Storage equipment reliability prediction method and device, equipment and storage medium

Abstract

The embodiment of the invention discloses a storage device reliability prediction method and device, equipment and a storage medium. The method and device are used for rapidly and accurately evaluating the health state of the storage device and improving the use reliability of the storage device. The method provided by the embodiment of the invention comprises the following steps: acquiring equipment state information of the storage equipment; the equipment state information at least comprises one of the following information: the nominal erasing and writing frequency of the super blocks, the number of the super blocks in a user area in a storage space of the storage equipment, the number of the super blocks in a system area in the storage space of the storage equipment and a writing amplification coefficient; determining reliability evaluation information of the storage device based on the device state information; the reliability evaluation information at least comprises one of the following information: DWPD (whole disk write-in times per day) during operation, the residual life of a user area, the residual life of a system area, the life consumption ratio of the user area and the life consumption ratio of the system area; and determining whether the storage device is abnormal or not according to the reliability evaluation information.

Description

Technical Field

[0001] The embodiments of the present application relate to the technical field of storage devices, and in particular to a method, apparatus, device and storage medium for predicting the reliability of a storage device. Background Art

[0002] With the rapid development of the information age, storage devices have become a vital component of information systems. The performance and reliability of storage devices directly affect the stability of the system and user experience. Therefore, reliability prediction and life management are of great significance, so as to identify potential failure risks in advance and avoid data loss and equipment damage.

[0003] Currently, the health status of storage devices is usually assessed based on the number of write and erase cycles of their non-volatile storage media. At the same time, machine learning algorithms can also be used to predict reliability. However, due to differences in the technical levels of different equipment manufacturers, the prediction results obtained by the above methods are often not accurate enough, resulting in underutilization or overuse of storage devices. Existing technologies still lack comprehensiveness and accuracy in evaluating the reliability and life of storage devices. Summary of the invention

[0004] Based on the above problems, the embodiments of the present application provide a storage device reliability prediction method, apparatus, device and storage medium, the purpose of which is to accurately evaluate the health status of the storage device and improve the reliability of the storage device.

[0005] In a first aspect, an embodiment of the present application provides a method for predicting reliability of a storage device, comprising:

[0006] Acquire device status information of the storage device; the device status information includes at least one of the following: nominal erase and write times of the super block, the number of super blocks in the user area of ​​the storage space of the storage device, the number of super blocks in the system area of ​​the storage space of the storage device, and the write amplification factor;

[0007] Determine reliability evaluation information of the storage device based on the device status information; the reliability evaluation information includes at least one of the following: the number of whole disk writes per day (DWPD, Drive Writes Per Day) during operation, the remaining life of the user area, the remaining life of the system area, the life consumption ratio of the user area, and the life consumption ratio of the system area;

[0008] It is determined whether the storage device is abnormal according to the reliability evaluation information.

[0009] In one embodiment, the write amplification factor includes a global write amplification factor; the device status information also includes: nominal capacity, power-on usage time, and nominal DWPD; and determining the reliability evaluation information of the storage device based on the device status information includes:

[0010] Based on the nominal number of erase and write times of the super block, the number of super blocks in the user area, the global write amplification factor, the nominal capacity, and the power-on usage time, the runtime DWPD is calculated and used as the reliability evaluation information of the storage device;

[0011] The determining, according to the reliability evaluation information, whether the storage device is abnormal includes:

[0012] If the runtime DWPD is greater than the nominal DWPD, determining that the storage device is normal;

[0013] If the runtime DWPD is not greater than the nominal DWPD, it is determined that an abnormality exists in the storage device.

[0014] In one embodiment, the runtime DWPD is calculated by the following formula:

[0015]

[0016] Among them, DWPD runtime represents the runtime DWPD, EPcycle represents the nominal erase and write times of the super block, PhyUserSblkCnt represents the number of super blocks in the user area, WA represents the global write amplification factor, DeviceVol represents the nominal capacity size, usedTime represents the power-on usage time, T g Characterizes the warranty period of the storage device.

[0017] In one embodiment, the write amplification factor includes a user area write amplification factor and a system area write amplification factor; the device status information also includes: the remaining erasable times of the user area, the remaining erasable times of the system area, the amount of written data of the system area per unit time, and the amount of written data of the user area per unit time; the reliability evaluation information also includes: data write overhead ratio;

[0018] The step of determining the reliability evaluation information of the storage device based on the device status information includes:

[0019] Calculating the remaining life of the user area based on the remaining number of erasable times of the user area and the write amplification factor of the user area;

[0020] Calculating the remaining life of the system area based on the remaining number of erasable times of the system area and the write amplification factor of the system area;

[0021] Calculating the data write overhead ratio based on the amount of data written to the system area within the unit time and the amount of data written to the user area within the unit time;

[0022] using the remaining life of the user area, the remaining life of the system area, and the data writing overhead ratio as reliability evaluation information;

[0023] The determining, according to the reliability evaluation information, whether the storage device is abnormal includes:

[0024] If the product of the remaining life of the user area and the data write overhead ratio is not greater than the remaining life of the system area, determining that the storage device is normal;

[0025] If the product of the remaining life of the user area and the data write overhead ratio is greater than the remaining life of the system area, it is determined that an abnormality exists in the storage device.

[0026] In one embodiment, the device status information further includes: the number of times the user area has been erased and written, and the number of times the system area has been erased and written; and determining the reliability evaluation information of the storage device based on the device status information includes:

[0027] Calculate the life consumption ratio of the user area based on the number of times the user area has been erased, the nominal number of times the super block has been erased, and the number of super blocks in the user area;

[0028] Calculating the life consumption ratio of the system area based on the number of times the system area has been erased, the nominal number of times the super block has been erased, and the number of super blocks in the system area;

[0029] The lifetime consumption ratio of the user area and the lifetime consumption ratio of the system area are used as reliability evaluation information;

[0030] The determining, according to the reliability evaluation information, whether the storage device is abnormal includes:

[0031] Determine a life consumption evaluation result based on the life consumption proportion of the user area and the life consumption proportion of the system area;

[0032] If the life consumption evaluation result is not less than a preset value, it is determined that the storage device is normal;

[0033] If the life consumption evaluation result is less than a preset value, it is determined that an abnormality exists in the storage device.

