Computing power transaction method, device and equipment, storage medium and computer program product

Abstract

The invention discloses a computing power transaction method, device and equipment, a storage medium and a computer program product, and the method comprises the steps: determining a task score of a computing power provider according to a target demand of a computing power demand side and a transaction request of the computing power provider; and determining a computing power price according to the task score, screening the computing power providers according to the task score, and obtaining a target computing power provider to perform computing power settlement according to the computing power price. According to the method, screening of the optimal computing power providers adapting to the target demand of the computing power demand side can be realized, and better-quality computing power service is provided for the computing power demand side while transaction fairness and the standard reaching quality of the target demand of the computing power demand side are ensured; and the computing power price is adjusted according to the task score, so that higher computing power reward is provided for the computing power provider, and the computing power provider is promoted to improve the computing power service level.

Description

Technical Field

[0001] The present invention relates to the field of blockchain technology, and in particular to a computing power trading method, device, equipment, storage medium and computer program product. Background Art

[0002] At present, large-scale data processing and computing tasks require a lot of computing resources to complete, such as artificial intelligence, data mining, deep learning, etc. The traditional way of providing computing power is often monopolized by a few large computing power service providers, resulting in unfairness and inefficiency in the computing power trading market. In addition, most of the existing computing power trading platforms adopt a centralized management method, and the trading parties need to trust the platform's intermediary services, which poses certain security risks. The use of blockchain's decentralized storage, content immutability, and data encryption characteristics can specifically solve the problems existing in the above centralized computing power trading methods.

[0003] However, the current computing power trading method based on blockchain technology lacks high-quality screening of computing power providers in matching computing power demanders and computing power providers, and is unable to obtain computing power providers that are more adapted to the target needs of computing power demanders, resulting in a situation where the target needs of computing power transactions cannot effectively reach the optimal matching computing power provider; in addition, existing computing power transactions often use fixed-amount transactions and lack effective incentives for computing power providers. During the computing power trading process, it is difficult for computing power demanders to meet their target needs. Summary of the invention

[0004] The technical problem to be solved by the present invention is to provide a computing power trading method, device, equipment, storage medium and computer program product, which can realize the screening of the optimal computing power provider that meets the target requirements of the computing power demander, while ensuring the fairness of the transaction and the quality of the computing power demander's target requirements, and provide the computing power demander with better quality computing power services; adjust the computing power price according to the task score, so as to achieve higher computing power remuneration for the computing power provider, and promote the computing power provider to improve the computing power service level.

[0005] In order to achieve the above object, an embodiment of the present invention provides a computing power trading method, including: Determine the task score of the computing power provider according to the target demand of the computing power demander and the transaction request of the computing power provider; The computing power pricing is determined according to the task score, and the computing power providers are screened according to the task score to obtain a target computing power provider for computing power settlement at the computing power pricing.

[0006] As an improvement of the above solution, the task score of the computing power provider is determined according to the target demand of the computing power demander and the transaction request of the computing power provider, including: Determine the standard score and reward score of the computing power provider according to the target demand of the computing power demander and the transaction request of the computing power provider; wherein the target demand includes a description of the target demand, a description of the data, an average of the target score, and a standard budget and reward budget for completing the target demand; The task score of the computing power provider is calculated based on the standard score and the reward score.

[0007] As an improvement of the above solution, the standard score and reward score of the computing power provider are determined according to the target demand of the computing power demander and the transaction request of the computing power provider, including: Based on the target demand of the computing power demander and the transaction request of the computing power provider, the calculation results of both parties of the computing power transaction are obtained; wherein the calculation results are processed by data desensitization; Identify the calculation accuracy of the calculation result according to the target requirement description to obtain the calculation accuracy of the calculation power provider; If the computing power accuracy does not exceed the target accuracy described in the target requirement, the standard score of the computing power provider is calculated based on the total amount of low-precision calculation results and the total amount of target requirement description results; If the computing power accuracy exceeds the target accuracy described in the target requirement, the reward score of the computing power provider is calculated based on the total amount of high-precision calculation results and the total amount of target requirement description results.

