A computing power resource transaction management method and system

Abstract

The present invention provides a computing power resource transaction management method and system, which relates to the field of computing power resource transaction technology. The method includes: obtaining a computing power transaction request issued by a computing power demander and determining multiple reference computing power providers; obtaining historical computing power transaction data of multiple reference computing power providers, analyzing multiple groups of historical computing power transaction data, and determining the computing power transaction evaluation value of each reference computing power provider; determining a target computing power provider from multiple reference computing power providers based on a preset computing power transaction screening threshold, and recommending computing power transaction objects to the computing power demander based on the target computing power provider; in response to the computing power demander selecting to conduct computing power transactions with the target computing power provider, providing computing power services to the computing power demander based on the target computing power provider. The present invention improves the computing power transaction experience of the computing power demander.

Description

Technical Field

[0001] The present invention relates to the field of computing power resource trading technology, and in particular to a computing power resource trading management method and system. Background Art

[0002] With the rapid development of cloud computing and big data technologies, the demand for computing resources continues to grow. Effective management and efficient utilization of computing resources have become important factors in improving overall computing performance and cost-effectiveness.

[0003] Existing technologies simply select computing power providers based on the computing power demander's needs and provide computing power services to them, without considering the volatility of computing resource usage. When computing resources from different computing power providers execute tasks, actual execution time and resource utilization may fluctuate due to factors such as hardware performance, task complexity, and system load. This can affect the computing power demander's experience with computing power services. Furthermore, potential failures encountered during task execution can affect the time it takes to ultimately complete the computing goal. Some pricing methods can cause a discrepancy between the estimated cost and the actual cost for computing power demanders, impacting the accuracy of their decision-making. Summary of the Invention

[0004] The present invention proposes a computing power resource transaction management method and system, aiming to solve at least one technical problem existing in the above-mentioned background technology.

[0005] To achieve the above objectives, the present invention provides a computing resource transaction management method in a first aspect, comprising:

[0006] Obtain a computing power transaction request from a computing power demander, determine computing power demand information based on the computing power transaction request, and determine multiple reference computing power providers from the computing power transaction platform based on the computing power demand information;

[0007] Obtain historical computing power transaction data from multiple reference computing power providers, analyze multiple sets of historical computing power transaction data, and determine the computing power transaction evaluation value of each reference computing power provider;

[0008] Determine the target computing power provider from multiple reference computing power providers based on the preset computing power transaction screening threshold, and recommend computing power transaction partners to the computing power demander based on the target computing power provider;

[0009] In response to the computing power demander selecting to conduct a computing power transaction with the target computing power provider, the computing power provider provides computing power services to the computing power demander based on the target computing power provider;

[0010] Among them, by analyzing multiple sets of historical computing power transaction data, the computing power transaction evaluation value of each reference computing power provider is determined, including:

[0011] Extract the task execution time data, resource utilization data, and failure rate data corresponding to different computing tasks in each set of historical computing power transaction data. Determine the efficiency factor and failure rate factor based on the task execution time data and failure rate data. Analyze the resource utilization data based on the computing power configuration data of each reference computing power provider to determine the resource utilization factor. Calculate the computing power transaction evaluation value of each reference computing power provider using the following formula:

[0012]

[0013] Where, is the computing power transaction evaluation value, is the efficiency factor, is the failure rate factor, is the resource utilization factor, 、 、 are the weight parameters of efficiency factor, failure rate factor and resource utilization factor respectively.

