DETAILED ACTION
Statement of claims
The present amended application includes:
Claims 1 and 4-5 were amended.
Claims 6-7 were added.
Claims 1-7 remain pending in the application. Claims 1-7 are being considered on the merits.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 10/23/2023, 02/28/2024, 11/18/2024. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Priority
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). The certified copy has been filed on 10/23/2023. However, Should applicant desire to obtain the benefit of foreign priority under 35 U.S.C. 119(a)-(d) prior to declaration of an interference, a certified English translation of the foreign application must be submitted in reply to this action. 37 CFR 41.154(b) and 41.202(e).
Failure to provide a certified translation may result in no benefit being accorded for the non-English 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 .
Specification
The title of the invention is not descriptive. A new title is required that is clearly
indicative of the invention to which the claims are directed.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-7 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
As to per claims 1 and 5 , it is not clearly understood what is meant by "..enters an operation state..." and "…enters a stop state...", ", since it’s not known which element "enters" refers to.
Applicant can make corrections in this claim in response to this office action.
Dependent claims 2--4 and 6-7 are affected by the rejections of claims 1 and 5 above.
Double Patenting
Claims 1 and 5 are provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1 and 4 of copending Application No. 18/287,914 in view of with Hoshihara et al.( US 2013/0218402). Although the claims at issue are not identical, they are not patentably distinct from each other . See below for a detail comparison and explanation:
Current Application 18/287,914
copending Application 18/287,892
1.(Currently Amended) A management system that manages grid computing processing of causing an arithmetic device that is available among a plurality of arithmetic devices, each of which is mounted on a vehicle, enters an operation state when the vehicle is traveling, and enters a stop state when a power supply ofthe vehicle is turned off, to process job data, the management system comprising:
a memory ; and a controller, wherein the memory unit memorizes has stored therein calculation capability information indicating a calculation capability of each of the plurality of arithmetic devices and operation status information indicating an operation status of each of the plurality of arithmetic devices, and the controller performs, prediction processing of predicting a temporal change in the calculation capability available in the grid computing processing of each of the plurality of arithmetic devices on a basis of the calculation capability information and the operation status information, and
job acceptance processing of accepting the job data requested for calculation by a client
matching processing of allocating the arithmetic device available in the grid computing processing among the plurality of arithmetic devices to the job data accepted in the job acceptance processing on a basis of a result of the prediction processing.
1. (Currently Amended) A management system that manages grid computing processing of causing an arithmetic device that is available among a plurality of arithmetic devices , each ofwhich is owned by a user, ismounted on avehicle, enters anoperation state when the vehicle is traveling, and enters a stop state when a power supply ofthe vehicle is turned off, to process job data, the management system comprising:
a memory ; and a controller, wherein the memory memorizes has stored therein calculation capability information indicating a calculation capability of each of the plurality of arithmetic devices and operation status information indicating an operation status of each of the plurality of arithmetic devices, and the controller performs prediction processing of predicting a temporal change in the calculation capability available in the grid computing processing of each of the plurality of arithmetic devices on a basis of the calculation capability information and the operation status information,
selection processing of presenting a job list that introduces a plurality of jobs to the user and allowing the user to select the job for which the calculation capability of the arithmetic device owned by the user is desired to be provided from the jobs introduced by the job list, and
matching processing of allocating, to the job data corresponding to the job selected by the user in the selection processing among the plurality of jobs, the arithmetic device that is available in the grid computing processing and is owned by the user among the plurality of arithmetic devices on a basis of a result of the prediction processing and a result of the selection processing.
5.(Currently Amended) A management method of managing, by a computer, grid computing processing of causing an arithmetic device that is available among a plurality of arithmetic devices, each of which is mounted on a vehicle, enters an operation state when the vehicle is traveling, and enters a stop state when a power supply of the vehicle is turned off, to process job data, the management method comprising:
a prediction step of predicting, by the computer, a temporal change in a calculation capability available in the grid computing processing of each of the plurality of arithmetic devices on a basis of calculation capability information indicating the calculation capability of each of the plurality of arithmetic devices and operation status information indicating an operation status of each of the plurality of arithmetic devices;
a job acceptance step of accepting, by the computer, the job data requested for calculation by a client; and
a matching step of allocating, by the computer, the arithmetic device that is available in the grid computing processing among the plurality of arithmetic devices to the job data accepted in the job acceptance step on a basis of a result of the predicting step.
