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

Abstract

Embodiments of the present application disclose a storage device reliability prediction method and device, equipment and a storage medium, which are used for quickly and accurately evaluating the health status of a storage device and improving the reliability of the storage device. The method comprises: obtaining device state information of the storage device; the device state information at least comprises one of the following: a super block nominal erase number, a super block number of a user area in a storage space of the storage device, a super block number of a system area in the storage space of the storage device, and a write 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: a daily whole disk write number DWPD in runtime, a remaining life of the user area, a remaining life of the system area, a life consumption proportion of the user area, and a life consumption proportion of the system area; and determining whether the storage device has an abnormality according to the reliability evaluation information.

Description

Technical Field

[0001] This application relates to the field of storage device technology, and in particular to storage device reliability prediction methods, apparatus, devices and storage media. Background Technology

[0002] With the rapid development of the information age, storage devices have become a crucial component of information systems. The performance and reliability of storage devices directly affect system stability and user experience. Therefore, reliability prediction and lifespan management of storage devices are of great significance, enabling the early identification of potential failure risks and preventing data loss and equipment damage.

[0003] Currently, the health status assessment of storage devices is typically based on the number of write and erase cycles of their non-volatile storage media, and reliability predictions can also be made using machine learning algorithms. However, due to differences in the technological capabilities of different device manufacturers, the predictions obtained by these methods are often not accurate enough, leading to underutilization or overuse of storage devices. Existing technologies still lack comprehensiveness and accuracy in assessing the reliability and lifespan of storage devices. Summary of the Invention

[0004] Based on the above problems, embodiments of this application provide a method, apparatus, device and storage medium for predicting the reliability of storage devices, with the aim of accurately assessing the health status of storage devices and improving the reliability of storage device use.

[0005] In a first aspect, embodiments of this application provide a method for predicting the reliability of storage devices, including:

[0006] Obtain device status information of the storage device; the device status information includes at least one of the following: nominal number of superblock erase / write cycles, number of superblocks in the user area of ​​the storage space of the storage device, number of superblocks in the system area of ​​the storage space of the storage device, and write amplification factor;

[0007] Based on the device status information, the reliability evaluation information of the storage device is determined; the reliability evaluation information includes at least one of the following: drive writes per day (DWPD), remaining lifetime of the user area, remaining lifetime of the system area, lifetime consumption percentage of the user area, and lifetime consumption percentage of the system area.

[0008] Based on the reliability evaluation information, determine whether the storage device is malfunctioning.

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

[0010] Based on the nominal number of erase / write cycles of the superblock, the number of superblocks 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 step of determining whether the storage device is abnormal based on the reliability evaluation information includes:

[0012] If the runtime DWPD is greater than the nominal DWPD, then the storage device is determined to be normal.

[0013] If the runtime DWPD is not greater than the nominal DWPD, then the storage device is determined to be abnormal.

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

[0015]

[0016] Among them, DWPD runtime The runtime DWPD is represented by EPcycle, the nominal number of erase / write cycles for the superblock is represented by PhyUserSblkCnt, the number of superblocks in the user area is represented by WA, the global write amplification factor is represented by DeviceVol, the nominal capacity is represented by usedTime, and the power-on usage time is represented by T. g This indicates the warranty period for 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 further includes: the remaining number of erase / write cycles for the user area, the remaining number of erase / write cycles for 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 per unit time; the reliability evaluation information further 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] The remaining lifetime of the user area is calculated based on the remaining number of erase / write cycles of the user area and the write amplification factor of the user area.

[0020] The remaining lifetime of the system region is calculated based on the remaining erasable / rewrite cycles of the system region and the write amplification factor of the system region.

[0021] 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 within the same unit of time.

[0022] The remaining lifetime of the user area, the remaining lifetime of the system area, and the data write overhead ratio are used as reliability evaluation information.

