Information processing device and information processing method

Abstract

This information processing device (10) comprises: a data cooperation processing unit (11) that executes processing relating to aggregation in which cooperation is achieved between own company data and other company data; an acquisition unit (12) that acquires configuration determination data for determining the configuration of a calculation resource that executes the processing relating to aggregation, at the start of execution or after the start of execution of the processing relating to aggregation; and a determination unit (13) that determines the configuration of the calculation resource on the basis of the acquired configuration determination data.

Description

Information Processing Apparatus and Information Processing Method

[0001] The present disclosure relates to an information processing apparatus and an information processing method.

[0002] By utilizing data held by a plurality of enterprises (including various companies, organizations, groups, etc. here), it is expected to create value that cannot be obtained from data held by a single enterprise. As one method of realizing data utilization among multiple enterprises, there is a method of performing aggregation processing that links the plurality of data without mutually disclosing the data held by each of the plurality of enterprises and outputting the aggregation result (see Patent Document 1). On the other hand, in large-scale data processing, it is important to improve processing efficiency by optimizing hardware resources (for example, meaning a CPU, memory, etc., hereinafter referred to as "computing resources") used for computational processing.

[0003] International Publication No. WO2022 / 254821

[0004] However, in the process of integrating and aggregating data held by a plurality of enterprises without mutually disclosing the data, it is impossible to grasp the characteristics of the other party's data (for example, the amount of data, etc.) before the start of processing, and it is impossible to appropriately grasp in advance the computing resources required for processing. Therefore, there is a problem that it is difficult to improve processing efficiency by optimizing computing resources.

[0005] Also, in a situation where data can be mutually disclosed, it is possible to grasp in advance the computing resources required for processing by performing additional processing such as mutually exchanging the characteristic information of the data to be processed in advance. However, the addition of processing may hinder the improvement of processing efficiency, and it cannot be said to be a desirable response.

[0006] The present disclosure has been made to solve the above problems, and an object thereof is to improve processing efficiency by optimizing computing resources even in a situation where it is impossible to grasp in advance the computing resources required for processing.[[ID=第十九]]

[0007] The information processing device relating to this disclosure includes a data linkage processing unit that performs aggregation processing by linking the company's own data with data from other companies; an acquisition unit that acquires configuration determination data for determining the configuration of computing resources that perform the aggregation processing at or after the start of the aggregation processing; and a determination unit that determines the configuration of the computing resources based on the acquired configuration determination data.

[0008] According to this disclosure, even in situations where the computing resources required for processing cannot be known in advance, it is possible to improve processing efficiency by optimizing computing resources.

[0009] This is a diagram illustrating the overall system configuration, including the information processing device, in the embodiment. It is a diagram explaining the processing flow and the data being processed in relation to aggregation. This is a flowchart showing the first process. This is a flowchart showing the second process. This is a flowchart showing the third process. This is a diagram showing an example of the hardware configuration of the information processing device.

[0010] Hereinafter, various embodiments of the information processing apparatus and information processing method relating to this disclosure will be described with reference to the drawings.

[0011] As shown in Figure 1, the system in this embodiment includes an information processing device 10A of company A and an information processing device 10B of company B, both of which are equipped with a plurality of functional units described later for realizing the functions related to this disclosure, and are collectively referred to as the information processing device 10. Furthermore, the system includes a terminal 20A operated by an operator of company A who gives instructions and monitors the execution of processing by the information processing device 10A, and a terminal 20B operated by an operator of company B who gives instructions and monitors the execution of processing by the information processing device 10B.

[0012] The following describes the functional block configuration of the information processing device 10, using the configuration of information processing device 10A of company A as an example. To realize the functions related to this disclosure, the information processing device 10A includes a data linkage processing unit 11, an acquisition unit 12, a determination unit 13, and an input / output unit 14. Each functional unit will be described in order below.

[0013] The data linkage processing unit 11 is a functional unit that, by linking with another company's information processing device (in this case, company B's information processing device 10B), performs aggregation processing that links the company's data and the other company's data without mutual disclosure of the company's data and the other company's data with the information processing device 10B by adding noise. The above-mentioned "aggregation processing" broadly includes de-identification processing, aggregation processing, and concealment processing. The data linkage processing unit 11 includes a de-identification processing unit 11A that performs de-identification processing (including anonymization processing, irreversible ID conversion, and encryption), an aggregation processing unit 11B that performs aggregation processing, and a concealment processing unit 11C that performs concealment processing that adds noise based on differential privacy standards. The "aggregation processing" is the same as processing in existing technologies and will be outlined in the processing description later. In this embodiment, as an example of "aggregation processing," processing that integrates and aggregates data without mutual disclosure (so-called concealed cross-statistics) will be explained. However, the point that data is not mutually disclosed is not essential for "aggregation processing," and it is applicable to all processing that links and aggregates data from multiple companies.

