A financial data transmission path optimization method and device and a storage medium

Abstract

The present specification relates to the technical field of blockchains, and can be applied to the financial field, in particular to a financial data transmission path optimization method and device and a storage medium, comprising: obtaining multiple groups of transmission paths composed of multiple transmission nodes, the transmission nodes including routing nodes with routing functions, and verification nodes with routing functions and verification functions, the routing functions being used for forwarding financial data, and the verification functions being used for forwarding the financial data while consensus verifying the financial data; calculating, for each group of transmission paths, a transmission performance score of each group of transmission paths according to routing performance of each transmission node; determining a number of verification nodes in each group of transmission paths, and determining a multiplexing score of each group of transmission paths according to the number of verification nodes; and ranking each group of transmission paths according to the transmission performance score and the multiplexing score and determining a final transmission path, which can realize optimization of a financial data transmission path, reduce a loss value of financial data, and significantly improve a financial data transmission speed.

Description

Technical Field

[0001] The embodiments in this specification relate to the field of blockchain technology and can be applied to the financial field, particularly a method, apparatus, and storage medium for optimizing financial data transmission paths. Background Technology

[0002] Financial data refers to market data, company data, industry indices, and pricing data related to the financial industry. All data related to the financial industry can be incorporated into the financial market big data system to provide reference for practitioners in market analysis. There are many academic definitions, but a simple example is that the price data of a stock over a period of time, arranged in a predetermined chronological order, can be considered financial data. However, current technology typically uses a fixed transmission path when transmitting financial data from the sending end to the receiving end. When a large amount of financial data is transmitted in parallel along this fixed path, the data transmission loss is relatively high. Summary of the Invention

[0003] In view of the above-mentioned problems in the prior art, the purpose of this specification is to provide a method, apparatus and storage medium for optimizing financial data transmission paths, so as to solve the problem of high loss value in the data transmission process in the prior art.

[0004] To solve the above-mentioned technical problems, the specific technical solution in this specification is as follows:

[0005] On the one hand, this specification provides a method for optimizing financial data transmission paths, including:

[0006] Multiple transmission paths composed of multiple transmission nodes are obtained, wherein the starting point of the transmission path is the financial data sending end, the ending point of the transmission path is the financial data receiving end, and the transmission nodes include routing nodes with routing function and verification nodes with routing function and verification function. The routing function is used to forward the financial data, and the verification function is used to verify the financial data through consensus while forwarding the financial data.

[0007] For each group of transmission paths, a transmission performance score is calculated based on the routing performance of each transmission node.

[0008] Determine the number of verification nodes in each transmission path group, and determine the multiplexing score of each transmission path group based on the number of verification nodes.

[0009] Each group of transmission paths is ranked based on the transmission performance score and the multiplexing score, and the final transmission path is determined.

[0010] As one embodiment of this specification, obtaining the transmission path composed of the various transmission nodes further includes:

[0011] Transmission nodes with computing resources exceeding the computing threshold are designated as idle transmission nodes.

[0012] By using enumeration, different idle transmission nodes are combined to form multiple transmission paths from the financial data sender to the financial data receiver.

[0013] As an embodiment of this document, the calculation of a transmission performance score for each group of transmission paths based on the routing performance of each transmission node further includes:

[0014] Calculate the transmission performance score for each transmission path using the following formula:

[0015]

[0016] Where, N t P is the transmission performance score for the t-th transmission path. ti K represents the remaining computing resources of the i-th transmission node in the t-th transmission path. ia Let I be the computing power of the graphics card in the i-th transmission node. t Let be the total number of transmission nodes in the t-th transmission path.

[0017] As an embodiment of this document, determining the number of verification nodes in each group of transmission paths and determining the multiplexing fraction of each group of transmission paths based on the number of verification nodes further includes:

[0018] Calculate the multiplexing fraction for each transmission path using the following formula:

[0019]

[0020] Among them, D t Let F be the multiplexing fraction of the t-th transmission path. t Let I be the number of verification nodes in the t-th transmission path, and α be the additional weight of the verification nodes. t Let be the total number of transmission nodes in the t-th transmission path.

[0021] As an embodiment of this document, the step of ranking each group of transmission paths and determining the final transmission path based on the transmission performance score and the multiplexing score further includes:

[0022] Calculate the overall score for each group of transmission paths using the following formula:

[0023] M t =N t +D t

[0024] Among them, M t Let N be the overall score of the t-th transmission path. tD is the transmission performance score for the t-th transmission path. t Let be the multiplexing fraction of the t-th transmission path;

[0025] The paths are ranked from highest to lowest based on the overall score.

[0026] As one embodiment of this specification, after determining the final transmission path, the method further includes:

[0027] Each transmission node in the final transmission path forwards the financial data;

[0028] The verification nodes in the final transmission path perform consensus verification on the financial data while forwarding it.

[0029] Once the financial data receiving end receives the financial data, it initiates consensus verification in the blockchain network;

[0030] When the verification node receives the consensus verification request, it directly provides the verification result;

[0031] When the consensus verification of the blockchain network is successful, the financial data is stored in the blockchain.

