Carbon asset transaction matchmaking method and device and computer equipment

Abstract

The invention relates to the technical field of carbon asset transaction, and discloses a carbon asset transaction matching method and device and computer equipment. The method comprises the following steps: acquiring target carbon emission data of a target transaction object corresponding to a target node; performing data processing on the target carbon emission data to generate a first transaction request corresponding to the target transaction object; sending the first transaction request to other nodes of the node network, and obtaining second transaction requests corresponding to other transaction objects sent by other nodes; matching the first transaction request with each second transaction request according to a preset price matching rule to obtain a matching result; and performing carbon asset transaction between the target transaction object and other transaction objects by using the matching result to generate a transaction result. By implementing the technical scheme of the invention, automatic matching and efficient matching of carbon asset transactions can be realized based on the decentralized node network.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of carbon asset transaction, and particularly relates to a carbon asset transaction matching method and device and computer equipment. BACKGROUND

[0002] With the increasingly serious global climate change problem, carbon emission management has become a key measure to cope with climate change. As a market-oriented emission reduction means, carbon asset transaction has been popularized and implemented in many regions. At present, the transaction operation of regional carbon market mainly relies on centralized transaction platform. In this mode, the carbon emission data and transaction requests of all transaction parties need to be uploaded to the central server for unified storage, processing, matching and settlement.

[0003] However, although the centralized architecture is convenient for management, its transaction efficiency is easily restricted by the performance bottleneck of the central server, especially when handling high concurrency requests, the system delay is significant, which affects market liquidity. Moreover, due to the high centralization of the system, there is a risk of single point failure, once the central server has a problem, the entire transaction system may be paralyzed. SUMMARY

[0004] Therefore, the present application provides a carbon asset transaction matching method, device and computer equipment to solve the problem of low efficiency and single point failure risk of centralized carbon asset transaction platform when handling high concurrency requests.

[0005] In a first aspect, the present application provides a carbon asset transaction matching method applied to a target node in a node network, the node network including nodes created for each transaction object, comprising: obtaining target carbon emission data of a target transaction object corresponding to the target node; performing data processing on the target carbon emission data to generate a first transaction request corresponding to the target transaction object; sending the first transaction request to each other node of the node network and obtaining second transaction requests corresponding to other transaction objects sent by each other node; matching the first transaction request and each second transaction request according to a preset price matching rule to obtain a matching result; and performing carbon asset transaction between the target transaction object and the other transaction objects by using the matching result to generate a transaction result.

[0006] The carbon asset transaction matching method provided by the present application embodiment realizes the decentralized and automated processing of the whole process of carbon asset transaction by the target node independently obtaining and processing the carbon emission data of the local transaction object to generate the transaction request, exchanging the request information with other nodes, and then automatically matching and executing the transaction according to the preset rule, which effectively improves the transaction efficiency and reduces the system risk caused by the dependence on the central node.

[0007] In an optional implementation, the target carbon emission data is processed to generate a first transaction request corresponding to the target transaction object, including: obtaining a carbon emission index corresponding to the target transaction object; comparing the target carbon emission data with the carbon emission index to determine a transaction type corresponding to the target transaction object based on a comparison result; determining a transaction quantity and an expected transaction value corresponding to the transaction type; and generating the first transaction request corresponding to the target transaction object by using the transaction type, the transaction quantity, and the expected transaction value.

[0008] The carbon asset transaction matching method provided by the embodiments of the present application realizes the objectivity, standardization, and executability of transaction demand generation by automatically comparing the carbon emission data with the preset index to generate a transaction type, and quantifying a transaction quantity and an expected value to construct a structured transaction request.

[0009] In an optional implementation, the first transaction request corresponding to the target transaction object is generated by using the transaction type, the transaction quantity, and the expected transaction value, including: obtaining a current total carbon asset transaction quantity and a current carbon asset average transaction value corresponding to a plurality of transaction objects; determining a first ratio between the transaction quantity and the current total carbon asset transaction quantity, and determining a second ratio between the expected transaction value and the current carbon asset average transaction value; determining a priority corresponding to the target transaction object by using the first ratio and the second ratio; and generating the first transaction request corresponding to the target transaction object by using the transaction type, the transaction quantity, the expected transaction value, and the priority.

[0010] The carbon asset transaction matching method provided by the embodiments of the present application significantly improves the efficiency and fairness of the subsequent matching link by introducing a priority calculation mechanism based on market real-time dynamics, combining transaction quantity proportion and price rationality double evaluation, so that the generated transaction request has market adaptability and sorting value.

[0011] In an optional implementation, the first transaction request is sent to each other node of the node network, including: obtaining a current network transmission rate of the target node and delay parameter data between the target node and each other node; comparing the delay parameter data with a first preset threshold value, and adjusting the current network transmission rate based on a first comparison result to obtain a target transmission rate between the target node and each other node; and respectively encrypting and sending the first transaction request corresponding to the target node to each other node according to each target transmission rate.

[0012] The carbon asset transaction matching method provided by the embodiments of the present application optimizes the request transmission efficiency and security between decentralized nodes under the premise of ensuring data integrity by dynamically monitoring network delay and adaptively adjusting transmission rate.

[0013] In an optional implementation, the delay parameter data is compared with the first preset threshold, and a target transmission rate between the target node and each of the other nodes is obtained based on a first comparison result, including: when the first comparison result indicates that the delay parameter data is greater than the first preset threshold, the current network transmission rate is reduced by a first step, and the target transmission rate between the target node and each of the other nodes is obtained; the first step is determined according to a ratio of the first preset threshold to the delay parameter data; when the first comparison result indicates that the delay parameter data is less than or equal to the first preset threshold, the current network transmission rate is increased by a second step, and the target transmission rate between the target node and each of the other nodes is obtained; the second step is determined according to a ratio of the delay parameter data to the first preset threshold.

[0014] The carbon asset transaction matching method provided by the embodiment of the application realizes fine and elastic regulation and control of the transmission rate through dynamic ratio calculation, avoids the risk of data loss when the network is congested, maximizes the use of bandwidth resources in the low-delay period, and significantly improves the stability and efficiency of the decentralized network transmission.