4.(Currently Amended) A management method of managing, by a computer, grid computing processing of causing an arithmetic device that is available among a plurality of arithmetic devices , each of which is owned by a user, is mounted on a vehicle, enters an operation state when the vehicle is traveling, and enters a stop state when a power supply of the vehicle is turned off, to process job data, the management method comprising:
a prediction step of predicting, by the computer, a temporal change in the calculation capability available in the grid computing processing of each of the plurality of arithmetic devices on a basis of calculation capability information indicating a calculation capability of each of the plurality of arithmetic devices and operation status information indicating an operation status of each of the plurality of arithmetic devices;
a selection step of presenting, by the computer, a job list that introduces a plurality of jobs to the user and allowing the user to select the job for which the calculation capability of the arithmetic device owned by the user is desired to be provided from the jobs introduced by the job list; and
a matching step of allocating, by the computer, to the job data corresponding to the job selected by the user in the selection step among the plurality of jobs, the arithmetic device that is available in the grid computing processing and is owned by the user among the plurality of arithmetic devices on a basis of a result of the prediction step and a result of the selection step.
As to claims 1 and 4 and 1 and 5, the only differences between the current application and the copending Application No. 18/287,892 is the limitation of: job acceptance processing of accepting the job data requested for calculation by a client. However , Hoshihara teaches job acceptance processing of accepting the job data requested for calculation by a client ( see rejection of claim 1 below) . Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the copending Application No. 18/287,892 with Hoshihara et al.( US 2013/0218402) because it would allow to have “ an advantage of being able to provide a vehicle with a driving environment enabling traveling without the trouble due to charging shortage, enabling battery charge of the electric vehicle without fail (See Hoshihara para 09 and 11).
This is a provisional nonstatutory double patenting rejection because the patentably indistinct claims have not in fact been patented.
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.
Claim(s) 1-7 are rejected under 35 U.S.C. 103 as being unpatentable over Hoshihara et al. (US 2013/0218402, Hoshihara hereinafter) in view of Xu Zhang et al. “Reservation Enhanced Autonomous Valet Parking Concerning Practicality Issues” , Zhang hereinafter ,PUBLICATION DATE: 2020-11-24.
As to claim 1, Hoshihara teaches a management system that manages grid computing processing (e.g., see FIG. 6, “spot C and spot B”, para 68, “a visiting spot of an electric vehicle. FIG. 6(a) shows a usual visiting spot of a driver, and FIG. 6(b) shows an occurrence of unusual visiting. In FIG. 6, the driver usually drives the electric vehicle to travel between spot C and spot B (see FIG. 6(a))”) of causing an arithmetic device that is available among a plurality of arithmetic devices, each of which is mounted on a vehicle (e.g., see FIG. 1, para 31, “an arithmetic unit 6” for “ the body 1 of an electric vehicle incorporating a navigation system 2 “and “The arithmetic unit 6, which carries out calculations” in para 39 ) , enters an operation state when the vehicle is traveling, and enters a stop state when a power supply of the vehicle is turned off, to process job data (e.g., para [0039] The arithmetic unit 6, which carries out calculations of the individual processing in the navigation system 2, estimates the usual charging spot, charge start time and charging duration taken for the charge of the battery 14, for example, and retains them in the storage unit 5 as a learning result.” and
“the vehicle is in a parking state that enables charging” , “the power consumed by the traveling “ in para 96, 98 and FIG. 8, “state”, Running”, “parking”. Thus, the “charge start time, and the charging duration “ include the job data “, the “state”, Running”, “parking” include the state, therefore an operation state when the vehicle is traveling, and enters a stop state when a power supply of the vehicle is turned off) , the management system comprising:
a memory (e.g., “a storage unit 5”, FIG. 1); and
a controller (e.g., “6”, FIG. 1 and FIG. 2, para , 41, “In FIG. 2, the arithmetic unit 6 comprises “ , “a learning processing unit 24, a decision processing unit 25 and a charge guidance processing unit 26”), wherein
the memory has stored therein calculation capability information indicating a calculation capability of each of the plurality of arithmetic devices (e.g., para [0039] The arithmetic unit 6, which carries out calculations of the individual processing in the navigation system 2, estimates the usual charging spot, charge start time and charging duration taken for the charge of the battery 14, for example, and retains them in the storage unit 5 as a learning result “) and operation status information indicating an operation status of each of the plurality of arithmetic devices (e.g., see FIG. 7, “State”, “running”, “parking”, Charging”, para 69, wherein “parking and charging and the visiting spots of an electric vehicle, which corresponds to FIG. 6(a). Incidentally, the upper half of FIG. 7 shows the states of the electric vehicle with respect to time, and the lower half shows parking spots (visiting spots) of the electric vehicle with respect to time”, therefore operation status information indicating an operation status), and
the controller performs
job acceptance processing of accepting the job data requested for calculation by a client (e.g., see para 55 “ the functions of the foregoing components in the charge guidance processing programs by the arithmetic unit 6 which is a computer for realizing the navigation system 2, for example.” and “displays on the display unit 8 a selection screen for selecting the charging spot at which the frequency of executing the charging processing is not less than the prescribed number of times, its charge start time, and the charging duration required to provide an HMI for causing a user to select the charging spot, charge start time and charging duration using the input unit 7, so that the user can select the appropriate charging spot, charge start time and charging duration.” ,“ a plurality of spots”, “a parking lot where a plurality of vehicles can park at random” , The arithmetic unit 6, which carries out calculations of the individual processing in the navigation system 2, estimates the usual charging spot,” in para 39, 62, 67 and “.
