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 .
Claim Objections
Claims 7 and 15 are objected to because of the following informalities:
Claims 7 and 15 disclose “based on a value associated with the second minimum cost device being greater as a value associated with the first minimum cost device” (emphasis added). The phrase “greater as” is grammatically incorrect and confusing. It should likely be amended to “greater than.”
Claim Rejections - 35 USC § 102
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 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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless -
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-3, 8-11, and 16-18 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by RAMESH (US 11,548,473, hereinafter RAMESH).
Regarding claim 1, RAMESH discloses
An apparatus for controlling a vehicle, the apparatus comprising (col. 7, lines 12-15: the computing system 100 can control operation of the autonomous vehicle by controlling, for example, acceleration, braking, steering, parking, etc. of the autonomous vehicle):
a memory configured to store at least one instruction; and a control device operatively connected to the memory, wherein the at least one instruction, when executed by the control device, cause the apparatus to (col. 7, lines 33-35: A multi-chip device can include a number of different memory devices 123, 125; col. 9, lines 56-58: the host 102 includes one or more central processors that execute instructions to control operation of an autonomous vehicle):
generate profiling data comprising an access count of each of a plurality of sections, wherein the plurality of sections are associated with at least one task performed for an operation control of the vehicle (col. 10, lines 18-22: The processor 122 can perform operations to monitor and/or determine characteristics of workloads… The characteristics can include information such as… access frequency; col. 5, lines 45-47: Access frequency of the data can refer to a quantity of accesses (e.g., reads, writes, etc.) involving the data in execution of the workloads; Note: Under BRI, RAMESH teaching of monitoring the quantity of accesses of data involved in a workload maps to generating profiling data comprising an access count of each of a plurality of sections associated with a task);
determine, based on the profiling data, a priority for each of the plurality of sections (col. 5, lines 47-48: Access frequency of the data can be referred to herein in terms of “hot data” and “cold data”; col. 15, lines 7-9: the controller 220 can determine that cold data and/or data corresponding to lower priority applications are running; Note: Under BRI, RAMESH teaching of classifying data into “hot data” or “cold data” tiers based on the access frequency (the profiling data), and correlating this to lower priority applications, constitutes determining a priority for each of the plurality of sections);
sequentially assign, based on the priority, the plurality of sections to one or more of a plurality of storage devices included in the memory (col. 18, lines 7-9: data that is classified as hot data can be written to the SLC portion 335 while data that is classified as cold data can be written to the TLC portion 337; col. 5, lines 15-18: cause at least a portion of the data corresponding to one or more of the workloads to be written to a memory device that is characterized by a faster memory access time; Note: Under BRI, a processor executing instructions to write distinct data classifications (e.g., hot data to a fast memory device, and cold data to a slower memory device) inherently performs the assignment sequentially in time (i.e., processing one data section/instruction after another)); and
output, based on the sequentially assigned plurality of sections, a signal for the operation control of the vehicle (col. 10, lines 60-67: If it is determined that current operator of the vehicle is not the authorized operator of the vehicle, the processor 122 can transmit a notification to the authorized operator of the vehicle and/or disable the vehicle … if it is determined that the current operator of the vehicle is the authorized operator of the vehicle, the processor 122 can allow continued operation of the vehicle; Note: Under BRI, RAMESH teaching of outputting commands to disable the vehicle or allow continued operation of the vehicle constitutes outputting a signal for the operation control of the vehicle).
Regarding claim 9 referring to claim 1, RAMESH discloses A method for controlling a vehicle, the method comprising: … (See the rejection for claim 1).
Regarding claim 16 referring to claim 1, RAMESH discloses A non-transitory computer-readable recording medium including a program for executing a method, the method comprising: … (col. 14, lines 26-29: The memory devices 223, 225, and 227 can be configured to read, write, and/or store data, such as GPS data, base station data, and/or internal sensor data corresponding to one or more workloads executed by the computing system 20).
