Information processing method, information processing device, and information processing program

Abstract

Provided is an information processing device including a processor, the processor determining execution timing of an additional transaction to a block chain on the basis of a history of a transaction fee related to a transaction for trail writing to the block chain and a history of occurrence of trail writing to the block chain.

Description

Information processing method, information processing device, and information processing program

[0001] The disclosed technology relates to an information processing method, an information processing device, and an information processing program.

[0002] JP 2021-136031 A describes an aspect in which a historical reference value is determined based on the actual fees of existing block transaction requests in a blockchain, and if the actual fees of the transaction request are equal to or greater than the historical reference value, it is determined that the result satisfies the transaction execution condition, and if the actual fees of the transaction request are lower than the historical reference value, the time order in which the transaction request satisfies the transaction execution condition is determined according to the processing capacity of the initiating node.

[0003] JP 2022-25720 A describes a credit device and credit system capable of calculating processing fees for digital currency information processing on a blockchain network. In particular, it describes an aspect in which the processing fees are calculated based on fee billing rules, and transaction history corresponding to the digital currency user identification information address is collected from the blockchain network and used as transaction information.

[0004] JP 2022-542168 A describes an asset trading system that ensures transparency of purchase history during online transactions of high-value assets, preventing counterfeiting or alteration. In particular, the system matches sales conditions, such as the number and price of divided ownership tokens to be sold, requested by a seller with purchase conditions, such as the number and price of divided ownership tokens to be purchased, requested by a buyer, and executes a transaction for the divided ownership tokens if the seller's sales conditions and the buyer's purchase conditions match. Each time a transaction is completed, the details of the transaction are added or reflected in a ledger for the asset registered in a transaction history information database.

[0005] JP 2021-33360 A describes a method of acquiring blockchain data containing multiple transaction histories of virtual currencies, acquiring chart data showing the price fluctuations of the virtual currencies over time, and displaying on a screen some of the multiple transaction histories contained in the blockchain data and the chart data showing the price fluctuations of the virtual currencies over a specified period of time.

[0006] JP 2021-18514 A describes a technology for proving that data collected by companies and the like has not been tampered with, and in particular describes an aspect in which a transaction is sent to a blockchain, a recommended fee is calculated for immediate approval of the transaction being written to the blockchain, and costs are calculated based on the recommended fee and the number of transactions.

[0007] The cost of using a public blockchain (gas fee) is determined dynamically based on the congestion level at the time a transaction is approved and the price of the public blockchain token itself, and the range of fluctuations is large. As a result, companies using public blockchains face the challenge of finding it difficult to estimate the operating costs of the entire system over a certain period of time.

[0008] Depending on the type of blockchain, it is possible to stabilize transaction fees by specifying a gas fee when a transaction occurs and waiting until it is approved. However, if this method is adopted, there is a problem in that it is not known when the transaction will be approved, and if no writing to the blockchain occurs for a long period of time, the reliability of transaction execution decreases.

[0009] In one aspect, the present invention aims to provide an information processing method, an information processing device, and an information processing program that can determine the timing of transaction execution taking into account the transaction fee for the transaction and the reliability of the transaction execution.

[0010] A first aspect of the present disclosure is an information processing method that determines the timing of executing an additional transaction to the blockchain based on a history of transaction fees for transactions for writing a trail to the blockchain and a history of when a trail was written to the blockchain.

[0011] A second aspect of the present disclosure is an information processing device, including a processor,

[0012] The timing of executing an additional transaction to the blockchain is determined based on the history of transaction fees for transactions for writing a trail to the blockchain and the history of when a trail was written to the blockchain.

[0013] A third aspect of the present disclosure is an information processing program that causes a computer to execute a process for determining the timing of executing an additional transaction to the blockchain based on a history of transaction fees related to transactions for writing a trail to the blockchain and a history of when a trail was written to the blockchain.

[0014] In one aspect, the timing of transaction execution can be determined taking into consideration the transaction fee for the transaction and the reliability of the transaction execution.