Thus, one of the “functions” include the “ job ” for “a which carries out calculations of the individual processing”, the “charge start time and charging duration “ include the job data requested for calculation by a client , therefore job acceptance processing of accepting the job data requested for calculation by a client) , and
matching processing of allocating the arithmetic device available in the grid computing processing among the plurality of arithmetic devices to the job data accepted in the job acceptance processing on a basis of a result (e.g., see FIG. 6, “spot C and spot B”, para 68, a visiting spot of an electric vehicle. FIG. 6(a) “, “ FIG. 6, the driver usually drives the electric vehicle to travel between spot C and spot B (see FIG. 6(a)”.Thus, matching processing of allocating, to the job data corresponding to the job selected by the user in the selection processing among the plurality of jobs, the arithmetic device that is available in the grid computing processing ) and is owned by the user among the plurality of arithmetic devices on a basis of a result of the selection processing (e.g., para 62, “for causing a user to select the charging spot, charge start time and charging duration using the input unit 7, so that the user can select the appropriate charging spot, charge start time and charging duration” and “he charge guidance processing unit 26 of the decision result ” and “The arithmetic unit 6, which carries out calculations of the individual processing in the navigation system 2, estimates the usual charging spot, charge start time and charging duration taken for the charge of the battery 14”, in para 39.).
However, Hoshihara does not explicitly teach prediction processing of predicting a temporal change in the calculation capability available in the grid computing processing of each of the plurality of arithmetic devices on a basis of the calculation capability information and the operation status information, matching processing of allocating on a basis of a result of the prediction processing.
Zhang teaches prediction processing of predicting a temporal change in the calculation capability available in the grid computing processing of each of the plurality of arithmetic devices on a basis of the calculation capability information and the operation status information (e.g., see page 353 and 354, “Fig. 2. Time sequences of Reservation Enhanced LAVP. “, “Real-time monitoring: The GC keeps track on all CPs of their parking status, including the number of parked vehicles, their expected parking period”, “traffic information around the D/P area will be updated to GC in real-time (typically periodically), so as to inform the AV”, “While on the move, avr may send a parking request to GC for optimal selections on D/P spots and CPs.” and see Fig. 5, “ Influence of AV density. (a) Average parking waiting time. (b) Average AV traveling time. (c) Average customer trip duration”, “1) Average Parking Waiting Time:”, “2) Average AV Traveling Time”, “3) Average Customer Trip Duration” for predictions on future parking states across
the parking network” in page 358) ,
matching processing of allocating the arithmetic device available in the grid computing processing among the plurality of arithmetic devices to the job data accepted in the job acceptance processing on a basis of a result of the prediction processing. (e.g., see Fig. 1. “Big picture ofLAVPwhere anAVselects optimal D/P point and parking
lot with the aid of a cloud server GC.” and page 353, 356 and 357, “Algorithm 4: CP-Selection Decision Making. “, “2: calculate Tldp,cp av 3: calculate EWcp av via Algorithm 3 “ “D. CP-Selection Logic”, “By running the cost value C for each CP in Algorithm 4, the one meets the minimum cost value [according to (4)] for avr is selected”, see Fig. 1. Big picture ofLAVPwhere anAVselects optimal D/P point and parking
lot with the aid of a cloud server GC.
Thus, the “a cloud server GC” include the grid computing processing” for “enable accurate estimations on future parking states. “ , “Selection Decision Making “. Therefore, matching processing of allocating the arithmetic device available in the grid computing processing among the plurality of arithmetic devices to the job data accepted in the job acceptance processing on a basis of a result of the prediction processing).
Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Hoshihara with those of Zhang because both references are directed to related systems addressing similar technical problems within the same field and seek to improve system performance, reliability, and efficiency.
Hoshihara et al. disclose a management system that manages grid computing processing, the calculation capability of the arithmetic device , allowing a user to select the arithmetic device that is available in the grid computing processing while Zhang et al. teach prediction processing of predicting the temporal change in the calculation capability available in the grid computing processing, matching processing of allocating on a basis of a result of the prediction processing.
Incorporating the teachings of Zhang et al. into the system of Hoshihara et al. would have been a predictable and logical modification, yielding improved operational robustness and efficiency without requiring undue experimentation.