[0015] In an optional implementation, the first transaction request and each of the second transaction requests are matched according to a preset price matching rule to obtain a matching result, including: first transaction data corresponding to the target node is extracted from the first transaction request; for any other node, second transaction data corresponding to the other node is extracted from the second transaction request; the matching degree between the target node and each of the other nodes is determined by using the first transaction data and each of the second transaction data; the first transaction request and each of the second transaction requests are matched according to the matching degree to obtain the matching result.

[0016] The carbon asset transaction matching method provided by the embodiment of the application realizes automatic and objective matching of carbon asset transactions in a decentralized environment by extracting quantitative data of both parties of a transaction and calculating accurate matching degrees between nodes, and significantly improves the matching accuracy and execution efficiency.

[0017] In an optional implementation, the first transaction data includes a first transaction type and a first expected transaction value corresponding to the target node, and the second transaction data includes a second transaction type and a second expected transaction value corresponding to the other node; the matching degree between the target node and each of the other nodes is determined by using the first transaction data and each of the second transaction data, including: the first transaction type and each of the second transaction types are matched to determine a transaction type matching result between the target node and each of the other nodes; a difference between the first expected transaction value and each of the second expected transaction values is determined, and the matching degree between the target node and each of the other nodes is determined by using the transaction type matching result and the difference.

[0018] The carbon asset transaction matching method provided by the embodiment of the present application combines the screening of the transaction type matching and the quantification of the expected value difference, constructs a matching degree evaluation model considering the transaction feasibility and economic rationality, and effectively improves the transaction rate and quality of the matching result.

[0019] In an optional implementation, the first transaction request and each second transaction request are matched according to the matching degree to obtain a matching result, including: judging whether the matching degree is greater than a second preset threshold; if the matching degree is greater than the second preset threshold, then performing transaction matching between any other node and the target node whose matching degree is greater than the second preset threshold to obtain the matching result.

[0020] The carbon asset transaction matching method provided by the embodiment of the present application performs hard screening on the node transaction request by setting the matching degree threshold, and only performs matching on the node with high matching degree, thereby effectively reducing invalid matching operations and improving the transaction success rate and resource utilization rate.

[0021] In a second aspect, the present application provides a carbon asset transaction matching device applied to a target node in a node network, the node network including nodes created for each transaction object; including: an acquisition module configured to acquire target carbon emission data of a target transaction object corresponding to the target node; a processing module configured to perform data processing on the target carbon emission data to generate a first transaction request corresponding to the target transaction object; a sending module configured to send the first transaction request to each other node of the node network and acquire second transaction requests of other transaction objects sent by each other node; a matching module configured to match the first transaction request and each second transaction request according to a preset price matching rule to obtain a matching result; and a transaction module configured to perform carbon asset transaction between the target transaction object and the other transaction objects by using the matching result to generate a transaction result.

[0022] In a third aspect, the present application provides a computer device, including a memory and a processor, the memory and the processor are communicatively connected with each other, the memory stores computer instructions, and the processor executes the carbon asset transaction matching method of the first aspect or any of the corresponding embodiments thereof by executing the computer instructions.

[0023] In a fourth aspect, the present application provides a computer readable storage medium, the computer readable storage medium stores computer instructions, and the computer instructions are used to make the computer execute the carbon asset transaction matching method of the first aspect or any of the corresponding embodiments thereof.

[0024] In a fifth aspect, the present application provides a computer program product, including computer instructions, and the computer instructions are used to make the computer execute the carbon asset transaction matching method of the first aspect or any of the corresponding embodiments thereof. BRIEF DESCRIPTION OF DRAWINGS

[0025] In order to more clearly illustrate the technical solutions in the specific embodiments of the present application or the prior art, the accompanying drawings required by the specific embodiments or prior art description will be briefly introduced as follows. Obviously, the accompanying drawings in the following description are some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor on the basis of these drawings.

[0026] Figure 1 is a flowchart of a carbon asset transaction matching method according to an embodiment of the present application;

[0027] Figure 2 is a flowchart of another carbon asset transaction matching method according to an embodiment of the present application;

[0028] Figure 3 is a flowchart of still another carbon asset transaction matching method according to an embodiment of the present application;

[0029] Figure 4 is a flowchart of yet another carbon asset transaction matching method according to an embodiment of the present application;

[0030] Figure 5 is a structural block diagram of a carbon asset transaction matching device according to an embodiment of the present application;

[0031] Figure 6 is a hardware structure schematic diagram of a computer device according to an embodiment of the present application. DETAILED DESCRIPTION

[0032] In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the accompanying drawings of the embodiments of the present application. Obviously, the described embodiments are some of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0033] At present, the transactions of regional carbon markets mainly rely on centralized trading platforms. In this mode, all carbon asset transaction information is stored and processed centrally, and the trading platform is responsible for collecting, matching and settling transaction data. Traditional centralized platforms usually have a data center, and enterprises upload carbon emission data and transaction demand to the center, which is processed by the center server.

[0034] However, the traditional centralized platform is prone to performance bottlenecks when handling large-scale transaction requests, resulting in data transmission and processing delays, which affects the speed of transaction matching and market liquidity; secondly, the centralized system has the risk of single point failure. Once the central server fails, is attacked or is upgraded and maintained, the entire carbon market transaction may be affected; finally, the problem of data security and privacy is serious. The sensitive data of enterprises is stored centrally on the platform, which has the risk of leakage and abuse, so enterprises are more concerned about data security and privacy protection. These problems are due to the limitations of centralized architecture, which is difficult to meet the needs of large-scale carbon trading market for high concurrency, efficiency and security.

[0035] Therefore, the technical scheme of the present application builds a carbon asset transaction matching system based on edge computing and decentralized architecture, which sinks data collection, processing and matching functions to distributed edge nodes, and uses blockchain technology to ensure data security and consistency. The target node obtains local carbon emission data and preprocesses it through edge computing to generate a first transaction request; then, through a dynamic rate adjustment mechanism, the request is broadcast to other nodes to ensure privacy and eliminate the risk of single point failure; finally, based on the preset price matching rules, the matching degree of the request is calculated, and the nodes with high matching degree are matched to generate a transaction result, improve market liquidity and price rationality, and realize the decentralized, automated and high-reliability operation of carbon asset transaction.