[0015] It is an explanatory diagram showing an example of the configuration of an information processing system. It is a schematic block diagram of an example of a computer that functions as a server and a user terminal of this embodiment. It is a block diagram showing the configuration of the server of this embodiment. It is a flowchart showing an execution timing determination processing routine in the server of this embodiment. It is a flowchart showing transaction execution processing in the server of this embodiment.

[0016] An example of an embodiment of the disclosed technology will be described below with reference to the drawings. Note that the same reference numerals are used to designate identical or equivalent components and parts in each drawing. Also, the dimensional proportions in the drawings are exaggerated for the sake of explanation and may differ from the actual proportions.

[0017] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed by connecting them with "and / or."

[0018] <System Configuration> Fig. 1 is an explanatory diagram showing an example configuration of an information processing system 2. In this embodiment, an information processing system 2 that executes transactions that write trails will be described. The information processing system 2 includes a server 10 and a user terminal 20. The server 10 and the user terminal 20 are communicatively connected via a network N. The server 10 is an example of an information processing device.

[0019] The server 10 is, for example, a server computer capable of various information processing and sending and receiving information. Note that the device equivalent to the server 10 is not limited to a server computer, but may be, for example, a personal computer. In this embodiment, the server 10 functions as an information processing device that determines the execution timing of a transaction for writing a trail and executes the transaction according to the determined execution timing.

[0020] The user terminal 20 is a general-purpose computer such as a personal computer. In this embodiment, the user terminal 20 functions as a device that requests the server 10 to write a trail to the blockchain.

[0021] In this embodiment, the server 10 determines the timing of transaction execution and executes the transaction, but the local user terminal 20 may determine the timing of transaction execution and execute the transaction. In other words, the distinction between the two is for convenience, and a single computer may perform the series of processes.

[0022] <Configuration of Server According to This Embodiment> FIG. 2 is a block diagram showing the hardware configuration of the server 10 according to this embodiment.

[0023] 2, the server 10 includes a CPU (Central Processing Unit) 11, a ROM (Read Only Memory) 12, a RAM (Random Access Memory) 13, a storage 14, an input unit 15, a display unit 16, and a communication interface (I / F) 17. Each component is connected to each other via a bus 19 so as to be able to communicate with each other.

[0024] The CPU 11 is a central processing unit that executes various programs and controls each component. That is, the CPU 11 reads programs from the ROM 12 or the storage 14 and executes the programs using the RAM 13 as a work area. The CPU 11 controls the above-described components and performs various arithmetic processing in accordance with the programs stored in the ROM 12 or the storage 14. In this embodiment, the ROM 12 or the storage 14 stores an information processing program for determining the execution timing of transactions and for executing transactions. The information processing program may be a single program or a group of programs composed of multiple programs or modules.

[0025] The ROM 12 stores various programs and various data. The RAM 13 temporarily stores programs or data as a working area. The storage 14 is configured with an HDD (Hard Disk Drive) or an SSD (Solid State Drive) and stores various programs including the operating system and various data.

[0026] The input unit 15 includes a pointing device such as a mouse and a keyboard, and is used to input various types of information.

[0027] The display unit 16 is, for example, a liquid crystal display, and displays various information. The display unit 16 may be a touch panel type and function as the input unit 15.

[0028] The communication interface 17 is an interface for communicating with other devices, and uses standards such as Ethernet (registered trademark), FDDI, and Wi-Fi (registered trademark).

[0029] Next, a description will be given of the functional configuration of the server 10. Fig. 3 is a block diagram showing an example of the functional configuration of the server 10.

[0030] As shown in FIG. 3, the server 10 functionally comprises a first model generation unit 110, a second model generation unit 112, an execution timing determination unit 114, and a transaction execution unit 116.

[0031] The first model generation unit 110 creates a first stochastic process model for predicting transaction fees based on the history of transaction fees for transactions for writing evidence to the blockchain 50.

[0032] Specifically, the transaction fee history is obtained from the fee history database 40 that stores the history of transaction fees for past transactions, and a pair of past transaction fee market price f and time t (f １ , t ｐ，１ ), (f ２ , t ｐ，２ ), ...(f ｎ , t ｐ，ｎ ) to create a first stochastic process model.

