Processing method, device, storage medium and program product of storage resource

Abstract

Embodiments of the present application provide a storage resource processing method and device, a storage medium and a program product. The method comprises: determining, in a cloud storage system, a storage capacity corresponding to a user and a first storage resource providing the storage capacity; detecting at least one performance index data corresponding to the first storage resource to obtain a storage performance of the user actually using the first storage resource; determining storage performance data corresponding to a unit storage capacity according to the storage capacity and the at least one performance index data; and performing a processing operation on the first storage resource according to the storage performance data. The present application improves the accuracy of storage performance measurement and can perform corresponding processing operations based on the storage performance to ensure the accuracy of storage resource processing.

Description

Technical Field

[0001] This application relates to the field of artificial intelligence technology, and in particular to a method, device, storage medium, and program product for processing storage resources. Background Technology

[0002] Cloud storage is an online storage model where users who need data storage hosting rent storage space from cloud service providers to meet their data storage needs.

[0003] Typically, cloud service providers allocate appropriate cloud storage resources to users based on their storage capacity needs, thereby providing storage services to users.

[0004] In practical applications, the actual storage performance required by users may not match the allocated storage resources. The inventors have found that if the storage performance of storage resources can be measured, corresponding processing operations can be performed. Therefore, how to accurately measure the storage performance of storage resources has become a problem that needs to be solved. Summary of the Invention

[0005] This application provides a method, apparatus, storage medium, and program product for processing storage resources to accurately measure the storage performance of storage resources.

[0006] In a first aspect, embodiments of this application provide a method for processing storage resources, the method comprising:

[0007] Determine the storage capacity and a first storage resource to provide the storage capacity;

[0008] Detect at least one performance metric data corresponding to the first storage resource;

[0009] Based on the storage capacity and the at least one performance indicator data, determine the storage performance data corresponding to the unit storage capacity;

[0010] Based on the storage performance data, perform processing operations on the first storage resource.

[0011] Secondly, embodiments of this application provide a storage resource processing apparatus, the apparatus comprising:

[0012] A storage resource determination module is used to determine the storage capacity and the first storage resource to provide the storage capacity.

[0013] The detection module is used to detect at least one performance indicator data generated by the first storage resource;

[0014] The storage performance determination module is used to determine the storage performance data corresponding to a unit of storage capacity based on the storage capacity and at least one performance indicator data.

[0015] The resource processing module is used to perform processing operations on the first storage resource based on the storage performance data.

[0016] Thirdly, embodiments of this application provide an electronic device, including: a memory, a processor, and a communication interface; wherein, the memory stores executable code, and when the executable code is executed by the processor, the processor performs the storage resource processing method as described in the first aspect.

[0017] Fourthly, embodiments of this application provide a non-transitory machine-readable storage medium storing executable code, which, when executed by a processor of an electronic device, enables the processor to at least implement the storage resource processing method described in the first aspect.

[0018] Fifthly, embodiments of this application provide a computer program product, the computer program product including a computer program, which, when executed by a processor, can implement the storage resource processing method as described in the first aspect.

[0019] In the storage resource processing scheme provided in this application embodiment, the cloud storage system determines the storage capacity and a first storage resource providing the storage capacity, and detects at least one performance indicator data generated by the first storage resource to obtain the storage performance of the first storage resource actually used by the user. Based on the storage capacity and at least one performance indicator data, the storage performance data corresponding to a unit storage capacity is determined to obtain storage performance data that accurately reflects the storage performance of the first storage resource actually used by the user, thereby improving the accuracy of storage performance measurement. Based on the storage performance data, processing operations are performed on the first storage resource to ensure the accuracy of storage resource processing. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 A schematic diagram of the hardware execution environment for a storage resource processing method provided in an embodiment of this application;

[0022] Figure 2 This is an application diagram of a cloud storage environment provided in an embodiment of this application;

[0023] Figure 3A flowchart illustrating a method for processing storage resources provided in an embodiment of this application;

[0024] Figure 4 A flowchart illustrating a method for processing storage resources provided in an embodiment of this application;

[0025] Figure 5 A flowchart illustrating a method for processing storage resources provided in an embodiment of this application;

[0026] Figure 6 A flowchart illustrating a method for processing storage resources provided in an embodiment of this application;

[0027] Figure 7 A flowchart illustrating a method for processing storage resources provided in an embodiment of this application;

[0028] Figure 8 A flowchart illustrating a method for processing storage resources provided in an embodiment of this application;

[0029] Figure 9 A schematic diagram of a storage resource processing device provided in an embodiment of this application;

[0030] Figure 10 This is a schematic diagram of the structure of an electronic device provided in this embodiment. Detailed Implementation

[0031] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application. In addition, the timing of the steps in the following method embodiments is only an example and not a strict limitation.

[0032] It should be noted that, in the cases involving user information in the embodiments of this application, the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in the embodiments of this application are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, use, and processing of related data must comply with the relevant laws, regulations, and standards of the relevant countries and regions, and corresponding operation entry points are provided for users to choose to authorize or refuse. In addition, the various models involved in this application (including but not limited to large language models or other models) comply with relevant laws and standards.

[0033] First, the terms or concepts involved in the embodiments of this application will be explained:

[0034] Storage capacity refers to the amount of data a storage device can hold, usually measured in binary information. Its basic unit is the byte (Byte). Common storage units include kilobytes (KB), megabytes (MB), gigabytes (GB), and terabytes (TB).

[0035] Storage performance refers to the speed and efficiency exhibited by a storage system when processing data. Storage performance typically includes technical metrics such as Input / Output Operations Per Second (IOPS), latency, bandwidth, throughput, and response time.

[0036] Input / output (I / O): Input refers to writing data to the storage system, and output refers to reading data from the storage system. I / O can be simply understood as reading and writing to the disk.

[0037] IOPS: This refers to the number of read and write operations performed per second, and is commonly used to measure the performance of storage devices. IOPS measures the number of read and write requests a storage device can handle per unit of time, usually expressed as the number of I / O requests per second.

[0038] Latency: also known as delay or latency, refers to the speed at which a single I / O request is processed.

[0039] Bandwidth refers to the average amount of data read and written per second. Under the same latency conditions, increasing concurrency can improve throughput.

[0040] Throughput: Represents the rate at which data is read from / written to the disk.

[0041] Response time refers to the time from when a user sends a request to when the application completes the request and returns a response to the user. Response time is a crucial parameter for user-perceived performance. Shorter response times are generally considered to indicate a better user experience.

