Method, electronic device and computer program product for managing a disk

Abstract

Embodiments of the present disclosure provide a method, an electronic device and a computer program product for managing disks. The method can include determining performance information of an access pattern of a disk slice based on a difference of performance parameters of the access pattern on a plurality of disks. Further, the method can include determining a score of the disk slice based on the performance information and access frequency information of the disk slice. Further, the method can include determining a location of the disk slice in the plurality of disks based on the score. By utilizing the method, more reasonable and efficient storage management can be achieved, and user experience can be improved.

Description

Technical Field

[0001] Embodiments of this disclosure relate to the field of data storage, and more specifically, to methods, electronic devices, and computer program products for managing disks. Background Technology

[0002] Fast Virtual Pool Fully Automatic Storage Tiling (FAST VP) technology is used to automatically categorize different types of data into different types of storage media within a tiered pool. To implement FAST VP, for example, frequently accessed or important data can be moved to faster, higher-performance, and correspondingly more expensive disks, while less frequently accessed or less important data can be moved to slower, lower-performance, and correspondingly less expensive disks. FAST VP can reduce the total cost of ownership (TCO) and improve performance. However, traditional FAST VP technology only considers the activity level of disk slices, i.e., access frequency, which may result in inefficient data movement. Summary of the Invention

[0003] Embodiments of this disclosure provide a method, electronic device, and computer program product for managing disks.

[0004] According to a first aspect of this disclosure, a method for managing disks is provided. The method includes determining performance information of the access patterns of a disk slice based on differences in performance parameters of the disk slice's access patterns across multiple disks. Furthermore, the method includes determining a score for the disk slice based on the performance information and access frequency information of the disk slice. Further, the method includes determining the position of the disk slice among the multiple disks based on the score.

[0005] According to a second aspect of this disclosure, an electronic device is provided. The electronic device includes: a processor; and a memory storing computer program instructions, wherein the processor executes the computer program instructions in the memory to control the electronic device to perform actions, the actions including: determining performance information of the access patterns of a disk slice based on differences in performance parameters of the disk slice's access patterns across multiple disks; determining a score for the disk slice based on the performance information and access frequency information of the disk slice; and determining the position of the disk slice among the multiple disks based on the score.

[0006] According to a third aspect of this disclosure, a computer program product is provided, which is tangibly stored on a non-volatile computer-readable medium and includes machine-executable instructions that, when executed, cause a machine to perform the steps of the method in the first aspect of this disclosure. Attached Figure Description

[0007] The above and other objects, features and advantages of this disclosure will become more apparent from the accompanying drawings, in which like reference numerals generally denote like parts.

[0008] Figure 1 A schematic diagram illustrating an application scenario of a management disk according to an embodiment of the present disclosure is shown;

[0009] Figure 2 A flowchart illustrating a process for managing a disk according to an embodiment of the present disclosure is shown;

[0010] Figure 3 A flowchart illustrating a process for determining performance information according to an embodiment of the present disclosure is shown;

[0011] Figure 4 A schematic diagram of an application scenario for managing disk slices according to an embodiment of the present disclosure is shown.

[0012] Figure 5 A schematic block diagram of an example device suitable for implementing embodiments of the present disclosure is shown.

[0013] In the various figures, the same or corresponding reference numerals indicate the same or corresponding parts. Detailed Implementation

[0014] Embodiments of this disclosure will now be described in more detail with reference to the accompanying drawings. While some embodiments of this disclosure are shown in the drawings, it should be understood that this disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of this disclosure. It should be understood that the accompanying drawings and embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of protection of this disclosure.

[0015] In the description of embodiments of this disclosure, the term "comprising" and similar terms should be understood as open-ended inclusion, i.e., "including but not limited to". The term "based on" should be understood as "at least partially based on". The term "one embodiment" or "the embodiment" should be understood as "at least one embodiment". The terms "first", "second", etc., may refer to different or the same objects. Other explicit and implicit definitions may also be included below.