Regarding claims 2, 10, and 17, RAMESH discloses
wherein the at least one instruction, when executed by the control device, cause the apparatus to: determine, based on a level of the access count, the priority for each of the plurality of sections. (col. 5, lines 45-51: Access frequency of the data can refer to a quantity of accesses (e.g., reads, writes, etc.) involving the data… “Cold data,” as used herein, means that a particular memory object has not been accessed for a long duration relative to other memory objects… “Hot data,” as used herein, means that a particular memory object has been accessed frequently relative to other memory objects; col. 15, lines 7-9: the controller 220 can determine that cold data and/or data corresponding to lower priority applications are running; Note: Under BRI, RAMESH teaching of evaluating the quantity of accesses or how frequently a memory object is accessed (the level of the access count) to classify data as “hot data” or “cold data” (which corresponds to lower priority applications), constitutes determining, based on a level of the access count, the priority for each of the plurality of sections).
Regarding claims 3, 11, and 18, RAMESH discloses
wherein the at least one instruction, when executed by the control device, cause the apparatus to: generate, based on the profiling data, a table comprising the priority; and determine, based on the table, a section for traversal among the plurality of sections col. 13, lines 15-18: the set of SLCs can be configured to store a look-up table to facilitate writing of at least the portion of the data to the other of the first memory device 123 or the second memory device 125; col. 18, lines 39-48: The look-up table can be a data structure that contains indexing information … the look-up table can facilitate writing of at least a portion of data involved in a workload to one of the memory devices described herein; Note: Under BRI, RAMESH teaching of utilizing a “look-up table” containing indexing information to facilitate the writing and routing of data portions to specific memory devices, where the routing is based on the data being prioritized as “hot” or “cold” from the profiling data, as established in Claim 1, maps to generating a table comprising the priority. Furthermore, using this table to facilitate the writing of a portion of data inherently requires identifying and accessing that specific data portion, which maps to determining, based on the table, a section for traversal among the plurality of sections).
Regarding claim 8, RAMESH discloses
further comprising: a communication device (col. 9, lines 22-30: The ECU 101 can further include a radio-frequency integrated circuit (RFIC) 111 … facilitate communications between an autonomous vehicle… a base station… and/or other autonomous vehicles),
wherein the at least one instruction, when executed by the control device, cause the apparatus to: receive, based on the communication device and from an outside of the apparatus, additional profiling data regarding the plurality of sections (col. 10, lines 46-47: information received from a global positioning satellite (GPS); and information received from a base station; col. 22, lines 20-22: receipt of information from other autonomous vehicles on the road and/or from base stations; Note: Under BRI, RAMESH teaching of utilizing the RFIC (i.e., communication device) to receive data/information from external sources such as a GPS, base station, or other vehicles (i.e., from an outside of the apparatus) to be processed by the system maps to receiving additional profiling data regarding the plurality of sections); and
determine, based on the additional profiling data, a priority for each of the plurality of sections (col. 12, lines 30-38: The processor 122 can process information received from a GPS… a base station… The processor 122 can determine characteristics of the workload; col. 12, lines 48-51: The processor 122 can determine, based on the characteristics of the workload, whether to write at least a portion of data associated with the workload to the other of the first memory device 123 or the second memory device 125; Note: Under BRI, RAMESH teaching of processing the externally received information as a workload, determining the characteristics of that workload, and using those characteristics to decide which memory tier (e.g., hot/cold, fast/slow) to assign the data to constitutes determining a priority for each of the plurality of sections based on the additional profiling data).
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 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 of this title, 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
Claims 4-7, 12-15, 19, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over RAMESH (US 11,548,473, hereinafter RAMESH) in view of KANSAL et al. (US 2012/0317578, hereinafter KANSAL).