[0033] Here, the history of transaction fees stored in the fee history database 40 is, for example, a graph of publicly available transaction fee rates and a record of transaction fees paid for past trail writing.

[0034] The blockchain 50 is constructed by a blockchain network consisting of multiple computer terminals, and is a chronological sequence of blocks 51 each containing a trail. The server 10 can prevent tampering with the trail by writing the trail to a block 51 on the blockchain 50 each time a trail is written.

[0035] The second model generation unit 112 creates a second stochastic process model for predicting the timing at which a trail writing request to the blockchain 50 will occur at the user terminal 20, based on the history of trail writing requests to the blockchain 50 occurring at the user terminal 20.

[0036] Specifically, the second model generation unit 112 acquires the history of trail write requests from the write occurrence history database 42, which stores the history of trail write requests to the blockchain 50 that were issued in the past in the user terminal 20. The second model generation unit 112 acquires the history of trail write requests from the time t ｒ，１ , t ｒ，２ , ..., t ｒ，ｎ From this, a second stochastic process model can be created by assuming a distribution of occurrence times such as an exponential distribution.

[0037] The history of occurrences of trail writing requests stored in the writing occurrence history database 42 is, for example, a history of the times when trail writing requests were made in the past on the user terminal 20 in question.

[0038] The execution timing determination unit 114 determines the execution timing of an additional transaction to the blockchain 50 based on the first stochastic process model and the second stochastic process model.

[0039] Specifically, the execution timing determination unit 114 determines the execution timing of the additional transaction so as to optimize an objective function, which is expressed using the timing of the occurrence of the trail writing predicted based on the second stochastic process model and the transaction fee at the execution timing of the additional transaction corresponding to the timing of the occurrence of the trail writing predicted based on the first stochastic process model.

[0040] More specifically, the objective function is expressed using the expected value of the transaction fee at the time of execution of the additional transaction, the standard deviation (variance) of the transaction fee at the time of execution of the additional transaction, and the waiting time from the time of occurrence of the trail writing to the time of execution of the additional transaction.

[0041] In this optimization calculation of the objective function, it is defined as a multi-objective optimization problem that optimizes three factors: (i) the standard deviation (variance) of the total value of transaction fees, (ii) the expected value of the total value of transaction fees, and (iii) the waiting time from when the trail is written to when the transaction is actually issued. In this case, a solution that simultaneously optimizes all objective functions does not generally exist, and a Pareto optimal curve is obtained. When the execution plan is actually executed, a point on the curve is selected based on the predetermined weighted sum of each of the objective functions.

[0042] There is a trade-off between (i) the standard deviation (variance) of the total transaction fees and (iii) the waiting time. If the write frequency is low (once a month), the standard deviation (variance) of transaction fees will be small, but the waiting time will be long. If the write frequency is high, the standard deviation (variance) will be large and the waiting time will be short.

[0043] (ii) Regarding the expected total value of transaction fees, if a large amount is specified as the transaction fee, the transaction will be written immediately, but in that case the waiting time will be short and the standard deviation (variance) will be small. Conversely, if a small amount is specified as the transaction fee, the waiting time will be long and the standard deviation (variance) will be large.

[0044] (iii) As an example of latency, if a transaction comes three times (high frequency) in one second (short time), you can expect writing to continue for a while, whereas if it comes once (low frequency) in one hour (long time), you can expect a longer latency.

[0045] For example, the objective function is expressed by the following equation:

[0046] However, F ｔ Let t be the transaction fee at time t predicted based on the first stochastic process model. ｉ The transaction that writes to the blockchain ｉ The time when the execution is performed is defined as τ. ｊ Let s be the time when the user terminal 20 makes the jth write request to the blockchain, predicted based on the first stochastic process model. ｉLet C be the oldest transaction number when executing a transaction that collectively writes to the i-th blockchain. １ , C ２ , C ３ is a weighting constant used to select one solution from the Pareto solutions. For example, C １ >C ２ >C ３ Let's say.

[0047] The decision variable obtained by this objective function optimization is the time t ｉ and a variable k that represents how many times a transaction that writes to the blockchain will ultimately be executed.