[0016] The principles of this disclosure will now be described with reference to several exemplary embodiments illustrated in the accompanying drawings. While preferred embodiments of this disclosure are shown in the drawings, it should be understood that these embodiments are described only to enable those skilled in the art to better understand and implement this disclosure, and are not intended to limit the scope of this disclosure in any way.

[0017] Most data has a long lifespan from its creation. As data progresses through its lifecycle, its capabilities, such as access frequency, change. For example, data is typically used frequently when it is created, meaning the disk slice containing the data is accessed a high number of times per unit of time. Over time, the number of times the data is accessed decreases. Virtual Pool Fully Automatic Storage Tiering (FAST VP) technology can dynamically match storage needs with changes in data access frequency. For example, frequently accessed data can be stored in flash drives at the very high performance tier. When the data is accessed at a moderate frequency, it can be moved to a Serial Attached SCSI (SAS) drive at the performance tier. And when the data is accessed even less frequently, it can be further moved to a nearline SAS (NL-SAS) drive at the capacity tier.

[0018] Traditional FAST VP technology still has many limitations. For example, it only considers the access frequency of disk slices and does not take into account the performance information of each disk slice (which has a specific access pattern) within a specific storage disk. Therefore, it is possible that a disk slice has a high access frequency, but if the disk slice is moved to a higher-level storage disk, the cost-effectiveness of the data move is low. How to comprehensively consider these parameters to achieve hierarchical operation of data in various disk slices within a storage disk is a problem that urgently needs to be solved.

[0019] To address the aforementioned issues, this disclosure proposes a scheme for managing disks. In this scheme, by statistically analyzing the specific performance information of disk slices under various access modes across different storage disk tiers, as well as the access frequency information of the corresponding disk slices, a comprehensive score for each disk slice can be calculated. Furthermore, more specifically, when considering the performance information of disk slices, at least one performance parameter can be comprehensively considered, such as disk slice bandwidth, read / write operations per unit time, and response time, thereby providing a more objective evaluation of the disk slice's status. The following first combines... Figure 1 Discuss the basic concept of this disclosure.

[0020] Figure 1 A schematic diagram illustrating an application scenario 100 of a management disk according to an embodiment of the present disclosure is shown. Figure 1As shown, storage disks 110, 120, and 130 are all used for storing data. In some embodiments, storage disks 110, 120, and 130 are used to store different types of data. As an example, storage disks 110, 120, and 130 can be flash drives (including NVMe Flash, SAS Flash), serial-attached SCSI (SAS) drives, and nearline SAS (NL-SAS) drives, respectively. It should be understood that flash drives are typically in the very high-performance tier and are used to store data that is accessed frequently. Serial-attached SCSI (SAS) drives are in the performance tier and are used to store data that is accessed moderately. Nearline SAS (NL-SAS) drives are in the capacity tier and are used to store data that is accessed even less frequently.

[0021] In storage systems, various algorithms can be used to organize physical storage disks. To better understand storage systems, Figure 1 An application scenario 100 for the storage system is illustrated. For example... Figure 1 As shown, the storage disk is divided into multiple storage blocks. These storage blocks are also called multiple disk slices. Figure 1 As shown, storage disk 110 can contain at least disk slices 111, 112, 113, and 114; storage disk 120 can contain at least disk slices 121, 122, and 123; and storage disk 130 can contain at least 131, 132, and 133. This partitioning of storage disks can be logical. The size of each disk slice depends on the storage disk size and the partitioning method. In some examples, the disk slice size can be in the gigabyte range. Of course, other disk slice sizes are possible depending on actual deployment needs.