[0032] As one embodiment of this specification, the method for selecting candidate nodes includes:

[0033] Within the time window, a response speed verification mechanism is used to select the top-performing verification nodes as candidate nodes.

[0034] As one embodiment of this specification, storing financial data in a blockchain further includes:

[0035] After the leader node broadcasts the financial data to all the verification nodes, the leader node verifies whether the financial data stored by all the follower nodes is consistent with the financial data it broadcasts.

[0036] If they match, the financial data will be stored in the blockchain;

[0037] If there is a discrepancy, a re-verification instruction is sent to the follower node, which is then instructed to send financial data request information to the remaining follower nodes.

[0038] As one embodiment of this specification, before the leader node receives the financial data, the following is included:

[0039] The financial data received by the financial data receiving end is imported into the trained knowledge graph embedding model to obtain financial data in a unified format.

[0040] As one embodiment of this specification, the training method of the knowledge graph embedding model includes:

[0041] The entity vector and context entity vector of the financial data are calculated.

[0042] The entity vectors and the context entity vectors are mapped from the entity space to the word vector space through the relation-entity alignment transformation function, and the features are concatenated together as the input of the knowledge graph embedding model.

[0043] Several preset keywords are input into the Softmax classifier of the knowledge graph embedding model, and the output probability of financial data for each keyword is obtained after normalization.

[0044] The adaptive moment estimation algorithm is used to determine the minimization objective function of the knowledge graph embedding model;

[0045] The model parameters of the knowledge graph embedding model are updated in each iteration by backpropagation until the minimization objective function of the knowledge graph embedding model satisfies the preset conditions, thereby obtaining the trained knowledge graph embedding model, wherein the input of the knowledge graph embedding model is the financial data and the output is the keywords of the financial data.

[0046] As one embodiment of this specification, after the financial data is stored in the blockchain, the following steps are included:

[0047] The leader node enters a dormant state, and the leader node and the follower node are restored as candidate nodes. During the dormant state, the candidate node is prohibited from applying to become the leader node until the dormant state ends.

[0048] As one embodiment of this specification, after importing the financial data received by the financial data receiving end into the trained knowledge graph embedding model to obtain financial data in a unified format, the process includes:

[0049] Collect relevant processing information from staff, optimize and update the knowledge graph embedding model based on the processing information, and generate relevant update logs for operation and maintenance personnel to view.

[0050] On the other hand, this specification also provides a financial data transmission path optimization device, comprising:

[0051] The acquisition unit is used to acquire multiple sets of transmission paths composed of multiple transmission nodes, wherein the starting point of the transmission path is the financial data sending end, the ending point of the transmission path is the financial data receiving end, and the transmission node includes a routing node with routing function and a verification node with routing function and verification function. The routing function is used to forward the financial data, and the verification function is used to verify the financial data in consensus while forwarding the financial data.

[0052] A transmission performance calculation unit is used to calculate the transmission performance score of each group of transmission paths based on the routing performance of each transmission node.

[0053] The multiplexing performance calculation unit is used to determine the number of verification nodes in each group of transmission paths and to determine the multiplexing score of each group of transmission paths based on the number of verification nodes.

[0054] The ranking unit is used to rank each group of transmission paths and determine the final transmission path based on the transmission performance score and the multiplexing score.

[0055] On the other hand, this specification also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement any of the financial data transmission path optimization methods described above.

[0056] On the other hand, this specification also provides a computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor, provides any one of the financial data transmission path optimization methods described above.

[0057] By employing the above technical solution, multiple transmission paths composed of multiple transmission nodes are obtained. The starting point of each transmission path is a financial data sender, and the ending point is a financial data receiver. Each transmission node includes a routing node with routing functionality and a verification node with both routing and verification functions. The routing function forwards the financial data, and the verification function simultaneously verifies the financial data upon forwarding. This allows for the acquisition of multiple transmission paths, each containing several routing and verification nodes. The routing nodes can only forward financial data, while the verification nodes can not only forward data but also verify it before it is uploaded to the blockchain. By reusing verification nodes, subsequent blockchain verification time can be saved. Furthermore, by calculating the transmission performance score for each transmission path based on the routing performance of each transmission node, the performance of each path can be determined. A transmission performance score is used to evaluate factors affecting transmission efficiency, such as transmission speed and latency. By determining the number of verification nodes in each transmission path group, and then assigning a reuse score to each group, the number of verification nodes in each path can be determined. These verification nodes can handle both forwarding financial data and pre-chain verification. Ranking each transmission path based on the transmission performance score and reuse score, and determining the final transmission path, allows for the selection of a path with faster transmission speed and faster on-chain financial data processing. This path considers both the forwarding time of financial data and the waiting time for on-chain verification, integrating these two factors to allow some pre-chain verification to be completed during forwarding, thus reducing the time from forwarding to final on-chain processing.

[0058] To make the above and other objects, features and advantages of this specification more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0059] To more clearly illustrate the technical solutions in the embodiments or prior art of this specification, the drawings used in the description of the embodiments or prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this specification. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0060] Figure 1 This specification illustrates an overall system diagram of a financial data transmission path optimization method according to an embodiment.