[0036] According to an embodiment of the present application, a carbon asset transaction matching method is provided. It should be noted that the steps shown in the flowchart of the drawing can be executed in a computer system such as a set of computer executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0037] A carbon asset transaction matching method is provided in this embodiment, which can be used for a target node in a node network, and the node network includes nodes created for each transaction object; Figure 1 The flowchart of the carbon asset transaction matching method according to the embodiment of the present application is shown in Figure 1 The flowchart includes the following steps.

[0038] Step S101, obtaining target carbon emission data of a target transaction object corresponding to a target node.

[0039] The node network refers to a decentralized transaction node network constructed based on blockchain technology, which is composed of edge computing nodes of each transaction object. The target node refers to an edge computing node created in the node network for a specific transaction object. The target transaction object refers to a carbon asset transaction participant corresponding to the target node, which can be an enterprise or an institution. The target carbon emission data refers to the preprocessed real-time carbon emission data of the target transaction object. Specifically, the target node is deployed inside the target transaction object, and real-time raw data is collected by carbon emission monitoring devices distributed in the target transaction object, which can include daily, hourly carbon emission, energy consumption data, etc. The collection frequency can be set by a preset frequency parameter F (times / hour), which is adjusted by the target transaction object according to its production characteristics and carbon emission stability, for example, a high carbon emission enterprise can set F = 12 (i.e. collect every 5 minutes), to ensure the real-time and pertinence of the data. The collected raw data {D raw} is preprocessed by removing outliers and noise, and then mapped to the interval [0, 1] using a normalization formula as follows:

[0040]

[0041] where D normalized is the data type after cleaning by the normalization formula, D min is the minimum value of the data type, and D max is the maximum value of the data type.

[0042] Step S102, data processing is performed on the target carbon emission data to generate a first transaction request corresponding to the target transaction object.

[0043] The first transaction request refers to a carbon asset transaction request generated by the target node after processing the target carbon emission data. Specifically, after obtaining the raw carbon emission data, the target node analyzes it and calculates the carbon asset transaction demand according to the preset business rules to form the first transaction request.

[0044] Step S103, the first transaction request is sent to each other node of the node network, and a second transaction request corresponding to each other transaction object sent by each other node is obtained.

[0045] The other nodes refer to other edge computing nodes in the node network except the target node. The other transaction objects refer to carbon asset transaction participants corresponding to the respective other nodes, which form transaction counterparties with the target transaction object. The second transaction request refers to a carbon asset transaction request generated by the other nodes for the other transaction objects, and has the same format as the first transaction request. Specifically, after the target node generates the first transaction request, the target node broadcasts the first transaction request to all other nodes in the network by using a point-to-point communication mechanism of a decentralized node network constructed based on a blockchain. Meanwhile, the target node also continuously listens to the network to receive the second transaction requests broadcast by the other nodes and representing the respective corresponding transaction objects of the other nodes, so that the transaction requests among all nodes are shared.

[0046] In step S104, the first transaction request and the respective second transaction requests are matched according to a preset price matching rule to obtain a matching result.

[0047] The price matching rule is a standard for judging whether the transaction requests are matched. The matching result refers to a determined tradable transaction pair and related parameters after the first transaction request and the second transaction requests are matched. Specifically, the target node matches the first transaction request with the second transaction requests sent by the other nodes. The price matching rule is matched according to the carbon asset parameters involved in the transaction requests of both parties. For example, when the target transaction object wants to sell a certain amount of carbon assets and the other transaction objects have purchase demand, the parameters such as the price, quantity, and priority of both parties are compared and matched according to the preset matching rule. If the matching conditions are met, the matching is performed and the matching result is generated, which clearly indicates the tradable transaction objects and transaction parameters.

[0048] In step S105, carbon asset transactions are performed between the target transaction object and the other transaction objects by using the matching result to generate a transaction result.

[0049] The transaction result refers to a final state generated after the carbon asset transactions are performed according to the matching result. Specifically, after the matching result is confirmed, the transactions are automatically executed by using smart contract technology. The target node and the other nodes update the local carbon asset account books to record the transfer of the carbon assets, and synchronize the transaction information to all nodes in the network through the blockchain network to ensure the consistency and non-tamperability of the data. Finally, the transaction result containing the asset transfer state and the account book update record is generated to complete the whole process of the carbon asset transactions.

[0050] The carbon asset transaction matching method provided by the embodiment of the application realizes the decentralized and automated processing of the whole process of the carbon asset transactions by the target node to independently acquire and process the carbon emission data of the local transaction object to generate the transaction request, exchange the request information with the other nodes, and automatically match and execute the transactions according to the preset rule, which effectively improves the transaction efficiency and reduces the system risk caused by the dependence on the central node.

[0051] A carbon asset transaction matching method is provided in the embodiment, which can be used for a target node in a node network including nodes created for each transaction object; Figure 2 is a flowchart of the carbon asset transaction matching method according to the embodiment of the application, as shown in the figure, the flow includes the following steps. Figure 2

[0052] Step S201, obtaining target carbon emission data of a target transaction object corresponding to the target node. For details, please refer to step S101 of the embodiment shown in the figure, which will not be repeated here. Figure 1

[0053] Step S202, performing data processing on the target carbon emission data to generate a first transaction request corresponding to the target transaction object.

[0054] Specifically, the above step S202 includes:

[0055] Step S2021, obtaining a carbon emission index corresponding to the target transaction object.

[0056] The carbon emission index refers to the upper limit or benchmark value of the carbon emission allocated or set for the target transaction object, which is used to measure whether the actual carbon emission exceeds the standard. Specifically, the carbon emission index of the target transaction object is pre-allocated by the carbon market management institution or the relevant regulatory department (such as the carbon quota of an enterprise), and is stored in the local database or related system of the target node. The target node obtains the carbon emission index of the target transaction object by reading the locally stored index data or interfacing with the external management system, as a benchmark for judging transaction demand.

[0057] Step S2022, comparing the target carbon emission data with the carbon emission index, and determining the transaction type corresponding to the target transaction object based on the comparison result.