[0022] A storage system (not shown) can obtain relevant parameters of multiple storage disks it manages. As an example, the storage system can determine at least one performance parameter among the following for each disk slice: bandwidth, read / write operations per unit time (IOPS), and response time, and determine the performance information of the corresponding disk slice based on these parameters. Furthermore, the storage system can obtain access frequency information or access count information for each disk slice. By comprehensively considering the performance information and access frequency information of the disk slices, FAST VP can be executed more accurately and efficiently, improving storage efficiency.

[0023] Referenced above Figure 1 Implementations of managing storage disks 110, 120, and 130 and disk slices therein are described. The examples above are merely illustrative and not intended to limit the scope of this disclosure. The following will combine... Figure 2 A flowchart detailing the process used to manage disks.

[0024] Figure 2A flowchart of a process 200 for managing a disk according to an embodiment of the present disclosure is shown. In some embodiments, process 200 may be performed at... Figure 5 Implemented in the device shown. As an example, process 200 can be implemented according to... Figure 1 The application scenario 100 shown is implemented using the management storage disks 110, 120, and 130. Now refer to... Figure 1 This description describes a process 200 for managing a disk according to an embodiment of the present disclosure. For ease of understanding, the specific data mentioned in the following description are exemplary and are not intended to limit the scope of this disclosure.

[0025] In step 202, the storage system can determine performance information about the access patterns of the disk slices based on the differences in performance parameters across multiple storage disks 110, 120, and 130. It should be understood that the number of multiple storage disks is not limited to... Figure 2 The numbers shown can be other numbers as well. It should also be understood that disk slices typically have specific access patterns (IO patterns). For example, depending on factors such as access size (IO size), read / write ratio, and random / sequential ratio, a disk slice can have multiple access patterns. For instance, disk slice access patterns can include: 128K_70R_0S, 4K_70R_0S, 8K_0R_100S, 8K_70R_0S, 32K_70R_0S, 8K_90R_100S, etc. It should be understood that the access pattern "128K_70R_0S" indicates that the access size is 128KB, the ratio of read operations in the access operations is 70%, and 0% of the access operations are sequential. And so on; the meanings of the other access patterns will not be elaborated here.

[0026] Experiments revealed that disk slices with different access modes exhibit varying performance across different storage disk tiers, and this performance variation can be predetermined. Therefore, when determining the performance information of a disk slice, one can first obtain its general information and then identify its specific access mode, thus determining the disk slice's performance information.

[0027] The following will be through Figure 3 The description details the process used to determine the performance information of disk slices. Figure 3 A flowchart of a process 300 for determining performance information according to an embodiment of the present disclosure is shown. In some embodiments, process 300 may be performed at... Figure 5 Implemented in the device shown. As an example, process 300 can be implemented according to... Figure 1 The application scenario 100 shown is implemented using the management storage disks 110, 120, and 130. Now refer to... Figure 1This description describes a process 300 for managing a disk according to an embodiment of the present disclosure. For ease of understanding, the specific data mentioned in the following description are exemplary and are not intended to limit the scope of this disclosure.

[0028] At 302, the storage system can obtain at least one of the following performance metrics for disk slices with different access modes across multiple storage disks 110, 120, and 130: bandwidth, read / write operations per unit time, and response time. As an example, a performance table for different access modes corresponding to different storage disks can be determined by obtaining system data, as shown in Table 1 below.

[0029]

[0030] Table 1

[0031] In 304, the storage system can determine the corresponding comprehensive performance parameters for each access mode on the aforementioned disks based on the above-mentioned multiple performance parameters.

[0032] As an example, suppose C Bj,k It is a certain access mode P j The bandwidth C on a certain storage disk k Ij,k It is access mode P j IOPS on storage disk k, C Rj,k It is access mode P j The response time on a certain storage disk k. Since these three performance parameters have different units, they need to be normalized using the following equation:

[0033]

[0034]

[0035]

[0036] Among them NC Bj,k It is C Bj,k The normalized result, NC Ij,k It is C Ij,k The normalization results, and NC Rj,k It is C Rj,k The normalized result. Therefore, the corresponding comprehensive performance parameters for each access mode on the aforementioned disks can be determined using the following equation, namely, access mode P. j The overall performance parameter G on storage disk k j,k :

[0037] G j,k =NC Bj,k +NC Ij,k +NCRj,k Equation 4.