[0042] Performance density: Performance per unit of storage capacity, typically used to measure the performance level a storage system can provide at a specific capacity. The formula is: Performance / Capacity.

[0043] It should be noted that the technical solution provided in this application is applicable to the virtual network environment, and the user described generally refers to "virtual user". Real users can register user accounts through registration and other means to obtain user identity in the network environment.

[0044] In practical applications, users typically estimate their required storage capacity to determine their storage needs. Cloud service providers then allocate storage resources to users based on these needs, providing corresponding storage performance. This, in turn, provides storage services to the user.

[0045] In some scenarios, such as when a cloud service provider allocates storage resources with a certain storage performance, but the user actually uses lower performance, the allocated storage resources may not be fully utilized. Conversely, if the user uses higher performance, the allocated storage resources may not meet their needs. Therefore, the actual storage performance required by the user may not match the available storage resources.

[0046] Therefore, in order to accurately process storage resources, this application proposes a storage resource processing method. By comprehensively considering the performance indicators of storage resources when actually used by users, the method determines the storage performance data corresponding to the unit storage capacity that can accurately reflect the storage performance when actually used by users. This improves the accuracy of storage performance measurement and allows corresponding processing operations to be performed based on storage performance, thereby ensuring the accuracy of storage resource processing.

[0047] The following describes the storage resource processing scheme provided in the embodiments of this application.

[0048] Figure 1 A schematic diagram of the hardware execution environment for a storage resource processing method provided in an embodiment of this application is shown below. Figure 1 As shown, the hardware execution environment for this storage resource processing method can consist of a client device 101 and a server device 102, with the client device 101 and server device 102 communicating with each other. The client device 101 can be a laptop, tablet, PC, robot, etc. The server device 102 can be a cloud server from a cloud service provider.

[0049] In an optional embodiment, the execution process of the above-described storage resource processing method may be as follows: Client device 101 sends a storage service request to server device 102. This storage service request may be a data read / write request or other request to operate on the storage resource. The interaction process is illustrated below using the example of client device 101 sending a data read request to server device 102. Server device 102 obtains the data to be read from the storage resource allocated to client device 101. Then, server device 102 sends the read data back to client device 101. During the data read / write process performed by client device 101 through server device 102, server device 102 can obtain the first storage resource allocated to the user corresponding to client device 101 and the storage capacity provided by the first storage resource, and detect at least one performance indicator data corresponding to the first storage resource. Based on the storage capacity and at least one performance indicator data, storage performance data corresponding to a unit storage capacity is determined. Based on the storage performance data, processing operations are performed on the first storage resource.

[0050] In practical applications, the aforementioned server-side device 102 can be a cloud server maintained by a cloud service provider, and a single cloud server can contain at least one computing node. In cases such as... Figure 2 The cloud storage environment shown may include several distributed deployments. Figure 2 The diagram illustrates compute nodes 1, 2, ..., n. Each compute node primarily deploys computing resources such as CPUs and a certain amount of storage resources to perform various computing tasks, such as data filtering and aggregation.

[0051] Each compute node can connect to a storage node via a network. Multiple storage nodes can form a storage cluster, and each storage cluster includes a management node and several distributed (...) Figure 2 The diagram illustrates storage nodes (node ​​1, node 2, ..., node n). Each storage node has corresponding storage resources deployed on it, and user data is stored in these resources. A management node manages the various storage nodes connected to it.

[0052] During operation, the compute node executes a request from client device 101, which can be a data read / write request. The compute node parses the request, determines the storage node to perform the operation on the storage resource, and then performs the corresponding operation on the user data in the storage resource through that storage node.

[0053] In this embodiment, processing functions that provide storage resources can be deployed in computing nodes or management nodes.

[0054] The execution process of the storage resource processing method provided in the embodiments of this application is described in detail below with reference to the accompanying drawings. Optionally, the storage resource processing method can be executed by a computing node or a storage node in the aforementioned cloud computing environment.

[0055] Figure 3 A flowchart illustrating a method for processing storage resources provided in an embodiment of this application is shown below. Figure 3 As shown, the method includes the following steps:

[0056] 301. Determine the storage capacity corresponding to the user and the first storage resource to provide the storage capacity.

[0057] 302. Detect at least one performance indicator data corresponding to the first storage resource.

[0058] 303. Based on the storage capacity and at least one performance indicator, determine the storage performance data corresponding to a unit of storage capacity.

[0059] 304. Based on the storage performance data, perform processing operations on the first storage resource.

[0060] In this practical application, within a cloud storage environment, storage resources may be allocated to multiple users, each exercising usage rights over a first allocated storage resource. The first allocated storage resource has a certain storage capacity. For any given user, the first allocated storage resource and its storage capacity are determined.

[0061] In some embodiments, the first storage resource may be a storage resource of a corresponding storage capacity allocated to the user based on the user's storage capacity requirements. Alternatively, the first storage resource may be allocated to the user in other ways; this application does not limit the allocation method of the first storage resource.

[0062] During the user's use of the first storage resource, at least one performance metric data corresponding to the first storage resource is detected. Performance metric data refers to data that reflects the storage performance of the first storage resource.

[0063] Furthermore, performance metrics data may include IOPS.

[0064] Furthermore, performance metrics data may include throughput.

[0065] Furthermore, performance metrics data may include latency.

[0066] Optionally, when detecting at least one performance metric data corresponding to the first storage resource, the detection can be performed periodically or in real time.

[0067] Based on storage capacity and at least one performance metric, determine the storage performance data corresponding to each unit of storage capacity. Hereinafter, the storage performance data corresponding to each unit of storage capacity will be referred to as storage performance data. It can be understood that this storage performance data is obtained by comprehensively considering the performance metrics corresponding to the first storage resource. The storage performance data is used to indicate the average storage performance generated per unit of storage capacity in the first storage resource.

[0068] Subsequently, based on the storage performance data, processing operations are performed on the first storage resource. These processing operations may include various methods; two examples are provided below, but it should be understood that the processing operations are not limited to these two. These two processing operations will be described in detail in subsequent embodiments.

[0069] In one possible embodiment, the processing operation for the first storage resource may be: reallocating storage resources for the stored data in the first storage resource. For example, if migration conditions are met, at least a portion of the user's stored data in the first storage resource is scheduled to a second storage resource; the first and second storage resources have different storage performance.