[0008] As an improvement of the above solution, the total amount of low-precision calculation results is: ; In the formula, Indicates the total amount of low-precision calculation results; Indicates the total number of low-precision calculation results, that is, the total number of calculation results corresponding to the target precision described by the target requirement; Represents the number of weighted low-precision calculation results, , a Indicates the number of items in the i-th low-precision calculation result, Indicates the precision loss level of the i-th low-precision calculation result The corresponding weights; The total amount of high-precision calculation results is: ; In the formula, Indicates the total amount of high-precision calculation results; Indicates the total number of high-precision calculation results, that is, the total number of calculation results corresponding to the target accuracy described by the target requirement; Represents the number of weighted high-precision calculation results, , b Indicates the number of items in the i-th high-precision calculation result, H i represents the precision gain coefficient of the i-th high-precision calculation result, V i The business value coefficient representing the i-th high-precision calculation result; Then, the calculation formula of the standard score is: ; In the formula, Indicates the total amount of target requirement description results, that is, the number of all calculation result items contained in the target requirement description; The calculation formula for the reward score is: ; The calculation formula for the task score is: Task score = standard weight * standard score + bounty weight * bounty score.

[0009] As an improvement of the above solution, the method of determining the computing power pricing according to the task score includes: According to the standard score and the reward score in the task score, the computing power pricing is calculated as: Computing power pricing = standard budget * standard score + bounty budget * bounty score.

[0010] As an improvement of the above solution, the computing power providers are screened according to the task scores to obtain the target computing power providers for computing power settlement at the computing power pricing, including: Calculate the budget computing power required for the target demand based on the reference computing power for completing the target demand; According to the budgeted computing power, the target score average, the standard budget, and the task score, a computing power provider that meets the target requirement is selected from all computing power providers as a candidate computing power provider; Calculate the evaluation value of the candidate computing power provider based on the bid and task score of the candidate computing power provider; The candidate computing power provider corresponding to the highest evaluation value is selected from all evaluation values ​​as the target computing power provider, and computing power settlement is performed based on the computing power pricing.

[0011] The embodiment of the present invention further provides a computing power trading device, including: A task scoring module, used to determine the task score of the computing power provider according to the target demand of the computing power demander and the transaction request of the computing power provider; The computing power trading module is used to determine the computing power pricing according to the task score, and screen the computing power providers according to the task score to obtain the target computing power provider for computing power settlement at the computing power pricing.

[0012] An embodiment of the present invention also provides a terminal device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor implements any of the above-mentioned computing power trading methods when executing the computer program.

[0013] An embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium includes a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute any one of the above-mentioned computing power trading methods.

[0014] An embodiment of the present invention further provides a computer program product, which includes a computer program or computer instructions. When the computer program or the computer instructions are executed by a processor, any of the above-mentioned computing power trading methods is implemented.

[0015] Compared with the prior art, the beneficial effects of a computing power trading method, device, equipment, storage medium and computer program product provided by the embodiments of the present invention are: determining the task score of the computing power provider according to the target demand of the computing power demander and the transaction request of the computing power provider; determining the computing power pricing according to the task score, and screening the computing power providers according to the task score, so as to obtain the target computing power provider to settle computing power at the computing power pricing. The embodiments of the present invention can realize the screening of the optimal computing power provider that meets the target demand of the computing power demander, and provide the computing power demander with better computing power services while ensuring the fairness of the transaction and the quality of the computing power demander's target demand; adjusting the computing power price with the standard budget and the bounty budget, so as to achieve higher computing power rewards for the computing power providers, promote the computing power providers to improve the computing power service level, and form a virtuous circle. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a flow chart of a preferred embodiment of a computing power trading method provided by the present invention; Figure 2 It is a structural schematic diagram of a preferred embodiment of a computing power trading device provided by the present invention; Figure 3 It is a structural schematic diagram of a preferred embodiment of a terminal device provided by the present invention. DETAILED DESCRIPTION

[0017] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0018] See also Figure 1 , Figure 1 The figure is a flow chart of a preferred embodiment of a computing power trading method provided by the present invention. The computing power trading method comprises: S1, determining the task score of the computing power provider according to the target demand of the computing power demander and the transaction request of the computing power provider; S2, determining the computing power pricing according to the task score, and screening the computing power providers according to the task score, obtaining the target computing power provider to perform computing power settlement at the computing power pricing.