[0038] In this way, performance information from different dimensions can be integrated into performance information of a unified dimension, which is convenient for subsequent performance evaluation.

[0039] In 306, the storage system can determine performance information based on the differences in overall performance parameters of access patterns across multiple disks. In some embodiments, to determine performance information, the storage system can determine the standard deviation of the overall performance parameters of access patterns across multiple disks.

[0040] As an example, when the comprehensive performance parameter G is determined j,k Then, optionally, the following equation can be used to further normalize it to obtain the normalized comprehensive performance parameter NG. j,k :

[0041]

[0042] And from this, the access mode P can be determined. j Average overall performance parameters NG on storage disk k average :

[0043]

[0044] Once the access mode P is determined j Normalized overall performance parameters NG on storage disk k j,k and NG average Then, the access mode P can be determined. j Standard deviation of performance on storage disk k:

[0045]

[0046] It should be understood that the methods for determining performance information described above are not limited to calculating the standard deviation; variance, mean squared error, and other methods can also be used to determine performance information. Alternatively or additionally, since higher bandwidth results in higher IOPS, shorter response times, and thus higher performance parameters, the aforementioned performance information can be calculated using the principle that bandwidth, IOPS, and performance parameters are directly proportional, while response time is inversely proportional to performance parameters. In this way, the performance information of various access modes on various storage disks can be quantitatively and accurately determined, and this performance information is used to represent the performance differences of an access mode on different storage disks.

[0047] In step 204, the storage system can determine the score of a disk slice based on the performance information and access frequency information of the disk slice determined above. In some embodiments, the storage system can obtain the access mode of each disk slice in the storage disk through system query. It should be understood that a disk slice typically corresponds to only one access mode. Since the storage system can determine the performance information of various access modes on various storage disks according to the above equation, the storage system can further determine the performance information of the disk slice that currently needs to perform FAST VP on each storage disk. Since the storage system can also obtain the access frequency information or access count information of the disk slice as in the conventional FAST VP technology, the score can be determined based on the performance information and access frequency information. As an example, the score can be determined based on the corresponding access mode P of a specific disk slice Si. i Performance information σ on each storage disk k i and access frequency information C i The product of the two is used to determine the score D using the following equation. i :

[0048]

[0049] It should be understood that the score is D. i The determination is not limited to performance information σ i Access frequency information C i The product of these factors is determined. In this way, the scoring integrates disk slice performance information and access frequency information, thus taking into account more factors.

[0050] At 206, the storage system can determine the location of the disk slice among the plurality of storage disks based on a score. In some embodiments, if the score is determined to be higher than or equal to a threshold score, the storage system can move the disk slice to a location with a first priority among the plurality of storage disks, and if the score is determined to be lower than the threshold score, the disk slice is moved to a location with a second priority among the plurality of storage disks. It should be understood that the first priority is higher than the second priority.

[0051] Figure 4 A schematic diagram illustrating an application scenario 400 for managing disk slices according to an embodiment of the present disclosure is shown. Figure 1 Similarly, storage disks 110, 120, and 130 can be flash drives (including NVMe Flash and SAS Flash), serial SCSI (SAS) drives, and nearline SAS (NL-SAS) drives, respectively. Storage disk 110 can contain at least disk slices 111 and 112, storage disk 120 can contain at least disk slices 121 and 122, and storage disk 130 can contain at least slices 131, 132, and 133.