[0014] Preferably, the efficiency factor, the failure rate factor and the resource utilization factor further include:

[0015] For any reference computing power provider, determine the reference computing amount of each computing task in the historical computing power transaction data of the reference computing power provider. Determine the first completion time and second completion time of each computing task based on the reference computing amount of each computing task. Calculate the efficiency reference factor of each computing task based on the actual completion time of each computing task: ,in, is the first completion time, The second completion time, The actual completion time;

[0016] Calculate the average of the efficiency reference factors of multiple computing tasks and record it as the efficiency factor of the reference computing power provider;

[0017] Calculate the average failure rate of multiple computing tasks and determine the failure rate factor of the reference computing power provider based on the average failure rate: ,in, is the mean failure rate;

[0018] Calculate multiple computing resource usage parameters for each computing task based on the computing power configuration data of the computing power provider and the resource utilization data of each computing task. Determine the resource utilization reference factor for each computing task based on the multiple computing resource usage parameters: ,in, Indicates the first Resource usage parameters, Indicates the The standard parameters of resource usage parameters, Indicates the number of resource usage parameters;

[0019] Calculate the average of the resource utilization reference factors of multiple computing tasks and record it as the resource utilization factor of the reference computing power provider.

[0020] Preferably, determining a target computing power provider from a plurality of reference computing power providers based on a preset computing power transaction screening threshold comprises:

[0021] Filter out multiple reference computing power providers whose computing power transaction evaluation values ​​are greater than a preset computing power transaction screening threshold from multiple reference computing power providers and construct a target computing power set;

[0022] Calculate the hash rate stability factor of each reference hash rate provider in the target hash rate set based on the historical hash rate transaction data corresponding to each reference hash rate provider. Calculate the hash rate transaction reference price of each reference hash rate provider in the target hash rate set based on the hash rate stability factor. Select the reference hash rate provider with the lowest hash rate transaction reference price as the target hash rate provider.

[0023] The reference price of computing power transaction for each reference computing power provider in the target computing power set is calculated based on the computing power stability factor, including:

[0024]

[0025] Where, It is the reference price for computing power transactions. Estimated price for computing power transactions, It is the computing power stability factor.

[0026] Preferably, the computing power stability factor of each reference computing power provider in the target computing power set is calculated based on the historical computing power transaction data corresponding to each reference computing power provider, including:

[0027] For any reference computing power provider, the execution time deviation of each computing task is calculated based on the mean value of the efficiency reference factor, and the resource usage deviation of each computing task is calculated based on the resource utilization reference factor.

[0028] The computing power stability reference factor of each computing task is calculated using the following formula:

[0029]

[0030] Where, It is a reference factor for computing power stability. is the execution time deviation, is resource usage deviation, is the failure rate;

[0031] Calculate the standard deviation of the computing power stability reference factors of multiple computing tasks under the reference computing power provider, and use it as the computing power stability factor of the reference computing power provider.

[0032] Preferably, the difference between the efficiency reference factor of the computing task and the average of multiple efficiency reference factors is the execution time deviation of the computing task, and the difference between the resource utilization reference factor of the computing task and the average of the resource utilization reference factors is the resource usage deviation of the computing task.

[0033] Preferably, the computing power demand information includes computing task type data, computing resource specification data, computing task quantity data, time requirement data and budget data.

[0034] A second aspect of the present invention provides a computing power resource transaction management system, which is used to implement the above-mentioned computing power resource transaction management method, including:

[0035] A computing power transaction request processing module is used to obtain computing power transaction requests issued by computing power demanders, determine computing power demand information based on the computing power transaction requests, and determine multiple reference computing power providers from the computing power transaction platform based on the computing power demand information;

[0036] The computing power transaction evaluation module is used to obtain historical computing power transaction data of multiple reference computing power providers, analyze multiple sets of historical computing power transaction data, and determine the computing power transaction evaluation value of each reference computing power provider;

[0037] A computing power transaction provider recommendation module is used to determine a target computing power provider from multiple reference computing power providers based on a preset computing power transaction screening threshold, and recommend computing power transaction partners to computing power demanders based on the target computing power provider;

[0038] The computing power transaction execution module is used to respond to the computing power demander's selection to conduct computing power transactions with the target computing power provider, and provide computing power services to the computing power demander based on the target computing power provider.