[0014] The acquisition unit 12 is a functional unit that acquires configuration determination data to determine the configuration of computing resources to execute the aggregation process at the start of execution or after the start of execution of the aggregation process. The acquisition unit 12 acquires various information and data as "configuration determination data". For example, the acquisition unit 12 acquires the following as configuration determination data: (1) the characteristics of the company's own data and the data of other companies that are the subject of the aggregation process (e.g., the number of records), (2) metrics data of resources consumed during the execution of the aggregation process (e.g., CPU usage rate, memory usage), and (3) actual processing time data for the aggregation process. It should be noted that the acquisition unit 12 is not required to acquire all of the above data (1) to (3), and will acquire at least one of the above (1) to (3).

[0015] The decision unit 13 is a functional unit that determines the configuration of computing resources based on the acquired configuration determination data. Specifically, the decision unit 13 makes decisions regarding the configuration of computing resources as follows, depending on the various types of configuration determination data acquired. For example, the decision unit 13: (1) determines the division of functions between the information processing device of the other company and its own information processing device based on the characteristics of the acquired company data and other company data; (2) determines the requirements for the CPU from the CPU usage rate information included in the acquired metrics data, and the requirements for memory from the memory usage information included in the metrics data, and determines the type and size of computing resources based on the determined requirements for the CPU and memory; (3) calculates the estimated processing time and operating cost for each candidate combination of computing resource size and number of execution units based on the acquired processing time actual data, and determines the size and number of execution units of computing resources based on the calculated estimated processing time and operating cost, as well as predetermined operating cost requirements. It should be noted that the decision unit 13 is not required to perform all of the decision processes described in (1) to (3) above. Instead, it makes a decision regarding the configuration of at least one of the computing resources described in (1) to (3) above, based on the configuration determination data acquired by the acquisition unit 12.

[0016] The input / output unit 14 is a functional unit that serves as an interface for sending and receiving various information and data with the terminal 20A.

[0017] The information processing device 10B of company B has a configuration similar to that of the information processing device 10A described above. The data linkage processing unit 11 in each information processing device 10 is capable of sending and receiving various information and data with the data linkage processing unit 11 of the other party, and the acquisition unit 12 is also capable of sending and receiving information and data with the acquisition unit 12 of the other party.

[0018] The following three types of processing (the first to the third processing) performed in the information processing device 10 will be explained in accordance with the flowcharts in Figures 3 to 5.

[0019] The first process shown in Figure 3 includes the acquisition unit 12 acquiring the characteristics of the company's own data and the data of other companies that are the subject of the aggregation process described in (1) above as configuration determination data, and the determination unit 13 determining the division of functions between the information processing device of other companies and the company's own information processing device based on the characteristics of the acquired company's own data and the data of other companies.

[0020] The second process shown in Figure 4 includes the acquisition unit 12 acquiring metric data of consumed resources during the execution of the aggregation process described in (2) above as configuration determination data, the determination unit 13 determining CPU requirements from the CPU usage information included in the acquired metric data, and memory requirements from the memory usage information included in the metric data, and then determining the type and size of computing resources based on the determined CPU requirements and memory requirements.

[0021] The third process shown in Figure 5 includes a process in which the acquisition unit 12 acquires actual processing time data for the aggregation process described in (3) above as configuration determination data, the determination unit 13 calculates estimated processing time and operating costs for each candidate combination of computing resource size and number of execution machines based on the acquired actual processing time data in (3), and determines the computing resource size and number of execution machines based on the calculated estimated processing time and operating costs, as well as predetermined operating cost requirements.

[0022] First, the first process will be explained in accordance with the flowchart in Figure 3. The data linkage processing units 11 of the information processing devices 10A and 10B cooperate with each other and perform the aggregation process that links the data of company A and the data of company B as follows (step S1 in Figure 3). The "aggregation process" here is, for example, a confidential cross-statistical processing similar to the technology described in Patent Document 1 of the prior art documents mentioned above, and broadly includes "de-identification processing," "aggregation processing," and "confidential processing." The process of step S1 will be outlined below.