[0052] like Figure 4As shown, disk slices 401 and 402 are disk slices being evaluated to determine their tier. It should be understood that disk slices 401 and 402 may originally belong to one of storage disks 110, 120, or 130, or they may be new disk slices to which data is being written. The storage system can determine and sort the respective scores for disk slices 401 and 402 to form a sorted disk slice group 410. In disk slice group 410, since disk slice 401 has a higher score than disk slice 402, disk slice 401 can be assigned to the higher-tier storage disk 110, and disk slice 402 can be assigned to the lower-tier storage disk 120. It should be understood that, for clarity, Figure 4 The illustration only involves two disk slices to be allocated. This illustration is not intended to limit this disclosure. There may be multiple disk slices to be allocated, and several disk slices may be allocated to storage disks at the same level based on their scores.

[0053] By implementing the above embodiments, a score for each disk slice can be determined based on more comprehensive information. Using this score as a benchmark, the storage disk to which each disk slice belongs can be further determined, ensuring that each storage disk is used evenly and rationally. Therefore, disk slices with small performance variations between different storage disk tiers can be assigned to lower-tier storage disks, while disk slices with large performance variations between different storage disk tiers and high access frequency can be assigned to higher-tier storage disks to improve storage efficiency.

[0054] Figure 5 A schematic block diagram of an example device 500 suitable for implementing embodiments of the present disclosure is shown. As shown, device 500 includes a central processing unit (CPU) 501, which can perform various appropriate actions and processes according to computer program instructions stored in read-only memory (ROM) 502 or loaded from storage unit 508 into random access memory (RAM) 503. Various programs and data required for the operation of device 500 may also be stored in RAM 503. CPU 501, ROM 502, and RAM 503 are interconnected via bus 504. Input / output (I / O) interface 505 is also connected to bus 504.

[0055] Multiple components in device 500 are connected to I / O interface 505, including: input unit 506, such as keyboard, mouse, etc.; output unit 507, such as various types of monitors, speakers, etc.; storage unit 508, such as disk, optical disk, etc.; and communication unit 509, such as network card, modem, wireless transceiver, etc. Communication unit 509 allows device 500 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0056] The various processes and handling described above, such as processes 200 and / or 300, may be executed by processing unit 501. For example, in some embodiments, processes 200 and / or 300 may be implemented as computer software programs tangibly contained in a machine-readable medium, such as storage unit 508. In some embodiments, part or all of the computer program may be loaded and / or installed on device 500 via ROM 502 and / or communication unit 509. When the computer program is loaded into RAM 503 and executed by CPU 501, one or more actions of processes 200 and / or 300 described above may be performed.

[0057] This disclosure can be a method, apparatus, system, and / or computer program product. A computer program product may include a computer-readable storage medium having computer-readable program instructions loaded thereon for performing various aspects of this disclosure.

[0058] Computer-readable storage media can be tangible devices capable of holding and storing instructions for use by an instruction execution device. Computer-readable storage media can be, for example, (but not limited to) electrical storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of computer-readable storage media include: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital multifunction disc (DVD), memory sticks, floppy disks, mechanical encoding devices, such as punch cards or recessed protrusions storing instructions thereon, and any suitable combination of the foregoing. The computer-readable storage media used herein are not to be construed as transient signals themselves, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., light pulses through fiber optic cables), or electrical signals transmitted through wires.

[0059] The computer-readable program instructions described herein can be downloaded from computer-readable storage media to various computing / processing devices, or downloaded via a network, such as the Internet, local area network, wide area network, and / or wireless network, to an external computer or external storage device. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards them to the computer-readable storage media in the respective computing / processing device.

[0060] Computer program instructions used to perform the operations of this disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, status setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, etc., and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, electronic circuitry, such as programmable logic circuitry, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), is personalized by utilizing the status information of the computer-readable program instructions to implement various aspects of this disclosure.

[0061] Various aspects of this disclosure are described herein with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-readable program instructions.