[0034] In one embodiment, the write amplification factor includes a global write amplification factor, a user area write amplification factor, and a system area write amplification factor; the device status information also includes: nominal capacity size, power-on usage time, nominal DWPD, remaining erasable times of the user area, remaining erasable times of the system area, amount of written data of the system area per unit time, and amount of written data of the user area; the reliability evaluation information also includes: data write overhead ratio; the reliability evaluation information of the storage device determined based on the device status information includes:

[0035] Based on the nominal number of erase and write times of the super block, the number of super blocks in the user area, the global write amplification factor, the nominal capacity, and the power-on usage time, the runtime DWPD is calculated;

[0036] Calculating the remaining life of the user area based on the remaining number of erasable times of the user area and the write amplification factor of the user area;

[0037] Calculating the remaining life of the system area based on the remaining number of erasable times of the system area and the write amplification factor of the system area;

[0038] Calculating the data writing overhead ratio based on the amount of data written to the system area and the amount of data written to the user area within the unit time;

[0039] using the runtime DWPD, the remaining life of the user area, the remaining life of the system area, and the data write overhead ratio as reliability evaluation information;

[0040] The determining, according to the reliability evaluation information, whether the storage device is abnormal includes:

[0041] If the runtime DWPD is greater than the nominal DWPD, and / or if the product of the remaining life of the user area and the data write overhead ratio is not greater than the remaining life of the system area, determining that the storage device is normal;

[0042] If the runtime DWPD is not greater than the nominal DWPD, and / or if the product of the remaining life of the user area and the data write overhead ratio is greater than the remaining life of the system area, it is determined that the storage device is abnormal.

[0043] In one embodiment, the write amplification factor includes a global write amplification factor; the device status information further includes: nominal capacity size, power-on usage time, nominal DWPD, the number of times the user area has been erased and written, and the number of times the system area has been erased and written;

[0044] The step of determining the reliability evaluation information of the storage device based on the device status information includes:

[0045] Based on the nominal number of erase and write times of the super block, the number of super blocks in the user area, the global write amplification factor, the nominal capacity, and the power-on usage time, the runtime DWPD is calculated;

[0046] Based on the number of times the user area has been erased and written, the nominal number of times the super block has been erased and written, and the number of super blocks in the user area, the life consumption ratio of the user area is calculated;

[0047] Based on the number of times the system area has been erased and written, the nominal number of times the super block has been erased and written, and the number of super blocks in the system area, the life consumption ratio of the system area is calculated;

[0048] The runtime DWPD, the lifetime consumption ratio of the user area, and the lifetime consumption ratio of the system area are used as reliability evaluation information;

[0049] The determining, according to the reliability evaluation information, whether the storage device is abnormal includes:

[0050] Determine a life consumption evaluation result based on the life consumption proportion of the user area and the life consumption proportion of the system area;

[0051] If the runtime DWPD is greater than the nominal DWPD, and / or if the life consumption evaluation result is not less than a preset value, determining that the storage device is normal;

[0052] If the runtime DWPD is not greater than the nominal DWPD, and / or if the life consumption evaluation result is less than a preset value, it is determined that an abnormality exists in the storage device.

[0053] In one embodiment, determining the life consumption evaluation result based on the life consumption proportion of the user area and the life consumption proportion of the system area includes:

[0054] Determine a life consumption evaluation result by using a first formula or a second formula based on the life consumption proportion of the user area and the life consumption proportion of the system area;

[0055] The first formula includes:

[0056]

[0057] Among them, Result LifeConsumedIndicates the evaluation result of life consumption; UserLifeConsumed indicates the proportion of life consumption in the user area; SysLifeConsumed indicates the proportion of life consumption in the system area; MIN{} indicates the minimum value; β is a constant, indicating the boundary value;

[0058] The second formula includes:

[0059]

[0060] Among them,?: represents the conditional operator; Result A ,Result B is a constant with different values; the second formula means that if If true, the life consumption evaluation result is Result A ;like If it is false, the life consumption evaluation result is Result B .

[0061] In a second aspect, an embodiment of the present application further provides a storage device reliability prediction device, comprising:

[0062] an acquisition unit, configured to acquire device status information of a storage device; the device status information includes at least one of the following: a nominal number of erasures and writes of a super block, a number of super blocks in a user area in a storage space of the storage device, a number of super blocks in a system area in a storage space of the storage device, and a write amplification factor;

[0063] A determination unit, configured to determine reliability evaluation information of the storage device based on the device status information; the reliability evaluation information includes at least one of the following: runtime DWPD, the remaining life of the user area, the remaining life of the system area, the life consumption ratio of the user area, and the life consumption ratio of the system area;

[0064] The determining unit is further configured to determine whether the storage device is abnormal based on the reliability evaluation information.

[0065] In a third aspect, an embodiment of the present application further provides a storage device, including:

[0066] CPU, memory, input and output interfaces;

[0067] The memory is a short-term storage memory or a persistent storage memory;

[0068] The central processing unit is configured to communicate with the memory and execute instruction operations in the memory to perform any one of the above-mentioned storage device reliability prediction methods.

[0069] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, any one of the above-mentioned storage device reliability prediction methods is executed.

[0070] It can be seen from the above technical solutions that the embodiments of the present application have the following advantages:

[0071] This application collects multi-dimensional device status information (such as the nominal number of super block erase and write times, write amplification factor, etc.), combined with the actual status during operation (such as the remaining life / life consumption ratio of the user area or system area, etc.), to comprehensively analyze the health status of the device. Compared with a single reliability indicator, the embodiment of this application can more accurately reflect the actual usage status of the storage device, realize the accurate assessment of the health status of the storage device, and has the advantages of strong real-time performance, high adaptability, and refined life management. It can effectively improve the security, reliability and use efficiency of the storage device and reduce the possibility of data loss. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0073] Figure 1 A schematic diagram of a storage device reliability prediction method provided in an embodiment of the present application;

[0074] Figure 2 A schematic diagram of the structure of a storage device reliability prediction device provided in an embodiment of the present application;

[0075] Figure 3 A schematic diagram of the structure of a storage device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0076] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0077] With the rapid development of the information age, storage devices have become a vital component of information systems. The performance and reliability of storage devices directly affect the stability of the system and user experience. Therefore, reliability prediction and life management are of great significance, so as to identify potential failure risks in advance and avoid data loss and equipment damage.

[0078] Currently, the health status of storage devices is usually assessed based on the number of write and erase cycles of their non-volatile storage media. At the same time, machine learning algorithms can also be used to predict reliability. However, due to differences in the technical levels of different equipment manufacturers, the prediction results obtained by the above methods are often not accurate enough, resulting in underutilization or overuse of storage devices. Existing technologies still lack comprehensiveness and accuracy in evaluating the reliability and life of storage devices.

[0079] Based on this, in each embodiment of the present application, multi-dimensional device status information is collected and then combined with the actual status of the storage device during operation, so as to comprehensively analyze the health status of the device.