[0039] Preferably, the computing power transaction evaluation module analyzes multiple sets of historical computing power transaction data to determine the computing power transaction evaluation value of each reference computing power provider, including:

[0040] Extract the task execution time data, resource utilization data, and failure rate data corresponding to different computing tasks in each set of historical computing power transaction data. Determine the efficiency factor and failure rate factor based on the task execution time data and failure rate data. Analyze the resource utilization data based on the computing power configuration data of each reference computing power provider to determine the resource utilization factor. Calculate the computing power transaction evaluation value of each reference computing power provider using the following formula:

[0041]

[0042] Where, is the computing power transaction evaluation value, is the efficiency factor, is the failure rate factor, is the resource utilization factor, 、 、 are the weight parameters of efficiency factor, failure rate factor and resource utilization factor respectively.

[0043] The present invention has the following beneficial effects:

[0044] The present invention conducts a detailed analysis of historical computing power transaction data, fully considering factors such as hardware performance fluctuations, task complexity and system load changes that may occur during the calculation process, and generates a computing power transaction evaluation value for evaluating the stability and reliability of the computing power provider by analyzing the computing efficiency factor, failure rate factor and resource utilization factor. It provides a comprehensive, accurate, standardized and quantitative computing power provider evaluation method, which not only improves the accuracy and comprehensiveness of computing resource selection, but also facilitates automated evaluation and decision-making, and helps computing power demanders to complete computing tasks more scientifically, economically and efficiently when selecting and using computing resources, thereby improving the computing power transaction experience of computing power demanders. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 A flowchart of a computing resource transaction management method provided in an embodiment of the present invention.

[0046] Figure 2 A schematic diagram of the structure of a computing power resource transaction management system provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0047] In order to enable those skilled in the art to better understand the technical solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0048] See also Figure 1 The present invention provides a method for managing computing power resource transactions, which specifically includes the following steps:

[0049] S10. Obtain a computing power transaction request from a computing power demander, determine computing power demand information based on the computing power transaction request, and determine multiple reference computing power providers from the computing power transaction platform based on the computing power demand information;

[0050] Specifically, the computing power trading platform serves as an intermediary platform connecting computing power providers and demanders, providing transaction infrastructure and services. The platform is responsible for the release, matching, transaction execution, and payment settlement of computing power resources. Computing power providers who possess computing resources and are willing to rent or sell them can provide computing power services to demanders through the computing power trading platform. The platform extracts computing power demand information from computing power demanders' requests, including but not limited to computing task type data (e.g., data processing, AI training, image rendering, etc.); computing resource specification data (e.g., number of CPU cores, number of GPUs, memory size, storage capacity, etc.); computing task volume data (e.g., estimated computing power (GFLOPS, data processing volume, etc.); time requirement data (e.g., task start time, deadline, execution time range, etc.); and budget data (e.g., the range of fees the demander is willing to pay). Based on the computing power demand information, multiple computing power providers can be preliminarily screened to identify reference computing power providers that meet the computing power demand information.

[0051] S20. Obtain historical computing power transaction data of multiple reference computing power providers, analyze the multiple sets of historical computing power transaction data, and determine a computing power transaction evaluation value for each reference computing power provider;

[0052] Specifically, historical computing power transaction data includes at least the transaction data involved in each computing power transaction process, as well as specific task execution data, such as time data, resource utilization data, computing volume data, and fault data during the execution of computing tasks. When computing resources of different computing power providers execute tasks, the actual execution time and resource utilization may fluctuate significantly due to factors such as hardware performance, task complexity, and system load. As a result, even if multiple reference computing power providers meet the computing power requirements, the actual execution performance of different reference computing power providers may vary. In order to improve the experience of computing power demanders, by analyzing the historical computing power transaction data of each reference computing power provider, a computing power transaction evaluation value is calculated to represent the degree to which each reference computing power provider is worth trading with, to assist computing power demanders in selecting computing power providers.