[0061] Figure 2This specification illustrates a step diagram of a financial data transmission path optimization method according to an embodiment of the present invention.

[0062] Figure 3 This specification illustrates a schematic diagram of the nodes between the financial data sender and the financial data receiver in an embodiment of the specification.

[0063] Figure 4 A schematic diagram illustrating the training method of the knowledge graph embedding model in the embodiments of this specification is shown;

[0064] Figure 5 This specification illustrates a schematic diagram of financial data being uploaded to the blockchain according to an embodiment.

[0065] Figure 6 This specification shows a schematic diagram of a financial data transmission path optimization device according to an embodiment of the present specification;

[0066] Figure 7 A schematic diagram of a computer device according to an embodiment of this specification is shown.

[0067] Explanation of symbols in the attached drawings:

[0068] 101. Financial data sending end;

[0069] 102. Transmission Node;

[0070] 103. Verification Node;

[0071] 104. Financial data receiving end;

[0072] 601. Acquisition Unit;

[0073] 602. Transmission performance calculation unit;

[0074] 603. Reusable performance calculation unit;

[0075] 604, Ranking Unit;

[0076] 702. Computer equipment;

[0077] 704, Processor;

[0078] 706. Memory;

[0079] 708. Drive mechanism;

[0080] 710. Input / Output Module;

[0081] 712. Input devices;

[0082] 714. Output devices;

[0083] 716. Presentation equipment;

[0084] 718. Graphical User Interface;

[0085] 720. Network interface;

[0086] 722. Communication link;

[0087] 724. Communication bus. Detailed Implementation

[0088] The technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this specification, and not all embodiments. Based on the embodiments in this specification, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this specification.

[0089] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, apparatus, product, or device that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or devices.

[0090] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in the embodiments of this specification are all information and data authorized by the user or fully authorized by all parties.

[0091] like Figure 1 The overall system diagram of a financial data transmission path optimization method shown includes: financial data sending end 101, transmission node 102, verification node 103, and financial data receiving end 104.

[0092] The financial data transmitter 101 is used to send financial data. Several transmission nodes and verification nodes are set between the financial data transmitter and the financial data receiver. Several transmission nodes and verification nodes can form several transmission paths. It should be noted that in this specification, the transmission path is a virtual path, that is, any two transmission nodes and verification nodes, two transmission nodes and transmission nodes, or two verification nodes and verification nodes can transmit data. Therefore, during the preparation of financial data transmission, several verification nodes and transmission nodes can be planned to form a transmission path to transmit financial data.

[0093] Transmission node 102 is used to forward financial data.

[0094] Verification node 103 is used to verify financial data while forwarding it.

[0095] The financial data receiving end 104 is used to receive financial data, translate the financial data, extract some words from the financial data, and then store it in the blockchain.

[0096] In existing technologies, financial data is often transmitted through dedicated transmission paths. These dedicated transmission paths are constructed using a fixed number of transmission nodes. When a transmission node in the dedicated transmission path fails or malfunctions, financial data cannot be transmitted. Furthermore, during transmission, the transmission nodes can only forward financial data and cannot be reused. Therefore, the process of transmitting financial data to the blockchain is time-consuming, and the process of transmitting financial data to storage is also time-consuming.

[0097] To address the aforementioned issues, embodiments of this specification provide a method for optimizing financial data transmission paths, which takes into account the multiplexing function of transmission nodes and improves the efficiency of transmitting financial data to storage. Figure 2 This diagram illustrates the steps of a financial data transmission path optimization method provided in the embodiments of this specification. This specification provides the operational steps of the method described in the embodiments or flowcharts, but based on conventional or non-inventive labor, more or fewer operational steps may be included. The order of steps listed in the embodiments is merely one possible execution order among many and does not represent the only possible execution order. In actual system or device products, the methods shown in the embodiments or drawings can be executed sequentially or in parallel. Specifically, as shown in the diagrams... Figure 2 As shown, the method may include:

[0098] Step 201: Obtain multiple sets of transmission paths composed of multiple transmission nodes, wherein the starting point of the transmission path is the financial data sending end, the ending point of the transmission path is the financial data receiving end, and the transmission node includes a routing node with routing function and a verification node with routing function and verification function. The routing function is used to forward the financial data, and the verification function is used to verify the financial data in consensus while forwarding the financial data.

[0099] Step 202: For each group of transmission paths, calculate the transmission performance score of each group of transmission paths based on the routing performance of each transmission node;

[0100] Step 203: Determine the number of verification nodes in each transmission path group, and determine the multiplexing score of each transmission path group based on the number of verification nodes.

[0101] Step 204: Rank each group of transmission paths according to the transmission performance score and the multiplexing score, and determine the final transmission path.