[0019] It should be noted that the decentralized computing power trading method based on blockchain is a new and innovative trading model. It fully utilizes the advantages of blockchain technology and improves the transparency, security and efficiency of transactions. First of all, blockchain technology avoids the single point of failure and trust problems that may exist in traditional centralized exchanges through a decentralized approach. In computing power transactions, this means that the two parties to the transaction can directly conduct point-to-point transactions without the need for matchmaking and matching through an intermediary, thereby reducing transaction costs and improving transaction efficiency. At the same time, since the data on the blockchain is open and transparent, the two parties to the transaction can verify each other's identity and transaction records, which further enhances the security of the transaction. However, due to its openness and transparency, it is easy to cause the leakage of computing power transaction content, and the transaction has limitations. Secondly, blockchain technology ensures the immutability and traceability of computing power transactions. During the computing power transaction process, data is stored on the blockchain to form a continuous and immutable record. This effectively guarantees the integrity and authenticity of the transaction and prevents the forgery and tampering of data. At the same time, blockchain technology can also realize real-time reconciliation and protocol preservation of transactions, solving the problems of data traceability and bill reconciliation in computing power transactions. In addition, the application of smart contract technology has further enriched the way of decentralized computing power transactions. Smart contracts can automatically execute transaction conditions. When certain conditions are met, the contract can be automatically triggered and complete the transaction. This not only improves the degree of automation of transactions, but also reduces delays and uncertainties in the transaction process.

[0020] Specifically, the embodiment of the present invention proposes a computing power trading method based on reward incentives, builds a decentralized computing power trading platform based on blockchain, and connects computing power providers and computing power demanders to the computing power trading platform to build an optimal solution matching method for computing power providers and computing power demanders. The computing power demander sends the target demand to the computing power trading platform for broadcasting; before broadcasting, the computing power trading platform verifies the target demand issued by the computing power demander. After verification, it generates a task corresponding to the computing power demander according to the target demand, as a reward task, and broadcasts it; on the contrary, if the verification fails, it does not broadcast it. The computing power provider responds according to the broadcast; at this time, the computing power provider can respond to multiple reward tasks at the same time; wherein the response includes the quotation for the reward task and the computing power that can be provided. The computing power trading platform determines the task score of the computing power provider according to the target demand of the computing power demander and the transaction request of the computing power provider. The task score is used as the data that runs through the entire transaction between the computing power provider and the computing power demander, providing support for the positive incentive closed-loop control of computing power trading. The computing power pricing is determined based on the task score, and the computing power providers are screened based on the task score to obtain the optimal computing power provider as the target computing power provider, and the computing power settlement is carried out according to the computing power pricing.

[0021] The embodiments of the present invention can realize the screening of the optimal computing power provider that meets the target requirements of the computing power demander, and provide the computing power demander with better computing power services while ensuring the fairness of transactions and the quality of the computing power demander's target requirements. The computing power price is adjusted according to the task score, so as to achieve higher computing power remuneration for the computing power provider, promote the computing power provider to improve the computing power service level, and form a virtuous circle.

[0022] In another preferred embodiment, determining the task score of the computing power provider according to the target demand of the computing power demander and the transaction request of the computing power provider includes: Determine the standard score and reward score of the computing power provider according to the target demand of the computing power demander and the transaction request of the computing power provider; wherein the target demand includes a description of the target demand, a description of the data, an average of the target score, and a standard budget and reward budget for completing the target demand; The task score of the computing power provider is calculated based on the standard score and the reward score.

[0023] Specifically, when determining the task score of the computing power provider, the embodiment of the present invention first determines the standard score and bounty score of the computing power provider according to the target demand of the computing power demander and the transaction request of the computing power provider. Among them, the target demand includes the target demand description, data description, target score mean, and the standard budget and bounty budget for completing the target demand. It should be noted that the target demand description refers to a detailed description of the computing task, including the goal of the task, the problem to be solved, the expected output, etc., which helps the computing power provider understand the specific requirements of the task and formulate a suitable computing strategy for it; the data description refers to the original data or data set required for the computing task, including various types of data such as text, images, videos, audio, etc. The computing power provider will use these input data for calculation and analysis to obtain the calculation results; the bounty budget is the maximum bounty for the part of the final computing power pricing that exceeds the standard budget. Then, based on the standard score and the bounty score, the task score of the computing power provider is calculated.

[0024] In another preferred embodiment, determining the standard score and reward score of the computing power provider according to the target demand of the computing power demander and the transaction request of the computing power provider includes: Based on the target demand of the computing power demander and the transaction request of the computing power provider, the calculation results of both parties of the computing power transaction are obtained; wherein the calculation results are processed by data desensitization; Identify the calculation accuracy of the calculation result according to the target requirement description to obtain the calculation accuracy of the calculation power provider; If the computing power accuracy does not exceed the target accuracy described in the target requirement, the standard score of the computing power provider is calculated based on the total amount of low-precision calculation results and the total amount of target requirement description results; If the computing power accuracy exceeds the target accuracy described in the target requirement, the reward score of the computing power provider is calculated based on the total amount of high-precision calculation results and the total amount of target requirement description results.