[0080] The various embodiments of the present application are described in further detail below in conjunction with the accompanying drawings.

[0081] The present application embodiment provides a method for predicting the reliability of a storage device. Figure 1 As shown, the method includes steps S101-S103.

[0082] S101: Acquire device status information of a storage device.

[0083] The device status information of storage devices can usually be collected from storage devices through the system or management tools. The device status information is mainly used to monitor the operating status, health status and service life of the device. The device status information includes but is not limited to the following items: the nominal number of erase and write times of the super block, the number of super blocks in the user area of ​​the storage space of the storage device, the number of super blocks in the system area of ​​the user area of ​​the storage space of the storage device, and the write amplification factor; these device status information can be used separately or in combination, depending on the monitoring requirements and device conditions to decide whether to collect all or part of the information, so as to achieve efficient health status assessment and life prediction.

[0084] It should be understood that a superblock (SBLK) is a logical unit composed of specific physical blocks selected from different NAND flash memory dies. For example, SBLK0 may be composed of blocks with the same physical block identifier on 128 dies (such as Block 0 of each die).

[0085] The write amplification factor is the ratio of the amount of data actually written to the NAND flash memory to the amount of data requested to be written by the host, reflecting the write efficiency of the storage device. The main causes of write amplification include: (1) Garbage Collection: NAND flash memory is erased in blocks, but can only be written in pages. When some data pages fail (marked as invalid pages), the valid pages still need to be migrated to new blocks and then the old blocks are erased, which will result in additional write operations. (2) Write alignment problem: If the size of the data written by the user is not aligned with the physical size of the flash page or block (for example, the user writes 4KB, but the flash page size is 8KB), it will lead to reduced write efficiency and aggravated write amplification effect. By monitoring the write amplification factor, the actual write load of the device can be quantified, and the data management strategy can be analyzed to optimize device performance.

[0086] The nominal erase and write times of the super block is the physical erase and write life limit of the NAND flash memory particles. By comparing the erase and write times with the nominal erase and write times, the remaining life of the device can be evaluated. When the erase and write times are close to the nominal value, the device is prone to data errors or failures.

[0087] S102: Determine reliability evaluation information of the storage device based on the device status information; the reliability evaluation information includes at least one of the following: the number of disk writes per day (DWPD) during operation, the remaining life of the user area, the remaining life of the system area, the life consumption ratio of the user area, and the life consumption ratio of the system area;

[0088] DWPD indicates the number of times a user can write to the disk every day during the warranty period of the SSD. The following formula can be used to calculate DWPD: DWPD = TBW ÷ warranty days, where TBW (Total Bytes Written) is the total number of bytes that can be written to the SSD during its life. Taking a 300TB TBW SSD with a 10-year warranty as an example, and using the formula "DWPD = TBW ÷ warranty days", it can be calculated that the DWPD of the SSD is about 84.16GB, which means that if 84.16GB of data is written every day, the SSD will begin to wear out.

[0089] The user zone is a part of the storage space of the storage device that is specifically allocated to store user data, while the system zone is used to store metadata, management information, and perform garbage collection operations. The remaining life of the user zone or system zone refers to the unconsumed portion of the physical erasable life. The life consumption ratio refers to the proportion of the consumed life in each zone relative to its total life.

[0090] By providing indicators such as runtime DWPD, remaining life, and life consumption percentage, it is possible to determine whether the storage device is overloaded, as well as the write pressure of the user area and system area in the storage device, to avoid premature failure of local areas.

[0091] S103: Determine whether the storage device is abnormal based on the reliability evaluation information.

[0092] Reliability evaluation information is obtained by analyzing device status information. When determining whether a storage device is abnormal, the reliability evaluation information (such as DWPD, remaining life, and life consumption ratio) can be compared with the nominal value or preset threshold of the storage device design. For example: if the DWPD during operation is greater than the nominal DWPD, it means that the device is overloaded; if the remaining life is less than the critical threshold, it means that the device life is about to expire and backup or replacement measures need to be taken; if the life consumption ratio of the user area is much higher than that of the system area, it is necessary to consider whether there is an uneven data distribution problem and optimize the write strategy.

[0093] This application collects multi-dimensional device status information (such as the nominal number of erase and write times of the super block, write amplification factor, etc.), combined with the actual status during operation (such as the remaining life / life consumption ratio of the user area or system area, etc.), to comprehensively analyze the reliability of the device. Compared with a single evaluation index, the embodiment of this application can more accurately reflect the actual usage status of the storage device, realize the accurate assessment of the health status of the storage device, and has the advantages of strong real-time performance, high adaptability, and refined life management. It can effectively improve the security, reliability and use efficiency of the storage device and reduce the possibility of data loss.

[0094] It should be noted that in order to more intuitively quantify the reliability of storage devices, multiple reliability evaluation information can be generated based on different device status information. By combining this information, the reliability of storage devices can be comprehensively analyzed and predicted and evaluated from different angles and evaluation methods. The following explains several different combination methods, in which the evaluation logic of each method for storage devices is not exactly the same.

[0095] Method 1: In this method, the write amplification factor includes the global write amplification factor; the device status information also includes: nominal capacity, power-on time, and nominal DWPD;

[0096] Based on the device status information, the reliability evaluation information of the storage device is determined, including: based on the nominal erase and write times of the super block, the number of super blocks in the user area, the global write amplification factor, the nominal capacity size, and the power-on usage time, the runtime DWPD is calculated and used as the reliability evaluation information of the storage device;

[0097] Alternatively, the nominal DWPD can be calculated using the following formula:

[0098]

[0099] The runtime DWPD is calculated using the following formula:

[0100]

[0101] Among them, DWPD runtime Represents DWPD during operation; EPcycle represents the nominal erase and write times of the super block, indicating the upper limit of the physical erase and write life of each super block; PhyUserSblkCnt represents the number of super blocks in the user area, indicating the number of user-available storage blocks; WA represents the global write amplification factor; DeviceVol represents the nominal capacity size, indicating the physical storage capacity of the storage device; usedTime represents the power-on usage time, which refers to the time the storage device has been put into use; T g The warranty period of a storage device refers to the designed service life of the storage device. For example, in days, a 5-year warranty period is T g It can be expressed as 365*5.

[0102] The specific meanings of some parameters in the above formula are introduced below.

[0103] (1) EPcycle (Program / Erase Cycle): The nominal number of times the super block of UserZone and SysZone can be erased. Each time the entire SSD is programmed (written) or erased once, the P / E count is calculated once. When writing data, the master control program will automatically write data evenly to all NAND particles to achieve balanced wear.