[0053] S30: Determine a target computing power provider from multiple reference computing power providers based on a preset computing power transaction screening threshold, and recommend a computing power transaction partner to the computing power demander based on the target computing power provider;

[0054] S40: In response to the computing power demander selecting to conduct a computing power transaction with the target computing power provider, the target computing power provider provides computing power services to the computing power demander;

[0055] Specifically, the target computing power provider is determined from multiple reference computing power providers in combination with the preset computing power transaction screening threshold. If the computing power transaction evaluation value corresponding to the target computing power provider is greater than the preset computing power transaction screening threshold, the target computing power provider is recommended to the computing power demander as the computing power transaction object. If the computing power demander chooses to conduct computing power transaction with the target computing power provider, computing power services can be provided to the computing power demander based on the target computing power provider, thereby completing the computing power resource transaction process.

[0056] In an optional implementation process, for step S20, multiple sets of historical computing power transaction data are analyzed to determine the computing power transaction evaluation value of each reference computing power provider, specifically including:

[0057] Extract the task execution time data, resource utilization data and failure rate data corresponding to different computing tasks in each set of historical computing power transaction data, determine the efficiency factor and failure rate factor based on the task execution time data and failure rate data, and analyze the resource utilization data based on the computing power configuration data of each reference computing power provider to determine the resource utilization factor.

[0058] Taking any reference computing power provider as an example, for the calculation of the efficiency factor, the reference computing amount of each computing task in the historical computing power transaction data of the reference computing power provider is determined, and the first completion time and second completion time of each computing task are determined based on the reference computing amount of each computing task.

[0059] Specifically, for multiple computing tasks involving multiple computing power transactions in historical computing power transaction data, the reference computing load corresponding to these tasks can be determined based on the historical computing power transaction data. Then, based on the computing power configuration data of the reference computing power provider, the first and second completion times required to complete this reference computing load can be estimated. Specifically, this estimation is based on the theoretical performance of the computing power provider, with the first and second completion times corresponding to the maximum and minimum completion times, respectively, of the reference computing power provider. For example, let's assume the theoretical computing load of Task X is 1000 GFLOPS. Under high-performance conditions, the maximum computing power of the computing power provider is 200 GFLOPS, with an estimated minimum completion time of 5 seconds. Under low-performance conditions, the minimum computing power is 50 GFLOPS, with an estimated maximum completion time of 20 seconds.

[0060] It is worth noting that the reference computing amount can be estimated based on historical data. For example, based on historical data, it is determined that the actual computing amount of processing 1,000 images based on a certain AI model is 200 GFLOPS (Giga Floating Point Operations Per Second). For a new computing task, for example, 5,000 images need to be processed by the corresponding model, and the estimated reference computing amount is 1,000 GFLOPS. Optionally, it can also be determined based on the actual execution data of each computing task, for example, based on the task execution time (the time from the start to the end of the task), resource utilization (the utilization of resources such as CPU, GPU, memory during the task execution process) and hardware performance (performance parameters of computing resources, such as GFLOPS of CPU, TFLOPS of GPU, etc.) and other data to determine the actual computing amount, and then consider the computing amount wasted in the fault process, so as to obtain the computing amount required to theoretically complete the corresponding computing task, that is, the reference computing amount. The method for determining the reference computing amount is a technical means well known to those skilled in the art and will not be repeated in this embodiment.

[0061] After determining the first completion time and the second completion time of each computing task, the efficiency reference factor of each computing task is calculated based on the actual completion time of each computing task. Specifically:

[0062] Efficiency reference factor = ,in, is the first completion time, The second completion time, The actual completion time.

[0063] After calculating the efficiency reference factor of each computing task in the above manner, the average of the efficiency reference factors of multiple computing tasks is calculated and recorded as the efficiency factor of the reference computing power provider.

[0064] For the calculation of the failure rate factor, the average failure rate of multiple computing tasks is calculated, and the failure rate factor of the reference computing power provider is determined based on the average failure rate. Specifically:

[0065] Failure rate factor = ,in, is the mean failure rate.

[0066] For the calculation of the resource utilization factor, multiple computing resource usage parameters of each computing task are calculated based on the computing power configuration data of the reference computing power provider and the resource utilization data of each computing task. The computing resource usage parameter is used to characterize the usage of a certain computing resource per unit time. For example, assuming that the CPU parameter of the reference computing power provider is 100 GFLOPS and the CPU utilization rate when executing a certain computing task is 70%, the computing resource usage parameter corresponding to the CPU is 70GFLOPS, which is used to characterize the actual CPU computing power used.