[0102] By employing the above technical solution, multiple transmission paths composed of multiple transmission nodes are obtained. The starting point of each transmission path is a financial data sender, and the ending point is a financial data receiver. Each transmission node includes a routing node with routing functionality and a verification node with both routing and verification functions. The routing function forwards the financial data, and the verification function simultaneously verifies the financial data upon forwarding. This allows for the acquisition of multiple transmission paths, each containing several routing and verification nodes. The routing nodes can only forward financial data, while the verification nodes can not only forward data but also verify it before it is uploaded to the blockchain. By reusing verification nodes, subsequent blockchain verification time can be saved. Furthermore, by calculating the transmission performance score for each transmission path based on the routing performance of each transmission node, the performance of each path can be determined. A transmission performance score is used to evaluate factors affecting transmission efficiency, such as transmission speed and latency. By determining the number of verification nodes in each transmission path group, and then assigning a reuse score to each group, the number of verification nodes in each path can be determined. These verification nodes can handle both forwarding financial data and pre-chain verification. Ranking each transmission path based on the transmission performance score and reuse score, and determining the final transmission path, allows for the selection of a path with faster transmission speed and faster on-chain financial data processing. This path considers both the forwarding time of financial data and the waiting time for on-chain verification, integrating these two factors to allow some pre-chain verification to be completed during forwarding, thus reducing the time from forwarding to final on-chain processing.

[0103] As one embodiment of this specification, obtaining the transmission path composed of the various transmission nodes further includes:

[0104] Transmission nodes with computing resources exceeding the computing threshold are designated as idle transmission nodes.

[0105] By using enumeration, different idle transmission nodes are combined to form multiple transmission paths from the financial data sender to the financial data receiver.

[0106] like Figure 3 The diagram illustrates the nodes between the financial data sender and receiver. In this specification, there are multiple transmission nodes and verification nodes between the financial data sender and receiver. For example, if there are nine transmission nodes and financial nodes in total, they can be divided into a first batch, a second batch, and a third batch according to the transmission process. The first batch includes three transmission nodes, the second batch includes three, and the third batch includes three, resulting in twenty-seven different transmission paths. Some of these paths may include one verification node, some may include two verification nodes, and so on. Since financial data needs permission from some verification nodes during the on-chain process, verification nodes can both forward data and perform verification during financial data transmission, reducing the number of verification nodes required for subsequent on-chain verification and improving on-chain efficiency.

[0107] As an embodiment of this specification, step 202, calculating the transmission performance score of each transmission path based on the routing performance of each node, further includes:

[0108] Calculate the transmission performance score for each transmission path using the following formula:

[0109]

[0110] Where, N t P is the transmission performance score for the t-th transmission path. ti K represents the remaining computing resources of the i-th transmission node in the t-th transmission path. ia Let I be the computing power of the graphics card in the i-th transmission node. t Let be the total number of transmission nodes in the t-th transmission path.

[0111] This transmission performance score characterizes the efficiency of each transmission node in forwarding financial data and the latency of each transmission node in transmitting financial data in a transmission path. Through this transmission performance score, the time from receiving financial data to sending the financial data to the receiving end of the financial data can be accurately identified.

[0112] In this instruction manual Figure 3 In the example, the transmission performance scores for twenty-seven transmission paths can be obtained.

[0113] As an embodiment of this specification, step 203, determining the number of verification nodes in each transmission path and determining the multiplexing fraction of each transmission path based on the number of verification nodes, further includes:

[0114] Calculate the multiplexing fraction for each transmission path using the following formula:

[0115]

[0116] Among them, D t Let F be the multiplexing fraction of the t-th transmission path. t Let I be the number of verification nodes in the t-th transmission path, and α be the additional weight of the verification nodes. t Let be the total number of transmission nodes in the t-th transmission path.

[0117] The reuse score represents the time saved by each verification node in a transmission path when verifying financial data while forwarding it. This transmission performance score can accurately identify the verification time saved by a transmission path from receiving financial data, sending financial data, and saving financial data on the blockchain.

[0118] As an embodiment of this specification, step 204, ranking each transmission path according to the transmission performance score and the multiplexing score, further includes:

[0119] Calculate the overall score for each group of transmission paths using the following formula:

[0120] M t =N t +D t

[0121] Among them, M t Let N be the overall score of the t-th transmission path. t D is the transmission performance score for the t-th transmission path. t Let be the multiplexing fraction of the t-th transmission path;

[0122] The paths are ranked from highest to lowest based on the overall score.

[0123] In this step, the transmission performance scores are used to rank the time taken by each transmission path to forward financial data. For example, the first transmission path scores 60 points, the second 50 points, the third 55 points, the fourth 61 points, the fifth 68 points, and so on. This ranking, from highest to lowest, yields the fifth, fourth, first, third, and second transmission paths.

[0124] Then, by using the reuse score, we can rank the time saved by each transmission path in simultaneously performing financial data verification and forwarding. For example, the first transmission path scores 10 points, the second transmission path scores 20 points, the third transmission path scores 15 points, the fourth transmission path scores 21 points, the fifth transmission path scores 18 points, and so on. In this way, we can obtain the transmission performance score ranking, from high to low: the fourth transmission path, the second transmission path, the fifth transmission path, the third transmission path, and the first transmission path.

[0125] The overall scores are calculated as follows: the first transmission path has a score of 60 + 10 = 70, the second transmission path has a score of 50 + 20 = 70, the third transmission path has a score of 55 + 15 = 70, the fourth transmission path has a score of 61 + 21 = 82, and the fifth transmission path has a score of 68 + 18 = 86. The final ranking based on the overall scores, from highest to lowest, is: the fifth transmission path, the fourth transmission path, the third transmission path, the second transmission path, and the first transmission path.