[0058] The transaction type refers to the direction of carbon asset transaction determined according to the comparison result of the actual carbon emission of the target transaction object and the index, including buying or selling. Specifically, the target node compares the target carbon emission data with the carbon emission index in numerical value, if the actual emission corresponding to the target carbon emission data exceeds the index, it means that the target transaction object needs to supplement carbon assets, and the transaction type is determined as buying; if the actual emission is lower than the index, it means that there is excess carbon quota, and the transaction type is determined as selling.

[0059] Step S2023, determining the transaction quantity and expected transaction value corresponding to the transaction type.

[0060] ​​The transaction quantity refers to the quantity of carbon assets that the target transaction object intends to buy or sell in the carbon asset transaction. The expected transaction value refers to the expected transaction price of the target transaction object in the carbon asset transaction. Specifically, the transaction quantity is determined by the difference between the target carbon emission data and the carbon emission index. For example, if the carbon emission index is 1000 tons and the actual emission is 1200 tons, the buy quantity is 200 tons; if the actual emission is 800 tons, the sell quantity is 200 tons. The expected transaction value can be set by the target transaction object according to the current market average price and its own demand. When buying, the expected transaction value should not be higher than the market average price to reduce the cost; when selling, the expected transaction value should not be lower than the market average price to obtain a profit.

[0061] In step S2024, a first transaction request corresponding to the target transaction object is generated by using the transaction type, the transaction quantity, and the expected transaction value.

[0062] The transaction type, the transaction quantity, and the expected transaction value are packaged into a standard format transaction request data set {R=(T type , Q, P)}. Wherein, T type is the transaction type identifier, Q is the transaction quantity, and P is the expected transaction value. The generated first transaction request will be further sorted by the priority function of the target node to ensure that reasonable transaction requests are given priority to enter the matching process.

[0063] In some optional embodiments, the above step S2024 includes:

[0064] In step a1, the current total carbon asset transaction quantity and the current carbon asset average transaction value corresponding to a plurality of transaction objects are obtained.

[0065] The current total carbon asset transaction quantity refers to the total quantity of carbon asset transactions of all transaction objects in the node network in the current period, denoted as Q total . The current carbon asset average transaction value refers to the weighted average price of carbon asset transactions in the current period, denoted as P market . Specifically, a market snapshot can be generated at a fixed period (such as every hour), and the total quantity of carbon asset transactions of all transaction objects in the node network is counted through the blockchain network to obtain the current total carbon asset transaction quantity Q total . At the same time, the weighted average price of transactions in the period is calculated to form the current carbon asset average transaction value P market , which is broadcast to all nodes in the node network through the blockchain. The target node can obtain the current total carbon asset transaction quantity and the current carbon asset average transaction value from the local cache or the blockchain network to ensure real-time and consistency.

[0066] In step a2, a first ratio between the transaction quantity and the current total carbon asset transaction quantity is determined, and a second ratio between the expected transaction value and the current carbon asset average transaction value is determined.

[0067] The first ratio refers to the ratio of the transaction quantity Q of the target transaction object to the total transaction quantity Q of the current carbon assets total . The second ratio refers to the ratio of the expected transaction value P of the target transaction object to the average transaction value P of the current carbon assets market . Specifically, the first ratio is obtained by dividing the transaction quantity Q of the target transaction object by the total transaction quantity Q of the current carbon assets total The second ratio is obtained by dividing the expected transaction value P of the target transaction object by the average transaction value P of the current carbon assets market When the transaction type is buy, the second ratio is P buy , which is the expected transaction value when buying; when the transaction type is sell, the second ratio is P sell , which is the expected transaction value when selling.

[0068] Step a3, using the first ratio and the second ratio, determine the priority corresponding to the target transaction object.

[0069] The priority refers to a transaction request processing order index calculated by a weight coefficient according to the first ratio and the second ratio, denoted as Priority. Specifically, the priority corresponding to the target transaction object is calculated by a preset priority function in combination with the first ratio and the second ratio, and the formula is as follows:

[0070]

[0071] where ω1 and ω2 are weight coefficients, and PriceScore is 1 when the buy request is buy P market , then When the sell request is sell P market , then Otherwise, both are 0. This function combines the transaction size proportion and the price rationality to generate a priority value, and the higher the value, the higher the transaction request priority.

[0072] Step a4, using the transaction type, transaction quantity, expected transaction value, and priority, generate the first transaction request corresponding to the target transaction object.

[0073] The transaction type, transaction quantity Q, expected transaction value P, and calculated priority are packaged into a standard format transaction request data set. The specific format is {R=(T type , Q, P, Priority)}. Priority is embedded as a priority parameter in the request to ensure that the request is broadcast and matched in the node network in order of priority.

[0074] ​​In the above embodiment, by introducing a priority computer mechanism based on market real-time dynamics, combining double evaluation of transaction volume proportion and price rationality, the generated transaction request has market adaptability and sorting value, significantly improving the efficiency and fairness of the subsequent matching link.

[0075] In step S203, the first transaction request is sent to each other node of the node network, and a second transaction request corresponding to another transaction object sent by each other node is obtained. For details, please refer to Figure 1 The step S103 of the embodiment shown will not be repeated here.

[0076] In step S204, the first transaction request and each second transaction request are matched according to a preset price matching rule to obtain a matching result. For details, please refer to Figure 1 The step S104 of the embodiment shown will not be repeated here.

[0077] In step S205, carbon asset transaction is performed between the target transaction object and the other transaction object by using the matching result to generate a transaction result. For details, please refer to Figure 1 The step S105 of the embodiment shown will not be repeated here.

[0078] The carbon asset transaction matching method provided by the embodiment of the present application realizes the objectivity, standardization and executability of transaction demand generation by automatically comparing the carbon emission data with the preset index to generate a transaction type, and quantifying the transaction quantity and the expected value to construct a structured transaction request.

[0079] In the embodiment, a carbon asset transaction matching method is provided, which can be used for a target node in a node network, and the node network includes nodes created for each transaction object; Figure 3 The flowchart of the carbon asset transaction matching method according to the embodiment of the present application is shown in Figure 3 The flowchart includes the following steps.

[0080] In step S301, target carbon emission data of a target transaction object corresponding to a target node is obtained. For details, please refer to Figure 2 The step S201 of the embodiment shown will not be repeated here.