[0023] First, the deidentification processing units 11A of each information processing device 10A and 10B, in cooperation with the other party's deidentification processing unit 11A, execute existing deidentification processes (including anonymization processes (e.g., k-anonymization, l-diversity, t-approximation, etc.), irreversible transformation processes (e.g., ID hashing, etc.), and encryption processes) on their respective company data. In particular, during the encryption process, the deidentification processing unit 11A of information processing device 10A performs a first encryption on A company data based on A company's encryption key and keyed one-way commutative operations. Furthermore, it performs a second encryption on B company data received from information processing device 10B through the exchange of encryption results with information processing device 10B (i.e., B company data after the first encryption based on B company's encryption key and keyed one-way commutative operations) based on A company's encryption key and keyed one-way commutative operations. This generates B company data that has been double-encrypted using A company's encryption key and B company's encryption key. Furthermore, the anonymization processing unit 11A of the information processing device 10B also performs the same processing, generating double-encrypted data of company A using company A's encryption key and company B's encryption key, and the generated double-encrypted data of company A is transferred to the information processing device 10A.

[0024] In the encryption process described above, the "part corresponding to the user ID" and the "other parts" of the target data are executed separately. Furthermore, since both encryption processes are based on keyed, one-way, commutative arithmetic, it is possible to determine whether the double-encrypted data of Company A and the double-encrypted data of Company B belong to the same user based on the matching or mismatch of the bit sequences of the "part corresponding to the user ID" identified based on the data structure information shared in advance between the information processing devices 10A and 10B.

[0025] Next, the aggregation processing unit 11B of the information processing device 10A compares the double-encrypted A company data with the double-encrypted B company data and counts the number of data where the "part corresponding to the user ID" matches, thereby aggregating the number of target users. In the example shown in Figure 2, the number of data where the "part corresponding to the user ID" matches in the A company data and B company data (for example, the data with the ID "00000002" shown in bold in Figure 2) is counted to aggregate the number of target users (number of matching IDs), and the aggregation result "10,011" is obtained. Note that in Figure 2, for the sake of explanation, the content of the data being compared is shown in a way that makes it identifiable, but the data actually being compared is double-encrypted data.

[0026] Furthermore, the concealment processing unit 11C of the information processing device 10A performs concealment processing based on differential privacy on the aggregated results. Figure 2 shows an example in which concealment processing based on differential privacy is performed on the aggregated result "10,011", and the aggregated result "10,327" after noise is added is obtained.

[0027] Returning to Figure 3, in the next step S2, the acquisition units 12 of the information processing devices 10A and 10B each acquire the characteristics of their own company data that is the subject of aggregation processing as configuration determination data. The acquisition unit 12 of the information processing device 10B then transmits the acquired characteristics of its own company data (Company B data) to the acquisition unit 12 of the information processing device 10A. As a result, the acquisition unit 12 of the information processing device 10A acquires the characteristics of its own company data (Company A data) and the characteristics of the other company's data (Company B data). These characteristics of Company A data and Company B data, for example, the number of records in both companies' data, are passed to the determination unit 13 of the information processing device 10A.

[0028] Then, the determination unit 13 of the information processing device 10A determines the division of functions between the information processing devices 10A and 10B based on the characteristics of the acquired A company data and B company data (step S3). To explain the division of functions, in step S1 described above, only the information processing device 10A performed the following operations: (a) matching the double-encrypted A company data with the double-encrypted B company data and counting the number of data where the "part corresponding to the user ID" matches to aggregate the number of target users, and (b) performing confidentiality processing based on differential privacy on the aggregated results. Thus, the content of the processing performed by the data linkage processing unit 11 is asymmetrical between the information processing devices 10A and 10B. Therefore, for example, if the number of records in Company B's data is less than the number of records in Company A's data, it is assumed that the processing load on the information processing device 10B will be lighter. In step S1 (processing related to aggregation), the functional division between the information processing devices 10A and 10B may be determined such that (a) the number of target users is aggregated by matching the double-encrypted Company A data with the double-encrypted Company B data and counting the number of data where the "part corresponding to the user ID" matches, and (b) the aggregation results are subjected to confidentiality processing based on differential privacy.