[0126] Therefore, based on the comprehensive score above, the fifth transmission path can be considered the final transmission path for the current financial data. Of course, this final transmission path is only for the current financial data transmission. During the continuous transmission of financial data by various transmission and verification nodes, some nodes may operate faster and have more remaining computing resources in the first few transmission cycles, making them more suitable for handling the current few cycles of financial data transmission. However, as financial data transmission continues, the computing resources of some transmission nodes or verification nodes in this final transmission path will tend to saturate. Therefore, the final transmission path in this specification is dynamic, and path planning can be performed each time financial data is transmitted to ensure transmission efficiency.

[0127] After determining the final transmission path, this manual also needs to translate the financial data received by the financial data receiving end, that is, to summarize and integrate the key information in the financial data so that users can understand it at a glance.

[0128] As an embodiment of this specification, it further includes, after the financial data receiving end receives the financial data, importing the financial data received by the financial data receiving end into the trained knowledge graph embedding model to obtain financial data in a unified format.

[0129] like Figure 4 The diagram shown illustrates a training method for a knowledge graph embedding model. As an embodiment of this specification, the training method for the knowledge graph embedding model includes:

[0130] Step 401: Calculate the entity vector and context entity vector of the financial data;

[0131] In this step, matrix transformation functions can be used to convert text-based financial data into vector-based data for subsequent calculations.

[0132] Step 402: Map the entity vector and the context entity vector from the entity space to the word vector space using the relation-entity alignment transformation function, and concatenate the features together as input to the knowledge graph embedding model;

[0133] In this step, words containing key information in the financial data can be used as entity vectors, and words connected to the key information can be used as context entity vectors. For example, if account A100 has withdrawn 10,000 yuan and the withdrawal of 10,000 yuan has been verified, then account A100 and the verification status can be used as context information.

[0134] Step 403: Input several preset keywords into the Softmax classifier of the knowledge graph embedding model, and obtain the output probability of financial data for each keyword after normalization;

[0135] In this step, for example, the final output consists of three words: A100 account +10000, A100 account -10000, and A100 account. The output probability of A100 account +10000 is 0.8, the output probability of A100 account -10000 is 0.5, and the output probability of A100 account is 0.5.

[0136] Step 404: Determine the minimization objective function of the knowledge graph embedding model using the adaptive moment estimation algorithm;

[0137] In this step, since the financial data in this manual shows a verified withdrawal of 10,000 yuan from account A100, the classifier should output a probability of 1.0 for account A100 + 10,000, a probability of 0 for account A100 - 10,000, and a probability of 0 for account A100. Therefore, by continuously optimizing the model by minimizing the objective function, better classification results can be achieved.

[0138] Step 405: Update the model parameters of the knowledge graph embedding model in each iteration through backpropagation until the minimization objective function of the knowledge graph embedding model satisfies the preset conditions, thereby obtaining the trained knowledge graph embedding model, wherein the input of the knowledge graph embedding model is the financial data and the output is the keywords of the financial data.

[0139] In this step, knowledge graphs can be used to quickly translate technical financial data terms into common-sense data that the general public can understand, so that it can be made public on the blockchain.

[0140] More preferably, after importing the financial data received by the financial data receiving end into the trained knowledge graph embedding model to obtain financial data in a unified format, the process includes:

[0141] Collect relevant processing information from staff, optimize and update the knowledge graph embedding model based on the processing information, and generate relevant update logs for operation and maintenance personnel to view.

[0142] Deploy relevant log collection plugins on different financial platforms or obtain log data recorded on different financial platforms through a syslog server, and filter out log information that meets the preset conditions of the staff.

[0143] The remaining log data is processed into a unified format. Then, the user operation behavior recorded in the processed log information is matched with the abnormal behavior characteristics, and corresponding alarm information is generated based on the matching results. At the same time, the risk score of each alarm information is calculated and the calculation result is output. Then, the alarm information is fed back to the relevant staff and the relevant operation process is interrupted.

[0144] As one embodiment of this specification, after translating the financial data to obtain the keywords of the financial data, the keywords can be uploaded to the blockchain. Similarly, the financial data can also be uploaded directly to the blockchain without translation. This specification does not limit this.

[0145] like Figure 5 The schematic diagram of financial data on-chain shown is an embodiment of this specification. After determining the final transmission path, it also includes:

[0146] Step 501: Each transmission node in the final transmission path forwards the financial data;

[0147] Step 502: The verification node in the final transmission path performs consensus verification on the financial data while forwarding it.

[0148] In steps 501-502, the final transmission path includes several transmission nodes and verification nodes. Transmission nodes can only forward financial data, while verification nodes can forward financial data and perform pre-chain verification of the financial data.

