DETAILED ACTION
Claims 1-20 are pending in the 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 .
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.
Examiner’s Notes
The Examiner cites particular sections in the references as applied to the claims below for the convenience of the applicant(s). Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested that, in preparing responses, the applicant(s) fully consider the references in their entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the Examiner.
Claim Objections
Claims 5, 6, 13, and 20 are objected to because of the following informalities:
Claim 5: “the one” (line 2) should have been –one—.
Claim 6: “the results” (line 5) should have been –results—.
Claim 13: “the results” (line 5) should have been –results—.
Claim 20: “the results” (line 5) should have been –results—.
Appropriate corrections are required. Applicant is advised to review the entire claims for further corrections.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-4, 6-10, and 14-17 are rejected under 35 U.S.C. 103 as being unpatentable over Nagpal et al. (US 2010/0324751 A1; hereinafter Nagpal) in view of Nanda et al. (US 2018/0260253 A1; Nanda).
With respect to claim 1, Nagpal teaches: A method residing as instructions on a non-transitory computer-readable medium, the instructions being configured to cause a processor to perform operations (see e.g. Nagpal, paragraphs 28-30) comprising:
receiving a request (see e.g. Nagpal, paragraph 34: “receives data operation requests”), the request being associated with a batch process for manipulating a dataset (see e.g. Nagpal, paragraph 34: “data operation requests, such as read, write, and delete operations, for the first data center 106 and the second data center 108 from the one or more clients 120”; and paragraph 36: “data is mirrored or replicated, it is available from both the first data center 106 and the second data center 108 over the data network 118, and both the first data center 106 and the second data center 108 are capable of fulfilling data operation requests”);
evaluating a set of requirements for executing the request (see e.g. Nagpal, paragraph 42: “customer may provide data center cooling efficiency factors like data storage device temperature information, ambient indoor temperature information, cost of electricity information, and data storage device efficiency information for the first data center 106 and the second data center 108 to the control module 102. The control module 102 may compare the customer provided information to select either the first data center 106 or the second data center 108”; and paragraph 34: “compares multiple data center cooling efficiency factors to determine whether to send the data operation requests to the first data center 106 or the second data center”)
entering the request… being associated with a hardware location physically hosting the dataset (see e.g. Nagpal, paragraph 34: “determine whether to send the data operation requests to the first data center 106 or the second data center 108”; and paragraph 37: “ the first data center 106 is located in Australia 114 and the second data center 116 is located in Greenland 116”); and
determining an optimum time… for executing the request (see e.g. Nagpal, paragraph 34: “By comparing multiple data center cooling efficiency factors, such as data storage device temperatures, ambient indoor data center temperature, cost of electricity, and data storage device efficiency, and the like, the control module 102 distributes data requests such that both data center operational costs and negative environmental effects are minimized”; paragraph 37: “first data center 106 and the second data center 108 are geographically separate, such that one or more data center cooling efficiency factors such as ambient temperature, cost of electricity, and the like, may be different between the first data center 106 and the second data center 108… control module 102 may use data center cooling efficiency factors such as these to determine whether to send the data operation request to the first data center 106 or the second data center 108”; and paragraph 51: “cost reduction module 212 compares sets of data center cooling efficiency factors with each other to select a data center to fulfill a data operation request for a client. Each set of data center cooling efficiency factors corresponds to a data center and represents operational cost statistics for the corresponding data center”; note that such statistical operational cost analysis for determining optimum location for executing the request inherently teaches time data associated with the optimum location).
Nagpal does not but Nanda teaches:
receiving a deadline by which the request must be executed (see e.g. Nanda, paragraph 42: “tasks 130 pertain to allocation of computing jobs for execution on multiple cloud resources, e.g., servers, the first rule and the second rule may be different job priorities… completion deadlines”; and paragraph 63: “rules may include rules for individual computing jobs, such as, a job execution deadline rule that may define an execution deadline time for an individual computing job”);
by the deadline (see e.g. Nanda, paragraph 42: “completion deadline”; and paragraph 63: “job execution deadline rule that may define an execution deadline time for an individual computing job”);
into a queue, the queue (see e.g. Nanda, paragraph 42: “job priorities (job request times, requester priorities, lengths of time in a queue”; note that determining a length of time a job is in a queue inherently discloses a queue that receives jobs)
within the deadline (within the deadline (see e.g. Nanda, paragraph 42: “completion deadline”; and paragraph 63: “job execution deadline rule that may define an execution deadline time for an individual computing job”)
Nagpal and Nanda are analogous art because they are in the same field of endeavor: job distribution to different data centers based on data center locations. Therefore, it would have been obvious to one with ordinary skill in the art before the effective filing date of the claimed invention to modify Nagpal with the teachings of Nanda. The motivation/suggestion would be to improve the efficiency of the job distribution and processing.
With respect to claim 2, Nagpal as modified teaches: The method of claim 1, wherein the optimum time is a time at the hardware location when power is cheapest (see e.g. Nagpal, paragraph 34: “By comparing multiple data center cooling efficiency factors, such as… cost of electricity… the control module 102 distributes data requests such that both data center operational costs and negative environmental effects are minimized”).