[0025] Specifically, the embodiment of the present invention introduces a blockchain computing power trading platform in the determination link of the standard score and the bounty score to ensure the authenticity and validity of the standard score and the bounty score, and effectively avoids data leakage by desensitizing. The embodiment of the present invention builds a side chain based on the computing power provider and the computing power demander, and uses data encryption to provide the computing power provider and the computing power demander for data transmission. The encrypted data is stored in the side chain during the transmission process. After the computing power provider obtains the corresponding calculation results according to the target requirements of the computing power demander, the computing power provider is first required to perform a self-check on the calculation results, that is, to verify the calculation results. The verification method is provided and implemented by the computing power provider. At the same time, the computing power provider transmits the verification method and the calculation results of the calculation results to the computing power demander through the side chain. The computing power demander verifies the calculation results according to the verification method of the calculation results provided by the computing power provider, with the purpose of performing secondary verification to facilitate the judgment of the accuracy of the calculation results. After the verification is passed, the calculation result is judged to be correct; otherwise, the computing power demander sends a recalculation request to the computing power provider until the calculation result is confirmed to be correct. The computing power provider provides the method for verification, and the computing power demander implements the verification. The two parties to the computing power transaction will upload the final calculation result and the target demand description after verification to the computing power trading platform to ensure that the entire calculation process is authentic, effective and traceable.

[0026] It should be noted that the calculation results need to be desensitized before being uploaded to the computing power trading platform to ensure the security of the transaction results and effectively avoid data leakage. The method of desensitizing the calculation results is: use regular expressions to replace the digital data in the calculation results except punctuation marks with preset English letters, and delete the numbers with the suffix data "0" to obtain the desensitized data. Design the precision identification blockchain smart contract. After the computing power trading platform obtains the final calculation results, scoring process, scoring results and target demand description after verification, it will perform calculation precision identification on the desensitized data according to the target precision of the corresponding items in the target demand description. The precision loss levels include severe low precision, general low precision and slight low precision. For example, the precision in the target demand description is ten thousandths, thousandths is slightly low precision, hundredths is generally low precision, and tenths and above are severe low precision.

[0027] The desensitized data is transmitted to the computing power trading platform. The computing power trading platform identifies the punctuation marks in the desensitized data and reads the number of English letters suffixed with the punctuation marks. The calculation accuracy of the desensitized data is obtained according to the number; the desensitized data of the corresponding items are marked according to the calculation accuracy of the desensitized data: the desensitized data whose calculation accuracy does not exceed the target accuracy described in the target requirements of the corresponding project is highlighted; the desensitized data whose calculation accuracy exceeds the target accuracy described in the target requirements of the corresponding project is highlighted. It should be noted that the colors of these two highlights are inconsistent. If the accuracy of the determined calculation result, that is, the computing power accuracy of the computing power provider does not exceed the target accuracy described in the target requirements, the standard score of the computing power provider is calculated based on the total amount of low-precision calculation results and the total amount of target requirements description results. If the computing power accuracy of the computing power provider exceeds the target accuracy described in the target requirements, the reward score of the computing power provider is calculated based on the total amount of high-precision calculation results and the total amount of target requirements description results.

[0028] The embodiment of the present invention proposes to use calculation accuracy as a reference for standard scoring and bounty scoring, and use the standard scoring and bounty scoring to score the tasks of computing power providers as a judgment indicator for the computing power processing quality of the computing power providers, thereby realizing the screening of the optimal computing power providers that meet the target requirements of the computing power demanders.

[0029] In another preferred embodiment, the total amount of low-precision calculation results is: ; In the formula, Indicates the total amount of low-precision calculation results; Indicates the total number of low-precision calculation results, that is, the total number of calculation results corresponding to the target precision described by the target requirement; Represents the number of weighted low-precision calculation results, , a Indicates the number of items in the i-th low-precision calculation result, Indicates the precision loss level of the i-th low-precision calculation result The corresponding weights; The total amount of high-precision calculation results is: ; In the formula, Indicates the total amount of high-precision calculation results; Indicates the total number of high-precision calculation results, that is, the total number of calculation results corresponding to the target accuracy described by the target requirement; Represents the number of weighted high-precision calculation results, , b Indicates the number of items in the i-th high-precision calculation result, H irepresents the precision gain coefficient of the i-th high-precision calculation result, V i The business value coefficient representing the i-th high-precision calculation result; Then, the calculation formula of the standard score is: ; In the formula, Indicates the total amount of target requirement description results, that is, the number of all calculation result items contained in the target requirement description; The calculation formula for the reward score is: ; The calculation formula for the task score is: Task score = standard weight * standard score + bounty weight * bounty score.