[0067] After calculating multiple computing resource usage parameters for each computing task, the resource utilization reference factor for each computing task is determined using the following formula:

[0068] Resource utilization reference factor = ,in, Indicates the first Resource usage parameters, Indicates the The standard parameters of resource usage parameters, Indicates the number of resource usage parameters.

[0069] Specifically, the standard parameter of the resource usage parameter is a pre-set value. Its function is to convert multiple resource usage parameters into dimensionless parameters to achieve data standardization. After calculating the resource utilization reference factor for each computing task, the average of the resource utilization reference factors of multiple computing tasks is calculated and recorded as the resource utilization factor of the reference computing power provider.

[0070] Finally, based on the efficiency factor, failure rate factor, and resource utilization factor, the following formula is used to calculate the computing power transaction evaluation value of each reference computing power provider:

[0071]

[0072] Where, is the computing power transaction evaluation value, is the efficiency factor, is the failure rate factor, is the resource utilization factor, 、 、 are the weight parameters of efficiency factor, failure rate factor and resource utilization factor respectively.

[0073] The aforementioned analysis of historical computing power transaction data and calculation of computing power transaction evaluation values, derived through detailed analysis of historical computing power transaction data, accurately assesses the computing power and reliability of each computing power provider. Taking into account multiple key factors such as task execution time, resource utilization, and failure rate, this comprehensive reflection of the actual performance of computing power providers can help computing power demanders more accurately select computing power resources that meet their needs, avoiding performance issues and increased costs caused by inappropriate selection. Evaluating the comprehensive performance of computing power providers from multiple perspectives avoids the potential bias associated with a single metric, making the evaluation results more comprehensive and reliable. Resource utilization rates of different computing power providers can be fairly compared under the same standards. This solution for quantitatively analyzing computing power transaction evaluation values ​​can be directly used in automated evaluation and decision-making processes, facilitates computer system processing, and can be integrated into computing power trading platforms to achieve automated and intelligent computing power resource selection.

[0074] In an optional implementation process, for step S30, determining a target computing power provider from multiple reference computing power providers based on a preset computing power transaction screening threshold specifically includes:

[0075] Filter out multiple reference computing power providers whose computing power transaction evaluation values ​​are greater than a preset computing power transaction screening threshold from multiple reference computing power providers and construct a target computing power set;

[0076] Specifically, using the preset computing power transaction screening threshold as a reference standard, a preliminary screening is first performed on multiple reference computing power providers, and the multiple reference computing power providers obtained by screening are stored through the target computing power set.

[0077] Calculate the hash rate stability factor of each reference hash rate provider in the target hash rate set based on the historical hash rate transaction data corresponding to each reference hash rate provider. Calculate the hash rate transaction reference price of each reference hash rate provider in the target hash rate set based on the hash rate stability factor. Select the reference hash rate provider with the lowest hash rate transaction reference price as the target hash rate provider.

[0078] The computing power stability factor of each reference computing power provider in the target computing power set is calculated based on the historical computing power transaction data corresponding to each reference computing power provider, specifically including:

[0079] For any reference computing power provider, the execution time deviation of each computing task is calculated based on the mean of the efficiency reference factor, and the resource usage deviation of each computing task is calculated based on the resource utilization reference factor. The execution time deviation of the computing task is specifically the difference between the efficiency reference factor of the computing task and the mean of multiple efficiency reference factors, and the resource usage deviation of the computing task is specifically the difference between the resource utilization reference factor of the computing task and the mean of the resource utilization reference factors.

[0080] After calculating the execution time deviation and resource usage deviation of each computing task, the computing power stability reference factor of each computing task is calculated using the following formula:

[0081]

[0082] Where, It is a reference factor for computing power stability. is the execution time deviation, is resource usage deviation, is the failure rate;

[0083] After calculating the computing power stability reference factor of each computing task corresponding to the reference computing power provider in the above manner, the standard deviation of the computing power stability reference factors of multiple computing tasks under the reference computing power provider is calculated as the computing power stability factor of the reference computing power provider.