[0029] Furthermore, the determination unit 13 of the information processing device 10A transmits the determined functional assignment to the data linkage processing units 11 of both information processing devices 10A and 10B, and as a result, the subsequent processing (processing related to aggregation) is executed by the data linkage processing units 11 of both information processing devices 10A and 10B according to the determined functional assignment (step S4).

[0030] The first process described above has the effect of reducing the overall processing time by determining the division of functions according to the characteristics of the input data. For example, since the content of the processing performed by the data linkage processing unit 11 is asymmetrical (different) between the information processing devices 10A and 10B, if there is a large difference in the number of records in the data of the two companies, the division of functions can be re-determined, and by executing subsequent processing according to the determined division of functions, the overall efficiency of the processing can be greatly improved.

[0031] Next, the second process will be explained in accordance with the flowchart in Figure 4. The data linkage processing units 11 of the information processing devices 10A and 10B work together to perform the aggregation process that links the data of company A and the data of company B (step S11 in Figure 4). Note that the process in step S11 is the same as the process in step S1 in Figure 3 described above, so a redundant explanation will be omitted here.

[0032] Next, the acquisition unit 12 of the information processing devices 10A and 10B acquires metric data of consumed resources after processing some of the data (step S12). The metric data of consumed resources here includes the CPU usage rate and memory usage of each information processing device. The acquired metric data from both companies is transmitted to the decision unit 13 of the information processing device 10A and aggregated.

[0033] Next, the determination unit 13 of the information processing device 10A determines the requirements for computing resources (step S13). For example, it determines the requirements for clock speed and number of cores from the CPU usage rate, and the requirements for memory size from the memory usage rate.

[0034] Next, the determination unit 13 of the information processing device 10A extracts candidates for the type and size of computing resources that match (satisfy) the determined requirements (step S14). Here, "type of computing resource" corresponds to the so-called instance type, and examples include general-purpose, CPU-specialized, and memory-specialized types. Here, "general-purpose" means computing resources equipped with a good balance of CPU configuration (performance and number) and memory configuration (performance and capacity), "CPU-specialized" means computing resources with a configuration that prioritizes CPU configuration (performance and number) over memory, and "memory-specialized" means computing resources with a configuration that prioritizes memory configuration (performance and capacity) over CPU. The extracted candidates for the type and size of computing resources are listed, for example, in a list that includes multiple candidates for the type and size of computing resources that can be secured.

[0035] Next, the determination unit 13 of the information processing device 10A determines the type and size of computing resources from the "candidates for type and size of computing resources" in the list above, according to predetermined criteria (step S15). For example, under the criterion of minimizing the cost of configuration, the "candidate for type and size of computing resources" with the lowest configuration cost among the above candidates is selected.

[0036] Furthermore, the determination unit 13 of the information processing device 10A transmits the determined "type and size of computing resources" to the configuration change control unit (not shown), which controls configuration changes in the information processing devices 10A and 10B respectively. As a result, the configuration of the computing resources is changed to the determined "type and size of computing resources," and subsequent processing (processing related to aggregation) is executed using the computing resources with the changed configuration (step S16).

[0037] Through the second process described above, CPU and memory requirements can be determined from metric data of consumed resources (including CPU usage and memory usage) during the execution of the aggregation process, and the appropriate type and size of computing resources can be determined in accordance with predetermined criteria from the "candidate types and sizes of computing resources" that match the determined requirements.

[0038] Next, the third process will be explained in accordance with the flowchart in Figure 5. The data linkage processing units 11 of the information processing devices 10A and 10B work together to perform the aggregation process that links the data of company A and the data of company B (step S21 in Figure 5). Note that the process in step S21 is the same as the process in step S1 in Figure 3 described above, so a redundant explanation will be omitted here.

[0039] Next, the acquisition unit 12 of the information processing devices 10A and 10B acquires actual processing time data from the data linkage processing unit 11 of each information processing device 10 after processing some of the data (step S22). The acquired actual processing time data includes, for example, the number of tasks, the processing time for each task, and the total processing time, and is transmitted to the decision unit 13 of the information processing device 10A for aggregation.

[0040] Next, the determination unit 13 of the information processing device 10A extracts the number of tasks, the processing time for each task, and the total processing time from the acquired processing time data (step S23), and estimates the overhead time according to, for example, the following formula (1) (step S24). Overhead time = Total processing time - Total task processing time / Number of parallel processes (1) In the above formula (1), the extracted total processing time is applied to "Total processing time", the sum of the processing times for each task is applied to "Total task processing time", and the number of parallel processes in the task processing is applied to "Number of parallel processes".