[0023] The step of determining whether the storage device is abnormal based on the reliability evaluation information includes:

[0024] If the product of the remaining lifetime of the user area and the data write overhead ratio is not greater than the remaining lifetime of the system area, then the storage device is determined to be normal.

[0025] If the product of the remaining lifetime of the user area and the data write overhead ratio is greater than the remaining lifetime of the system area, then the storage device is determined to be faulty.

[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; determining the reliability evaluation information of the storage device based on the device status information includes:

[0027] The lifetime consumption percentage of the user region is calculated based on the number of erase / write cycles of the user region, the nominal number of erase / write cycles of the superblock, and the number of superblocks in the user region.

[0028] Based on the number of erase / write operations of the system region, the nominal number of erase / write operations of the superblock, and the number of superblocks in the system region, calculate the lifetime consumption percentage of the system region;

[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 step of determining whether the storage device is abnormal based on the reliability evaluation information includes:

[0031] The lifetime consumption evaluation result is determined based on the lifetime consumption ratio of the user area and the lifetime consumption ratio of the system area.

[0032] If the lifespan consumption evaluation result is not less than the preset value, then the storage device is determined to be normal;

[0033] If the lifespan consumption evaluation result is less than the preset value, it is determined that the storage device is abnormal.

[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 further includes: nominal capacity, power-on usage time, nominal DWPD, remaining erase / write cycles for the user area, remaining erase / write cycles for the system area, amount of data written to the system area per unit time, and amount of data written to the user area; the reliability evaluation information further includes: data write overhead ratio; determining the reliability evaluation information of the storage device based on the device status information includes:

[0035] The runtime DWPD is calculated based on the nominal number of erase / write cycles of the superblock, the number of superblocks in the user area, the global write amplification factor, the nominal capacity, and the power-on usage time.

[0036] The remaining lifetime of the user area is calculated based on the remaining number of erase / write cycles of the user area and the write amplification factor of the user area.

[0037] The remaining lifetime of the system region is calculated based on the remaining erasable / rewrite cycles of the system region and the write amplification factor of the system region.

[0038] 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.

[0039] The runtime DWPD, the remaining lifetime of the user area, the remaining lifetime of the system area, and the data write overhead ratio are used as reliability evaluation information;

[0040] The step of determining whether the storage device is abnormal based on the reliability evaluation information includes:

[0041] If the runtime DWPD is greater than the nominal DWPD, and / or if the product between the remaining lifetime of the user area and the data write overhead ratio is not greater than the remaining lifetime of the system area, then the storage device is determined to be normal.

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

[0043] In one embodiment, the write amplification factor includes the global write amplification factor; the device status information further includes: nominal capacity, power-on usage time, nominal DWPD, the number of erase / write cycles for the user area, and the number of erase / write cycles for the system area;

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

[0045] The runtime DWPD is calculated based on the nominal number of erase / write cycles of the superblock, the number of superblocks in the user area, the global write amplification factor, the nominal capacity, and the power-on usage time.

[0046] Based on the number of erase / write cycles of the user region, the nominal number of erase / write cycles of the superblock, and the number of superblocks in the user region, the lifetime consumption percentage of the user region is calculated.

[0047] Based on the number of erase / write cycles of the system region, the nominal number of erase / write cycles of the superblock, and the number of superblocks in the system region, the lifetime consumption percentage of the system region 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 step of determining whether the storage device is abnormal based on the reliability evaluation information includes:

[0050] The lifetime consumption evaluation result is determined based on the lifetime consumption ratio of the user area and the lifetime consumption ratio of the system area.

[0051] If the runtime DWPD is greater than the nominal DWPD, and / or if the lifetime consumption evaluation result is not less than a preset value, then the storage device is determined to be normal.

[0052] If the runtime DWPD is not greater than the nominal DWPD, and / or if the lifetime consumption evaluation result is less than a preset value, then it is determined that the storage device is abnormal.