Regarding claims 4, 12, and 19, RAMESH discloses
wherein the at least one instruction, when executed by the control device, cause the apparatus to: determine, based on a first size of a first section of the plurality of sections, a first minimum cost device among the plurality of storage devices for the first section, … (col. 3, line 65-col. 4, line 1: An amount of computing resources (e.g., processing resources and/or memory resources) consumed in execution of an application can be measured in terms of a “workload”; col. 5, lines 21-34: optimizing execution of the workload by utilizing memory devices and/or media types that exhibit different memory capacities versus bandwidth capabilities. For example, a memory device that exhibits high capacity but low bandwidth… can be utilized for execution of some types of workloads… while a memory device that exhibits high bandwidth but low capacity … can be utilized… optimize an amount of time, processing resources, and/or power consumed); and
assign the first section to the first minimum cost device. (col. 5, lines 15-18: cause at least a portion of the data corresponding to one or more of the workloads to be written to a memory device that is characterized by a faster memory access time; col. 5, lines 57-59: such data can be written to a memory device that includes a media type that is well suited for making data quickly accessible; Note: Under BRI, RAMESH teaching of writing the data corresponding to the workload to the selected optimized memory device constitutes assigning the first section to the first minimum cost device).
RAMESH does not disclose wherein the first size corresponds to a first rank among the plurality of sections. KANSAL discloses wherein the first size corresponds to a first rank among the plurality of sections (paragraph [0023]: the available processor time is partitioned according to a ratio between a processor time requirement of one of the matching tasks and a processor time requirement for the other matching task; paragraph [0031]: the assignment mechanism 108 allocates an amount of each available resource in proportion to a ratio of resource requirements between the two or more matching tasks; Note: Under BRI, KANSAL teaching of evaluating the resource requirements (the size of the workload) of tasks and allocating resources based on a ratio/proportion maps to the first size corresponding to a first rank among the plurality of sections). It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify the memory optimization method of RAMESH to include the proportional ranking of resource requirements as taught by KANSAL. The motivation would have been to ensure that available computing resources are partitioned efficiently and proportionally based on the exact size of the incoming workloads, thereby preventing system bottlenecks and improving overall resource utilization efficiency (KANSAL, paragraphs [0024] and [0037]).
Regarding claims 5, 13, and 20, RAMESH discloses
wherein the at least one instruction, when executed by the control device, cause the apparatus wherein the at least one instruction, when executed by the control device, cause the apparatus to: … determine a storage device, of the first group of storage devices, as the first minimum cost device, wherein an access cycle of the storage device is smallest among the first group of storage devices (col. 5, lines 15-19: cause at least a portion of the data corresponding to one or more of the workloads to be written to a memory device that is characterized by a faster memory access time than another memory device associated with the autonomous vehicle; col. 11, line 67-col. 12, line 5: re-allocate the computing resources between the first memory device 123 and the second memory device 125 such that greater than a threshold amount of computing resources that exhibit a higher bandwidth, a faster memory access time, and/or a lower latency … are available; Note: Under BRI, RAMESH teaching of selecting a memory device from the available options specifically because it exhibits a “faster memory access time” and/or “lower latency” maps directly to determining a storage device where the “access cycle of the storage device is smallest.”).
RAMESH does not disclose determine a first group of storage devices of the plurality of storage devices, wherein each storage device of the first group has a storage capacity that is greater than the first size. KANSAL discloses determine a first group of storage devices of the plurality of storage devices, wherein each storage device of the first group has a storage capacity that is greater than the first size (paragraph [0044]: the assignment mechanism 108 selects the server having a highest available amount of one or more resources … the matching tasks are assigned to the server such that a sum total of resource requirements equals or falls below a total available amount (i.e., capacity) of the one or more resources; paragraph [0049]: The assignment mechanism 108 selects one or more servers having a highest number of resources that can provide the required amount to execute the new jobs; Note: Under BRI, KANSAL’s teaching of identifying and selecting a group of resources/servers that have a total available capacity that is greater than or equal to the required amount (size) of the workload maps to determining a first group of storage devices having a storage capacity greater than the first size). It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify the memory allocation method of RAMESH to include the capacity-checking and filtering steps as taught by KANSAL. The motivation would have been to ensure that available computing resources are partitioned efficiently and proportionally based on the exact size of the incoming workloads, thereby preventing system bottlenecks and improving overall resource utilization efficiency (KANSAL, paragraphs [0024] and [0037]).