[0149] Step 503: After the financial data receiving end receives the financial data, it initiates consensus verification in the blockchain network;

[0150] In this step, the blockchain network includes all verification nodes in the blockchain. Before a certain financial data is expected to be uploaded to the chain, consensus verification is required. That is, the data can only be uploaded to the chain if more than a certain threshold percentage of verification nodes in the blockchain network agree. Since some verification nodes have already performed the verification of the financial data before it is uploaded to the chain in step 502, it is not necessary to broadcast the consensus verification to all verification nodes in the consensus verification stage. Moreover, the financial data can be uploaded to the chain if less than the threshold percentage of verification nodes agree.

[0151] In this step, the consensus verification process specifically includes:

[0152] Within the time window, a response speed verification mechanism is sent, selecting the top-performing verification nodes as candidate nodes. For example, if the blockchain network in this specification includes 100 verification nodes, a response speed verification mechanism, such as a calculation problem, is sent to the blockchain network. Once the verification node completes the verification, it broadcasts the result to the blockchain, thereby selecting the top ten verification nodes with the fastest response speeds from the 100 verification nodes as candidate nodes.

[0153] When the candidate nodes are selected, the first performance verification mechanism is sent to several candidate nodes in the verification nodes. One node is selected as the leader node and the other candidate nodes are selected as the follower nodes in the current time window.

[0154] The leader node receives the financial data and initiates consensus verification to other verification nodes that are not in the final transmission path.

[0155] Step 504: When the verification node receives the consensus verification request, it directly provides the verification result;

[0156] In this step, the verification result is either allowed or disallowed.

[0157] Step 505: When the consensus verification of the blockchain network is successful, the financial data is stored in the blockchain.

[0158] In this step, after the leader node broadcasts the financial data to all the verification nodes, the leader node verifies whether the financial data stored by all the follower nodes is consistent with the financial data it broadcast.

[0159] If they match, the financial data will be stored in the blockchain;

[0160] If there is a discrepancy, a re-verification instruction is sent to the follower node, which is then instructed to send financial data request information to the remaining follower nodes.

[0161] As one embodiment of this specification, after the financial data is stored in the blockchain, the following steps are included:

[0162] The leader node enters a dormant state, and the leader node and the follower node are restored as candidate nodes. During the dormant state, the candidate node is prohibited from applying to become the leader node until the dormant state ends.

[0163] This method allows for multiple rotations of leadership nodes, preventing cheating by leadership nodes.

[0164] This instruction manual also provides, for example Figure 6 The schematic diagram shown is of a financial data transmission path optimization device, comprising:

[0165] The acquisition unit 601 is used to acquire multiple sets of transmission paths composed of multiple transmission nodes, wherein the starting point of the transmission path is the financial data sending end, the ending point of the transmission path is the financial data receiving end, and the transmission node includes a routing node with routing function and a verification node with routing function and verification function. The routing function is used to forward the financial data, and the verification function is used to verify the financial data in consensus while forwarding the financial data.

[0166] The transmission performance calculation unit 602 is used to calculate the transmission performance score of each group of transmission paths based on the routing performance of each transmission node.

[0167] The multiplexing performance calculation unit 603 is used to determine the number of verification nodes in each group of transmission paths and to determine the multiplexing score of each group of transmission paths based on the number of verification nodes.

[0168] Ranking unit 604 is used to rank each group of transmission paths and determine the final transmission path based on the transmission performance score and the multiplexing score.

[0169] By employing the above technical solution, multiple transmission paths composed of multiple transmission nodes are obtained. The starting point of each transmission path is a financial data sender, and the ending point is a financial data receiver. Each transmission node includes a routing node with routing functionality and a verification node with both routing and verification functions. The routing function forwards the financial data, and the verification function simultaneously verifies the financial data upon forwarding. This allows for the acquisition of multiple transmission paths, each containing several routing and verification nodes. The routing nodes can only forward financial data, while the verification nodes can not only forward data but also verify it before it is uploaded to the blockchain. By reusing verification nodes, subsequent blockchain verification time can be saved. Furthermore, by calculating the transmission performance score for each transmission path based on the routing performance of each transmission node, the performance of each path can be determined. A transmission performance score is used to evaluate factors affecting transmission efficiency, such as transmission speed and latency. By determining the number of verification nodes in each transmission path group, and then assigning a reuse score to each group, the number of verification nodes in each path can be determined. These verification nodes can handle both forwarding financial data and pre-chain verification. Ranking each transmission path based on the transmission performance score and reuse score, and determining the final transmission path, allows for the selection of a path with faster transmission speed and faster on-chain financial data processing. This path considers both the forwarding time of financial data and the waiting time for on-chain verification, integrating these two factors to allow some pre-chain verification to be completed during forwarding, thus reducing the time from forwarding to final on-chain processing.

[0170] like Figure 7The illustration shows a computer device 702 provided in an embodiment of this specification. The computer device runs the financial data transmission path optimization method described in this specification. The computer device 702 may include one or more processors 704, such as one or more central processing units (CPUs), each of which can implement one or more hardware threads. The computer device 702 may also include any memory 706 for storing information of any kind, such as code, settings, data, etc. Non-limitingly, for example, the memory 706 may include any type of RAM, any type of ROM, flash memory, hard disk, optical disk, etc. More generally, any memory can use any technology to store information. Further, any memory can provide volatile or non-volatile retention of information. Further, any memory can represent a fixed or removable component of the computer device 702. In one case, when the processor 704 executes associated instructions stored in any memory or combination of memories, the computer device 702 can perform any operation of the associated instructions. The computer device 702 also includes one or more drive mechanisms 708 for interacting with any memory, such as hard disk drive mechanisms, optical disk drive mechanisms, etc.