[0041] Next, the determination unit 13 of the information processing device 10A sets a range of expected parallelisms based on the number of tasks, the processing time for each task, and the total processing time (step S25). The processes in steps S26 to S29 are executed for each of the multiple candidates (candidate combinations of computing resource size and number of execution machines) within the range of parallelisms.

[0042] In step S26, the determination unit 13 of the information processing device 10A sets a new number of parallel processes for new candidates regarding the size of the computing resources and the number of execution machines, and calculates the maximum processing time according to the following formula (2) (step S27). Maximum processing time = Total task processing time / Number of parallel processes (2)

[0043] Next, the determination unit 13 of the information processing apparatus 10A estimates the parallel processing time (step S28) by adding the overhead time estimated in step S24 to the maximum processing time calculated in step S27 (in accordance with the following formula (3)). Parallel processing time = Maximum processing time + Overhead time (3) Note that the overhead time may take into account variations associated with changes in the degree of parallelism.

[0044] Next, the determination unit 13 of the information processing apparatus 10A calculates the operation cost of the computing resources (step S29), for example, from the size and number of execution units of the computing resources, and the parallel processing time, while also referring to the past operation cost records.

[0045] Thereafter, the processes of steps S26 to S29 are executed for each candidate within the range of the degree of parallelism (candidates for the size and number of execution units of the computing resources). When the execution is completed for all candidates within the range of the degree of parallelism, it is determined as YES in step S30, and the process proceeds to step S31.

[0046] In step S31, the determination unit 13 of the information processing apparatus 10A determines the size and number of execution units of the computing resources (step S31) based on the parallel processing time estimated in step S28, the operation cost calculated in step S29, and a predetermined operation cost requirement. For example, the determination unit 13 of the information processing apparatus 10A may determine, as the size and number of execution units of the computing resources, the candidate with the shortest parallel processing time among the candidates that satisfy the operation cost requirement (that is, a plurality of combinations of the size and number of execution units of the computing resources).

[0047] Furthermore, the determination unit 13 of the information processing apparatus 10A transmits the determined "size and number of execution units of the computing resources" to a configuration change control unit (not shown) that controls the configuration changes in each of the information processing apparatuses 10A and 10B. As a result, the configuration of the computing resources is changed to the determined "size and number of execution units of the computing resources", and subsequent processes (processes related to aggregation) are executed using the computing resources with the changed configuration (step S32).

[0048] Through the third process as described above, based on the processing time performance data, the estimated processing time and operation cost for each combination candidate of the size of computing resources and the number of execution units are calculated. Based on the calculated estimated processing time and operation cost, and the predetermined operation cost requirement, the size of computing resources and the number of execution units can be appropriately determined, and the processing time can be optimized by executing the processing with the changed configuration.

[0049] According to the embodiment including the three processes described above, even in a situation where the computing resources required for processing cannot be grasped in advance, based on the information obtained at the start of processing (the characteristics of the company's and other companies' data to be processed respectively) or the information obtained after the start of processing (metric data of consumed resources, or processing time performance data), an appropriate configuration of computing resources (type, size, number of execution units, etc. of computing resources) can be determined, and the processing efficiency can be improved by executing the processing with the determined changed configuration.

[0050] In addition, in the above embodiment, as an example of the "processing related to aggregation", the processing of integrating and aggregating data without mutual disclosure (so-called confidential cross-statistics) was described. Regarding the "processing related to aggregation", the point of not mutually disclosing data is not essential, and it is applicable to all processing of aggregating by linking multiple companies' data. That is, among the "de-identification processing", "aggregation processing", and "confidential processing", it is not essential to execute the "de-identification processing" and the "confidential processing".

[0051] [Explanation of terms, explanation of hardware configuration (Figure 6), etc.] The block diagram used in the description of the above embodiment shows functional units. These functional blocks (components) are realized by any combination of at least one of hardware and software. Furthermore, the method of realizing each functional block is not particularly limited. That is, each functional block may be realized using one device that is physically or logically coupled, or it may be realized using two or more physically or logically separated devices that are directly or indirectly connected (for example, using wired, wireless, etc.). A functional block may be realized by combining the above one device or the above multiple devices with software.