[0048] By optimizing this objective function, the time t ｉ and a variable k, which represents how many times a transaction that writes to the blockchain will ultimately be executed, are determined. At this time, the expected value of the transaction fee at the time of execution of the additional transaction is small, the variance of the transaction fee at the time of execution of the additional transaction is small, and the waiting time from the time when the trail is written to the time when the additional transaction is executed is short. ｉ and a variable k are determined.

[0049] In the objective function optimization, for example, the objective function is optimized for each value of k (k=1, 2, 3, ...). ｉ The value of k that minimizes the optimal value of the objective function is determined, and the determined value of k and the time t at that value of k are calculated. ｉ are determined as variables for optimizing the objective function.

[0050] In addition, in the modeling, the method of optimal control theory may be used instead of the method of objective function optimization. In addition, in the objective function optimization, it may be solved as an optimization problem of equivalent decision variables, or metaheuristics such as the Monte Carlo method may be used. In addition, the weight constant C １ , C ２ , C ３ may be fixed values ​​that can be manually adjusted each time, or may be realized in a way that dynamically changes using an algorithm. Furthermore, the first stochastic process model and the second stochastic process model may be parametric models defined by calculations between decision variables, or may be realized by regression using a non-parametric model such as a regression tree.

[0051] The transaction execution unit 116 actually executes the transaction to be added to the blockchain 50 according to the execution timing of the transaction to be added to the blockchain 50 determined by the execution timing determination unit 114.

[0052] <Configuration of User Terminal According to This Embodiment> FIG. 2 is a block diagram showing the hardware configuration of the user terminal 20 according to this embodiment.

[0053] 2, the user terminal 20, like the server 10, has a CPU 11, a ROM 12, a RAM 13, a storage 14, an input unit 15, a display unit 16, and a communication interface (I / F) 17. Each component is connected to each other via a bus 19 so as to be able to communicate with each other.

[0054] The ROM 12 or the storage 14 stores a program for requesting the server 10 to write a trail. This program may be a single program, or may be a group of programs made up of multiple programs or modules.

[0055] The input unit 15 receives a trail to be written to the blockchain 50. For example, the input unit 15 receives a trail related to medical data or inventory data.

[0056] When the CPU 11 receives a trail to be written to the blockchain 50, it requests the server 10 to write the trail.

[0057] <Operation of Server 10 According to This Embodiment> Next, the operation of the server 10 according to this embodiment will be described.

[0058] First, the CPU 11 reads out the information processing program from the ROM 12 or the storage 14, expands it in the RAM 13, and executes it, thereby performing the execution timing determination process shown in Fig. 4. If there are multiple user terminals 20, the execution timing determination process is performed for each user terminal 20.

[0059] First, in step S100 , the CPU 11 as the first model generation unit 110 obtains the history of transaction fees from the fee history database 40 .

[0060] In step S102, the CPU 11 functions as the first model generation unit 110 and updates the first stochastic process model for predicting transaction fees based on the history of transaction fees.

[0061] In step S104 , the CPU 11 , functioning as the second model generation unit 112 , acquires from the writing occurrence history database 42 the history of when a trail writing request was issued in the user terminal 20 .

[0062] In step S106, the CPU 11, as the second model generation unit 112, creates a second stochastic process model for predicting the timing of the occurrence of a trail writing request in the user terminal 20, based on the acquired history of occurrences of trail writing requests.

[0063] In step S108, the CPU 11, functioning as the execution timing determination unit 114, determines the execution timing of the additional transaction so as to optimize the objective function. Here, the execution timing of the additional transaction is determined to be longer than the waiting time, which will be described later. The objective function is expressed using the timing of the occurrence of the trail writing request, predicted based on the second stochastic process model, and the transaction fee at the execution timing of the additional transaction corresponding to the occurrence timing of the trail writing request, predicted based on the first stochastic process model.

[0064] In step S110, the CPU 11, functioning as the execution timing determination unit 114, determines an execution plan for the transaction based on the execution timing of the additional transaction determined in step S108.