[0104] (2) The global write amplification factor (WA) can be calculated using the following formula:

[0105]

[0106] Among them, OP represents over-provisioning, that is, the proportion of unallocated storage space reserved by the device to the total storage space. OP is usually expressed in decimal form. For example, if the total storage space of the device is 1TB, 10% (100GB) of which is used for reserved space, then OP = 0.1). For the constant α: It can be understood that even if there is no obvious over-provisioning in a storage device, or even if the over-provisioning space is very large, the storage device still needs to perform management tasks (such as garbage collection and wear leveling), so there will still be a certain amount of write amplification, so the constant α can be understood as the baseline value of write amplification in flash memory.

[0107] (3) OP can be calculated by the following formula:

[0108]

[0109] Among them, PhyVol is the actual physical available capacity. PhyVol = nominal capacity size (DeviceVol) + reserved space size. The reserved space size is determined by the manufacturer's policy. Usually, the device manufacturer will add an additional 5%-30% of the physical capacity for OP.

[0110] Runtime DWPD is a core indicator for measuring the current write load of the device. By comparing the calculated runtime DWPD with the nominal DWPD of the device, it is possible to determine whether the storage device is operating normally: if the runtime DWPD is greater than the nominal DWPD, it means that the current write load of the device is within the design range and can work normally, and the storage device is determined to be normal; if the runtime DWPD is not greater than the nominal DWPD, it is determined that the storage device has an abnormal write load, and there may be a risk of performance degradation or shortened life, and further inspection or maintenance is required.

[0111] Method 1: By calculating the runtime DWPD based on the device status information (such as the nominal erase and write times of the super block, the number of super blocks in the user area, the global write amplification factor, etc.) combined with the actual usage time, the running load of the storage device can be quickly detected.

[0112] Mode 2: In this mode, the write amplification factor includes the user area write amplification factor and the system area write amplification factor; the device status information also includes: the remaining erasable times of the user area, the remaining erasable times of the system area, the amount of written data in the system area per unit time, and the amount of written data in the user area per unit time; the reliability evaluation information also includes: data write overhead ratio;

[0113] Based on the device status information, the reliability evaluation information of the storage device is determined, including: based on the remaining erasable times of the user area and the write amplification factor of the user area, the remaining life of the user area is calculated:

[0114]

[0115] Among them, UserZone Lifetime indicates the remaining life of the user zone; RemainEP indicates the total number of all super blocks in the user area; user Indicates the remaining number of erase and write times for each super block in the user area; WA user Indicates the user area write amplification factor;

[0116] Optionally, the user area write amplification factor WA user It can be calculated by the following formula:

[0117]

[0118] The amount of data written by the user refers to the amount of data actually written by the user. By comparing the amount of data written by the user and the amount of data actually written, the efficiency of writing user data is quantified. The higher the user area write amplification factor, the more additional write operations there are in the device, which will reduce the remaining life of the user area.

[0119] Based on the remaining number of erasable times of the system area and the write amplification factor of the system area, calculate the remaining life of the system area:

[0120]

[0121] SysZone Lifetime indicates the remaining life of the system zone; RemainEP indicates the total number of all super blocks in the system area; sys Indicates the remaining number of erase and write times for each super block in the system area; WA Sys Indicates the write amplification factor of the system area.

[0122] Optionally, the system area write amplification factor WA Sys It can be calculated by the following formula:

[0123]

[0124] The amount of data written by the system refers to the amount of write request data generated by system management operations (such as garbage collection). The higher the system area write amplification factor, the more additional write operations there are in the device, which will reduce the remaining life of the system area.

[0125] Based on the amount of data written to the system area per unit time and the amount of data written to the user area per unit time, calculate the data write overhead ratio:

[0126]

[0127] Among them, CreateSysWriteRate represents the data write overhead ratio; ΔSysWrite represents the amount of data written to the system area per unit time; ΔUserWrite represents the amount of data written to the user area per unit time.

[0128] The data write overhead ratio is used to monitor the load distribution between user writes and system operations. If the overhead ratio is too large, it means that the system operation generates a large number of additional writes, and the write strategy may need to be optimized.

[0129] The remaining life of the user area, the remaining life of the system area and the data write overhead ratio are used as reliability evaluation information; based on the above reliability evaluation information, it is determined whether there is an abnormality in the storage device, including: if the product of the remaining life of the user area and the data write overhead ratio is not greater than the remaining life of the system area, that is, UserZone LifetimeCreateSysWriteRate≤SysZone Lifetime, then the storage device is determined to be normal; if the product of the remaining life of the user area and the data write overhead ratio is greater than the remaining life of the system area, that is, UserZone Lifetime*CreateSysWriteRate>SysZone Lifetime, then it is determined that there is an abnormality in the storage device.

[0130] Method 2 can analyze different functional areas of the storage device independently by distinguishing the remaining life of the user area and the system area, providing a more detailed health status assessment than a single indicator. In addition, combining the remaining life of the user area, the remaining life of the system area and the data write overhead can not only evaluate the remaining life of the storage device, but also discover potential load distribution problems and improve the stability of device operation.

[0131] Method 3: In this method, the device status information also includes: the number of times the user area has been erased and the number of times the system area has been erased;

[0132] Based on the device status information, reliability evaluation information of the storage device is determined, including:

[0133] Based on the number of times the user area has been erased, the nominal number of times the super block has been erased, and the number of super blocks in the user area, calculate the life consumption ratio of the user area:

[0134]

[0135] Among them, UserLifeConsumed represents the life consumption ratio of the user area; Indicates the sum of the number of erases and writes consumed by all super blocks in the user area; UserSblkUsedEC i is the number of times super block i in the user area has been erased; EPcycle represents the nominal number of times the super block is erased; PhyUserSblkCnt represents the total number of super blocks in the user area.

[0136] Based on the number of times the system area has been erased, the nominal number of times the super block has been erased, and the number of super blocks in the system area, calculate the life consumption ratio of the system area:

[0137]

[0138] Among them, SysLifeConsumed represents the life consumption ratio of the system area; Indicates the sum of the erase and write times consumed by all super blocks in the system area; SysSblkUsedEC i is the number of times super block i in the system area has been erased; EPcycle represents the nominal number of times the super block is erased; PhySysSblkCnt represents the total number of super blocks in the system area.