[0053] In one embodiment, determining the lifetime consumption evaluation result based on the lifetime consumption ratio of the user region and the lifetime consumption ratio of the system region includes:

[0054] Based on the lifetime consumption ratio of the user area and the lifetime consumption ratio of the system area, the lifetime consumption evaluation result is determined using the first formula or the second formula.

[0055] The first formula includes:

[0056]

[0057] Among them, Result LifeConsumedThis represents the lifetime consumption evaluation result; UserLifeConsumed represents the lifetime consumption percentage of the user region; SysLifeConsumed represents the lifetime consumption percentage of the system region; MIN{} represents taking the minimum value; β is a constant representing the boundary value;

[0058] The second formula includes:

[0059]

[0060] Where, ?: represents the conditional operator; Result A Result B For different values ​​of constants; the second formula represents if If true, then the lifespan consumption evaluation result is Result. A ;like If the result is false, then the lifespan consumption evaluation result is Result. B .

[0061] Secondly, embodiments of this application also provide a storage device reliability prediction apparatus, comprising:

[0062] The acquisition unit is used to acquire device status information of the storage device; the device status information includes at least one of the following: nominal number of superblock erase / write cycles, number of superblocks in the user area of ​​the storage space of the storage device, number of superblocks in the system area of ​​the storage space of the storage device, and write amplification factor;

[0063] The determining unit is configured to determine the 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, remaining lifetime of the user area, remaining lifetime of the system area, lifetime consumption percentage of the user area, and lifetime consumption percentage 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] Thirdly, embodiments of this application also provide a storage device, including:

[0066] Central processing unit, memory, input / output interfaces;

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

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

[0069] Fourthly, embodiments of this application also provide a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, it performs the storage device reliability prediction method described in any of the above-mentioned embodiments.

[0070] As can be seen from the above technical solutions, the embodiments of this application have the following advantages:

[0071] This application comprehensively analyzes the health status of storage devices by collecting multi-dimensional device status information (such as the nominal number of superblock erase / write cycles and write amplification factor) and combining it with the actual operating status (such as the remaining lifetime / lifetime consumption ratio of user area or system area). Compared with a single reliability indicator, the embodiments of this application can more accurately reflect the actual usage status of storage devices, achieving accurate assessment of the health status of storage devices. It has the advantages of strong real-time performance, high adaptability, and fine-grained lifetime management, which can effectively improve the security, reliability, and usage efficiency of storage devices and reduce the possibility of data loss. Attached Figure Description

[0072] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0073] Figure 1 This is a schematic flowchart of a storage device reliability prediction method provided in an embodiment of this application;

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

[0075] Figure 3 This is a schematic diagram of a storage device structure provided in an embodiment of this application. Detailed Implementation

[0076] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0077] With the rapid development of the information age, storage devices have become a crucial component of information systems. The performance and reliability of storage devices directly affect system stability and user experience. Therefore, reliability prediction and lifespan management of storage devices are of great significance, enabling the early identification of potential failure risks and preventing data loss and equipment damage.

[0078] Currently, the health status assessment of storage devices is typically based on the number of write and erase cycles of their non-volatile storage media, and reliability predictions can also be made using machine learning algorithms. However, due to differences in the technological capabilities of different device manufacturers, the predictions obtained by these methods are often not accurate enough, leading to underutilization or overuse of storage devices. Existing technologies still lack comprehensiveness and accuracy in assessing the reliability and lifespan of storage devices.

[0079] Based on this, in the various embodiments of this application, multi-dimensional device status information is collected and combined with the actual running status of the storage device to comprehensively analyze the health status of the device.

[0080] The various embodiments of this application will now be described in further detail with reference to the accompanying drawings.

[0081] This application provides a method for predicting the reliability of storage devices, such as... Figure 1 As shown, the method includes steps S101-S103.

[0082] S101: Obtain the device status information of the storage device.