[0084] It is worth noting that, considering the computing power transaction process, some pricing methods use a time-based pricing method to determine the computing power transaction price. These methods do not take into account the fluctuations in actual execution time and resource utilization caused by various factors such as hardware performance, task complexity, and system load. As a result, in the process of providing computing power services to computing power demanders, the actual time spent is greater than the pre-estimated price, which may cause the computing power demanders to incur cost overruns when experiencing computing power services.

[0085] In this embodiment, based on the historical computing power transaction data corresponding to each reference computing power provider, each reference computing power provider in the target computing power set is analyzed from the perspective of computing power stability, and the computing power stability factor of each reference computing power provider is calculated. The computing power transaction estimated price is corrected by the computing power stability factor, and the computing power transaction reference price of each reference computing power provider is calculated. The reference computing power provider with the lowest computing power transaction reference price is selected and recorded as the target computing power provider.

[0086] Specifically, the hashrate transaction reference price of each reference hashrate provider in the target hashrate set is calculated based on the hashrate stability factor, including:

[0087]

[0088] Where, It is the reference price for computing power transactions. Estimated price for computing power transactions, It is the computing power stability factor.

[0089] It is worth noting that the estimated price of computing power trading is specifically the computing amount estimated based on the computing task that needs to be performed and the estimated time required for the computing power provider to complete the computing amount. The computing power service price to be paid under the estimated time is then determined according to the charging rules. On this basis, taking into account the computing power stability factor, the highest estimated price under fluctuations is calculated, which is the computing power trading reference price.

[0090] The calculation process for the aforementioned reference price for computing power trading takes into account the fact that traditional time-based pricing methods fail to fully account for factors such as hardware performance fluctuations, task complexity, and system load variations that may occur during the computational process, which can easily lead to actual execution times exceeding expectations and, in turn, cost overruns. By introducing a computing power stability factor, the reference price for computing power trading is more accurately estimated, improving the accuracy of cost forecasts and ensuring that computing power demanders can complete their computing tasks within their expected costs. This helps computing power demanders better understand and select the computing power resources that best suit their needs. Analysis of the computing power stability factor can help identify computing power providers that demonstrate stable and reliable performance under varying computing loads, thereby improving the reliability of computing power resource selection. For computing power demanders, this helps avoid task interruptions or calculation errors caused by unstable computing resources, ensuring smooth task completion. By selecting the computing power provider with the lowest reference price for computing power trading, computing power demanders can further optimize costs and achieve greater economic benefits while ensuring smooth task completion.

[0091] See also Figure 2 , an embodiment of the present invention provides a computing power resource transaction management system, including:

[0092] A computing power transaction request processing module is used to obtain computing power transaction requests issued by computing power demanders, determine computing power demand information based on the computing power transaction requests, and determine multiple reference computing power providers from the computing power transaction platform based on the computing power demand information;

[0093] The computing power transaction evaluation module is used to obtain historical computing power transaction data of multiple reference computing power providers, analyze multiple sets of historical computing power transaction data, and determine the computing power transaction evaluation value of each reference computing power provider;

[0094] Among them, by analyzing multiple sets of historical computing power transaction data, the computing power transaction evaluation value of each reference computing power provider is determined, including:

[0095] Extract the task execution time data, resource utilization data, and failure rate data corresponding to different computing tasks in each set of historical computing power transaction data. Determine the efficiency factor and failure rate factor based on the task execution time data and failure rate data. Analyze the resource utilization data based on the computing power configuration data of each reference computing power provider to determine the resource utilization factor. Calculate the computing power transaction evaluation value of each reference computing power provider using the following formula:

[0096]

[0097] Where, is the computing power transaction evaluation value, is the efficiency factor, is the failure rate factor, is the resource utilization factor, 、 、 are the weight parameters of efficiency factor, failure rate factor and resource utilization factor respectively.