[0139] The life consumption ratio of the user area and the life consumption ratio of the system area are used as reliability evaluation information, and based on the reliability evaluation information, it is determined whether the storage device is abnormal:

[0140] First, the life consumption evaluation result is determined based on the life consumption proportion of the user area and the life consumption proportion of the system area;

[0141] In a possible implementation, the life consumption evaluation result is calculated by the following formula:

[0142]

[0143] Among them, Result LifeConsumed Indicates the life consumption evaluation result; UserLifeConsumed indicates the life consumption ratio of the user area; SysLifeConsumed indicates the life consumption ratio of the system area; MIN{} indicates the minimum value; β indicates the boundary value. In practical applications, β can be 0.01, which means that a 1% difference is allowed, that is, the life consumption ratio of the system area is allowed to be at most 1% more than the life consumption ratio of the user area. The life consumption evaluation result indicates that if the rate of life consumption of the system area is faster than that of the user area, it means that the flash memory device may be abnormal.

[0144] In another possible implementation, the life consumption evaluation result is calculated in the form of a ternary operator using the following formula:

[0145]

[0146] In the above formula, ?: represents a ternary operator, also known as a conditional operator, which is an operator with three operands. For example, in A? B:C, A? is the condition, B is the operation when condition A is true, and C is the operation when condition A is false. Therefore, when calculating Result LifeConsumed ', it can be judged Is it true? If true, the life consumption evaluation result is Result A ; If false, the life consumption evaluation result is Result B Here, Result A1 is acceptable, Result B It depends on the actual application scenario and project requirements, and can be a constant less than 1, such as 0.3.

[0147] After obtaining the life consumption evaluation result, it can be compared with the preset value to determine whether the storage device is abnormal: if the life consumption evaluation result is not less than the preset value, the storage device is determined to be normal; if the life consumption evaluation result is less than the preset value, the storage device is determined to be abnormal. In practical applications, the preset value can be 1.

[0148] Method 4: In this method, it can be regarded as a combination of the methods of obtaining reliability evaluation information in methods 1 and 2 and using the reliability evaluation information to judge the health status of the storage device. Specifically, the write amplification factor includes the global write amplification factor, the user area write amplification factor and the system area write amplification factor; the device status information also includes: nominal capacity size, power-on usage time, nominal DWPD, remaining erasable times of the user area, remaining erasable times of the system area, the amount of data written to the system area per unit time, and the amount of data written to the user area; the reliability evaluation information also includes: data write overhead ratio;

[0149] Based on the device status information, reliability evaluation information of the storage device is determined, including:

[0150] The runtime DWPD is calculated based on the nominal erase and write times of the super block, the number of super blocks in the user area, the global write amplification factor, the nominal capacity, and the power-on usage time. The remaining life of the user area is calculated based on the remaining erase and write times of the user area and the write amplification factor of the user area. The remaining life of the system area is calculated based on the remaining erase and write times of the system area and the write amplification factor of the system area. The data write overhead ratio is calculated based on the amount of data written to the system area and the amount of data written to the user area per unit time.

[0151] The specific method for calculating the runtime DWPD mentioned above can refer to the relevant description in method one, and the specific method for calculating the remaining life of the user area, the remaining life of the system area and the data write overhead ratio can refer to the relevant description in method two, which will not be repeated here.

[0152] The runtime DWPD, the remaining life of the user area, the remaining life of the system area, and the data write overhead ratio are used as reliability evaluation information; and according to the above reliability evaluation information, it is determined whether the storage device is abnormal, including:

[0153] If the runtime DWPD is greater than the nominal DWPD, and / or if the product between the remaining life of the user area and the data write overhead ratio is not greater than the remaining life of the system area, then determining that the storage device is normal;

[0154] If the runtime DWPD is not greater than the nominal DWPD, and / or if the product of the remaining life of the user area and the data write overhead ratio is greater than the remaining life of the system area, it is determined that the storage device is abnormal.

[0155] For example, the runtime DWPD (ie, DWPD runtime ) and nominal DWPD (ie DWPD spec ) into the following formula to obtain Result1:

[0156]

[0157] Substitute the remaining life of the system zone (i.e. SysZone Lifetime) and the remaining life of the user zone (i.e. UserZoneLifetime) into the following formula to obtain Result2:

[0158]

[0159] Based on the above Result1 and Result2, we get Result3:

[0160] Result3=(MIN[Result1,Result2]<1?0:1)

[0161] Result3 combines Result1 and Result2. If any one of the results indicates an abnormality (ie, Result1<1 or Result2<1), Result3=0, indicating that an abnormality exists in the storage device.

[0162] Method 4 comprehensively evaluates the reliability of storage devices by combining the DWPD during runtime with the remaining life of the user area / system area, reducing the misjudgment that may be caused by a single indicator (such as DWPD is normal but the life of the system area is exhausted). The combination of multiple reliability evaluation information can ensure that the reliability judgment of the storage device is more comprehensive and accurate.

[0163] Method 5: In this method, it can be regarded as a combination of the method of obtaining reliability evaluation information in Method 1 and Method 3 and using the reliability evaluation information to judge the health status of the storage device. In Method 5, the write amplification factor includes the global write amplification factor; the device status information also includes: nominal capacity size, power-on usage time, nominal DWPD, the number of times the user area has been erased and written, and the number of times the system area has been erased and written;

[0164] Based on the device status information, reliability evaluation information of the storage device is determined, including:

[0165] The runtime DWPD is calculated based on the nominal number of superblock erases, the number of superblocks in the user area, the global write amplification factor, the nominal capacity, and the power-on time. The user area life consumption ratio is calculated based on the number of times the user area has been erased, the nominal number of times the superblock has been erased, and the number of superblocks in the user area. The system area life consumption ratio is calculated based on the number of times the system area has been erased, the nominal number of times the superblock has been erased, and the number of superblocks in the system area.

[0166] The specific method for calculating the DWPD during runtime mentioned above can refer to the relevant description in method one. The specific method for calculating the life consumption proportion of the user area, the life consumption proportion of the system area, and the subsequent calculation of the life consumption evaluation results can refer to the relevant description in method three, which will not be repeated here.

[0167] The runtime DWPD, the life consumption ratio of the user area, and the life consumption ratio of the system area are used as reliability evaluation information; according to the above reliability evaluation information, it is determined whether the storage device is abnormal, including:

[0168] The life consumption evaluation result is determined based on the life consumption proportion of the user area and the life consumption proportion of the system area.

[0169] If the operating DWPD is greater than the nominal DWPD, and / or if the life consumption evaluation result is not less than a preset value, it is determined that the storage device is normal;

[0170] If the DWPD during operation is not greater than the nominal DWPD, and / or if the life consumption evaluation result is less than a preset value, it is determined that the storage device is abnormal. In practical applications, the preset value may be 1.