Regarding claims 6 and 14, RAMESH discloses
wherein the at least one instruction, when executed by the control device, cause the apparatus to: determine, based on a second size of a second section of the plurality of sections, a second minimum cost device among the plurality of storage devices for the second section, (col. 5, lines 9-18: if the computing system is deployed in an autonomous vehicle, available computing resources of the computing device may be strained when multiple demanding workloads are executed concurrently. Accordingly, in order to optimize resource consumption … cause at least a portion of the data corresponding to one or more of the workloads to be written to a memory device that is characterized by a faster memory access time; col. 5, lines 21-23: optimizing execution of the workload by utilizing memory devices and/or media types that exhibit different memory capacities).
RAMESH does not disclose wherein the second size corresponds to a second rank among the plurality of sections; compare, based on a value associated with the second minimum cost device being the same as a value associated with the first minimum cost device, a sum of the first size and the second size with a first storage capacity of the first minimum cost device; and assign, based on the sum being smaller than the first storage capacity, the second section to the first minimum cost device. KANSAL discloses wherein the second size corresponds to a second rank among the plurality of sections; compare, based on a value associated with the second minimum cost device being the same as a value associated with the first minimum cost device, a sum of the first size and the second size with a first storage capacity of the first minimum cost device; and assign, based on the sum being smaller than the first storage capacity, the second section to the first minimum cost device (paragraph [0031]: the assignment mechanism 108 allocates an amount of each available resource in proportion to a ratio of resource requirements between the two or more matching tasks; Paragraph [0044]: the matching tasks are assigned to the server such that a sum total of resource requirements equals or falls below a total available amount (i.e., capacity) of the one or more resources; Note: Under BRI, KANSAL’s teaching of allocating resources based on a “ratio of resource requirements” maps to the second size corresponding to a second rank. Furthermore, KANSAL explicitly teaches the mathematical step of calculating a “sum total” of the resource requirements (i.e., the first and second size) and comparing it to ensure it “falls below a total available amount” (i.e., capacity) prior to assigning the tasks to the same resource). It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify the memory optimization method of RAMESH to include the proportional ranking and the explicit sum-to-capacity comparison steps as taught by KANSAL. The motivation would have been to ensure that available computing resources are partitioned efficiently and proportionally based on the exact size of the incoming workloads, thereby preventing system bottlenecks and improving overall resource utilization efficiency (KANSAL, paragraphs [0024] and [0037]).
Regarding claims 7, RAMESH discloses
wherein the at least one instruction, when executed by the control device, cause the apparatus to: determine, based on a second size of a second section of the plurality of sections, a second minimum cost device for the second section, wherein the second size corresponds to a second rank among the plurality of sections; compare, based on a value associated with the second minimum cost device being the same as a value associated with the first minimum cost device, a sum of the first size and the second size with a first storage capacity of the first minimum cost device (col. 5, lines 9-12: if the computing system is deployed in an autonomous vehicle, available computing resources of the computing device may be strained when multiple demanding workloads are executed concurrently; col. 14, lines 40-44: the controller 220 can ensure that there are adequate computing resources and/or memory resources available to the memory device(s) 223, 225, and/or 227 with which the authentication operation will be performed; Note: As mapped in the rejection of Claim 6 above, RAMESH teaches evaluating multiple concurrent workloads, and KANSAL teaches the proportional ranking of those workloads and comparing the sum total of their resource requirements against the available capacity of the target device).