[0030] Specifically, if the computing power accuracy of the computing power provider does not exceed the target accuracy described in the target requirement, the standard score of the computing power provider is calculated based on the total amount of low-precision calculation results and the total amount of results described in the target requirement.

[0031] For each low-precision calculation result, determine the precision loss level to which it belongs according to its precision loss, that is, the low-precision level ; Among them, the accuracy loss levels include severe low accuracy, general low accuracy and slight low accuracy. For example, in the target requirement description, if the accuracy is ten thousandths, thousandths is slight low accuracy, hundredths is general low accuracy, and tenths and above are severe low accuracy; According to the low precision level , find the corresponding weight ; Calculate the weighted number of low-precision calculation results: ; It should be noted that here a Indicates the number of items of the i-th low-precision calculation result. For example, assume that the i-th low-precision result item count is 1, and then weight it according to its weight.

[0032] Sum up all weighted low-precision calculation results to get the total weighted low-precision calculation results: ; The standard score is calculated based on the total amount of weighted low-precision calculation results and the total amount of target requirement description results: .

[0033] If the computing power accuracy of the computing power provider exceeds the target accuracy described in the target requirement, the reward score of the computing power provider will be calculated based on the total amount of high-precision calculation results and the total amount of results described in the target requirement.

[0034] For each high-precision calculation result, the corresponding coefficient is determined according to its accuracy gain and business value. and ; Calculate the weighted number of high-precision calculation results: ; It should be noted that here b Indicates the number of items of the i-th high-precision calculation result. For example, assume that the i-th high-precision result item count is 1, and then weight it according to its precision gain and business value.

[0035] Sum up all weighted high-precision calculation results to get the total weighted high-precision calculation results: ; The reward score is calculated based on the total amount of weighted high-precision calculation results and the total amount of target requirement description results: ; The calculation formula for task score is: Task score = standard weight * standard score + bounty weight * bounty score.

[0036] It should be noted that the precision identification in the embodiment of the present invention is not limited to digital calculation results, and the precision identification of the calculation results can be performed as long as the required precision can be defined in the requirement description.

[0037] The embodiment of the present invention introduces a task score with computing power accuracy as the core as a judgment indicator for the computing power processing quality of the computing power provider, and realizes effective incentives for the computing power provider through the setting of standard scores and reward scores; at the same time, the indicator is introduced into the optimal solution matching method between the computing power provider and the computing power demander, forming a closed transaction loop.

[0038] In another preferred embodiment, determining the computing power pricing according to the task score includes: According to the standard score and the reward score in the task score, the computing power pricing is calculated as: Computing power pricing = standard budget * standard score + bounty budget * bounty score.

[0039] Specifically, the embodiment of the present invention introduces an incentive mechanism of a standard budget and a bounty budget, and adjusts the price of computing power with the standard budget and the bounty budget, thereby giving higher computing power rewards to computing power providers, promoting computing power providers to improve computing power service levels, and forming a virtuous circle.

[0040] In another preferred embodiment, the filtering of the computing power providers according to the task scores to obtain the target computing power providers for computing power settlement at the computing power pricing includes: Calculate the budget computing power required for the target demand based on the reference computing power for completing the target demand; According to the budgeted computing power, the target score average, the standard budget, and the task score, a computing power provider that meets the target requirement is selected from all computing power providers as a candidate computing power provider; Calculate the evaluation value of the candidate computing power provider based on the bid and task score of the candidate computing power provider; The candidate computing power provider corresponding to the highest evaluation value is selected from all evaluation values ​​as the target computing power provider, and computing power settlement is performed based on the computing power pricing.