[0171] Computer device 702 may also include an input / output module 710 (I / O) for receiving various inputs (via input device 712) and providing various outputs (via output device 714). A specific output mechanism may include a presentation device 716 and an associated graphical user interface (GUI) 718. In other embodiments, the input / output module 710 (I / O), input device 712, and output device 714 may be omitted, and the device may function solely as a computer device within a network. Computer device 702 may also include one or more network interfaces 720 for exchanging data with other devices via one or more communication links 722. One or more communication buses 724 couple the components described above together.

[0172] Communication link 722 can be implemented in any way, such as via a local area network, a wide area network (e.g., the Internet), a point-to-point connection, or any combination thereof. Communication link 722 may include any combination of hardwired links, wireless links, routers, gateway functions, name servers, etc., governed by any protocol or combination of protocols.

[0173] Corresponding to Figures 2-5 In addition to the methods described above, embodiments of this specification also provide a computer-readable storage medium storing a computer program that, when executed by a processor, performs the steps of the methods described above.

[0174] This specification also provides computer-readable instructions, wherein when a processor executes the instructions, the program therein causes the processor to perform the following... Figures 2-5 The method shown.

[0175] It should be understood that in the various embodiments of this specification, the sequence number of each process does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this specification.

[0176] It should also be understood that, in the embodiments of this specification, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this specification generally indicates that the preceding and following related objects have an "or" relationship.

[0177] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed in this specification can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of each example have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this specification.

[0178] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0179] In the several embodiments provided in this specification, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the couplings or direct couplings or communication connections shown or discussed may be indirect couplings or communication connections through some interfaces, devices, or units, or they may be electrical, mechanical, or other forms of connection.

[0180] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of the embodiments described in this specification, depending on actual needs.

[0181] Furthermore, the functional units in the various embodiments of this specification can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0182] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this specification, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this specification. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0183] This specification uses specific embodiments to illustrate the principles and implementation methods of this specification. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this specification. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this specification. Therefore, the content of this specification should not be construed as a limitation of this specification.

Claims

1. A method for optimizing financial data transmission paths, characterized in that, include: Multiple transmission paths composed of multiple transmission nodes are obtained, wherein the starting point of the transmission path is the financial data sending end, the ending point of the transmission path is the financial data receiving end, and the transmission nodes include routing nodes with routing function and verification nodes with routing function and verification function. The routing function is used to forward the financial data, and the verification function is used to verify the financial data through consensus while forwarding the financial data. For each group of transmission paths, a transmission performance score is calculated based on the routing performance of each transmission node; wherein, the routing performance includes the remaining computing resources of the transmission nodes and the computing power of the graphics cards; The number of verification nodes in each transmission path is determined, and the multiplexing score of each transmission path is determined based on the number of verification nodes; wherein, the multiplexing score is used to characterize the time saved by each verification node in a transmission path when verifying financial data while forwarding it. Each group of transmission paths is ranked based on the transmission performance score and the multiplexing score, and the final transmission path is determined. The step of calculating a transmission performance score for each group of transmission paths based on the routing performance of each transmission node further includes: Calculate the transmission performance score for each transmission path using the following formula: in, The transmission performance score for the t-th transmission path is... Let be the remaining computing resources of the i-th transmission node in the t-th transmission path. Let i be the computing power of the graphics card in the i-th transmission node. Let be the total number of transmission nodes in the t-th transmission path; The step of determining the number of verification nodes in each transmission path group and determining the multiplexing score of each transmission path group based on the number of verification nodes further includes: Calculate the multiplexing fraction for each transmission path using the following formula: in, Let be the multiplexing fraction of the t-th transmission path. Let be the number of verification nodes in the t-th transmission path. To verify the additional weights of the nodes, Let be the total number of transmission nodes in the t-th transmission path; The step of ranking each group of transmission paths and determining the final transmission path based on the transmission performance score and the multiplexing score further includes: Calculate the overall score for each group of transmission paths using the following formula: in, Let be the overall score of the t-th transmission path. The transmission performance score for the t-th transmission path is... Let be the multiplexing fraction of the t-th transmission path; The paths are ranked from highest to lowest based on the overall score.

2. The financial data transmission path optimization method according to claim 1, characterized in that, The acquisition of multiple sets of transmission paths composed of multiple transmission nodes further includes: Transmission nodes with computing resources exceeding the computing threshold are designated as idle transmission nodes. By using enumeration, different idle transmission nodes are combined to form multiple transmission paths from the financial data sender to the financial data receiver.

3. The financial data transmission path optimization method according to claim 1, characterized in that, After determining the final transmission path, the following is also included: Each transmission node in the final transmission path forwards the financial data; The verification nodes in the final transmission path perform consensus verification on the financial data while forwarding it. Once the financial data receiving end receives the financial data, it initiates consensus verification in the blockchain network; When the verification node receives the consensus verification request, it directly provides the verification result; When the consensus verification of the blockchain network is successful, the financial data is stored in the blockchain.