[0062] These computer-readable program instructions can be provided to a processing unit of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that, when executed by the processing unit of the computer or other programmable data processing apparatus, they create means for implementing the functions / actions specified in one or more blocks of the flowchart and / or block diagram. These computer-readable program instructions can also be stored in a computer-readable storage medium that causes a computer, programmable data processing apparatus, and / or other device to operate in a particular manner. Thus, the computer-readable medium storing the instructions comprises an article of manufacture that includes instructions for implementing aspects of the functions / actions specified in one or more blocks of the flowchart and / or block diagram.

[0063] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to perform the functions / actions specified in one or more boxes of a flowchart and / or block diagram.

[0064] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of an instruction containing one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than those shown in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0065] The various embodiments of this disclosure have been described above. These descriptions are exemplary and not exhaustive, and are not limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best explain the principles, practical applications, or technical improvements to the technology in the market, or to enable others skilled in the art to understand the embodiments disclosed herein.

Claims

1. A method for managing disks, comprising: Based on the differences in performance parameters of disk slice access patterns across multiple disks, the performance information of the disk slice access patterns is determined. Based on the performance information and the access frequency information of the disk slice, the score of the disk slice is determined; as well as Based on the score, the position of the disk slice among the plurality of disks is determined. Determining the position of the disk slice among the plurality of disks includes: If the score is determined to be higher than or equal to the threshold score, the disk slice is moved to a position with first priority among the plurality of disks; as well as If the score is determined to be below a threshold score, the disk slice is moved to a position with second priority among the plurality of disks. The first priority is higher than the second priority.

2. The method according to claim 1, wherein determining the performance information includes: Obtain the corresponding performance metrics for the access mode on the multiple disks; Based on the aforementioned multiple performance metrics, the corresponding comprehensive performance parameters of the access mode on the multiple disks are determined. as well as The performance information is determined based on the differences in comprehensive performance parameters among the multiple disks according to the access mode.

3. The method of claim 2, wherein the plurality of performances includes at least one of the following performance parameters: bandwidth; The number of read / write operations per unit of time; and Response time.

4. The method of claim 2, wherein the plurality of performances are normalized performance data.

5. The method according to claim 2, wherein determining the performance information based on the difference in the comprehensive performance parameters includes: The standard deviation of the comprehensive performance parameters of the access mode across the multiple disks is determined as the performance information.

6. An electronic device, comprising: processor; as well as A memory coupled to the processor, the memory having instructions stored therein, the instructions which, when executed by the processor, cause the electronic device to perform actions, the actions including: Based on the differences in performance parameters of disk slice access patterns across multiple disks, the performance information of the disk slice access patterns is determined. Based on the performance information and the disk slice access frequency information, a score for the disk slice is determined; and Based on the score, the position of the disk slice among the plurality of disks is determined. Determining the position of the disk slice among the plurality of disks includes: If the score is determined to be higher than or equal to a threshold score, the disk slice is moved to a position with first priority among the plurality of disks; and If the score is determined to be below a threshold score, the disk slice is moved to a position with second priority among the plurality of disks. The first priority is higher than the second priority.

7. The electronic device of claim 6, wherein determining the performance information includes: Obtain the corresponding performance metrics for the access mode on the multiple disks; Based on the aforementioned multiple performance parameters, the corresponding comprehensive performance parameters of the access mode on the multiple disks are determined; as well as The performance information is determined based on the differences in comprehensive performance parameters among the multiple disks according to the access mode.

8. The electronic device of claim 7, wherein the plurality of performance characteristics includes at least one of the following performance parameters: bandwidth; The number of read / write operations per unit of time; and Response time.

9. The electronic device of claim 7, wherein the plurality of performance parameters are normalized performance data.

10. The electronic device of claim 7, wherein determining the performance information based on the difference in the comprehensive performance parameters includes: The standard deviation of the comprehensive performance parameters of the access mode across the multiple disks is determined as the performance information.

11. A computer program product tangibly stored on a non-volatile computer-readable medium and comprising machine-executable instructions that, when executed, cause a machine to perform the steps of the method according to any one of claims 1 to 5.

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