[0041] Specifically, in the embodiment of the present invention, the computing power trading platform uses natural language processing technology to identify the characteristic data of the target demand description and data description, and searches for the completed bounty task with the highest similarity to the corresponding characteristic data in history, and uses the computing power of the completed bounty task as the reference computing power to calculate the budget computing power required to complete the bounty task. It should be noted that the reference computing power can also be provided by the computing power demander. Among them, the calculation formula of the budget computing power is: Budgeted computing power = reference computing power / similarity + reference computing power / similarity * computing power growth rate; Among them, computing power growth rate = (computing power required in the current quarter - computing power required in the adjacent quarter) / computing power required in the adjacent quarter * 100%; In the formula, the computing power required for the current quarter and the computing power required for the adjacent quarter are of the same type of computing power, including but not limited to: basic computing power / based on CPU chips, intelligent computing power / based on GPU and NPU chips, and supercomputing computing power.

[0042] The computing power trading platform obtains the quoted values ​​and the computing power that can be provided by multiple responding computing power providers corresponding to the current bounty task. The computing power trading platform obtains the task score of the computing power provider, which can also be the average task score. The average task score is the average of the task scores of the computing power provider after completing multiple bounty tasks. The computing power trading platform selects computing power providers that meet the budget computing power corresponding to the bounty task, the target score average and the standard budget, and locks them (after the computing power provider is locked, the computing power that the computing power provider responds to is locked and cannot be used as the computing power provided by the remaining bounty tasks) as candidate computing power providers. Then, the best candidate computing power provider is selected according to the evaluation value as the final target computing power provider. The calculation formula of the evaluation value is: Z = -A*B+C*(1-B) ; In the formula, Z represents the evaluation value, A represents the quotation value, B represents the weight of the quotation value (the weight can be determined by the computing power demander, and 0≤B≤1), and C represents the average task score of the computing power provider.

[0043] Based on the evaluation value calculation results, the candidate computing power provider corresponding to the highest evaluation value is selected as the final target computing power provider, and the computing power settlement is carried out according to the computing power pricing.

[0044] Correspondingly, the present invention also provides a computing power trading device that can implement all processes of the computing power trading method in the above embodiment.

[0045] See also Figure 2 , Figure 2 The figure is a schematic diagram of a preferred embodiment of a computing power trading device provided by the present invention. The computing power trading device comprises: The task scoring module 201 is used to determine the task score of the computing power provider according to the target demand of the computing power demander and the transaction request of the computing power provider; The computing power transaction module 202 is used to determine the computing power pricing according to the task score, and screen the computing power providers according to the task score to obtain the target computing power provider for computing power settlement at the computing power pricing.

[0046] Preferably, the task scoring module 201 includes: A first scoring unit is used to determine a standard score and a bounty score of the computing power provider according to the target demand of the computing power demander and the transaction request of the computing power provider; wherein the target demand includes a target demand description, a data description, a target score mean, and a standard budget and a bounty budget for completing the target demand; The second scoring unit is used to calculate the task score of the computing power provider according to the standard score and the reward score.

[0047] Preferably, the first scoring unit is specifically used for: Based on the target demand of the computing power demander and the transaction request of the computing power provider, the calculation results of both parties of the computing power transaction are obtained; wherein the calculation results are processed by data desensitization; Identify the calculation accuracy of the calculation result according to the target requirement description to obtain the calculation accuracy of the calculation power provider; If the computing power accuracy does not exceed the target accuracy described in the target requirement, the standard score of the computing power provider is calculated based on the total amount of low-precision calculation results and the total amount of target requirement description results; If the computing power accuracy exceeds the target accuracy described in the target requirement, the reward score of the computing power provider is calculated based on the total amount of high-precision calculation results and the total amount of description results of the target requirement.

[0048] Preferably, the total amount of low-precision calculation results is: ; In the formula, Indicates the total amount of low-precision calculation results; Indicates the total number of low-precision calculation results, that is, the total number of calculation results corresponding to the target precision described by the target requirement; Represents the number of weighted low-precision calculation results, , a Indicates the number of items in the i-th low-precision calculation result, Indicates the precision loss level of the i-th low-precision calculation result The corresponding weights; The total amount of high-precision calculation results is: ; In the formula, Indicates the total amount of high-precision calculation results; Indicates the total number of high-precision calculation results, that is, the total number of calculation results corresponding to the target accuracy described by the target requirement; Represents the number of weighted high-precision calculation results, , b Indicates the number of items in the i-th high-precision calculation result, H i represents the precision gain coefficient of the i-th high-precision calculation result, V i The business value coefficient representing the i-th high-precision calculation result; Then, the calculation formula of the standard score is: ; In the formula, Indicates the total amount of target requirement description results, that is, the number of all calculation result items contained in the target requirement description; The calculation formula for the reward score is: ; The calculation formula for the task score is: Task score = standard weight * standard score + bounty weight * bounty score.