[0098] For efficiency factors, failure rate factors, and resource utilization factors, also include:

[0099] For any reference computing power provider, determine the reference computing amount of each computing task in the historical computing power transaction data of the reference computing power provider. Determine the first completion time and second completion time of each computing task based on the reference computing amount of each computing task. Calculate the efficiency reference factor of each computing task based on the actual completion time of each computing task: ,in, is the first completion time, The second completion time, The actual completion time;

[0100] Calculate the average of the efficiency reference factors of multiple computing tasks and record it as the efficiency factor of the reference computing power provider;

[0101] Calculate the average failure rate of multiple computing tasks and determine the failure rate factor of the reference computing power provider based on the average failure rate: ,in, is the mean failure rate;

[0102] Calculate multiple computing resource usage parameters for each computing task based on the computing power configuration data of the computing power provider and the resource utilization data of each computing task. Determine the resource utilization reference factor for each computing task based on the multiple computing resource usage parameters: ,in, Indicates the first Resource usage parameters, Indicates the The standard parameters of resource usage parameters, Indicates the number of resource usage parameters;

[0103] Calculate the average of the resource utilization reference factors of multiple computing tasks and record it as the resource utilization factor of the reference computing power provider.

[0104] A computing power transaction provider recommendation module is used to determine a target computing power provider from multiple reference computing power providers based on a preset computing power transaction screening threshold, and recommend computing power transaction partners to computing power demanders based on the target computing power provider;

[0105] The target computing power provider is determined from multiple reference computing power providers based on a preset computing power transaction screening threshold, including:

[0106] Filter out multiple reference computing power providers whose computing power transaction evaluation values ​​are greater than a preset computing power transaction screening threshold from multiple reference computing power providers and construct a target computing power set;

[0107] Calculate the hash rate stability factor of each reference hash rate provider in the target hash rate set based on the historical hash rate transaction data corresponding to each reference hash rate provider. Calculate the hash rate transaction reference price of each reference hash rate provider in the target hash rate set based on the hash rate stability factor. Select the reference hash rate provider with the lowest hash rate transaction reference price as the target hash rate provider.

[0108] The reference price of computing power transaction for each reference computing power provider in the target computing power set is calculated based on the computing power stability factor, including:

[0109]

[0110] Where, It is the reference price for computing power transactions. Estimated price for computing power transactions, It is the computing power stability factor.

[0111] The computing power transaction execution module is used to respond to the computing power demander's selection to conduct computing power transactions with the target computing power provider, and provide computing power services to the computing power demander based on the target computing power provider.

[0112] The foregoing description is merely a detailed description of the present invention, which is intended to enable those skilled in the art to understand or implement the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art. Portions not described in detail in this specification are well known to those skilled in the art.