[0081] In step S302, the target carbon emission data is processed to generate a first transaction request corresponding to the target transaction object. For details, please refer to Figure 2 The step S202 of the embodiment shown will not be repeated here.

[0082] In step S303, the first transaction request is sent to each other node of the node network, and a second transaction request corresponding to another transaction object sent by each other node is obtained.

[0083] Specifically, the step S303 includes:

[0084] In step S3031, the current network transmission rate of the target node and the delay parameter data between the target node and each other node are obtained.

[0085] The current network transmission rate refers to the real-time data transmission rate of the target node when sending the first transaction request, and the unit is byte / s, denoted as V current . The delay parameter data refers to the real-time communication delay between the target node and each other node, and the unit is millisecond, denoted as τ. Specifically, the target node obtains the current network transmission rate through a real-time monitoring module, and the rate is determined by the real-time statistical data transmission amount. At the same time, the target node periodically sends a probe packet to each other node, and obtains the delay parameter data between the target node and each other node by calculating the round-trip time of the probe packet. The target node can also use a linear regression algorithm to predict future network status, dynamically correct the delay parameter and the adjustment coefficient, and ensure the real-time and accuracy of the data.

[0086] In step S3032, the delay parameter data and the first preset threshold are compared, and the current network transmission rate is adjusted based on the first comparison result to obtain the target transmission rate between the target node and each other node.

[0087] The first preset threshold refers to a preset delay judgment threshold, and the unit is millisecond, denoted as τ threshold . The first comparison result refers to the comparison result of the delay parameter data and the first preset threshold. The target transmission rate refers to the transmission rate adjusted according to the first comparison result, denoted as V new . Specifically, the real-time delay parameter data is compared with the first preset threshold. If the delay parameter data is greater than the first preset threshold, it means that the network delay is too high, and the current network transmission rate is reduced to prioritize data integrity; if the delay parameter data is less than the first preset threshold, the rate is gradually increased to increase the throughput.

[0088] In some optional embodiments, the step S3032 includes:

[0089] In step b1, when the first comparison result indicates that the delay parameter data is greater than the first preset threshold, the current network transmission rate is reduced by a first step to obtain the target transmission rate between the target node and each other node; the first step is determined according to the ratio of the first preset threshold to the delay parameter data.

[0090] When the delay parameter data τ is greater than the first preset threshold τ threshold , the first step is determined according to the ratio of the delay parameter data to the first preset threshold, and the target transmission rate is calculated according to the formula .

[0091] Step b2, when the first comparison result represents that the delay parameter data is less than or equal to the first preset threshold, increasing the current network transmission rate by a second step size to obtain a target transmission rate between the target node and each other node; the second step size is determined according to a ratio of the delay parameter data to the first preset threshold.

[0092] When the delay parameter data τ is less than the first preset threshold τ threshold , the second step size is determined according to a ratio of the first preset threshold to the delay parameter data, and the target transmission rate is calculated according to the formula .

[0093] In the above embodiments, the fine and elastic regulation of the transmission rate is achieved by dynamic ratio calculation, which not only avoids the risk of data loss when the network is congested, but also maximizes the use of bandwidth resources during the low delay period, significantly improving the stability and efficiency of the decentralized network transmission.

[0094] Step S3033, according to each target transmission rate, the first transaction request corresponding to the target node is respectively encrypted and sent to each other node.

[0095] The target node encapsulates and encrypts the first transaction request using an encryption communication protocol (such as TLS / SSL) according to the calculated target transmission rate, ensuring the security of data transmission. The nodes broadcast the encrypted transaction request package to each other node according to the self-adaptive adjusted target transmission rate through the point-to-point communication mechanism of the blockchain network.

[0096] Step S3034, obtaining the second transaction request corresponding to the other transaction object sent by each other node.

[0097] After the other nodes generate the encrypted second transaction request according to the above method, they broadcast it to the entire network through the blockchain network. After receiving the broadcasted encrypted request package, the target node decrypts it using the local key, parses the transaction type, quantity, price, and other information, and stores it in the local cache. At the same time, the target node can also verify the legality of the request, such as through the blockchain consensus mechanism, to ensure that the received second transaction request comes from a valid node and has not been tampered with, providing reliable data for the subsequent matching process.

[0098] Step S304, according to the preset price matching rule, the first transaction request and each second transaction request are matched to obtain a matching result. For details, please refer to the step S204 of the embodiment shown in Figure 2 , which will not be repeated here.

[0099] Step S305, using the matching result to conduct carbon asset transactions between the target transaction object and the other transaction objects to generate a transaction result. For details, please refer to the step S205 of the embodiment shown in Figure 2The step S205 of the illustrated embodiment will not be repeated here.

[0100] The carbon asset transaction matching method provided by the embodiment of the application optimizes the request transmission efficiency and security between decentralized nodes under the premise of ensuring data integrity by dynamically monitoring network delay and adaptively adjusting transmission rate.

[0101] A carbon asset transaction matching method is provided in the embodiment, which can be used for a target node in a node network, and the node network includes nodes created for each transaction object; Figure 4 The flowchart of the carbon asset transaction matching method according to the embodiment of the application is shown in Figure 4 The flowchart includes the following steps.

[0102] In step S401, target carbon emission data of a target transaction object corresponding to the target node is acquired. For details, please refer to step S301 of the embodiment shown in Figure 3 The step S301 of the illustrated embodiment will not be repeated here.

[0103] In step S402, the target carbon emission data is processed to generate a first transaction request corresponding to the target transaction object. For details, please refer to step S302 of the embodiment shown in Figure 3 The step S302 of the illustrated embodiment will not be repeated here.

[0104] In step S403, the first transaction request is sent to each other node of the node network, and a second transaction request corresponding to each other transaction object sent by each other node is acquired. For details, please refer to step S303 of the embodiment shown in Figure 3 The step S303 of the illustrated embodiment will not be repeated here.

[0105] In step S404, the first transaction request and each second transaction request are matched according to a preset price matching rule to obtain a matching result.

[0106] Specifically, the above step S404 includes:

[0107] In step S4041, first transaction data corresponding to the target node is extracted from the first transaction request; and for any other node, second transaction data corresponding to the other node is extracted from the second transaction request.