[0049] Preferably, determining the computing power pricing according to the task score includes: According to the standard score and the reward score in the task score, the computing power pricing is calculated as: Computing power pricing = standard budget * standard score + bounty budget * bounty score.

[0050] Preferably, the step of screening the computing power providers according to the task scores to obtain a target computing power provider for computing power settlement at the computing power pricing includes: Calculate the budget computing power required for the target demand based on the reference computing power for completing the target demand; According to the budgeted computing power, the target score average, the standard budget, and the task score, a computing power provider that meets the target requirement is selected from all computing power providers as a candidate computing power provider; Calculate the evaluation value of the candidate computing power provider based on the bid and task score of the candidate computing power provider; The candidate computing power provider corresponding to the highest evaluation value is selected from all evaluation values ​​as the target computing power provider, and computing power settlement is performed based on the computing power pricing.

[0051] In the specific implementation, the working principle, control process and technical effect achieved by the computing power trading device provided in the embodiment of the present invention are the same as those of the computing power trading method in the above embodiment, and will not be repeated here.

[0052] See also Figure 3 , Figure 3 3 is a schematic diagram of a preferred embodiment of a terminal device provided by the present invention. The terminal device includes a processor 301, a memory 302, and a computer program stored in the memory 302 and configured to be executed by the processor 301. When the processor 301 executes the computer program, the computing power trading method described in any of the above embodiments is implemented.

[0053] Preferably, the computer program may be divided into one or more modules / units (such as computer program 1, computer program 2, ...), and the one or more modules / units are stored in the memory 302 and executed by the processor 301 to complete the present invention. The one or more modules / units may be a series of computer program instruction segments capable of completing specific functions, and the instruction segments are used to describe the execution process of the computer program in the terminal device.

[0054] The processor 301 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor, or the processor 301 may be any conventional processor. The processor 301 is the control center of the terminal device, and various parts of the terminal device are connected using various interfaces and lines.

[0055] The memory 302 mainly includes a program storage area and a data storage area, wherein the program storage area can store an operating system, an application required for at least one function, etc., and the data storage area can store related data, etc. In addition, the memory 302 can be a high-speed random access memory, or a non-volatile memory, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, and a flash card (Flash Card), etc., or the memory 302 can also be other volatile solid-state storage devices.

[0056] It should be noted that the above terminal device may include, but is not limited to, a processor and a memory. Those skilled in the art will understand that Figure 3 The structural diagram is only an example of the above-mentioned terminal device and does not constitute a limitation of the above-mentioned terminal device. It may include more or less components than shown in the figure, or combine certain components, or different components.

[0057] An embodiment of the present invention further provides a computer-readable storage medium, which includes a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute the computing power trading method described in any of the above embodiments.

[0058] An embodiment of the present invention further provides a computer program product, which includes a computer program or computer instructions. When the computer program or the computer instructions are executed by a processor, the computing power trading method described in any of the above embodiments is implemented.

[0059] The embodiments of the present invention provide a computing power transaction method, apparatus, device, storage medium and computer program product, which determine the task score of the computing power provider according to the target demand of the computing power demander and the transaction request of the computing power provider; determine the computing power pricing according to the task score, and screen the computing power providers according to the task score to obtain the target computing power provider to settle computing power at the computing power pricing. The embodiments of the present invention can realize the screening of the optimal computing power provider that meets the target demand of the computing power demander, and provide the computing power demander with better computing power services while ensuring the fairness of the transaction and the quality of the computing power demander's target demand; adjust the computing power price with the standard budget and the bounty budget, so as to achieve higher computing power rewards for the computing power providers, promote the computing power providers to improve the computing power service level, and form a virtuous circle.

[0060] It should be noted that the system embodiment described above is merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. In addition, in the drawings of the system embodiment provided by the present invention, the connection relationship between the modules indicates that there is a communication connection between them, which may be specifically implemented as one or more communication buses or signal lines. A person of ordinary skill in the art may understand and implement it without paying any creative effort.

[0061] The above is a preferred embodiment of the present invention. It should be pointed out that a person skilled in the art can make several improvements and modifications without departing from the principle of the present invention. These improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A computing power trading method, characterized in that: include: Determine the task score of the computing power provider according to the target demand of the computing power demander and the transaction request of the computing power provider; The computing power pricing is determined according to the task score, and the computing power providers are screened according to the task score to obtain a target computing power provider for computing power settlement at the computing power pricing.