[0083] Device status information for storage devices can typically be collected from the storage device through systems or management tools. This information is primarily used to monitor the device's operational status, health condition, and lifespan. Device status information includes, but is not limited to, the following: nominal superblock write / erase count, the number of superblocks in the user area of ​​the storage device's storage space, the number of superblocks in the system area of ​​the user area of ​​the storage device's storage space, and write amplification factor. This device status information can be used individually or in combination, depending on monitoring needs and device conditions, to determine whether to collect all or part of the information, in order to achieve efficient health status assessment and lifespan prediction.

[0084] It's important to understand that a superblock (SBLK) is a logical unit composed of selected physical blocks from different NAND flash dies. For example, SBLK0 can consist of 128 dies with the same physical block identifier (such as Block0 of each die).

[0085] Write amplification is the ratio of the amount of data actually written to 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 erases data in blocks, but can only write data in pages. When some data pages fail (marked as invalid pages), valid pages still need to be migrated to new blocks before erasing the old blocks, which leads to additional write operations. (2) Write alignment issues: If the size of the data written by the user is not aligned with the physical size of the flash page or block (e.g., the user writes 4KB, while the flash page size is 8KB), it will lead to reduced write efficiency and exacerbate the write amplification effect. By monitoring the write amplification factor, the actual write load of the device can be quantified, the rationality of the data management strategy can be analyzed, and the device performance can be optimized.

[0086] The superblock's nominal write / erase cycles represent the physical write / erase lifespan limit of NAND flash memory chips. By comparing the actual write / erase cycles with the nominal cycles, the remaining lifespan of the device can be assessed. When the write / erase cycles approach the nominal value, the device is prone to data errors or malfunctions.

[0087] S102: Based on the device status information, determine the reliability evaluation information of the storage device; the reliability evaluation information shall include at least one of the following: daily disk writes (DWPD) during runtime, remaining lifetime of the user area, remaining lifetime of the system area, lifetime consumption percentage of the user area, and lifetime consumption percentage of the system area.

[0088] DWPD indicates the number of times a user can fill up an SSD per day within its warranty period. The DWPD can be calculated using the following formula: DWPD = TBW ÷ Warranty Days, where TBW (Total Bytes Written) is the total number of bytes an SSD can write during its lifetime. For example, a 300TB TBW SSD with a 10-year warranty, using the formula "DWPD = TBW ÷ Warranty Days," has a DWPD of approximately 84.16GB. This means that if 84.16GB of data is written daily, the SSD will begin to show signs of wear.

[0089] The UserZone is a portion of the storage space on a storage device specifically allocated for storing user data, while the SysZone is used to store metadata, management information, and perform garbage collection operations. The remaining lifetime of a user or system zone refers to the unused portion of its physical rewritable lifespan. Lifespan attrition percentage refers to the proportion of lifetime already consumed in each zone relative to its total lifetime.

[0090] Based on metrics such as runtime DWPD, remaining lifetime, and lifetime consumption percentage, it is possible to determine whether the storage device is overloaded and the write pressure on the user area and system area of ​​the storage device, thus preventing premature failure of local areas.

[0091] S103: Based on the reliability evaluation information, determine whether there is any abnormality in the storage device.

[0092] Reliability assessment information is derived from analyzing device status information. When determining whether a storage device is experiencing anomalies, reliability assessment information (such as DWPD, remaining lifetime, and lifetime attrition percentage) can be compared with the storage device's design specifications or preset thresholds. For example, if the runtime DWPD > nominal DWPD, it indicates that the device is overloaded; if the remaining lifetime < critical threshold, it means the device's lifespan is about to end, requiring backup or replacement; if the lifetime attrition percentage in the user area is much higher than in the system area, it is necessary to consider whether there is an uneven data distribution and optimize the write strategy.