[0070] In one possible embodiment, the processing operation for the first storage resource may further include: generating and outputting adjustment prompt information for the first storage resource based on the storage performance data corresponding to the unit storage capacity, i.e., the actual usage of storage resources by the user. Optionally, the process of outputting the adjustment prompt information may involve sending the adjustment prompt information to the user's corresponding terminal. For example, storage performance data is input into a performance density prediction model to obtain predicted storage performance data. The performance density prediction model is a model trained based on historical storage performance data. Based on the predicted storage performance data, adjustment prompt information for the first storage resource is obtained.

[0071] In summary, through the solution provided in the embodiments of this application, the cloud storage system internally determines the storage capacity corresponding to the user and the first storage resource providing that capacity, detects at least one performance indicator data generated by the first storage resource to obtain the storage performance of the user's actual use of the first storage resource. Based on the storage capacity and at least one performance indicator data, it determines the storage performance data corresponding to a unit of storage capacity to obtain storage performance data that accurately measures the user's actual use of the first storage resource. Based on this storage performance data, it performs processing operations on the first storage resource. This improves the accuracy of storage performance measurement and allows for the execution of corresponding processing operations based on storage performance, ensuring the accuracy of storage resource processing.

[0072] In some scenarios, the performance metrics data corresponding to the first storage resource being tested can be multiple. The following example... Figure 4 The illustrated embodiments will be described in detail.

[0073] Please see Figure 4 , Figure 4 A flowchart illustrating a method for processing storage resources provided in an embodiment of this application is shown below. Figure 4 As shown, the method includes the following steps:

[0074] 401. Determine the storage capacity and the first storage resource to provide the storage capacity.

[0075] 402. Detect multiple performance metrics data corresponding to the first storage resource.

[0076] 403. For any performance index data, determine the performance density data corresponding to the unit storage capacity based on the performance index data and storage capacity.

[0077] 404. Perform weighted processing on the performance density data of multiple performance indicators to determine the storage performance data corresponding to a unit storage capacity.

[0078] 405. Based on the storage performance data, perform processing operations on the first storage resource.

[0079] The execution of steps 401 and 405 can be referred to the relevant descriptions in the foregoing embodiments, and will not be repeated here.

[0080] In this embodiment, multiple performance index data corresponding to the first storage resource are detected. For any one of the detected performance index data, performance density data corresponding to that performance index data is obtained based on that performance index data and the storage capacity. The performance density data corresponding to the performance index data is used to indicate the storage performance of the storage resource per unit storage capacity reflected by that performance index data.

[0081] Next, the performance density data of multiple performance indicators are weighted to determine the storage performance data.

[0082] In one possible embodiment, the weighting coefficients in step 404 during the weighting process can be preset or dynamically updated and obtained before the weighting process is performed.

[0083] For example, weighting coefficients can be determined for multiple performance metrics based on at least one of storage capacity, service performance parameters, service interruption information, and service type. The performance density data corresponding to each of the multiple performance metrics is then weighted according to these weighting coefficients to obtain the storage performance data per unit storage capacity, i.e., the user's performance density data.

[0084] Furthermore, storage capacity, service performance parameters, and service interruption information can be determined according to a Service-Level Agreement (SLA). A SLA is typically a contract or agreement between a user and a cloud service provider, specifying the services the cloud service provider can offer. The SLA may include at least one of the following: storage capacity, service performance parameters, and service interruption information. The storage capacity included in the SLA is the same as the storage capacity corresponding to the aforementioned first storage resource. Service performance parameters refer to the performance corresponding to the service agreed upon between the cloud service provider and the user. For example, service performance parameters may include at least one of IOPS, BPS, and latency. Service interruption information indicates whether the service provided by the cloud service provider to the user is interruptible.

[0085] Furthermore, different service types may have different storage performance requirements. For example, for service types that prioritize latency (requiring relatively low latency), the latency weighting factor can be set relatively high compared to other weighting factors. On the other hand, for service types that prioritize bandwidth (requiring less sensitivity to latency), the latency weighting factor can be set relatively low compared to other weighting factors.

[0086] For example, suppose the storage capacity is C. Performance metrics data generated by the first storage resource can include: IOPS, throughput, and latency. The performance density data for these metrics are as follows: the performance density data for IOPS is... If throughput is represented using Throughput, then the performance density data for throughput is: If latency is represented using Latency, then the performance density data for latency is: Obtain the weighting coefficients for IOPS, throughput, and latency, assuming they are a, b, and r, respectively. Then, obtain the storage performance data D corresponding to each unit of storage capacity according to the following formula (1):

[0087]

[0088] The above embodiments describe a scenario for detecting multiple performance metrics. For any one of the performance metrics, its corresponding performance density is determined based on the performance metric and storage capacity. The performance density data of multiple performance metrics are weighted to normalize the data, resulting in storage performance data per unit storage capacity—that is, unified performance density data. Since this unified performance density data comprehensively considers the performance density data of multiple performance metrics, it can more accurately measure the storage performance of storage resources. Based on this storage performance data, processing operations are performed on the first storage resource. Performing corresponding processing operations based on storage performance ensures the accuracy of storage resource processing.

[0089] In some scenarios, the processing operation performed in step 304 on the first storage resource may be to reallocate storage resources for the stored data in the first storage resource. The following example... Figure 5 The illustrated embodiments will be described in detail.

[0090] Please see Figure 5 , Figure 5 A flowchart illustrating a method for processing storage resources provided in an embodiment of this application is shown below. Figure 5 As shown, the method includes the following steps:

[0091] 501. Determine the storage capacity and the first storage resource to provide the storage capacity.

[0092] 502. Detect at least one performance indicator data generated by the first storage resource.

[0093] 503. Based on the storage capacity and at least one performance indicator, determine the storage performance data corresponding to a unit of storage capacity.

[0094] 504. If the storage performance data meets the migration conditions, at least a portion of the storage data in the first storage resource is scheduled to the second storage resource; the storage performance of the first storage resource and the second storage resource are different.

[0095] The execution of steps 501-503 can be referred to the relevant descriptions in the foregoing embodiments, and will not be repeated here.

[0096] In this embodiment, the storage performance data corresponding to the unit storage capacity is used to determine whether the storage performance data meets the migration conditions. The migration conditions refer to the following: the storage performance of the first storage resource currently allocated to the user does not match the storage performance of the first storage resource actually used by the user.

[0097] If the migration conditions are met, at least a portion of the stored data in the first storage resource is scheduled to a second storage resource with different storage performance. For example, since different storage media may have different storage performance, storage resources can be divided into different storage layers according to storage performance, i.e., according to storage media. Several common storage media are described below as examples; however, it should be understood that this does not constitute a limitation on the storage media used in the storage resources of this application.