[0108] The first transaction data refers to the core transaction parameters extracted from the first transaction request generated by the target node. The second transaction data refers to the core transaction parameters extracted from the second transaction request sent by the other node. Specifically, the first transaction request and the second transaction request are both standard format data sets (such as {R=(T type , Q, P, Priority)}, and the first transaction data in the first transaction request and the second transaction data in the second transaction request are directly parsed when extracted.

[0109] Step S4042, determining the matching degree between the target node and each of the other nodes by using the first transaction data and each of the second transaction data.

[0110] The matching degree refers to a quantitative index for measuring whether the transaction request of the target node matches the transaction request of the other node. Specifically, the matching degree between the target node and each of the other nodes is calculated by using a preset matching degree function in combination with the first transaction data and each of the second transaction data.

[0111] In some optional embodiments, the first transaction data includes a first transaction type and a first expected transaction value corresponding to the target node, and the second transaction data includes a second transaction type and a second expected transaction value corresponding to the other node; and the step S4042 includes:

[0112] Step c1, matching the first transaction type with each of the second transaction types to determine a transaction type matching result between the target node and each of the other nodes.

[0113] The first transaction type (buy / sell of the target node) and the second transaction type of the other node need to form a complementary relationship. Specifically, if the first transaction type is buy and the second transaction type is sell, the transaction types match, and the result is recorded as 1; if both are buy or sell, they do not match, and the result is recorded as 0.

[0114] Step c2, determining the difference between the first expected transaction value and each of the second expected transaction values, and determining the matching degree between the target node and each of the other nodes by using the transaction type matching result and the difference.

[0115] The absolute difference between the first expected transaction value and the second expected transaction value is calculated as |P bry - sell | divided by the current market average transaction value P market , to obtain a relative price deviation; subtracting 1 from the deviation and multiplying by a weight coefficient β, and adding the result multiplied by a weight coefficient α of the transaction type matching result, that is, a pre-defined matching degree formula:

[0116] Wherein, α and β are preset weights for adjusting the influence degree of the transaction type and the price deviation on the matching degree.

[0117] In the above embodiments, by combining the screening of the transaction type matching and the quantification of the expected value difference, a matching degree evaluation model considering transaction feasibility and economic rationality is constructed, which effectively improves the transaction rate and quality of the matching result.

[0118] Step S4043, matching the first transaction request with each of the second transaction requests according to the matching degree to obtain a matching result. ​

[0119] With the extracted transaction data, the matching degree between the target node and each other node is calculated. The matching degree is measured based on the number of transactions, expected transaction value and other key parameters. According to the calculated matching degree, the first transaction request is matched with the second transaction request to obtain a matching result.

[0120] In some optional embodiments, the above step S4043 comprises:

[0121] Step d1, judging whether the matching degree is greater than a second preset threshold.

[0122] The calculated matching degree value is compared with a second preset threshold. If the matching degree is greater than the threshold, it means that the matching degree of the transaction request is high enough to enter the matching process; if it is less than or equal to the threshold, it is considered that the matching degree is insufficient and the matching is temporarily not performed.

[0123] Step d2, if the matching degree is greater than the second preset threshold, the transaction matching between any other node with the matching degree greater than the second preset threshold and the target node is performed to obtain a matching result.

[0124] When the matching degree is greater than the second preset threshold θ, it means that the target node and the other node have a high degree of fit in terms of transaction type and expected transaction value, and transaction matching can be performed. Specifically, when the target node calculates the matching degree with each other node, if the matching degree of the current detected other node is greater than the second preset threshold, the subsequent matching degree calculation is interrupted, and the transaction matching between the target node and the node that meets the standard is performed to generate a matching result containing only the transaction details of the node.

[0125] Optionally, when starting the matching process, the target node first sorts all the second transaction requests in descending order according to the priority values carried in all the received second transaction requests, so that the request with the highest priority is placed at the head of the detection queue. Then, the chain matching stage is entered. The target node selects the second transaction request with the highest priority from the sorted queue, calculates the matching degree between it and the first transaction request in real time; if the matching degree is greater than the second preset threshold, the transaction matching with the node with the highest priority is immediately performed, a matching result containing only the transaction details of the node is generated and the process is terminated. If the matching degree does not meet the threshold, the second transaction request with the second highest priority in the queue is automatically transferred, the matching degree is recalculated and the same matching judgment is performed, and if the matching is successful, the result is output and the process is terminated, and if the matching fails, the remaining nodes are continuously detected in descending order of priority. This process continues until the first node with a matching degree that meets the standard is found and the matching is successful.

[0126] In the above embodiments, the matching degree threshold is set to hard-screen the node transaction request, and only the high matching degree node is executed for matching, which effectively reduces the invalid matching operation and improves the transaction success rate and resource utilization.

[0127] Step S405, carbon asset transaction is carried out between the target transaction object and other transaction objects by using the matching result, and a transaction result is generated. For details, please refer to Figure 3 Step S305 of the embodiment shown will not be repeated here.

[0128] The carbon asset transaction matching method provided by the embodiment improves the matching accuracy and execution efficiency.

[0129] In the embodiment, a carbon asset transaction matching device is also provided, which is used to implement the above-mentioned embodiments and preferred embodiments, and will not be repeated here. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware, or a combination of software and hardware is also possible and is contemplated.

[0130] The embodiment provides a carbon asset transaction matching device, which is applied to a target node in a node network, and the node network includes nodes created for each transaction object. Figure 5 As shown, it includes:

[0131] The acquisition module 501 is configured to acquire target carbon emission data of the target transaction object corresponding to the target node.

[0132] The processing module 502 is configured to perform data processing on the target carbon emission data to generate a first transaction request corresponding to the target transaction object.

[0133] The sending module 503 is configured to send the first transaction request to each other node in the node network, and acquire a second transaction request corresponding to another transaction object sent by each other node.

[0134] The matching module 504 is configured to match the first transaction request and each second transaction request according to a preset price matching rule to obtain a matching result.

[0135] The transaction module 505 is configured to perform carbon asset transaction between the target transaction object and the other transaction objects by using the matching result to generate a transaction result.