[0093] This application comprehensively analyzes device reliability by collecting multi-dimensional device status information (such as the nominal number of erase / write cycles of the superblock and the write amplification factor) and combining it with the actual operating status (such as the remaining lifetime / lifetime consumption ratio of the user area or system area). Compared with a single evaluation indicator, the embodiments of this application can more accurately reflect the real usage status of the storage device, realize accurate assessment of the health status of the storage device, and have the advantages of strong real-time performance, high adaptability, and fine-grained lifetime management. It can effectively improve the security, reliability, and usage 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, various 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 from different perspectives and evaluation methods. The following explains several different combination methods, each of which has a slightly different evaluation logic for storage devices.

[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 usage time, and nominal DWPD;

[0096] Based on device status information, determine the reliability evaluation information of the storage device, including: calculating the runtime DWPD based on the nominal number of superblock erase / write cycles, the number of superblocks in the user area, the global write amplification factor, the nominal capacity, and the power-on usage time, and using it as the reliability evaluation information of the storage device.

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

[0098]

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

[0100]

[0101] Among them, DWPD runtime The runtime write amplification factor (DWPD) is represented by: EPcycle, representing the nominal write / erase cycle count of a superblock, indicating the upper limit of the physical write / erase lifetime for each superblock; PhyUserSblkCnt, representing the number of superblocks in the user area, indicating the number of available storage blocks for the user; WA, representing the global write amplification factor; DeviceVol, representing the nominal capacity, indicating the physical storage capacity of the storage device; usedTime, representing the power-on usage time, indicating the time the storage device has been in use; T... g The warranty period for storage devices refers to the designed lifespan of the storage device, for example, expressed in days, such as a 5-year warranty. g It can be represented as 365*5.

[0102] The following explains the specific meaning of some parameters in the above formula.

[0103] (1) EPcycle (Program / Erase Cycle): The nominal number of write / erase cycles for the superblock in UserZone and SysZone. Each time the entire SSD is programmed (i.e., written) or erased, one P / E cycle is counted. When writing data, the controller program automatically writes data evenly to all NAND chips to achieve wear leveling.

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

[0105]

[0106] Here, OP stands for Over-Provisioning, which is the proportion of unallocated storage space reserved by the device to the total storage space. OP is usually expressed as a decimal. For example, if the total storage space of the device is 1TB, and 10% (100GB) is used for over-provisioning, then OP = 0.1. As for the constant α: it can be understood that even if there is no significant over-provisioning space within 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 some write amplification. Therefore, the constant α can be understood as the baseline value of write amplification in flash memory.

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

[0108]

[0109] PhyVol represents the actual physical available capacity. PhyVol = Nominal capacity (DeviceVol) + Reserved space. The reserved space is determined by the manufacturer's strategy; typically, equipment manufacturers will add an extra 5%-30% of physical capacity for operation (OP).

[0110] Runtime Write Load Rate (DWPD) is a core metric for measuring the current write load of a device. By comparing the calculated runtime DWPD with the device's nominal DWPD, it can be determined whether the storage device is operating normally: if the runtime DWPD is greater than the nominal DWPD, it indicates that the device's current write load is within the design range and it can work normally, confirming that the storage device is functioning correctly; if the runtime DWPD is not greater than the nominal DWPD, it indicates that the storage device has an abnormal write load, which may pose a risk of performance degradation or shortened lifespan, requiring further testing or maintenance.

[0111] Method 1 uses device status information (such as the nominal number of superblock erase / write cycles, the number of superblocks in the user area, the global write amplification factor, etc.) combined with the actual usage time to calculate the runtime DWPD, which enables rapid detection of the storage device's operating load.

[0112] Method 2: In this method, 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 number of erase / write cycles for the user area, the remaining number of erase / write cycles for 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 per unit time; the reliability evaluation information also includes: the data write overhead ratio;

[0113] Based on device status information, determine the reliability evaluation information of the storage device, including: calculating the remaining lifetime of the user area based on the remaining erase / write cycles and the write amplification factor of the user area.