[0098] Optionally, the storage media may include, but are not limited to: hard disk drives (HDDs), solid-state drives (SSDs), persistent memory (PMEM), and hybrid drives. Hybrid drives refer to drives composed of different storage media, such as drives combining HDDs and SSDs, or SSDs and PMEMs. Therefore, the first storage resource and the second storage resource can be different storage layers.

[0099] For example, since the first storage resource may include multiple storage resources with different storage performance—that is, the user's storage data may be stored in storage resources with different storage performance—some or all of the storage data in the first storage resource can be scheduled to the second storage resource if the migration conditions are met. Additionally, if the storage performance data meets the migration conditions, some or all of the cold data can also be scheduled to the second storage resource. After the above scheduling process is completed, the storage performance of the storage resource currently allocated to the user can be made consistent with the storage performance of the storage resource actually used by the user.

[0100] In one possible embodiment, a first storage performance threshold can be preset. For example, the first storage performance threshold can be a value obtained through testing or evaluation. If the storage performance data is less than the first storage performance threshold, it indicates that the storage performance of the first storage resource actually used by the user is lower than the storage performance of the first storage resource allocated to the user. Furthermore, since storage performance data may fluctuate, the migration condition needs to consider that the obtained storage performance data is always less than the first storage performance threshold within a first preset time period. Accordingly, the migration condition can be: the storage performance data is always less than the first storage performance threshold within the first preset time period. To fully utilize storage resources, if this migration condition is met, at least a portion of the stored data in the first storage resource can be scheduled to a second storage resource with lower storage performance than the first storage resource. For example, data stored in the first storage resource that is used less frequently can be scheduled to the second storage resource.

[0101] It should also be noted that if the storage performance data is consistently below the first storage performance threshold within the first preset time period, but the current first storage resource is already the storage resource with the lowest storage performance, then no scheduling processing will be performed. If the storage performance data is consistently below the first storage performance threshold within the first preset time period, and the current first storage resource is not the storage resource with the lowest storage performance, then scheduling processing will be performed.

[0102] In another possible embodiment, a second storage performance threshold can be preset, which is greater than or equal to a first storage performance threshold. For example, the second storage performance threshold can be a value obtained through testing or evaluation. If the storage performance data is greater than the second storage performance threshold, it indicates that the storage performance of the first storage resource allocated to the user may not meet the user's actual storage performance requirements. Furthermore, since storage performance data may fluctuate, the migration condition needs to consider that the obtained storage performance data is greater than the second storage performance threshold within a second preset time period. Accordingly, the migration condition can be: the storage performance data is greater than the second storage performance threshold within the second preset time period. To meet the user's actual storage performance needs, if this migration condition is met, at least a portion of the storage data in the first storage resource can be scheduled to a second storage resource with higher storage performance than the first storage resource. For example, frequently used data stored in the first storage resource can be scheduled to the second storage resource.

[0103] It should also be noted that if the storage performance data is greater than the second storage performance threshold for the second preset time period, but the first storage resource is already the storage resource with the highest storage performance, then no scheduling processing will be performed. If the storage performance data is greater than the second storage performance threshold for the second preset time period, and the first storage resource is not the storage resource with the highest storage performance, then scheduling processing will be performed.

[0104] In some embodiments, if the migration conditions are not met, the detection of at least one performance metric data generated by the first storage resource may continue.

[0105] For example, we can determine the first storage resource allocated to user A and its storage capacity Q. We periodically monitor the IOPS generated by the first storage resource. The storage performance data per unit storage capacity is then IOPS / Q. If IOPS / Q is less than the first storage performance threshold, we determine that the migration conditions are met, and at least a portion of the storage data in the first storage resource is scheduled to the second storage resource with lower storage performance.

[0106] The solution provided in this embodiment involves the cloud storage system internally determining the storage capacity corresponding to a user and the first storage resource providing that capacity. It then detects at least one performance indicator data generated by the first storage resource to obtain the actual storage performance of the first storage resource used by the user. Based on the storage capacity and at least one performance indicator data, it determines the storage performance data corresponding to a unit of storage capacity, thus obtaining storage performance data that accurately reflects the actual storage performance of the first storage resource used by the user, improving the accuracy of storage performance measurement. If the storage performance data meets the migration conditions, it indicates that the storage performance of the first storage resource currently allocated to the user does not match the actual storage performance of the first storage resource used by the user. At least a portion of the stored data in the first storage resource is then scheduled to a second storage resource with different storage performance. This automatic reallocation of the user's storage resources is achieved without the user's awareness, realizing reasonable scheduling and allocation of storage resources and improving the overall efficiency and performance of the storage system.

[0107] In some scenarios, the amount of storage resources exchanged can be determined based on the storage performance data corresponding to a unit of storage capacity, to match the user's actual storage resource usage. The following section combines... Figure 6 A detailed introduction will be provided.

[0108] Figure 6 A flowchart illustrating a method for processing storage resources provided in an embodiment of this application is shown below. Figure 6 As shown, the method includes the following steps:

[0109] 601. Determine the storage capacity corresponding to the user and the first storage resource to provide the storage capacity.

[0110] 602. Detect at least one performance indicator data generated by the first storage resource.

[0111] 603. Based on the storage capacity and at least one performance indicator, determine the storage performance data corresponding to a unit of storage capacity.

[0112] 604. Based on storage performance data, determine the target amount of exchangeable resources corresponding to a unit of storage capacity.

[0113] 605. Based on the target exchangeable resource amount corresponding to the unit storage capacity and the storage capacity, determine the exchangeable resource amount corresponding to the first resource.

[0114] In this embodiment, the execution of steps 601-603 can be referred to the relevant descriptions in the foregoing embodiments, and will not be repeated here. It should be noted that... Figure 6 The embodiments shown can be executed alone or in combination with the embodiments described above.

[0115] In practical applications, the storage performance data corresponding to a unit of storage capacity is determined. Based on this storage performance data, the target exchange resource amount corresponding to a unit of storage capacity is determined. The target exchange resource amount can be understood as the average exchange resource amount per unit of storage capacity. Thus, based on the target exchange resource amount and the storage capacity, the exchange resource amount corresponding to the first storage resource is determined.

[0116] Optionally, the amount of resources to be exchanged for the first resource can be obtained by multiplying the target amount of exchangeable resources by the storage capacity.