2. The computing power trading method according to claim 1, characterized in that: Determining the task score of the computing power provider according to the target demand of the computing power demander and the transaction request of the computing power provider includes: Determine the standard score and reward score of the computing power provider according to the target demand of the computing power demander and the transaction request of the computing power provider; wherein the target demand includes a description of the target demand, a description of the data, an average of the target score, and a standard budget and reward budget for completing the target demand; The task score of the computing power provider is calculated based on the standard score and the reward score.

3. The computing power trading method according to claim 2, characterized in that: Determining the standard score and reward score of the computing power provider according to the target demand of the computing power demander and the transaction request of the computing power provider includes: Based on the target demand of the computing power demander and the transaction request of the computing power provider, the calculation results of both parties of the computing power transaction are obtained; wherein the calculation results are processed by data desensitization; Identify the calculation accuracy of the calculation result according to the target requirement description to obtain the calculation accuracy of the calculation power provider; If the computing power accuracy does not exceed the target accuracy described in the target requirement, the standard score of the computing power provider is calculated based on the total amount of low-precision calculation results and the total amount of target requirement description results; If the computing power accuracy exceeds the target accuracy described in the target requirement, the reward score of the computing power provider is calculated based on the total amount of high-precision calculation results and the total amount of target requirement description results.

4. The computing power trading method according to claim 3, characterized in that: The total amount of low-precision calculation results is: ； In the formula, Indicates the total amount of low-precision calculation results; Indicates the total number of low-precision calculation results, that is, the total number of calculation results corresponding to the target precision described by the target requirement; Represents the number of weighted low-precision calculation results, , a Indicates the number of items in the i-th low-precision calculation result, Indicates the precision loss level of the i-th low-precision calculation result The corresponding weights; The total amount of high-precision calculation results is: ； In the formula, Indicates the total amount of high-precision calculation results; Indicates the total number of high-precision calculation results, that is, the total number of calculation results corresponding to the target accuracy described by the target requirement; Represents the number of weighted high-precision calculation results, , b Indicates the number of items in the i-th high-precision calculation result, H i represents the precision gain coefficient of the i-th high-precision calculation result, V i The business value coefficient representing the i-th high-precision calculation result; Then, the calculation formula of the standard score is: ； In the formula, Indicates the total amount of target requirement description results, that is, the number of all calculation result items contained in the target requirement description; The calculation formula for the reward score is: ； The calculation formula for the task score is: Task score = standard weight * standard score + bounty weight * bounty score.

5. The computing power trading method according to claim 3 or 4, characterized in that: The determining of computing power pricing according to the task score includes: According to the standard score and the reward score in the task score, the computing power pricing is calculated as: Computing power pricing = standard budget * standard score + bounty budget * bounty score.

6. The computing power trading method according to claim 5, characterized in that: The filtering of the computing power providers according to the task scores to obtain a target computing power provider for computing power settlement at the computing power pricing includes: Calculate the budget computing power required for the target demand based on the reference computing power for completing the target demand; According to the budgeted computing power, the target score average, the standard budget, and the task score, a computing power provider that meets the target requirement is selected from all computing power providers as a candidate computing power provider; Calculate the evaluation value of the candidate computing power provider based on the bid and task score of the candidate computing power provider; The candidate computing power provider corresponding to the highest evaluation value is selected from all evaluation values ​​as the target computing power provider, and computing power settlement is performed based on the computing power pricing.

7. A computing power trading device, characterized in that: include: A task scoring module, used to determine the task score of the computing power provider according to the target demand of the computing power demander and the transaction request of the computing power provider; The computing power trading module is used to determine the computing power pricing according to the task score, and screen the computing power providers according to the task score to obtain the target computing power provider for computing power settlement at the computing power pricing.

8. A terminal device, characterized in that: It comprises a processor and a memory, wherein a computer program is stored in the memory, and the computer program is configured to be executed by the processor, and when the processor executes the computer program, the computing power trading method as described in any one of claims 1 to 6 is implemented.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, wherein when the device where the computer-readable storage medium is located executes the computer program, the computing power trading method according to any one of claims 1 to 6 is implemented.

10. A computer program product, characterized in that The computer program product includes a computer program or computer instructions, and when the computer program or the computer instructions are executed by a processor, the computing power trading method as described in any one of claims 1 to 6 is implemented.

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