[0052] Functions include, but are not limited to, judgment, decision, judgment, calculation, calculation, processing, derivation, investigation, exploration, confirmation, reception, transmission, output, access, resolution, selection, selection, establishment, comparison, assumption, expectation, assumption, broadcasting, notifying, communicating, forwarding, configuring, reconfiguring, allocating (mapping), and assigning. For example, a functional block (configuration part) that enables transmission is called a transmitting unit or transmitter. As mentioned above, the method of implementation is not particularly limited.

[0053] For example, the information processing device in one embodiment of the present disclosure may function as a computer that performs the processing of the present disclosure. Figure 6 is a diagram showing an example of the hardware configuration of the information processing device 10 according to one embodiment of the present disclosure. The information processing device 10 described above may be physically configured as a computer device including a processor 1001, memory 1002, storage 1003, communication device 1004, input device 1005, output device 1006, bus 1007, etc.

[0054] In the following explanation, the term "device" can be replaced with "circuit," "device," "unit," etc. The hardware configuration of the information processing device 10 may include one or more of the devices shown in the figure, or it may be configured to omit some of the devices.

[0055] Each function in the information processing device 10 is realized by loading predetermined software (programs) onto hardware such as the processor 1001 and memory 1002, which allows the processor 1001 to perform calculations, control communication by the communication device 1004, and control at least one of data reading and writing in the memory 1002 and storage 1003.

[0056] The processor 1001 controls the entire computer, for example, by running an operating system. The processor 1001 may be composed of a central processing unit (CPU) that includes interfaces with peripheral devices, control units, arithmetic units, registers, etc.

[0057] Furthermore, the processor 1001 reads programs (program code), software modules, data, etc., from at least one of the storage 1003 and the communication device 1004 into the memory 1002, and executes various processes accordingly. The program used is one that causes the computer to execute at least a part of the operations described in the above embodiment. Although it has been explained that the various processes are executed by one processor 1001, they may be executed simultaneously or sequentially by two or more processors 1001. The processor 1001 may be implemented by one or more chips. The program may also be transmitted from a network via a telecommunications line.

[0058] The memory 1002 is a computer-readable recording medium and may consist of at least one of the following: ROM (Read Only Memory), EPROM (Erasable Programmable ROM), EEPROM (Electrically Erasable Programmable ROM), RAM (Random Access Memory), etc. The memory 1002 may also be called a register, cache, main memory, etc. The memory 1002 can store executable programs (program code), software modules, etc., for carrying out a wireless communication method according to one embodiment of the present disclosure.

[0059] The storage 1003 is a computer-readable recording medium and may consist of at least one of the following: an optical disc such as a CD-ROM (Compact Disc ROM), a hard disk drive, a flexible disk, a magneto-optical disk (e.g., a compact disc, a digital multipurpose disc, a Blu-ray® disc), a smart card, flash memory (e.g., a card, a stick, a key drive), a floppy® disk, a magnetic strip, etc. The storage 1003 may also be called an auxiliary storage device. The above-mentioned storage medium may be, for example, a database, server, or other suitable medium including at least one of the memory 1002 and the storage 1003.

[0060] The communication device 1004 is hardware (transceiver / receiver device) for communicating between computers via at least one of a wired network and a wireless network, and is also referred to as a network device, network controller, network card, communication module, etc. The communication device 1004 may be configured to include, for example, a high-frequency switch, duplexer, filter, frequency synthesizer, etc., in order to implement at least one of frequency division duplex (FDD) and time division duplex (TDD).

[0061] The input device 1005 is an input device that accepts input from an external source (e.g., a keyboard, mouse, microphone, switch, button, sensor, etc.). The output device 1006 is an output device that outputs to an external source (e.g., a display, speaker, LED lamp, etc.). The input device 1005 and the output device 1006 may be configured as an integrated unit (e.g., a touch panel).

[0062] Furthermore, each device, such as the processor 1001 and the memory 1002, is connected by a bus 1007 for communicating information. The bus 1007 may be configured using a single bus, or different buses may be configured for each device.

[0063] Furthermore, the information processing device 10 may be configured to include hardware such as a microprocessor, a digital signal processor (DSP), an ASIC (Application Specific Integrated Circuit), a PLD (Programmable Logic Device), and an FPGA (Field Programmable Gate Array), and some or all of each functional block may be realized by such hardware. For example, the processor 1001 may be implemented using at least one of these hardware components.