[0117] In some embodiments, a basic exchangeable resource amount can be set, that is, the basic exchangeable resource amount corresponding to a unit of storage capacity. This basic exchangeable resource amount can be determined based on the storage performance of the storage resources; that is, storage resources with different performance levels correspond to different basic exchangeable resource amounts. Additionally, a first fluctuation coefficient corresponding to the storage performance data can be determined based on the storage performance data. The first fluctuation coefficient is used to characterize the adjustment of the basic exchangeable resource amount according to the actual storage performance used by the user. By adjusting the basic exchangeable resource amount using the first fluctuation coefficient, the target exchangeable resource amount corresponding to a unit of storage capacity is determined.

[0118] Optionally, the target amount of exchangeable resources can be obtained by multiplying the first floating coefficient by the basic amount of exchangeable resources.

[0119] There are multiple ways to determine the first floating coefficient corresponding to the storage performance data. Two methods are described below as examples. It should be understood that these two methods do not constitute a limitation of this application.

[0120] In one possible implementation, the storage performance data is divided into multiple intervals, and a floating coefficient is set for each interval. After determining the storage performance data corresponding to the first storage resource, the first storage performance interval to which the storage performance data belongs and the first floating coefficient corresponding to the first storage performance interval are determined from the multiple intervals. This first floating coefficient is used as the first floating coefficient corresponding to the storage performance data.

[0121] For example, storage performance data can be divided into intervals as follows: Let PDI represent storage performance data. Set 0 < PDI < 50 as the first interval, with a corresponding fluctuation factor of 'a'; set 50 ≤ PDI < 100 as the second interval, with a corresponding fluctuation factor of 'b'. Assuming the storage performance data is 30, it belongs to the first interval, so the first fluctuation factor is determined to be 'a'.

[0122] By implementing the above method, the storage performance data is divided into intervals to determine the first storage performance interval to which the storage performance data belongs, and the first fluctuation coefficient corresponding to the first storage performance interval.

[0123] In another possible implementation, a first fluctuation coefficient corresponding to the storage performance data can be determined based on the storage performance data, the upper threshold, the lower threshold, and a constant. The upper threshold is greater than the lower threshold.

[0124] In practical applications, optionally, the first floating coefficient corresponding to the storage performance data can be obtained by the following formula (2).

[0125]

[0126] Where j is the first floating coefficient; k is a constant; D is storage performance data; D max The upper limit threshold; D min This is the lower threshold.

[0127] As shown in formula (2), the larger D is, the higher the actual storage performance used by the user, and the higher the corresponding target exchange resource amount. Specifically, if D is greater than D... min If D is larger than D, the target exchange resource quantity will fluctuate upwards from the base exchange resource quantity, meaning the target exchange resource quantity is greater than the base exchange resource quantity; if D is larger than D... min If D is smaller, the target exchange resource quantity will fluctuate downwards from the base exchange resource quantity, meaning the target exchange resource quantity is less than the base exchange resource quantity; if D equals D... min Then the target amount of exchangeable resources is equal to the basic amount of exchangeable resources.

[0128] Next, based on the base exchange resource amount per unit of storage capacity and the first floating coefficient, the target exchange resource amount per unit of storage capacity is determined. Based on the target exchange resource amount per unit of storage capacity and the storage capacity, the exchange resource amount corresponding to the first storage resource is determined.

[0129] Optionally, when determining the amount of exchangeable resources corresponding to the first storage resource, the amount can be determined by multiplying the target amount of exchangeable resources by the storage capacity. Alternatively, a set upper limit threshold can be used to determine whether the user is currently exceeding the upper limit for using storage resources. For the portion exceeding the upper limit, a different method for determining the amount of exchangeable resources can be used compared to the portion not exceeding the upper limit. The following examples illustrate two methods for determining the amount of exchangeable resources in the case of exceeding the limit; however, these methods do not constitute a limitation of this application.

[0130] For the portion that does not exceed the limit, if the storage performance data is less than the upper limit threshold, the first amount of resources to be exchanged is determined based on the target amount of exchanged resources and the storage capacity.

[0131] For the portion exceeding the limit, in one possible approach, when storage performance data exceeds the upper limit threshold (i.e., storage resources are used beyond the limit), a pre-set redemption resource can be used for the upper limit threshold. That is, for the storage performance consumed beyond the upper limit threshold, a second redemption resource amount is determined based on the pre-set redemption resource and storage capacity. Determining the redemption resource amount corresponding to the first storage resource includes both the first and second redemption resource amounts.

[0132] In another possible approach, the number of requests obtained after the storage performance data exceeds an upper threshold is counted. For example, this number of requests could refer to the number of read / write requests for storage resources. The third redemption resource amount is determined based on the number of requests. Determining the redemption resource amount corresponding to the first storage resource includes both the first redemption resource amount and the third redemption resource amount.

[0133] By implementing the above method, and setting upper and lower thresholds as well as a constant, a first fluctuation coefficient that better reflects the user's actual storage performance data can be determined, thereby identifying the target redemption resources. This makes the determined redemption resources more reasonable.

[0134] In summary, the solution provided in the embodiments of this application determines the user's corresponding storage capacity and the first storage resource providing that capacity. It then detects at least one performance indicator data generated by the first storage resource to obtain the actual storage performance of the first storage resource used by the user. Based on the storage capacity and at least one performance indicator data, it determines the storage performance data corresponding to a unit of storage capacity, thus obtaining storage performance data that accurately reflects the user's actual use of the first storage resource and improving the accuracy of storage performance measurement. Based on the storage performance data, it determines the target exchange resource per unit of storage capacity that matches the current user's actual storage performance consumption. Based on the target exchange resource per unit of storage capacity and the storage capacity, it determines the exchange resource quantity corresponding to the first storage resource. Therefore, by determining the exchange resource quantity corresponding to the first storage resource based on the actual storage performance consumed, the determined exchange resource quantity is more reasonable, applicable to various storage service scenarios, and suitable for situations such as sudden load increases.

[0135] The above embodiments describe determining the amount of exchangeable resources corresponding to the first storage resource using storage performance data. In practice, the amount of exchangeable resources corresponding to the first storage resource can also be determined based on the current time period. To address this situation, combined with... Figure 7 The illustrated embodiment will be used for explanation.

[0136] Figure 7 A flowchart illustrating a method for processing storage resources provided in an embodiment of this application is shown below. Figure 7 As shown, the method includes the following steps:

[0137] 701. Determine the storage capacity and the first storage resource to provide the storage capacity.

[0138] 702. Detect at least one performance metric data generated by the first storage resource.

[0139] 703. Based on the storage capacity and at least one performance indicator, determine the storage performance data corresponding to a unit of storage capacity.