4. The financial data transmission path optimization method according to claim 3, characterized in that, The step of initiating consensus verification in the blockchain network after the financial data receiving end receives the financial data further includes: The first performance verification mechanism is sent to several candidate nodes in the verification nodes. One node is selected as the leader node from the candidate nodes, and the other candidate nodes are the follower nodes in the current time window. The leader node receives the financial data and initiates consensus verification to other verification nodes that are not in the final transmission path.

5. The financial data transmission path optimization method according to claim 4, characterized in that, The method for selecting candidate nodes includes: Within the time window, a response speed verification mechanism is used to select the top-performing verification nodes as candidate nodes.

6. The financial data transmission path optimization method according to claim 4, characterized in that, The step of storing the financial data in the blockchain further includes: After the leader node broadcasts the financial data to all the verification nodes, the leader node verifies whether the financial data stored by all the follower nodes is consistent with the financial data it broadcasts. If they match, the financial data will be stored in the blockchain; If there is a discrepancy, a re-verification instruction is sent to the follower node, which is then instructed to send financial data request information to the remaining follower nodes.

7. The financial data transmission path optimization method according to claim 4, characterized in that, Before the leadership node receives the financial data, the following is included: The financial data received by the financial data receiving end is imported into the trained knowledge graph embedding model to obtain financial data in a unified format.

8. The financial data transmission path optimization method according to claim 7, characterized in that, The training method for the knowledge graph embedding model includes: The entity vector and context entity vector of the financial data are calculated. The entity vectors and the context entity vectors are mapped from the entity space to the word vector space through the relation-entity alignment transformation function, and the features are concatenated together as the input of the knowledge graph embedding model. Several preset keywords are input into the Softmax classifier of the knowledge graph embedding model, and the output probability of financial data for each keyword is obtained after normalization. The adaptive moment estimation algorithm is used to determine the minimization objective function of the knowledge graph embedding model; The model parameters of the knowledge graph embedding model are updated in each iteration by backpropagation until the minimization objective function of the knowledge graph embedding model satisfies the preset conditions, thereby obtaining the trained knowledge graph embedding model, wherein the input of the knowledge graph embedding model is the financial data and the output is the keywords of the financial data.

9. The financial data transmission path optimization method according to claim 4, characterized in that, After the financial data is stored in the blockchain, the following steps are included: The leader node enters a dormant state, and the leader node and the follower node are restored as candidate nodes. During the dormant state, the candidate node is prohibited from applying to become the leader node until the dormant state ends.

10. The financial data transmission path optimization method according to claim 7, characterized in that, After importing the financial data received by the financial data receiving end into the trained knowledge graph embedding model to obtain financial data in a unified format, the process includes: Collect relevant processing information from staff, optimize and update the knowledge graph embedding model based on the processing information, and generate relevant update logs for operation and maintenance personnel to view.

11. A financial data transmission path optimization device, characterized in that, include: The acquisition unit is used to acquire multiple sets of transmission paths composed of multiple transmission nodes, wherein the starting point of the transmission path is the financial data sending end, the ending point of the transmission path is the financial data receiving end, and the transmission node includes a routing node with routing function and a verification node with routing function and verification function. The routing function is used to forward the financial data, and the verification function is used to verify the financial data in consensus while forwarding the financial data. A transmission performance calculation unit is used to calculate the transmission performance score of each group of transmission paths based on the routing performance of each transmission node; wherein, the routing performance includes the remaining computing resources of the transmission nodes and the computing power of the graphics cards. The multiplexing performance calculation unit is used to determine the number of verification nodes in each group of transmission paths and to determine the multiplexing score of each group of transmission paths based on the number of verification nodes; wherein, the multiplexing score is used to characterize the time saved by each verification node in a group of transmission paths when performing verification while forwarding financial data. The ranking unit is used to rank each group of transmission paths and determine the final transmission path based on the transmission performance score and the multiplexing score. The transmission performance calculation unit is specifically used for: Calculate the transmission performance score for each transmission path using the following formula: in, The transmission performance score for the t-th transmission path is... Let be the remaining computing resources of the i-th transmission node in the t-th transmission path. Let i be the computing power of the graphics card in the i-th transmission node. Let be the total number of transmission nodes in the t-th transmission path; The multiplexing performance calculation unit is specifically used for: Calculate the multiplexing fraction for each transmission path using the following formula: in, Let be the multiplexing fraction of the t-th transmission path. Let be the number of verification nodes in the t-th transmission path. To verify the additional weights of the nodes, Let be the total number of transmission nodes in the t-th transmission path; Specifically, the ranking unit is used for: Calculate the overall score for each group of transmission paths using the following formula: in, Let be the overall score of the t-th transmission path. The transmission performance score for the t-th transmission path is... Let be the multiplexing fraction of the t-th transmission path; The paths are ranked from highest to lowest based on the overall score.

12. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the financial data transmission path optimization method as described in any one of claims 1-10.

13. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the financial data transmission path optimization method as described in any one of claims 1-10.

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