[0136] In some optional embodiments, the processing module 502 includes:

[0137] The first acquisition sub-module is configured to acquire a carbon emission index corresponding to the target transaction object.

[0138] The comparison submodule is configured to compare the target carbon emission data with the carbon emission index, and determine a transaction type corresponding to the target transaction object based on a comparison result.

[0139] The first determination submodule is configured to determine a transaction quantity and an expected transaction value corresponding to the transaction type.

[0140] The generation submodule is configured to generate a first transaction request corresponding to the target transaction object by using the transaction type, the transaction quantity, and the expected transaction value.

[0141] In some optional embodiments, the generation submodule includes:

[0142] The acquisition unit is configured to acquire a total transaction quantity of current carbon assets and an average transaction value of the current carbon assets corresponding to a plurality of transaction objects.

[0143] The first determination unit is configured to determine a first ratio between the transaction quantity and the total transaction quantity of the current carbon assets, and determine a second ratio between the expected transaction value and the average transaction value of the current carbon assets.

[0144] The second determination unit is configured to determine a priority corresponding to the target transaction object by using the first ratio and the second ratio.

[0145] The generation unit is configured to generate the first transaction request corresponding to the target transaction object by using the transaction type, the transaction quantity, the expected transaction value, and the priority.

[0146] In some optional embodiments, the sending module 503 includes:

[0147] The second acquisition submodule is configured to acquire a current network transmission rate of the target node and delay parameter data between the target node and each other node.

[0148] The comparison submodule is configured to compare the delay parameter data with a first preset threshold, and adjust the current network transmission rate based on a first comparison result to obtain a target transmission rate between the target node and each other node.

[0149] The sending submodule is configured to respectively encrypt and send the first transaction request corresponding to the target node to each other node according to the target transmission rate.

[0150] In some optional embodiments, the comparison submodule includes:

[0151] The first comparison unit is configured to decrease the current network transmission rate by a first step length to obtain the target transmission rate between the target node and each other node when the first comparison result indicates that the delay parameter data is greater than the first preset threshold; the first step length is determined according to a ratio of the first preset threshold to the delay parameter data.

[0152] The second comparison unit is configured to increase the current network transmission rate by a second step length when the first comparison result represents that the delay parameter data is less than or equal to the first preset threshold, to obtain a target transmission rate between the target node and each other node; and the second step length is determined according to a ratio of the delay parameter data to the first preset threshold.

[0153] In some optional embodiments, the matching module 504 comprises:

[0154] The extraction sub-module is configured to extract first transaction data corresponding to the target node from the first transaction request, and extract second transaction data corresponding to each other node from the second transaction request;

[0155] The second determination sub-module is configured to determine a matching degree between the target node and each other node by using the first transaction data and each second transaction data.

[0156] The matching sub-module is configured to match the first transaction request with each second transaction request according to the matching degree, to obtain a matching result.

[0157] In some optional embodiments, the second determination sub-module comprises:

[0158] The matching unit is configured to match the first transaction type with each second transaction type, to determine a transaction type matching result between the target node and each other node.

[0159] The third determination unit is configured to determine a difference between the first expected transaction value and each second expected transaction value, and determine the matching degree between the target node and each other node by using the transaction type matching result and the difference.

[0160] Further function descriptions of each module and unit are the same as those of the corresponding embodiments, and will not be repeated here.

[0161] The carbon asset transaction matching device in the embodiment is presented in the form of a functional unit, where the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and a memory executing one or more software or fixed programs, and / or other devices that can provide the above functions.

[0162] The carbon asset transaction matching device provided by the embodiment can realize the decentralized and automated processing of the whole process of carbon asset transaction, effectively improve the transaction efficiency, and reduce the system risk caused by the dependence on the central node, by enabling the target node to autonomously acquire and process the carbon emission data of the local transaction object to generate a transaction request, exchange the request information with other nodes, and automatically match and execute the transaction according to a preset rule.

[0163] This invention also provides a computer device having the above-described features. Figure 5 The carbon asset trading matching device shown.

[0164] Please see Figure 6 , Figure 6 This is a schematic diagram of the structure of a computer device provided in an optional embodiment of the present invention, such as... Figure 6 As shown, the computer device includes one or more processors 10, memory 20, and interfaces for connecting the components, including high-speed interfaces and low-speed interfaces. The components communicate with each other via different buses and can be mounted on a common motherboard or otherwise installed as needed. The processors can process instructions executed within the computer device, including instructions stored in or on memory to display graphical information of a GUI on external input / output devices (such as display devices coupled to the interfaces). In some alternative implementations, multiple processors and / or multiple buses can be used with multiple memories and multiple memory modules, if desired. Similarly, multiple computer devices can be connected, each providing some of the necessary operations (e.g., as a server array, a group of blade servers, or a multiprocessor system). Figure 6 Take a processor 10 as an example.

[0165] Processor 10 may be a central processing unit, a network processor, or a combination thereof. Processor 10 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The programmable logic device may be a complex programmable logic device (CAMP), a field-programmable gate array (FPGA), a general-purpose array logic (GDA), or any combination thereof.

[0166] The memory 20 stores instructions executable by at least one processor 10 to cause at least one processor 10 to perform the method shown in the above embodiments.

[0167] The memory 20 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the computer device. Furthermore, the memory 20 may include high-speed random access memory and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some alternative embodiments, the memory 20 may optionally include memory remotely located relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0168] The memory 20 can include a volatile memory, such as a random access memory, and / or a non-volatile memory, such as a flash memory, a hard disk, or a solid state disk. The memory 20 can also include a combination of the above-mentioned types of memories.

[0169] The computer device also includes a communication interface 30 for the computer device to communicate with other devices or communication networks.

[0170] The embodiments of the present application also provide a computer readable storage medium, and the method according to the embodiments of the present application can be implemented in hardware, firmware, or recorded in a storage medium, or stored in a remote storage medium or a non-transitory machine readable storage medium and downloaded to a local storage medium through network, so that the method described herein can be processed by such software on a storage medium using a general purpose computer, a special purpose processor, or programmable or special purpose hardware. The storage medium can be a disk, an optical disk, a read-only memory, a random access memory, a flash memory, a hard disk, or a solid state disk, etc. Further, the storage medium can also include a combination of the above-mentioned types of memories. It can be understood that the computer, the processor, the microprocessor controller, or the programmable hardware includes a storage component that can store or receive software or computer code, when the software or computer code is accessed and executed by the computer, the processor, or the hardware, the method shown in the above embodiments is implemented.