[0140] 704. Based on the storage performance data, determine the first fluctuation coefficient corresponding to the storage performance data.

[0141] 705. Determine the second floating coefficient corresponding to the current time period.

[0142] 706. Based on the basic exchangeable resource amount per unit storage capacity, the first floating coefficient, and the second floating coefficient, determine the target exchangeable resource amount per unit storage capacity.

[0143] In this embodiment, the execution of steps 701-704 can be referred to the relevant descriptions in the foregoing embodiments, and will not be repeated here.

[0144] In practical applications, a certain time period can be divided into time slots, with each time slot corresponding to a floating coefficient. For example, a day can be divided into multiple time slots, such as peak time, normal time, and off-peak time. The floating coefficient for peak time is greater than that for normal time, and the floating coefficient for normal time is greater than that for off-peak time. When determining the amount of resources to be exchanged for the first storage resource, a second floating coefficient is determined based on the user's current time slot. Based on the basic exchangeable resource amount per unit storage capacity, the first floating coefficient, and the second floating coefficient, the target exchangeable resource amount per unit storage capacity is determined.

[0145] Optionally, the target exchangeable resource amount per unit storage capacity can be obtained by multiplying the basic exchangeable resource amount, the first floating coefficient, and the second floating coefficient.

[0146] It should be noted that steps 701-704 and step 705 are executed in no particular order. Step 706 is executed after steps 701-704 and step 705 are completed. Figure 7 The execution order described is merely an example and does not constitute a limitation of this application.

[0147] In this embodiment, a first floating coefficient corresponding to the actual storage performance consumed by the user is determined based on the storage performance data corresponding to the unit storage capacity. A second floating coefficient is then determined based on the current time period. The basic exchangeable resource amount per unit storage capacity is adjusted using the first and second floating coefficients to determine the target exchangeable resource amount per unit storage capacity, thereby determining the exchangeable resource amount corresponding to the first storage resource. The exchangeable resource amount corresponding to the first storage resource is determined based on the target exchangeable resource amount per unit storage capacity and the storage capacity. Therefore, by determining the exchangeable resource amount corresponding to the first storage resource based on the actual storage performance consumed and the current time period in which storage performance consumption occurs, the determined exchangeable resource amount corresponding to the first storage resource is more reasonable and applicable to various storage service scenarios.

[0148] In some scenarios, based on storage performance data corresponding to a unit of storage capacity—that is, the user's actual usage of storage resources—a prompt message can be generated and sent to the user to adjust resources accordingly. The following section combines... Figure 8 A detailed introduction will be provided.

[0149] Figure 8 A flowchart illustrating a method for processing storage resources provided in an embodiment of this application is shown below. Figure 8 As shown, the method includes the following steps:

[0150] 801. Determine the storage capacity and the first storage resource to provide the storage capacity.

[0151] 802. Detect at least one performance indicator data generated by the first storage resource.

[0152] 803. Based on the storage capacity and at least one performance indicator, determine the storage performance data corresponding to a unit of storage capacity.

[0153] 804. Input the storage performance data into the performance density prediction model to obtain the predicted storage performance data. The performance density prediction model is trained based on historical storage performance data and is a completed model.

[0154] 805. Based on the predicted storage performance data, obtain adjustment prompts for the first storage resource.

[0155] 806. Output adjustment prompt message.

[0156] In this embodiment, the execution of steps 801-803 can be referred to the relevant descriptions in the foregoing embodiments, and will not be repeated here. It should be noted that... Figure 8 The embodiments shown can be executed alone or in combination with the embodiments described above.

[0157] In this embodiment, an initial performance density prediction model can be pre-built, and historical storage performance data can be obtained as training data to train the constructed performance density prediction model, resulting in a trained performance density prediction model. The performance density prediction model is used to predict future storage performance data for a preset period based on the input storage performance data, thereby providing adjustment prompts. These adjustment prompts refer to suggestions for adjusting storage resources. For example, they could be strategy information for adjusting storage capacity and / or storage performance.

[0158] Optionally, the device for obtaining the performance density prediction model can be the server where the management node is located, or other servers, etc. This application does not limit this, but it is necessary to deploy the trained performance density prediction model on the server where the management node or computing node is located.

[0159] In practical applications, after obtaining storage performance data, this data can be input into the aforementioned performance density prediction model to obtain adjustment prompts. Optionally, this adjustment information can be sent to the user's corresponding terminal device.

[0160] In this embodiment, a pre-trained performance density prediction model can provide users with relatively accurate adjustment prompts based on the actual storage performance consumed by the user. Users can then adjust storage resources according to these prompts, improving the application experience. Furthermore, if users follow the adjustment prompts and configure storage resources to a lower level, ensuring more efficient use of storage resources, the amount of storage resources exchanged can be further reduced.

[0161] Figure 9 This is a schematic diagram of the structure of a storage resource processing device provided in an embodiment of this application, as shown below. Figure 9 As shown, the device includes: a storage resource determination module 11, a detection module 12, a storage performance determination module 13, and a migration module 14.

[0162] Storage resource determination module 11 is used to determine the storage capacity and provide a first storage resource for the storage capacity;

[0163] Detection module 12 is used to detect at least one performance indicator data generated by the first storage resource;

[0164] Storage performance determination module 13 is used to determine the storage performance data corresponding to a unit storage capacity based on the storage capacity and at least one performance indicator data.

[0165] Processing module 14 is used to perform processing operations on the first storage resource based on storage performance data.

[0166] Optionally, at least one performance metric data point may include multiple performance metric data points, and the storage performance determination module 13 is specifically used for:

[0167] For any given performance metric data, determine the corresponding performance density data based on the performance metric data and storage capacity.

[0168] The performance density data corresponding to multiple performance metrics are weighted to determine the storage performance data.

[0169] Optionally, the storage performance determination module 13 is specifically used for:

[0170] Based on at least one of the following: storage capacity, service performance parameters, service interruption information, and service type, determine the weighting coefficients corresponding to multiple performance metrics data.

[0171] The storage performance data is obtained by weighting the performance density data corresponding to the multiple performance indicators according to their respective weight coefficients.

[0172] Optionally, processing module 14 is specifically used for:

[0173] If the storage performance data meets the migration conditions, at least a portion of the storage data in the first storage resource will be scheduled to the second storage resource; the storage performance of the first storage resource and the second storage resource are different.

[0174] Optionally, processing module 14 is specifically used for:

[0175] If the storage performance data is less than the first storage performance threshold within a first preset time period, then at least a portion of the storage data in the first storage resource will be scheduled to the second storage resource; the storage performance of the second storage resource is lower than that of the first storage resource.