[0171] For example, the runtime DWPD (ie, DWPD runtime ) and nominal DWPD (ie DWPD spec ) into the following formula to obtain Result1:

[0172]

[0173] Substitute the life consumption ratio of the system area (i.e., SysLifeConsumed) and the life consumption ratio of the user area (i.e., UserLifeConsumed) into any of the following formulas to obtain Result2:

[0174]

[0175] or

[0176]

[0177] Based on the above Result1 and Result2, we get Result3:

[0178] Result3=(MIN[Result1,Result2]<1?0:1)

[0179] Result3 combines Result1 and Result2. If any one of the results indicates an abnormality (ie, Result1<1 or Result2<1), Result3=0, indicating that an abnormality exists in the storage device.

[0180] Methods 1 to 5 provided in the embodiments of the present application can accurately identify potential problems of storage devices by jointly analyzing the status parameters of each device, thereby improving the accuracy of reliability prediction of storage devices. After identifying that a storage device is abnormal, the final storage device status can be reported in a timely manner, and corresponding maintenance measures can be taken according to the reliability evaluation information obtained in different ways, thereby reducing the possibility of data loss and device failure.

[0181] In order to implement the storage device reliability prediction method of the embodiment of the present application, the embodiment of the present application also provides a storage device reliability prediction device, such as Figure 2 As shown, the device comprises:

[0182] The acquisition unit 201 is used to acquire device status information of the storage device; the device status information includes at least one of the following: the nominal number of erasures and writes of the super block, the number of super blocks in the user area of ​​the storage space of the storage device, the number of super blocks in the system area of ​​the storage space of the storage device, and the write amplification factor;

[0183] A determination unit 202 is used to determine reliability evaluation information of the storage device based on the device status information; the reliability evaluation information includes at least one of the following: the number of disk writes per day DWPD during operation, the remaining life of the user area, the remaining life of the system area, the life consumption ratio of the user area, and the life consumption ratio of the system area;

[0184] The determining unit 202 is further configured to determine whether the storage device is abnormal according to the reliability evaluation information.

[0185] In one embodiment, the device further includes: a processing unit; the processing unit is used to calculate the runtime DWPD based on the nominal erase and write times of the super block, the number of super blocks in the user area, the global write amplification factor, the nominal capacity size, and the power-on usage time, and use it as the reliability evaluation information of the storage device;

[0186] The determining unit 202 is further configured to determine that the storage device is normal if the runtime DWPD is greater than the nominal DWPD;

[0187] The determining unit 202 is further configured to determine that an abnormality exists in the storage device if the runtime DWPD is not greater than the nominal DWPD.

[0188] In one embodiment, the runtime DWPD is calculated by the following formula:

[0189]

[0190] Among them, DWPD runtime represents the runtime DWPD, EPcycle represents the nominal erase and write times of the super block, PhyUserSblkCnt represents the number of super blocks in the user area, WA represents the global write amplification factor, DeviceVol represents the nominal capacity size, usedTime represents the power-on usage time, T g Characterizes the warranty period of the storage device.

[0191] The processing unit is further configured to, in one embodiment, calculate the remaining life of the user area based on the remaining number of erasable times of the user area and the write amplification factor of the user area;

[0192] The processing unit is further used to calculate the remaining life of the system area based on the remaining number of erasable times of the system area and the write amplification factor of the system area;

[0193] The processing unit is further configured to calculate the data write overhead ratio based on the amount of data written to the system area within the unit time and the amount of data written to the user area within the unit time;

[0194] The processing unit is further configured to use the remaining life of the user area, the remaining life of the system area, and the data write overhead ratio as reliability evaluation information;

[0195] The determining unit 202 is further configured to determine that the storage device is normal if the product of the remaining life of the user area and the data write overhead ratio is not greater than the remaining life of the system area;

[0196] The determining unit 202 is further configured to determine that an abnormality exists in the storage device if the product of the remaining life of the user area and the data write overhead ratio is greater than the remaining life of the system area.

[0197] In one embodiment, the processing unit is further used to calculate the life consumption proportion of the user area based on the number of times the user area has been erased, the nominal number of times the super block has been erased, and the number of super blocks in the user area;

[0198] The processing unit is further used to calculate the life consumption proportion of the system area based on the number of times the system area has been erased, the nominal number of times the super block has been erased, and the number of super blocks in the system area;

[0199] The processing unit is further configured to use the life consumption ratio of the user area and the life consumption ratio of the system area as reliability evaluation information;

[0200] The determining unit 202 is further configured to determine a life consumption evaluation result based on the life consumption proportion of the user area and the life consumption proportion of the system area;

[0201] The determining unit 202 is further configured to determine that the storage device is normal if the life consumption evaluation result is not less than a preset value;

[0202] The determining unit 202 is further configured to determine that an abnormality exists in the storage device if the life consumption evaluation result is less than a preset value.

[0203] In one embodiment, the runtime DWPD is calculated based on the nominal erase and write times of the super block, the number of super blocks in the user area, the global write amplification factor, the nominal capacity, and the power-on usage time;

[0204] The processing unit is further used to calculate the remaining life of the user area based on the remaining erasable times of the user area and the write amplification factor of the user area;

[0205] The processing unit is further used to calculate the remaining life of the system area based on the remaining number of erasable times of the system area and the write amplification factor of the system area;

[0206] The processing unit is further configured to calculate the data write overhead ratio based on the amount of data written to the system area and the amount of data written to the user area within the unit time;

[0207] The processing unit is further configured to use the runtime DWPD, the remaining life of the user area, the remaining life of the system area, and the data write overhead ratio as reliability evaluation information;

[0208] The determining unit 202 is further configured to determine that the storage device is normal if the runtime DWPD is greater than the nominal DWPD, and / or if the product of the remaining life of the user area and the data write overhead ratio is not greater than the remaining life of the system area;

[0209] The determination unit 202 is further configured to determine that an abnormality exists in the storage device if the runtime DWPD is not greater than the nominal DWPD and / or if the product of the remaining life of the user area and the data write overhead ratio is greater than the remaining life of the system area.