[0171] Part of the present application can be applied as a computer program product, for example, computer program instructions, when executed by a computer, through the operation of the computer, the method and / or technical solutions according to the present application can be invoked or provided. Those skilled in the art should understand that the form of computer program instructions in a computer readable medium includes but is not limited to source files, executable files, installation package files, etc. Correspondingly, the way of computer program instructions executed by computer includes but is not limited to: the computer directly executes the instructions, or the computer compiles the instructions and then executes the corresponding compiled program, or the computer reads and executes the instructions, or the computer reads and installs the instructions and then executes the corresponding installed program. Here, the computer readable medium can be any available computer readable storage medium or communication medium accessible to the computer.

[0172] Although the embodiments of the present application are described in conjunction with the accompanying drawings, various modifications and changes can be made by those skilled in the art without departing from the spirit and scope of the present application, and such modifications and changes fall within the scope defined by the appended claims.

Claims

1. A carbon asset transaction matching method, characterized by, A target node applied to a node network, the node network comprising nodes created for respective transaction objects; the method comprising: obtaining target carbon emission data of a target transaction object corresponding to the target node; performing data processing on the target carbon emission data to generate a first transaction request corresponding to the target transaction object; sending the first transaction request to each other node of the node network and obtaining a second transaction request corresponding to another transaction object sent by each other node; matching the first transaction request with each second transaction request according to a preset price matching rule to obtain a matching result; performing carbon asset transaction between the target transaction object and the other transaction object using the matching result to generate a transaction result.

2. The method of claim 1, wherein, The data processing on the target carbon emission data to generate the first transaction request corresponding to the target transaction object comprises: obtaining a carbon emission index corresponding to the target transaction object; comparing the target carbon emission data with the carbon emission index to determine a transaction type corresponding to the target transaction object based on a comparison result; determining a transaction quantity and an expected transaction value corresponding to the transaction type; generating the first transaction request corresponding to the target transaction object using the transaction type, the transaction quantity and the expected transaction value.

3. The method of claim 2, wherein, The generation of the first transaction request corresponding to the target transaction object using the transaction type, the transaction quantity and the expected transaction value comprises: obtaining a current total carbon asset transaction volume and a current carbon asset average transaction value corresponding to a plurality of transaction objects; determining a first ratio between the transaction quantity and the current total carbon asset transaction volume and a second ratio between the expected transaction value and the current carbon asset average transaction value; determining a priority corresponding to the target transaction object using the first ratio and the second ratio; generating the first transaction request corresponding to the target transaction object using the transaction type, the transaction quantity, the expected transaction value and the priority.

4. The method of claim 1, wherein, The sending of the first transaction request to each other node of the node network comprises: obtaining a current network transmission rate of the target node and delay parameter data between the target node and each other node; comparing the delay parameter data with a first preset threshold value, adjusting the current network transmission rate based on a first comparison result to obtain a target transmission rate between the target node and each other node; encrypting and sending the first transaction request corresponding to the target node to each other node according to each target transmission rate.

5. The method of claim 4, wherein, The comparison of the delay parameter data with a first preset threshold value and the adjustment of the current network transmission rate based on a first comparison result to obtain a target transmission rate between the target node and each other node comprises: When the first comparison result represents that the delay parameter data is greater than the first preset threshold, the current network transmission rate is reduced by a first step length to obtain a target transmission rate between the target node and each of the other nodes; the first step length is determined according to a ratio of the first preset threshold to the delay parameter data; When the first comparison result represents that the delay parameter data is less than or equal to the first preset threshold, the current network transmission rate is increased by a second step length to obtain a target transmission rate between the target node and each of the other nodes; the second step length is determined according to a ratio of the delay parameter data to the first preset threshold.

6. The method of claim 1, wherein, The matching of the first transaction request and each of the second transaction requests according to the preset price matching rule to obtain a matching result, comprising: extracting first transaction data corresponding to the target node from the first transaction request; for any of the other nodes, extracting second transaction data corresponding to the other node from the second transaction request; determining a matching degree between the target node and each of the other nodes by using the first transaction data and each of the second transaction data; matching the first transaction request and each of the second transaction requests according to the matching degree to obtain the matching result.

7. The method of claim 6, wherein, The first transaction data includes a first transaction type and a first expected transaction value corresponding to the target node, and the second transaction data includes a second transaction type and a second expected transaction value corresponding to the other node; The determination of the matching degree between the target node and each of the other nodes by using the first transaction data and each of the second transaction data, comprising: matching the first transaction type and each of the second transaction type to determine a transaction type matching result between the target node and each of the other nodes; determining a difference between the first expected transaction value and each of the second expected transaction value, and determining the matching degree between the target node and each of the other nodes by using the transaction type matching result and the difference.

8. The method of claim 6, wherein, The matching of the first transaction request and each of the second transaction requests according to the matching degree to obtain the matching result, comprising: determining whether the matching degree is greater than a second preset threshold; if the matching degree is greater than the second preset threshold, matching the target node and any of the other nodes whose matching degree is greater than the second preset threshold to obtain the matching result.

9. A carbon asset trading matching device, characterized by, A target node applied to a node network, the node network comprising nodes created for each transaction object; the device comprising: an acquisition module configured to acquire target carbon emission data of a target transaction object corresponding to the target node; a processing module configured to perform data processing on the target carbon emission data to generate a first transaction request corresponding to the target transaction object; a sending module configured to send the first transaction request to each of other nodes of the node network, and acquire second transaction requests of other transaction objects sent by each of the other nodes; A matching module is configured to match the first transaction request with each of the second transaction requests according to a preset price matching rule to obtain a matching result. A transaction module is configured to perform carbon asset transaction between the target transaction object and the other transaction objects by using the matching result to generate a transaction result.

10. A computer device, comprising: The method comprises the following steps: A memory and a processor are communicatively connected, and the memory stores computer instructions. The processor executes the computer instructions to perform the carbon asset transaction matching method according to any one of claims 1 to 8.

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