[0176] If the storage performance data is greater than the second storage performance threshold within the second preset time period, at least a portion of the storage data in the first storage resource will be scheduled to the second storage resource; the second storage performance threshold is greater than or equal to the first storage performance threshold; and the storage performance of the second storage resource is higher than that of the first storage resource.

[0177] Optionally, the device may also include:

[0178] The resource exchange determination module is used to determine the target exchange resource amount corresponding to a unit of storage capacity based on storage performance data; and to determine the exchange resource amount corresponding to the first storage resource based on the target exchange resource amount corresponding to a unit of storage capacity and the storage capacity.

[0179] Optionally, the resource exchange determination module is specifically used for:

[0180] Based on the storage performance data, determine the first fluctuation coefficient corresponding to the storage performance data;

[0181] Based on the basic exchangeable resource amount per unit of storage capacity and the first floating coefficient, determine the target exchangeable resource amount corresponding to the unit of storage capacity.

[0182] Optionally, the resource exchange determination module is specifically used for:

[0183] Determine the first storage performance range to which the storage performance data belongs;

[0184] Determine the first fluctuation coefficient corresponding to the first storage performance range.

[0185] Optionally, the resource exchange determination module is specifically used for:

[0186] Based on storage performance data, upper threshold, lower threshold, and constants, determine the first floating coefficient corresponding to the storage performance data; the upper threshold is greater than the lower threshold.

[0187] Optionally, the resource exchange determination module is specifically used for:

[0188] The first floating coefficient is obtained using the following formula:

[0189]

[0190] Where j is the first floating coefficient; k is a constant; D is storage performance data; D max The upper limit threshold; D min This is the lower threshold.

[0191] Optionally, the resource exchange determination module is specifically used for:

[0192] Determine the second fluctuation coefficient corresponding to the current time period;

[0193] The target exchangeable resource amount per unit storage capacity is obtained by multiplying the base exchangeable resource amount per unit storage capacity, the first floating coefficient, and the second floating coefficient.

[0194] Optionally, the resource exchange determination module is specifically used for:

[0195] If the storage performance data is less than the upper limit threshold, a first exchangeable resource quantity is determined based on the target exchangeable resource quantity and storage capacity; and if the storage performance data is greater than the upper limit threshold, a predetermined exchangeable resource quantity corresponding to the upper limit threshold is determined, and a second exchangeable resource quantity is determined based on the predetermined exchangeable resource quantity and storage capacity; the determination of the storage exchangeable resource quantity includes the first exchangeable resource quantity and the second exchangeable resource quantity.

[0196] or,

[0197] If the storage performance data is less than the upper limit threshold, determine the first amount of exchangeable resources based on the target exchangeable resources and storage capacity; and count the number of requests obtained after the storage performance data is greater than the upper limit threshold, and determine the third amount of exchangeable resources based on the number of requests; the determination of the storage exchangeable resource amount includes the first amount of exchangeable resources and the third amount of exchangeable resources.

[0198] Optionally, processing module 14 is specifically used for:

[0199] The storage performance data is input into the performance density prediction model to obtain the predicted storage performance data. The performance density prediction model is trained based on historical storage performance data and is a completed model.

[0200] Based on the predicted storage performance data, adjustment prompts are obtained for the first storage resource;

[0201] Output adjustment prompts.

[0202] Figure 9 The device shown can perform the steps in the storage resource processing method in the foregoing embodiments. For detailed execution process and technical effects, please refer to the description in the foregoing embodiments, which will not be repeated here.

[0203] Figure 10 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application, such as... Figure 10 As shown, in practice, this electronic device includes a memory 21 and a processor 22.

[0204] Memory 21 is used to store computer programs and can be configured to store various other data to support operation on the electronic device. Examples of this data include instructions for any application or method used to operate on the electronic device, data structures, contact data, phone book data, messages, pictures, videos, etc.

[0205] The processor 22, coupled to the memory 21, is used to execute the computer program in the memory 21 to implement the prompt word input method provided in the foregoing embodiments.

[0206] Furthermore, such as Figure 10 As shown, the electronic device also includes other components such as a communication component 23, a display 24, a power supply component 25, and an audio component 26. Figure 10 The diagram only shows some components and does not mean that the electronic device includes only these components. Figure 9 The components shown are as follows. The electronic device in this embodiment can be a terminal device such as a desktop computer, laptop computer, smartphone, or IoT device, or a server device such as a conventional server, cloud server, or server array.

[0207] The aforementioned memory can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random-Access Memory (SRAM), Electrically Erasable Programmable Read Only Memory (EEPROM), Erasable Programmable Read Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0208] The aforementioned communication component is configured to facilitate wired or wireless communication between the device containing the communication component and other devices. The device containing the communication component can access wireless networks based on communication standards, such as 2G, 3G, 4G / LTE, 5G, or combinations thereof. In one exemplary embodiment, the communication component receives broadcast signals or broadcast-related information from an external broadcast management system via a broadcast channel.

[0209] The aforementioned display includes a screen, which may include a Liquid Crystal Display (LCD) and a Touch Panel (TP). If the screen includes a Touch Panel, the screen can be implemented as a touchscreen to receive input signals from the user. The Touch Panel includes one or more touch sensors to sense touches, swipes, and gestures on the Touch Panel. The touch sensors can sense not only the boundaries of touch or swipe actions but also the duration and pressure associated with the touch or swipe operation.

[0210] The aforementioned power supply components provide power to various components within the device in which they reside. These power supply components may include a power management system, one or more power sources, and other components associated with generating, managing, and distributing power to the device in which they reside.

[0211] The aforementioned audio component can be configured to output and / or input audio signals. For example, the audio component includes a microphone (MIC) configured to receive external audio signals when the device containing the audio component is in an operating mode, such as call mode, recording mode, or voice recognition mode. The received audio signals can be further stored in memory or transmitted via a communication component. In some embodiments, the audio component also includes a speaker for outputting audio signals.

[0212] Accordingly, embodiments of this application also provide a computer-readable storage medium storing a computer program, which, when executed by a processor, enables the processor to implement the steps in the above-described method embodiments. The computer-readable storage medium includes volatile or non-volatile components, or a combination thereof, and can be removable or non-removable. Examples of computer-readable storage media include, but are not limited to, phase-change random access memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random-access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), flash memory or other memory technologies, CD-ROM, digital video disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium.