[0210] In one embodiment, the processing unit is further used to calculate the runtime DWPD based on the nominal erase and write times of the super block, the number of super blocks in the user area, the global write amplification factor, the nominal capacity size, and the power-on usage time;

[0211] The processing unit is further used to calculate the life consumption ratio of the user area based on the number of times the user area has been erased and written, the nominal number of times the super block has been erased and written, and the number of super blocks in the user area;

[0212] The processing unit is further used to calculate the life consumption proportion of the system area based on the number of times the system area has been erased, the nominal number of times the super block has been erased, and the number of super blocks in the system area;

[0213] The processing unit is further configured to use the runtime DWPD, the life consumption ratio of the user area, and the life consumption ratio of the system area as reliability evaluation information;

[0214] The determining unit 202 is further configured to determine a life consumption evaluation result based on the life consumption proportion of the user area and the life consumption proportion of the system area;

[0215] The determining unit 202 is further configured to determine that the storage device is normal if the runtime DWPD is greater than the nominal DWPD and / or if the life consumption evaluation result is not less than a preset value;

[0216] The determining unit 202 is further configured to determine that an abnormality exists in the storage device if the runtime DWPD is not greater than the nominal DWPD and / or if the life consumption evaluation result is less than a preset value.

[0217] In one embodiment, the determining unit 202 is further configured to determine a life consumption evaluation result by using a first formula or a second formula based on the life consumption proportion of the user area and the life consumption proportion of the system area;

[0218] The first formula includes:

[0219]

[0220] Among them, Result LifeConsumed Indicates the evaluation result of life consumption; UserLifeConsumed indicates the proportion of life consumption in the user area; SysLifeConsumed indicates the proportion of life consumption in the system area; MIN{} indicates the minimum value; β is a constant, indicating the boundary value;

[0221] The second formula includes:

[0222]

[0223] Among them,?: represents the conditional operator; Result A ,Result B is a constant with different values; the second formula means that if If true, the life consumption evaluation result is Result A ;like If it is false, the life consumption evaluation result is Result B .

[0224] In actual application, the processing unit can be implemented by a processor in the storage device in combination with a communication interface, and the acquisition unit 201 and the determination unit 202 can be implemented by a communication interface in the reliability prediction device of the storage device.

[0225] It should be noted that: the above embodiment provides a storage device reliability prediction device, and when performing storage device reliability prediction, only the division of the above program modules is used as an example. In actual applications, the above processing can be assigned to different program modules as needed, that is, the internal structure of the device is divided into different program modules to complete all or part of the processing described above. In addition, the storage device reliability prediction device provided in the above embodiment and the storage device reliability prediction method embodiment belong to the same concept. The specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0226] Based on the hardware implementation of the above program modules, and in order to implement a storage device reliability prediction method provided in an embodiment of the present application, an embodiment of the present application further provides a storage device, such as Figure 3 As shown, the storage device 300 includes:

[0227] CPU 301, memory 302 and input / output interface 303;

[0228] The memory 302 is a temporary storage memory or a permanent storage memory;

[0229] The central processor 301 is configured to communicate with the memory 302 and execute instruction operations in the memory 302 to perform any one of the above storage device reliability prediction methods.

[0230] Of course, in actual application, the various components in the storage device 300 are coupled together through the bus system 304. It can be understood that the bus system 304 is used to realize the connection and communication between these components. In addition to the data bus, the bus system 304 also includes a power bus, a control bus and a status signal bus. However, for the sake of clarity, Figure 3 Various buses are labeled as bus system 304 .

[0231] The memory 302 in the embodiment of the present application is used to store various types of data to support the operation of the storage device 300. Examples of such data include: any computer program used to operate on the storage device 300.

[0232] It is understandable that when the processor in the storage device 300 described above executes the computer program, it can also implement the functions of the various units in the corresponding device embodiments described above, which will not be repeated here. Exemplarily, the computer program can be divided into one or more modules / units, one or more modules / units are stored in the memory, and executed by the processor to complete the various embodiments of the present application. One or more modules / units can be a series of computer program instruction segments that can perform specific functions, and the instruction segments are used to describe the execution process of the computer program in the storage device 300. For example, the computer program can be divided into the various units in the above-mentioned storage device 300, and each unit can implement the specific functions described in the above-mentioned corresponding storage device 300.

[0233] The storage device 300 may include, but is not limited to, a processor and a memory. Those skilled in the art will appreciate that the processor and the memory are merely examples of the storage device 300 and do not constitute a limitation on the storage device 300. The storage device 300 may include more or fewer components, or a combination of certain components, or different components, such as an error correction module (ECC), an interface controller (such as SATA, NVMe, PCIe interface), etc.

[0234] The processor may be a central processing unit (CPU), or other general-purpose processors, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the storage device 300, and uses various interfaces and lines to connect various parts of the entire storage device 300.

[0235] The memory can be used to store computer programs and / or modules. The processor implements various functions of the storage device 300 by running or executing the computer programs and / or modules stored in the memory and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, an application required for at least one function, etc.; the data storage area can store data created according to the use of the terminal, etc. In addition, the memory can include a high-speed random access memory and can also include a non-volatile memory, such as a small-capacity non-volatile storage (such as NOR flash memory (NOR Flash)).

[0236] An embodiment of the present application further provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, any one of the above-mentioned storage device reliability prediction methods is executed.

[0237] An embodiment of the present application also provides a computer program product having a computer program / instruction stored thereon. When the computer program / instruction is executed by a processor, it is used to implement the storage device reliability prediction method described in the first aspect of the embodiment of the present application or any specific implementation method of the first aspect.

[0238] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0239] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0240] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0241] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0242] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a storage device to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program code.

Claims

1. A method for predicting the reliability of a storage device, characterized in that: include: Get device status information of storage devices; The device status information includes at least one of the following: the nominal number of erasures and writes of the super block, the number of super blocks in the user area in the storage space of the storage device, the number of super blocks in the system area in the storage space of the storage device, and the write amplification factor; Based on the device status information, reliability evaluation information of the storage device is determined; the reliability evaluation information includes at least one of the following: the number of full disk writes per day DWPD during operation, the remaining life of the user area, the remaining life of the system area, the life consumption ratio of the user area, and the life consumption ratio of the system area; It is determined whether the storage device is abnormal according to the reliability evaluation information.

2. The storage device reliability prediction method according to claim 1, characterized in that: The write amplification factor includes a global write amplification factor; The device status information also includes: nominal capacity, power-on usage time, and nominal DWPD; and determining the reliability evaluation information of the storage device based on the device status information includes: Based on the nominal number of erase and write times of the super block, the number of super blocks in the user area, the global write amplification factor, the nominal capacity, and the power-on usage time, the runtime DWPD is calculated and used as the reliability evaluation information of the storage device; The determining, according to the reliability evaluation information, whether the storage device is abnormal includes: If the runtime DWPD is greater than the nominal DWPD, determining that the storage device is normal; If the runtime DWPD is not greater than the nominal DWPD, it is determined that an abnormality exists in the storage device.