Claims

1. A computing power resource transaction management method, characterized in that: include: Obtain a computing power transaction request from a computing power demander, determine computing power demand information based on the computing power transaction request, and determine multiple reference computing power providers from the computing power transaction platform based on the computing power demand information; Obtain historical computing power transaction data from multiple reference computing power providers, analyze multiple sets of historical computing power transaction data, and determine the computing power transaction evaluation value of each reference computing power provider; Determining a target computing power provider from a plurality of reference computing power providers based on a preset computing power transaction screening threshold, including screening out a plurality of reference computing power providers having computing power transaction evaluation values ​​greater than the preset computing power transaction screening threshold from the plurality of reference computing power providers and constructing a target computing power set; Calculate the hash rate stability factor of each reference hash rate provider in the target hash rate set based on the historical hash rate transaction data corresponding to each reference hash rate provider. Calculate the hash rate transaction reference price of each reference hash rate provider in the target hash rate set based on the hash rate stability factor. Select the reference hash rate provider with the lowest hash rate transaction reference price as the target hash rate provider. Recommend hash rate transaction partners to hash rate demanders based on the target hash rate provider. The reference price of computing power transaction for each reference computing power provider in the target computing power set is calculated based on the computing power stability factor, including: Where, It is the reference price for computing power transactions. Estimated price for computing power transactions, is the computing power stability factor; For any reference computing power provider, the execution time deviation of each computing task is calculated based on the mean value of the efficiency reference factor, and the resource usage deviation of each computing task is calculated based on the resource utilization reference factor. The computing power stability reference factor of each computing task is calculated using the following formula: Where, It is a reference factor for computing power stability. is the execution time deviation, is resource usage deviation, is the failure rate; Calculate the standard deviation of the computing power stability reference factors of multiple computing tasks under the reference computing power provider as the computing power stability factor of the reference computing power provider; respond to the computing power demander's choice to trade computing power with the target computing power provider, and provide computing power services to the computing power demander based on the target computing power provider; Among them, by analyzing multiple sets of historical computing power transaction data, the computing power transaction evaluation value of each reference computing power provider is determined, including: Extract the task execution time data, resource utilization data, and failure rate data corresponding to different computing tasks in each set of historical computing power transaction data. Determine the efficiency factor and failure rate factor based on the task execution time data and failure rate data. Analyze the resource utilization data based on the computing power configuration data of each reference computing power provider to determine the resource utilization factor. Calculate the computing power transaction evaluation value of each reference computing power provider using the following formula: Where, is the computing power transaction evaluation value, is the efficiency factor, is the failure rate factor, is the resource utilization factor, 、 、 are the weight parameters of efficiency factor, failure rate factor and resource utilization factor respectively.

2. A computing power resource transaction management method according to claim 1, characterized in that: For efficiency factors, failure rate factors, and resource utilization factors, also include: For any reference computing power provider, determine the reference computing amount of each computing task in the historical computing power transaction data of the reference computing power provider. Determine the first completion time and second completion time of each computing task based on the reference computing amount of each computing task. Calculate the efficiency reference factor of each computing task based on the actual completion time of each computing task: ,in, is the first completion time, The second completion time, The actual completion time; Calculate the average of the efficiency reference factors of multiple computing tasks and record it as the efficiency factor of the reference computing power provider; Calculate the average failure rate of multiple computing tasks and determine the failure rate factor of the reference computing power provider based on the average failure rate: ,in, is the mean failure rate; Calculate multiple computing resource usage parameters for each computing task based on the computing power configuration data of the computing power provider and the resource utilization data of each computing task. Determine the resource utilization reference factor for each computing task based on the multiple computing resource usage parameters: ,in, Indicates the first Resource usage parameters, Indicates the The standard parameters of resource usage parameters, Indicates the number of resource usage parameters; Calculate the average of the resource utilization reference factors of multiple computing tasks and record it as the resource utilization factor of the reference computing power provider.

3. A computing power resource transaction management method according to claim 2, characterized in that: The difference between the efficiency reference factor of the computing task and the average of multiple efficiency reference factors is the execution time deviation of the computing task, and the difference between the resource utilization reference factor of the computing task and the average of the resource utilization reference factors is the resource usage deviation of the computing task.

4. A computing power resource transaction management method according to claim 3, characterized in that: Computing power demand information includes computing task type data, computing resource specification data, computing task volume data, time requirement data and budget data.

5. A computing power resource transaction management system, used to implement a computing power resource transaction management method according to any one of claims 1 to 4, characterized in that: include: A computing power transaction request processing module is used to obtain computing power transaction requests issued by computing power demanders, determine computing power demand information based on the computing power transaction requests, and determine multiple reference computing power providers from the computing power transaction platform based on the computing power demand information; The computing power transaction evaluation module is used to obtain historical computing power transaction data of multiple reference computing power providers, analyze multiple sets of historical computing power transaction data, and determine the computing power transaction evaluation value of each reference computing power provider; A computing power transaction provider recommendation module is used to determine a target computing power provider from multiple reference computing power providers based on a preset computing power transaction screening threshold, and recommend computing power transaction partners to computing power demanders based on the target computing power provider; The computing power transaction execution module is used to respond to the computing power demander's selection to conduct computing power transactions with the target computing power provider, and provide computing power services to the computing power demander based on the target computing power provider.

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