[0213] Accordingly, this application also provides a computer program product, which includes a computer program or instructions. When the computer program or instructions are executed by a processor, the processor is able to implement the steps in the above method embodiments. It should be understood that each step or combination of steps in the above method flow can be implemented by the computer program or instructions. In addition, these computer programs or instructions can be applied to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device, so that the processor of the general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing device can be implemented as a means to implement the corresponding functions in the above method embodiments.

[0214] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A method for processing storage resources, characterized in that, The method includes: Determine the storage capacity and a first storage resource to provide the storage capacity; Detect at least one performance metric data corresponding to the first storage resource; Based on the storage capacity and the at least one performance indicator data, determine the storage performance data corresponding to the unit storage capacity; Based on the storage performance data, perform processing operations on the first storage resource.

2. The method according to claim 1, characterized in that, The at least one performance indicator data includes multiple performance indicator data, and the step of determining the storage performance data corresponding to a unit storage capacity based on the storage capacity and the at least one performance indicator data includes: For any given performance metric data, determine the corresponding performance density data based on the performance metric data and the storage capacity. The performance density data corresponding to the multiple performance index data are weighted to determine the storage performance data.

3. The method according to claim 2, characterized in that, The weighted processing of the performance density data of the multiple performance index data to determine the storage performance data corresponding to a unit storage capacity includes: Based on at least one of the storage capacity, service performance parameters, service interruption information, and service type, determine the weight coefficients corresponding to the multiple performance index data respectively; The storage performance data is obtained by weighting the performance density data corresponding to the multiple performance index data according to the weight coefficients corresponding to the multiple performance index data.

4. The method according to any one of claims 1-3, characterized in that, The step of performing processing operations on the first storage resource based on the storage performance data includes: If the storage performance data meets the migration conditions, at least a portion of the storage data in the first storage resource will be scheduled to the second storage resource; the storage performance of the first storage resource and the second storage resource are different.

5. The method according to claim 4, characterized in that, When the storage performance data meets the migration conditions, scheduling at least a portion of the storage data in the first storage resource to the second storage resource includes: If the storage performance data is less than the first storage performance threshold within a first preset time period, then at least a portion of the storage data in the first storage resource will be scheduled to the second storage resource; the storage performance of the second storage resource is lower than that of the first storage resource. If the storage performance data is greater than the second storage performance threshold within the second preset time period, at least a portion of the storage data in the first storage resource will be scheduled to the second storage resource; the second storage performance threshold is greater than or equal to the first storage performance threshold; and the storage performance of the second storage resource is higher than that of the first storage resource.

6. The method according to claim 1, characterized in that, Also includes: Based on the storage performance data, determine the target amount of exchangeable resources corresponding to each unit of storage capacity; The amount of exchangeable resources corresponding to the first storage resource is determined based on the target amount of exchangeable resources corresponding to the unit storage capacity and the storage capacity.

7. The method according to claim 6, characterized in that, The step of determining the target exchangeable resource amount corresponding to a unit of storage capacity based on the storage performance data includes: Based on the storage performance data, determine the first fluctuation coefficient corresponding to the storage performance data; Based on the basic exchangeable resource amount per unit storage capacity and the first floating coefficient, the target exchangeable resource amount corresponding to the unit storage capacity is determined.

8. The method according to claim 7, characterized in that, The step of determining the first fluctuation coefficient corresponding to the storage performance data based on the storage performance data includes: Determine the first storage performance range to which the storage performance data belongs; Determine the first fluctuation coefficient corresponding to the first storage performance range.

9. The method according to claim 7, characterized in that, The step of determining the first fluctuation coefficient corresponding to the storage performance data based on the storage performance data includes: Based on the storage performance data, the upper threshold, the lower threshold, and a constant, a first floating coefficient corresponding to the storage performance data is determined; the upper threshold is greater than the lower threshold.

10. The method according to claim 9, characterized in that, The step of determining the first fluctuation coefficient corresponding to the storage performance data based on the storage performance data, the upper threshold, the lower threshold, and a constant includes: The first floating coefficient is obtained according to the following formula: Where j is the first floating coefficient; k is a constant; D is storage performance data; D max The upper limit threshold; D min This is the lower threshold.

11. The method according to claim 7, characterized in that, Also includes: Determine the second fluctuation coefficient corresponding to the current time period; The determination of the target exchangeable resource amount per unit storage capacity based on the basic exchangeable resource amount per unit storage capacity and the first floating coefficient includes: The target exchangeable resource amount per unit storage capacity is obtained by multiplying the base exchangeable resource amount per unit storage capacity, the first floating coefficient, and the second floating coefficient.

12. The method according to any one of claims 6-11, characterized in that, The step of determining the amount of exchangeable resources corresponding to the first storage resource based on the target exchangeable resources per unit storage capacity and the storage capacity includes: If the storage performance data is less than the upper limit threshold, a first exchangeable resource amount is determined based on the target exchangeable resource amount and the storage capacity; and if the storage performance data is greater than the upper limit threshold, a predetermined exchangeable resource amount corresponding to the upper limit threshold is determined, and a second exchangeable resource amount is determined based on the predetermined exchangeable resource amount and the storage capacity; the determined storage exchangeable resource amount includes the first exchangeable resource amount and the second exchangeable resource amount. or, When the storage performance data is less than the upper limit threshold, a first amount of exchangeable resources is determined based on the target exchangeable resources and the storage capacity; and the number of requests obtained after the storage performance data is greater than the upper limit threshold is counted, and a third amount of exchangeable resources is determined based on the number of requests; the determined amount of storage exchangeable resources includes the first amount of exchangeable resources and the third amount of exchangeable resources.

13. The method according to any one of claims 1-3, characterized in that, The step of performing processing operations on the first storage resource based on the storage performance data includes: The storage performance data is input into the performance density prediction model to obtain the predicted storage performance data. The performance density prediction model is a model trained based on historical storage performance data. Based on the predicted storage performance data, adjustment prompts are obtained for the first storage resource; Output the adjustment prompt information.

14. An electronic device, characterized in that, include: The system includes a memory, a processor, and a communication interface; wherein the memory stores executable code, and when the executable code is executed by the processor, the processor performs a method for processing storage resources as described in any one of claims 1 to 13.

15. A non-transitory machine-readable storage medium, characterized in that, The non-transitory machine-readable storage medium stores executable code that, when executed by a processor of an electronic device, causes the processor to perform a method for processing storage resources as described in any one of claims 1 to 13.

16. A computer program product, characterized in that, include: A computer program, when executed by a processor of an electronic device, causes the processor to perform a method for processing storage resources as described in any one of claims 1 to 13.

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