With respect to claim 3, Nagpal as modified teaches: The method of claim 1, wherein the optimum time is a time at the hardware location where asset loading is optimal (see e.g. Nagpal, paragraph 34: “By comparing multiple data center cooling efficiency factors, such as… data storage device efficiency, and the like, the control module 102 distributes data requests such that both data center operational costs and negative environmental effects are minimized”).
With respect to claim 4, Nagpal as modified teaches: The method of claim 1, wherein the optimum time is a time at the hardware location where heat rejection is optimal (see e.g. Nagpal, paragraph 34: “By comparing multiple data center cooling efficiency factors, such as data storage device temperatures, ambient indoor data center temperature… the control module 102 distributes data requests such that both data center operational costs and negative environmental effects are minimized”).
With respect to claim 6, Nagpal as modified teaches: The method of claim 4, further including:
quantifying at least one parameter selected from the set of parameters consisting of (see e.g. Nagpal, paragraph 34: “multiple data center cooling efficiency factors”): cost (see e.g. Nagpal, paragraph 34: “cost of electricity”), power (see e.g. Nagpal, paragraph 34: “cost of electricity”; and paragraph 2: “electricity needed to power a data center”), emissions (see e.g. Nagpal, paragraph 34: “data storage device temperatures, ambient indoor data center temperature”), latency (see e.g. Nagpal, paragraph 46: “network connection costs, network connection speeds”; and paragraph 59: “a data performance factor like latency”), and compute loading (see e.g. Nagpal, paragraph 34: “data storage device efficiency”); and
comparing the results with a baseline profile (see e.g. Nagpal, paragraph 60: “differentials maybe calculated relative to a default value or relative to another data center. The result may be an efficiency metric of one of the data centers. If the product of the differentials, the efficiency metric, is above a predetermined threshold, that may be a default value or a user defined value, the cost reduction module 212 may select a specific data center, otherwise the cost reduction module 212 may select a different data center”).
With respect to claims 7-10: Claims 7-10 are directed to a system comprising a processor and a memory including instructions to implement active functions corresponding to the method disclosed in claims 1-4, respectively; please see the rejections directed to claims 1-4 above which also cover the limitations recited in claims 7-10. Note that, Nagpal also discloses a system 104 comprising a processor and a memory (see Nagpal, paragraph 32-33; Fig. 1-2) to implement the method disclosed in claims 1-4.
With respect to claims 14-17: Claims 14-17 are directed to a non-transitory computer-readable medium having instructions to implement active functions corresponding to the method disclosed in claims 1-4, respectively; please see the rejections directed to claims 1-4 above which also cover the limitations recited in claims 14-17. Note that, Nagpal also discloses a system 104 comprising a processor and a memory (see Nagpal, paragraph 32-33; Fig. 1-2) to implement the method disclosed in claims 14.
Claims 5, 11-13, and 18-20 are rejected under 35 U.S.C. 103 as being unpatentable over Nagpal in view of Nanda as applied to claims 4, 7, and 14 above, and further in view of Miller et al. (US 9,864,727 B1; hereinafter Miller).
With respect to claim 5, Nagpal as modified teaches: The method of claim 4, further including:
Nagpal does not but Miller teaches:
comparing the one or more predictions with results from executing the request (see e.g. Miller, column 23, lines 60-63: “a DCS Load Balancer module improves its predictions over time by measuring actual usage in comparison to predicted demand”); and
adjusting, based on the results, one or more extrapolation factors concerning the request and the hardware location (see e.g. Miller, column 23, lines 49-63: “Such predictions may be made for specific times (e.g., the current time, an indicated time period, etc.), and in some cases may vary based on location or other characteristic (e.g., when the computing nodes of a group are geographically distributed, and requests from external computing systems are forwarded to geographically proximate group computing nodes)… adjusting future predictions to reflect discrepancies”).
Nagpal and Miller are analogous art because they are in the same field of endeavor: job distribution to different data centers based on data center locations. Therefore, it would have been obvious to one with ordinary skill in the art before the effective filing date of the claimed invention to modify Nagpal with the teachings of Miller. The motivation/suggestion would be to improve load balancing associated with job distribution.
With respect to claims 11-13: Claims 11-13 are directed to a system comprising a processor and a memory including instructions to implement active functions corresponding to the method disclosed in claims 5-6, respectively; please see the rejections directed to claims 5 and 6 above which also covers the limitations recited in claim 11-13.
With respect to claims 18-20: Claims 18-20 are directed to a non-transitory computer-readable medium having instructions to implement active functions corresponding to the method disclosed in claims 5-6, respectively; please see the rejection directed to claims 5 and 6 above which also covers the limitations recited in claims 18-20.
CONCLUSION
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Fletcher (US 2012/0030356 A1) discloses a resource management unit that allocates server resources for servicing a request based on energy costs factors such as power supplied to a server, heat generated at the server, power supplied to the cooling units associated with the server, a current workload of the server, an estimated increase in power consumption if resources of the server are allocated for servicing the request, etc. (see paragraph 13).
Pienta et al. (US 2014/0297043 A1) discloses a method and arrangement that allocates processing tasks to servers based on the location of the servers based on efficiency characteristics of the air conditioning units (see paragraph 8).
Contact Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Umut Onat whose telephone number is (571)270-1735. The examiner can normally be reached M-Th 9:00-7:30.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Kevin L Young can be reached at (571) 270-3180. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/UMUT ONAT/Primary Examiner, Art Unit 2194
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