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 Arguments
Applicant argued that Hotchkies in view of Chaysinh failed to disclose deploying various virtualized elements in a network. Sinha is introduced to teach these elements.
The double patenting rejection is withdrawn on the filing of the terminal disclaimers.
The objection to the specification was not addressed, and is maintained.
Specification
The disclosure is objected to because of the following informalities: The specification should be updated to reflect the current status of all co-pending applications.
Appropriate correction is required.
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) 1-2, 4-9, and 11-13 are rejected under 35 U.S.C. 103 as being unpatentable over Hotchkies et al. (US 2019/0109926) in view of Chaysinh et al. (US 2021/0194988) in view of Sinha et al. (US 2022/0004417).
In regard to claim 1, Hotchkies disclosed:
aggregating historical request data for a plurality of requests; Hotchkies [0017]
training a machine learning model based on the aggregated historical request data; Hotchkies [0017]
generating, from the trained machine learning model, … Hotchkies [0018]
based on the generated predicted location, identifying an edge node (a subset of content serving devices), from a plurality of edge nodes (content serving devices), based on a physical location of the edge node; and Hotchkies [0018]
based on the generated predicted type of computing service and the predicted time, allocating computing resources for the computing service on the identified edge node. Hotchkies [0018] (pre-caching at least some content that were requested by the cluster of requests in anticipation of similar future requests routed their way)
Hotchkies failed to disclose a prediction for a type of computing service to be requested at a predicted time and a predicted location.
However, Chaysinh disclosed a prediction for a type of computing service to be requested at a predicted time and a predicted location. Chaysinh [0025] disclosed using machine learning techniques to predict which services will be most requested…at different edge locations…at different times.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to predict services requested at specific locations and times in Hotchkies so that the proper resources could be allocated in Hotchkies at the proper location and time, therefore conserving network resources.
Hotchkies and Chaysinh failed to disclose wherein allocating the computing resources comprises performing at least one of:
deploying a virtualized software;
deploying a virtualized instance;
deploying a virtualized machine;
deploying a virtualized infrastructure; or
deploying a virtualized container.
However, Sinha disclosed wherein allocating the computing resources comprises performing at least one of:
deploying a virtualized software;
deploying a virtualized instance;
deploying a virtualized machine;
deploying a virtualized infrastructure; or
deploying a virtualized container.
See Sinha [0022], which discloses deploying virtual machines, upgrading virtualized infrastructure (deploying a virtualized infrastructure), and deploying logical network services (deploying a virtualized software or container).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to deploy virtualized machines or services or infrastructure in Hotchkies / Chaysinh’s combination since Hotchkies dealt with routing content requests in a content distribution network and Sinha disclosed deploying the logical network portion of a network, which would be utilized in a content distribution network when routing content in said content distribution network.
In regard to claim 2, Hotchkies disclosed the machine learning model is at least one of a decision tree, a random forest, a neural network, a continual learning model, or a deep learning model. Hotchkies [0020] (the model can be a supervised learning model (e.g., a decision tree or artificial neural network)…)
In regard to claim 4, Hotchkies disclosed identified edge node includes at least one of a server, a graphics processing unit (GPU), a central processing unit (CPU), or a field-programmable gate array (FPGA). Hotchkies [0017]
In regard to claim 5, Hotchkies disclosed:
receiving, from a computing device, a request for the predicted service type at the predicted time; and Hotchkies [0018]-[0019]
performing, by the identified edge node, the requested service with the allocated computing resources. Hotchkies [0018]-[0019]
In regard to claim 6, Hotchkies disclosed the computing device is one of a smart phone, laptop, vehicle, drone, a mobile computer, or a plane. Hotchkies [0030]
Claim 7 is rejected for substantially the same reasons as claim 1.
In regard to claim 8, Hotchkies disclosed the historical request data includes at least the following data for a plurality of requests: a time of the request, a location of the device from where the request originated, and a type of service being requested. Hotchkies [0017]
Claim 9 is rejected for substantially the same reasons as claim 2.
Claim 11 is rejected for substantially the same reasons as claim 4.
Claim 12 is rejected for substantially the same reasons as claim 5.
Claim 13 is rejected for substantially the same reasons as claim 6.
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Jeffrey R. Swearingen whose telephone number is (571)272-3921. The examiner can normally be reached M-F 8:00 am - 5:00 pm.
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Jeffrey R. Swearingen
Primary Examiner
Art Unit 2445
/Jeffrey R Swearingen/Primary Examiner, Art Unit 2445
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