3. The method for predicting storage device reliability according to claim 2, characterized in that: The runtime DWPD is calculated by the following formula: Among them, DWPD runtime represents the runtime DWPD, ePcycle represents the nominal erase and write times of the super block, PhyUserSblkCnt represents the number of super blocks in the user area, WA represents the global write amplification factor, DeviceVol represents the nominal capacity size, usedTime represents the power-on usage time, T g Characterizes the warranty period of the storage device.

4. The storage device reliability prediction method according to claim 1, characterized in that: The write amplification factor includes a user area write amplification factor and a system area write amplification factor; the device status information also includes: the remaining erasable times of the user area, the remaining erasable times of the system area, the amount of written data of the system area per unit time, and the amount of written data of the user area per unit time; the reliability evaluation information also includes: data write overhead ratio; The step of determining the reliability evaluation information of the storage device based on the device status information includes: Calculating the remaining life of the user area based on the remaining number of erasable times of the user area and the write amplification factor of the user area; Calculating the remaining life of the system area based on the remaining number of erasable times of the system area and the write amplification factor of the system area; Calculating the data write overhead ratio based on the amount of data written to the system area within the unit time and the amount of data written to the user area within the unit time; using the remaining life of the user area, the remaining life of the system area, and the data writing overhead ratio as reliability evaluation information; The determining, according to the reliability evaluation information, whether the storage device is abnormal includes: If the product of the remaining life of the user area and the data write overhead ratio is not greater than the remaining life of the system area, determining that the storage device is normal; If the product of the remaining life of the user area and the data write overhead ratio is greater than the remaining life of the system area, it is determined that an abnormality exists in the storage device.

5. The storage device reliability prediction method according to claim 1, characterized in that: The device status information also includes: the number of times the user area has been erased and written, and the number of times the system area has been erased and written; and determining the reliability evaluation information of the storage device based on the device status information includes: Calculate the life consumption ratio of the user area based on the number of times the user area has been erased, the nominal number of times the super block has been erased, and the number of super blocks in the user area; Calculating the life consumption ratio of the system area based on the number of times the system area has been erased, the nominal number of times the super block has been erased, and the number of super blocks in the system area; The lifetime consumption ratio of the user area and the lifetime consumption ratio of the system area are used as reliability evaluation information; The determining, according to the reliability evaluation information, whether the storage device is abnormal includes: Determine a life consumption evaluation result based on the life consumption proportion of the user area and the life consumption proportion of the system area; If the life consumption evaluation result is not less than a preset value, it is determined that the storage device is normal; If the life consumption evaluation result is less than a preset value, it is determined that an abnormality exists in the storage device.

6. The method for predicting storage device reliability according to claim 1, characterized in that: The write amplification factor includes a global write amplification factor, a user area write amplification factor and a system area write amplification factor; The device status information further includes: nominal capacity, power-on usage time, nominal DWPD, remaining erasable times of the user area, remaining erasable times of the system area, amount of written data of the system area per unit time, amount of written data of the user area; the reliability evaluation information further includes: data write overhead ratio; the reliability evaluation information of the storage device determined based on the device status information includes: Based on the nominal number of erase and write times of the super block, the number of super blocks in the user area, the global write amplification factor, the nominal capacity, and the power-on usage time, the runtime DWPD is calculated; Calculating the remaining life of the user area based on the remaining number of erasable times of the user area and the write amplification factor of the user area; Calculating the remaining life of the system area based on the remaining number of erasable times of the system area and the write amplification factor of the system area; Calculating the data writing overhead ratio based on the amount of data written to the system area and the amount of data written to the user area within the unit time; using the runtime DWPD, the remaining life of the user area, the remaining life of the system area, and the data write overhead ratio as reliability evaluation information; The determining, according to the reliability evaluation information, whether the storage device is abnormal includes: If the runtime DWPD is greater than the nominal DWPD, and / or if the product of the remaining life of the user area and the data write overhead ratio is not greater than the remaining life of the system area, determining that the storage device is normal; If the runtime DWPD is not greater than the nominal DWPD, and / or if the product of the remaining life of the user area and the data write overhead ratio is greater than the remaining life of the system area, it is determined that the storage device is abnormal.

7. The method for predicting storage device reliability according to claim 1, characterized in that: The write amplification factor includes a global write amplification factor; The device status information also includes: nominal capacity, power-on usage time, nominal DWPD, the number of times the user area has been erased and written, and the number of times the system area has been erased and written; The step of determining the reliability evaluation information of the storage device based on the device status information includes: Based on the nominal number of erase and write times of the super block, the number of super blocks in the user area, the global write amplification factor, the nominal capacity, and the power-on usage time, the runtime DWPD is calculated; Based on the number of times the user area has been erased and written, the nominal number of times the super block has been erased and written, and the number of super blocks in the user area, the life consumption ratio of the user area is calculated; Based on the number of times the system area has been erased and written, the nominal number of times the super block has been erased and written, and the number of super blocks in the system area, the life consumption ratio of the system area is calculated; The runtime DWPD, the lifetime consumption ratio of the user area, and the lifetime consumption ratio of the system area are used as reliability evaluation information; The determining, according to the reliability evaluation information, whether the storage device is abnormal includes: Determine a life consumption evaluation result based on the life consumption proportion of the user area and the life consumption proportion of the system area; If the runtime DWPD is greater than the nominal DWPD, and / or if the life consumption evaluation result is not less than a preset value, determining that the storage device is normal; If the runtime DWPD is not greater than the nominal DWPD, and / or if the life consumption evaluation result is less than a preset value, it is determined that an abnormality exists in the storage device.

8. The method for predicting the reliability of a storage device according to any one of claims 5 and 7, characterized in that: The determining of the life consumption evaluation result based on the life consumption proportion of the user area and the life consumption proportion of the system area includes: Determine a life consumption evaluation result by using a first formula or a second formula based on the life consumption proportion of the user area and the life consumption proportion of the system area; The first formula includes: Among them, Result LifeConsumed Indicates the evaluation result of life consumption; UserLifeConsumed indicates the proportion of life consumption in the user area; SysLifeConsumed indicates the proportion of life consumption in the system area; MIN{} indicates the minimum value; β is a constant, indicating the boundary value; The second formula includes: Among them,?: represents the conditional operator; Result A ,Result B is a constant with different values; the second formula means that if If true, the life consumption evaluation result is Result A ;like If it is false, the life consumption evaluation result is Result B .

9. A storage device, characterized in that: include: CPU, memory and input / output interface; The memory is a transient storage memory or a persistent storage memory; The central processing unit is configured to communicate with the memory and execute instruction operations in the memory to perform the storage device reliability prediction method according to any one of claims 1 to 8.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the storage device reliability prediction method according to any one of claims 1 to 8 is performed.

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