[0065] In step S112, the CPU 11 determines whether a predetermined waiting time (for example, several hours, 24 hours, or one week) has elapsed, and if it determines that the waiting time has elapsed, returns to steps S100 and S104.

[0066] In this way, the execution timing determination process is realized by stepwise solving an optimization problem having stochastic variables and a regression problem for predicting the stochastic process of the decision variables.

[0067] Next, the CPU 11 reads the information processing program from the ROM 12 or the storage 14, loads it into the RAM 13, and executes it, thereby performing the transaction execution process shown in Fig. 5. Also, it is assumed that a trail writing request is input to the server 10 from the user terminal 20 at any time.

[0068] First, in step S120, the CPU 11 functions as the transaction execution unit 116 and reads the transaction execution plan obtained in the execution timing determination process.

[0069] In step S122, the CPU 11, functioning as the transaction execution unit 116, determines whether the execution conditions defined in the execution plan have been met. For example, if the current time is the execution timing defined in the execution plan and a new trail writing request has been received, it determines that the execution conditions have been met and proceeds to step S124. On the other hand, if the current time is not the execution timing defined in the execution plan or if a new trail writing request has not been received, it determines that the execution conditions have not been met and proceeds to step S126.

[0070] In step S124 , the CPU 11 functions as the transaction execution unit 116 to execute an additional transaction for writing a trail in accordance with the new trail writing request received from the user terminal 20 .

[0071] In step S126, the CPU 11 determines whether it is time to update the execution plan. For example, if a certain waiting time has elapsed, it is determined that it is time for the execution plan to be updated in the execution timing determination process, and the process returns to step S120. On the other hand, if the certain waiting time has not elapsed, it is determined that it is not time for the execution plan to be updated in the execution timing determination process, and the process returns to step S122.

[0072] In the above transaction execution process, step S126 may be omitted. In this case, the transaction execution plan obtained in the above execution timing determination process may be read in step S120 each time the transaction execution process is repeated.

[0073] As described above, the information processing system according to this embodiment determines the timing of executing an additional transaction to a blockchain based on the history of transaction fees and the history of when a request to write a trail has occurred. This allows the timing of transaction execution to be determined taking into consideration the transaction fees for the transaction and the reliability of the transaction execution. Furthermore, the timing of execution of the additional transaction can be controlled while balancing the transaction fees and reliability, taking into consideration the trade-off between the transaction fees for the transaction and the reliability of the transaction execution.

[0074] Furthermore, the optimization target variable in the objective function is the timing of transactions that write to the blockchain in bulk, and transactions are executed according to the solution obtained from the optimization calculation, which stabilizes the amount of transaction fees paid.

[0075] <Modifications> The present invention is not limited to the above-described embodiment, and various modifications and applications are possible without departing from the gist of the present invention.

[0076] For example, in the above embodiment, a transaction execution plan is calculated in advance from past history, and when a trail writing request occurs, the transaction is executed by referring to the transaction execution plan. However, this is not limited to this. For example, a transaction execution plan may be calculated by optimizing the objective function, taking into account not only past history but also currently pending transactions.

[0077] Furthermore, if a long-term trend in fluctuations in transaction fees is expected, optimizing the objective function over a long time span may increase the number of variables to be optimized, making it difficult to find an optimal solution. In such cases, it may be possible to first optimize the objective function corresponding to the long-term trend to determine the variables to be optimized, and then perform multi-stage optimization by sequentially repeating the optimization of the objective function over a relatively short time period.

[0078] In each of the above embodiments, the various processes executed by the CPU after reading the software (program) may be executed by various processors other than the CPU. Examples of such processors include a PLD (Programmable Logic Device) whose circuit configuration can be changed after manufacture, such as an FPGA (Field-Programmable Gate Array), and a dedicated electrical circuit, such as an ASIC (Application Specific Integrated Circuit), which is a processor having a circuit configuration designed specifically for executing specific processes. Furthermore, the execution timing determination process and the transaction execution process may be executed by one of these various processors, or may be executed by a combination of two or more processors of the same or different types (e.g., multiple FPGAs, or a combination of a CPU and an FPGA). Furthermore, the hardware structure of these various processors is, more specifically, an electrical circuit that combines circuit elements such as semiconductor elements.