RAMESH does not disclose exclude, based on a value associated with the second minimum cost device being greater as a value associated with the first minimum cost device, the first minimum cost device from the plurality of storage devices and assign the second section to the second minimum cost device. KANSAL discloses exclude, based on a value associated with the second minimum cost device being greater as a value associated with the first minimum cost device, the first minimum cost device from the plurality of storage devices and assign the second section to the second minimum cost device (Paragraph [0050]: Step 710 represents a determination as to whether any of the resources on any of the one or more servers is overloaded given the assignment of the new jobs… If one or more of the resources is overloaded, step 712 is performed where one or more corresponding allocations are modified to accommodate the new jobs; Note: Under BRI, KANSAL teaches that if the sum of the requirements is too great (i.e., the resource is “overloaded” because the required value is greater than the available capacity), the system excludes that initial allocation and modifies the assignment to route the job to a different, available resource (the second minimum cost device). It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify the memory optimization method of RAMESH to include the capacity-checking and reassignment steps as taught by KANSAL. The motivation would have been to ensure that available computing resources are partitioned efficiently and proportionally based on the exact size of the incoming workloads, thereby preventing system bottlenecks and improving overall resource utilization efficiency (KANSAL, paragraphs [0024] and [0037]).
Regarding claims 15, RAMESH discloses
Further comprising: determining, based on a second size of a second section of the plurality of sections, a second minimum cost device for the second section, wherein the second size corresponds to a second rank among the plurality of sections; comparing, based on a value associated with the second minimum cost device being the same as a value associated with the first minimum cost device, a sum of the first size and the second size with a first storage capacity of the first minimum cost device (col. 5, lines 9-12: if the computing system is deployed in an autonomous vehicle, available computing resources of the computing device may be strained when multiple demanding workloads are executed concurrently; col. 14, lines 40-44: the controller 220 can ensure that there are adequate computing resources and/or memory resources available to the memory device(s) 223, 225, and/or 227 with which the authentication operation will be performed; Note: As established in Claim 14, under BRI, RAMESH teaching of evaluating multiple concurrent workloads and ensuring that a specific desired memory device has “adequate memory resources available” to hold the data inherently requires comparing the total combined size of the incoming data workloads (i.e., the sum of the first size and second size) against the total available storage capacity of that memory device); or ….
RAMESH does not disclose excluding, based on a value associated with the second minimum cost device being greater as a value associated with the first minimum cost device, the first minimum cost device from the plurality of storage devices and assigning the second section to the second minimum cost device. KANSAL discloses excluding, based on a value associated with the second minimum cost device being greater as a value associated with the first minimum cost device, the first minimum cost device from the plurality of storage devices and assigning the second section to the second minimum cost device (Paragraph [0050]: Step 710 represents a determination as to whether any of the resources on any of the one or more servers is overloaded given the assignment of the new jobs… If one or more of the resources is overloaded, step 712 is performed where one or more corresponding allocations are modified to accommodate the new jobs; Note: Under BRI, KANSAL teaches that if the sum of the requirements is too great (i.e., the resource is “overloaded” because the required value is greater than the available capacity), the system excludes that initial allocation and modifies the assignment to route the job to a different, available resource (the second minimum cost device). It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to modify the memory optimization method of RAMESH to include the capacity-checking and reassignment steps as taught by KANSAL. The motivation would have been to ensure that available computing resources are partitioned efficiently and proportionally based on the exact size of the incoming workloads, thereby preventing system bottlenecks and improving overall resource utilization efficiency (KANSAL, paragraphs [0024] and [0037]).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure.
Mo et al. (US 2024/0386442) discloses adaptive data management in an edge computing environment, including determining data criticality and data quality to reduce resource requirements for sustainable storage (paragraphs [0041] and [0144]).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SISLEY N. KIM whose telephone number is (571)270-7832. The examiner can normally be reached M-F 11:30AM -7:30PM.
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/SISLEY N KIM/Primary Examiner, Art Unit 2196 9/14/2026
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