[0064] The notification of information is not limited to the embodiments described herein and may be carried out by other means. For example, the notification of information may be carried out by physical layer signaling (e.g., DCI (Downlink Control Information), UCI (Uplink Control Information)), upper layer signaling (e.g., RRC (Radio Resource Control) signaling, MAC (Medium Access Control) signaling, broadcast information (MIB (Master Information Block), SIB (System Information Block))), other signals, or combinations thereof. RRC signaling may also be called RRC messages, and may be, for example, RRC Connection Setup messages, RRC Connection Reconfiguration messages, etc.

[0065] Each aspect / embodiment described in this disclosure refers to LTE (Long Term Evolution), LTE-A (LTE-Advanced), SUPER 3G, IMT-Advanced, 4G (4th generation mobile communication system), 5G (5th generation mobile communication system), 6th generation mobile communication system (6G), xth generation mobile communication system (xG) (xG (where x is, for example, an integer or decimal)), FRA (Future Radio Access), NR (new Radio), New radio access (NX), Future generation radio access (FX), W-CDMA (registered trademark), GSM (registered trademark), CDMA2000, UMB (Ultra Mobile Broadband), IEEE 802.11 (Wi-Fi (registered trademark)), IEEE 802.16 (WiMAX (registered trademark)), IEEE 802.20, may apply to at least one system utilizing UWB (Ultra-WideBand), Bluetooth®, or other appropriate systems, and to next-generation systems extended, modified, generated, or defined based thereon. Alternatively, multiple systems may be applied in combination (e.g., a combination of at least one of LTE and LTE-A with 5G).

[0066] The processing procedures, sequences, flowcharts, etc., of each aspect / embodiment described in this disclosure may be reordered, provided they do not contradict each other. For example, the methods described in this disclosure present various step elements using exemplary order and are not limited to the specific order presented.

[0067] Input and output information may be stored in a specific location (e.g., memory) or managed using a management table. Input and output information may be overwritten, updated, or appended to. Output information may be deleted. Input information may be transmitted to other devices.

[0068] The determination may be made by a value represented by one bit (0 or 1), by a boolean value (true or false), or by a numerical comparison (for example, a comparison with a predetermined value).

[0069] Each aspect / embodiment described in this disclosure may be used individually, in combination, or switched between as needed during implementation. Furthermore, notification of specific information (e.g., notification that "X is") is not limited to explicit notification, but may also be implicit (e.g., by not providing such notification).

[0070] Although the present disclosure has been described in detail above, it will be clear to those skilled in the art that the present disclosure is not limited to the embodiments described herein. The present disclosure can be implemented in modified and altered forms without departing from the intent and scope of the present disclosure as defined by the claims. Therefore, the descriptions in the present disclosure are illustrative and not intended to be restrictive in any way.

[0071] Software should be broadly interpreted to mean instructions, instruction sets, code, code segments, program code, programs, subprograms, software modules, applications, software applications, software packages, routines, subroutines, objects, executable files, execution threads, procedures, functions, and so on, whether they are called software, firmware, middleware, microcode, hardware description languages, or by any other name.

[0072] Furthermore, software, instructions, information, etc., may be transmitted and received via a transmission medium. For example, if software is transmitted from a website, server, or other remote source using at least one of wired technology (such as coaxial cable, fiber optic cable, twisted pair, or digital subscriber line (DSL)) and wireless technology (such as infrared or microwave), then at least one of these wired and wireless technologies is included in the definition of a transmission medium.

[0073] The information, signals, etc. described in this disclosure may be represented using any of the various different techniques. For example, the data, instructions, commands, information, signals, bits, symbols, chips, etc. that may be referred to throughout the above description may be represented by voltage, current, electromagnetic waves, magnetic fields or magnetic particles, optical fields or photons, or any combination thereof.

[0074] In addition, terms used in this disclosure and terms necessary for understanding this disclosure may be replaced with terms having the same or similar meanings. For example, at least one of the channel and symbol may be a signal (signaling). Also, a signal may be a message. Furthermore, a component carrier (CC) may be called a carrier frequency, cell, frequency carrier, etc.

[0075] The terms “system” and “network” as used in this disclosure are interchangeable.

[0076] Furthermore, the information, parameters, etc., described in this disclosure may be expressed using absolute values, relative values ​​from a given value, or other corresponding information. For example, wireless resources may be indicated by an index.