Such a combination would merely involve the substitution or integration of known elements performing their established functions, as taught by Zhang et al., into the system of Hoshihara et al., consistent with design incentives and market demands for improved performance and scalability. Moreover, Zhang et al. explicitly recognize benefits to “minimized vehicle trip duration and car park waiting time, as well as enhanced customer experiences (in terms of customer travel period (see Zhang, in page 352) . —that would naturally be desirable in the system of Hoshihara et al.
Accordingly, to one of ordinary skill in the art would have had a reasonable expectation of success in combining Hoshihara et al. with Zhang et al., and the combination represents no more than the predictable use of prior art elements according to their known functions.
As to claim 2, Hoshihara teaches wherein, in the matching processing, the controller allocates, to the job data, the arithmetic device that is available in the grid computing processing among the plurality of arithmetic devices and has performance corresponding to a calculation type of the job data (e.g., para 39, wherein the “estimates the usual charging spot, charge start time and charging duration” in performance corresponding to a calculation type of the job data) .
As to claim 3, Hoshihara teaches wherein, in the matching processing, the controller allocates, to the job data, the arithmetic device that is available in the grid computing processing among the plurality of arithmetic devices and has performance corresponding to an execution condition of the job data (e.g., para 136, “detecting physical quantities for deciding vehicle conditions, and the arithmetic unit 6C decides whether to charge the battery 14 or not from not only the power consumption due to traveling of the vehicle, but also the power consumption which depends on the vehicle conditions and is estimated from the detection information of the sensors 37-39”.
Thus, the” vehicle conditions” include an execution condition of the job data).
As to claim 4, Hoshihara teaches wherein, in the matching processing, the controller allocates, to the job data, the arithmetic device that is available in the grid computing processing among the plurality of arithmetic devices so that the grid computing processing on the job data is completed until a delivery date set for the job data (e.g., para 65, “he period of time from the charge start time to the charge end time “ for “ the functions of the foregoing components in the charge guidance processing program”. Thus, the “the charge end time” include a delivery date set for the job data.) .
As to claim 5, see rejection of claim 1 above.
As to claim 6, see rejection of claim 4 above.
As to claim 7, see rejection of claim 4 above.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Chakrabarti et al. (US 2007/0250365) discloses A grid computing system, method, and computer program product, adapted to execute at least one workflow having a set of predefined operating parameters and including an execution module comprising a plurality of devices having a plurality of heterogeneous resources, wherein the plurality of devices is adapted to execute the at least one job by integrating the plurality of heterogeneous resources. The system further includes at least one grid workflow module. The grid workflow module includes a graphical user interface to provide at least one user to initiate and manage the at least one workflow based on the set of predefined operating parameters and the plurality of heterogeneous resources. Furthermore, the grid workflow module includes a manager module adapted to partition the at least one workflow into multiple jobs prior to the execution of the at least one workflow.
Dowson et al. (US 2007/0078960) discloses Performance data is captured periodically from resources and groups of resources in a grid computing environment and stored in a content-addressable data repository from which it can be accessed in response to an arbitrarily complex query in regard to specifics of particular jobs or job portions, particular resources utilized, grid architecture, application environment, concurrent jobs or job portions and the like. The data repository may be distributed or divided in regard to grid environment architecture, security domains or the like and each portion or division may be implemented in a modular fashion including an accounting and statistics management module and additional modules or computing engines for performing particular desired analyses or functions. Results of such analyses or functions may be communicated to a grid workload agent (and associated modules) to improve grid management on a fine-grained basis.
Golub et al. (US 2023/0281046) discloses one or more autonomous vehicles are clustered into one or more microgrids and at least one computing task is scheduled on at least one microgrid. Activation signals are received from a client of one or more autonomous vehicles when the vehicles are plugged into charging stations. Utilization rates of the autonomous vehicles are determined based on a set of parameters, which includes at least one of location of the autonomous vehicle and time. The autonomous vehicles are clustered into one or more microgrids of autonomous vehicles based on the utilization rates. At least one request for performing at least one computing task is received from a user device. The at least one request includes an estimated runtime of the at least one computing task. The at least one computing task is scheduled on at least one microgrid of autonomous vehicles based on the estimated runtime.
Orbay (US 2023/0161623) discloses Distributed computing vehicles (e.g., using a computerized tool) are enabled. For example, a system can comprise a memory that stores computer executable components, and a processor that executes the computer executable components stored in the memory, wherein the computer executable components comprise: a request component that determines a compute request received via a network from a network device registered to use the system, and a resource component that, in response to a compute criterion associated with a vehicle communicatively coupled to the network being determined to be satisfied, allocates at least some compute resources of the vehicle to the compute request.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ABDOU K SEYE whose telephone number is (571)270-1062. The examiner can normally be reached M-F 9-5:30.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Pierre Vital can be reached at 5712724215. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/ABDOU K SEYE/Examiner, Art Unit 2198
/PIERRE VITAL/Supervisory Patent Examiner, Art Unit 2198