[0079] In addition, in each of the above embodiments, the information processing program is pre-stored (installed) in the storage 14, but this is not limiting. The program may be provided in a form stored on a non-transitory storage medium such as a CD-ROM (Compact Disk Read Only Memory), a DVD-ROM (Digital Versatile Disk Read Only Memory), or a USB (Universal Serial Bus) memory. The program may also be downloaded from an external device via a network.

[0080] The embodiments disclosed herein are to be considered as illustrative in all respects and not restrictive. The scope of the present invention is defined by the claims, not by the above meaning, and is intended to include all modifications within the meaning and scope of the claims.

[0081] The following additional notes are provided regarding the above-described embodiments.

[0082] (Supplementary Note 1) An information processing method for determining the timing of executing an additional transaction to a blockchain based on the history of transaction fees for transactions for writing a trail to a blockchain and the history of when a trail was written to the blockchain.

[0083] (Appendix 2) An information processing method according to Appendix 1, which determines the timing of execution of the additional transaction based on a stochastic process model of transaction fees obtained from the history of transaction fees and / or a stochastic process model of the timing of trail writing obtained from the history of trail writing.

[0084] (Supplementary Note 3) An information processing method according to Supplementary Note 2, which determines the timing of execution of the additional transaction so as to optimize an objective function expressed using the timing of occurrence of the trail writing, estimated based on a stochastic process model of the timing of the trail writing, and the transaction fee at the execution timing of the additional transaction corresponding to the timing of occurrence of the trail writing, estimated based on a stochastic process model of the transaction fee.

[0085] (Supplementary Note 4) The information processing method according to Supplementary Note 3, wherein the objective function is expressed using: an expected value of the transaction fee at the timing of execution of the estimated additional transaction; a standard deviation of the transaction fee at the timing of execution of the estimated additional transaction; and a waiting time from the timing of the occurrence of trail writing to the timing of execution of the estimated additional transaction.

[0086] (Supplementary Note 5) An information processing device including a processor, wherein the processor determines the timing of executing an additional transaction to the blockchain based on a history of transaction fees for transactions for writing a trail to the blockchain and a history of when a trail was written to the blockchain.

[0087] (Supplementary Note 6) An information processing program that causes a computer to execute a process of determining the timing of executing an additional transaction to the blockchain based on the history of transaction fees for transactions for writing a trail to the blockchain and the history of when a trail was written to the blockchain.

[0088] The disclosure of Japanese Application No. 2023-203245 is incorporated herein by reference in its entirety.

[0089] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

Claims

1. An information processing method for determining the timing of executing an additional transaction to a blockchain based on the history of transaction fees for transactions for writing a trail to a blockchain and the history of when writing a trail to the blockchain occurred.

2. An information processing method as described in claim 1, further comprising determining the timing of execution of the additional transaction based on a stochastic process model of transaction fees obtained from the history of transaction fees and / or a stochastic process model of the timing of trail writing obtained from the history of trail writing.

3. An information processing method as described in claim 2, further comprising determining the timing of execution of the additional transaction so as to optimize an objective function expressed using the timing of occurrence of the trail writing, which is estimated based on a stochastic process model of the timing of the trail writing, and the transaction fee at the timing of execution of the additional transaction corresponding to the timing of occurrence of the trail writing, which is estimated based on a stochastic process model of the transaction fee.

4. An information processing method as described in claim 3, wherein the objective function is expressed using: an expected value of the transaction fee at the timing of execution of the estimated additional transaction; a standard deviation of the transaction fee at the timing of execution of the estimated additional transaction; and a waiting time from the timing of trail writing to the timing of execution of the estimated additional transaction.

5. An information processing device including a processor, the processor determining the timing of executing an additional transaction to the blockchain based on a history of transaction fees for transactions for writing a trail to the blockchain and a history of when writing a trail to the blockchain occurred.

6. An information processing program that causes a computer to execute a process of determining the timing of executing an additional transaction to the blockchain based on the history of transaction fees for transactions for writing a trail to the blockchain and the history of when writing a trail to the blockchain occurred.

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