[0077] The names used for the parameters described above are not restrictive in any way. Furthermore, the formulas and other expressions using these parameters may differ from those expressly disclosed in this disclosure. Various channels (e.g., PUCCH, PDCCH, etc.) and information elements can be identified by any suitable name, and therefore, the various names assigned to these various channels and information elements are not restrictive in any way.

[0078] As used in this disclosure, the terms “determining” and “determining” may encompass a wide variety of actions. “Determining” may include, for example, judging, calculating, computing, processing, deriving, investigating, looking up, searching, or inquiring (e.g., searching in a table, database, or other data structure), or ascertaining. “Determining” may also include receiving (e.g., receiving information), transmitting (e.g., sending information), inputting, outputting, or accessing (e.g., accessing data in memory). Furthermore, "judgment" and "decision" can include considering something as having been "judged" or "decided" after resolving, selecting, choosing, establishing, comparing, etc. In other words, "judgment" and "decision" can include considering something as having been "judged" or "decided" after some action. Also, "judgment (decision)" can be reinterpreted as "assuming," "expecting," or "considering."

[0079] In this disclosure, the phrase "based on" does not mean "based solely on" unless otherwise specified. In other words, the phrase "based on" means both "based solely on" and "based at least on."

[0080] Any reference to elements using the designations “first,” “second,” etc., as used in this disclosure does not generally limit the quantity or order of those elements. These designations may be used in this disclosure as a convenient way to distinguish between two or more elements. Accordingly, references to the first and second elements do not imply that only two elements may be employed, or that the first element must precede the second element in any way.

[0081] Where the terms “include,” “including,” and variations thereof are used in this disclosure, these terms are intended to be inclusive, as is the term “comprising.” Furthermore, the term “or” as used in this disclosure is not intended to mean exclusive OR.

[0082] In this disclosure, if articles are added through translation, such as a, an, and the in English, this disclosure may include the fact that the noun following these articles is plural.

[0083] In this disclosure, the term "A and B are different" may mean "A and B are different from each other." The term may also mean "A and B are each different from C." Terms such as "separate" and "combine" may be interpreted similarly to "different."

[0084] 10, 10A, 10B... Information processing device, 11... Data linkage processing unit, 11A... De-identification processing unit, 11B... Aggregation processing unit, 11C... Confidentiality processing unit, 12... Acquisition unit, 13... Judgment unit, 14... Input / Output unit, 20A, 20B... Terminal, 1001... Processor, 1002... Memory, 1003... Storage, 1004... Communication device, 1005... Input device, 1006... Output device, 1007... Bus.

Claims

1. An information processing device comprising: a data linkage processing unit that performs aggregation processing by linking the company's own data and data from other companies; an acquisition unit that acquires configuration determination data for determining the configuration of computing resources to perform the aggregation processing at or after the start of the aggregation processing; and a determination unit that determines the configuration of the computing resources based on the acquired configuration determination data.

2. The information processing apparatus according to claim 1, wherein the acquisition unit acquires the characteristics of the company's own data and the other company's data that are subject to the processing related to the aggregation as configuration determination data, and the determination unit determines the division of functions between the other company's information processing apparatus and the company's own information processing apparatus based on the acquired characteristics of the company's own data and the other company's data.

3. The information processing apparatus according to claim 1, wherein the acquisition unit acquires metric data of resources consumed during the execution of the aggregation process as configuration determination data, and the determination unit determines the type and size of the computing resources based on the acquired metric data.

4. The information processing apparatus according to claim 3, wherein the determination unit determines CPU requirements from CPU usage information included in the metrics data, and memory requirements from memory usage information included in the metrics data, and determines the type and size of the computing resources based on the determined CPU requirements and memory requirements.

5. The information processing apparatus according to claim 1, wherein the acquisition unit acquires actual processing time data for the aggregation process as configuration determination data, and the determination unit determines the size of the computing resources and the number of execution machines based on the acquired actual processing time data.

6. The information processing apparatus according to claim 5, wherein the determination unit calculates an estimated processing time and operating cost for each candidate combination of the size and number of computing resources based on the acquired processing time data, and determines the size and number of computing resources based on the calculated estimated processing time and operating cost, as well as predetermined operating cost requirements.

7. An information processing method comprising: a step of an information processing device performing a process related to aggregation that links the company's own data and the data of another company; a step of the information processing device acquiring configuration determination data for determining the configuration of computing resources to perform the aggregation process at the start of execution or after the start of execution; and a step of the information processing device determining the configuration of the computing resources based on the acquired configuration determination data.

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