also see [0050-0052] & Fig. 5A-5D for an example boost, wherein it shows that web page #3 is given a boost, from 20% to 50%, and then 50% to 80% over respective time intervals, wherein the change remained constant for each of the time intervals at a boost of 30% showing that a constant change over time is possible).”
It would have been obvious to a person of ordinary skill in the art before the effective
filing date to incorporate the teaching of Karstens to the combination of DASH and Villella for applying a constant percentage of compute resources allocated per time interval of time intervals. A person having ordinary skill in the art would have been motivated to make this combination in order to allow for the gradual allocation of resources, efficiently completing a task (Karstens [0032]) while maintaining stability within the system. Together, Karstens in combination with DASH and Villella, teach every limitation of the claimed invention. Since the teachings were analogous art known at the filing time of the invention, one of ordinary skill could have applied said teachings to achieve expected results.
5. Regarding claim 8, it is similar to claim 1 and is rejected for the same reasons. Claim 8 is directed towards “A computer system comprising: a number of processor units, wherein the processor executes program instructions (DASH [0085])”.
6. Regarding claim 15, it is similar to claim 1 and is rejected for the same reasons. Claim 15 is directed towards “A computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a computer system (DASH [0107-0108])”.
7. Regarding claim 2, wherein the combination, DASH teaches “The computer implemented method of claim 1, wherein the set of compute resources comprises at least one of central processing units, volatile memory, and persistent memory ([0054]).”
8. Regarding claim 9, it is similar to claim 2, and is rejected for the same reasons.
9. Regarding claim 3, wherein the combination, Villella teaches “The computer implemented method of claim 1, wherein a roll out window comprises the selected period of time ([0033 & 0056] teaches predetermined time intervals for resource allocation)”.
10. Regarding claims 10 and 16, they are similar to claim 2 and are rejected for the same reasons.
11. Claims 4-6, 11-13, and 17-19 are rejected under 35 U.S.C. 103 as being unpatentable over DASH, Villella, and Karstens as used in claim 1 above, and in further view of Harjono et al. Pat. No. US 11,461,150 B1 (hereafter Harjono).
12. Regarding claim 4, the combination teaches incremental scaling of resources within a time interval, however does not explicitly define discrete time notch steps per increment.
Harjono teaches incremental scaling of nodes such that it teaches the limitation “The computer implemented method of claim 1, wherein switching incrementally by the fixed percentage per increment defines a plurality of discrete notch steps ([Col. 14, line 53 – Col. 16, line 36] & Fig. 9 teaches that over a defined time interval, there may be the scaling in or out of nodes based on tasks, and as seen in Figure 9 or Figure 13, the cluster size was scaled out and done so in increments defined by a timestamp such that there are steps defined for scaling out).
It would have been obvious to a person of ordinary skill in the art before the effective
filing date to combine the teachings of Harjono with the invention of DASH and Villella for providing a discrete time per increment. A person having ordinary skill in the art would have been motivated to make this combination for showing the number of increments taken to achieve the target. Together, Harjono in combination with DASH, Villella, and Karstens teach every limitation of the claimed invention. Since the teachings were analogous art known at the filing time of the invention, one of ordinary skill could have applied said teachings to achieve expected results.
13. Regarding claims 11 and 17, they are similar to claim 4 and are rejected for the same reasons.
14. Regarding claim 5, the current combination does not explicitly teach a uniform constant time interval when switching.
Harjono teaches a periodic increment feature that if implemented, may teach the limitation “The computer implemented method of claim 1, wherein switching is performed at substantially constant time intervals (Harjono [Col. 12 line 44 – 64] teaches periodic incremental adjustments over a time period such that the incrementing is done in a constant, predictable manner).”
It would have been obvious to a person of ordinary skill in the art before the effective
filing date to combine the teachings of Harjono with the invention of DASH, Villella, and Karstens for providing switching over a constant period of time. A person having ordinary skill in the art would have been motivated to make this combination for providing a predictable change in resources, possibly reducing oscillation, minimizing disruptions.
15. Regarding claims 12 and 18, they are similar to claim 5 and are rejected for the same reasons.
16. Regarding claim 6, the combination teaches “The computer implemented method of claim 1, wherein switching is performed at uneven time intervals ([Harjono Fig. 9 and 13] show increments occurring at non-even times such that there is no constant predetermined time for each increment. This may also be true for DASH and Villella as they do not explicitly show when the increments occur, only that it happens to achieve the target).”
17. Regarding claims 13 and 19, they are similar to claim 6 and are rejected for the same reasons.
18. Claims 7, 14, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over DASH, Villella, and Karstens as used in claim 1 above, and in further view of Mathur et al. Pub. No. US 2020/0371896 A1 (hereafter Mathur).
19. Regarding claim 7, the combination does not explicitly teach that the fixed percentage is defined by r = ln(target allocation) – ln(original allocation).
Mathur teaches using exponential decay in forecasting resource usage, wherein the forecasted result is used in response to changes in a computing environment requiring more resources to be allocated, possibly preventing service downtime [0029]. Also in [0069-0079], Figures 6-10, it teaches applying the exponential functions to improve forecasting behavior compared to a linear approach showing a smooth out transition of resource usage.
It would have been obvious for a person of ordinary skill in the art before the effective
filing date to try to combine the exponential teachings of Mathur with the gradual incremental autoscaling of compute resource of DASH, Villella, and Karstens to obtain more gradual transition of resources, possibly reducing task disruptions from possible resource waste. A person having ordinary skill in the art could have pursued the known ways to implement the feature with a reasonable expectation of success as it would have been obvious to try.
20. Regarding claims 14 and 20, they are similar to claim 7 and are rejected for the same reasons.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to BRANDON A NGUYEN whose telephone number is (571)272-6074. The examiner can normally be reached Mon-Fri (10am-6pm).
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, Aimee Li can be reached at (571) 272-4169. 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.
/BRANDON NGUYEN/Examiner, Art Unit 2195
/Aimee Li/Supervisory Patent Examiner, Art Unit 2195