[0114]

[0115] UserZone Lifetime represents the remaining lifespan of the user's zone; RemainEP represents the total number of superblocks in the user region; user Indicates the remaining erase / write cycles for each superblock in the user region; WA user Indicates the magnification factor for the user area;

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

[0117]

[0118] The amount of data written by the user represents the actual amount of data requested for writing by the user. By comparing the amount of data requested for writing by the user with the actual amount of data written, the writing efficiency of user data is quantified. The higher the write amplification factor of the user area, the more additional write operations are performed inside the device, which will reduce the remaining lifespan of the user area.

[0119] Calculate the remaining lifetime of the system region based on the remaining erasable / rewrite cycles and the write amplification factor of the system region:

[0120]

[0121] SysZone Lifetime represents the remaining lifespan of the system zone; RemainEP represents the total number of superblocks in the system region; sys Indicates the remaining erase / write cycles for each superblock in the system region; WA Sys The amplification factor is written to indicate the system region.

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

[0123]

[0124] The amount of data written to the system refers to the amount of write requests generated by system management operations (such as garbage collection). A higher system area write amplification factor indicates more additional write operations within the device, which reduces the remaining lifespan of the system area.

[0125] Calculate the data write overhead ratio 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:

[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; and 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 high, it indicates that system operations are generating a large amount of extra writes, and the write strategy may need to be optimized.

[0129] The remaining lifetime of the user zone, the remaining lifetime of the system zone, and the data write overhead ratio are used as reliability evaluation information. Based on the above reliability evaluation information, it is determined whether the storage device is abnormal, including: if the product of the remaining lifetime of the user zone and the data write overhead ratio is not greater than the remaining lifetime of the system zone, i.e., UserZone LifetimeCreateSysWriteRate≤SysZone Lifetime, then the storage device is determined to be normal; if the product of the remaining lifetime of the user zone and the data write overhead ratio is greater than the remaining lifetime of the system zone, i.e., UserZone Lifetime*CreateSysWriteRate>SysZone Lifetime, then the storage device is determined to be abnormal.

[0130] Method two, by distinguishing between the remaining lifetime of the user area and the system area, enables independent analysis of different functional areas of the storage device, providing a more granular health assessment than a single metric. Furthermore, combining the remaining lifetime of the user area, the remaining lifetime of the system area, and data write overhead not only assesses the remaining lifetime of the storage device but also identifies potential load balancing issues, improving 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 written, and the number of times the system area has been erased and written;

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

[0133] Calculate the percentage of user region lifetime consumed based on the number of erase / write cycles in the user region, the nominal number of erase / write cycles in the superblock, and the number of superblocks in the user region:

[0134]

[0135] Wherein, UserLifeConsumed represents the percentage of lifespan consumed in the user's region; UserSblkUsedEC represents the sum of erase / write cycles consumed across all superblocks in the user region. i 1 represents the number of times superblock i in the user region has been erased and written; EPcycle represents the nominal number of times the superblock has been erased and written; PhyUserSblkCnt represents the total number of superblocks in the user region.

[0136] Based on the number of erase / write cycles of the system region, the nominal number of erase / write cycles of the superblock, and the number of superblocks in the system region, calculate the percentage of lifetime consumption of the system region:

[0137]

[0138] Among them, SysLifeConsumed represents the percentage of lifespan consumed in the system area; This represents the sum of erase / write cycles consumed by all superblocks in the system region; SysSblkUsedEC i 1 represents the number of times superblock i in the system region has been erased and written; EPcycle represents the nominal number of times the superblock has been erased and written; PhySysSblkCnt represents the total number of superblocks in the system region.

[0139] The lifetime attrition rate of the user area and the lifetime attrition rate of the system area are used as reliability evaluation information, and based on the above reliability evaluation information, it is determined whether there are any anomalies in the storage device:

[0140] First, the lifetime consumption evaluation results are determined based on the lifetime consumption ratio of the user region and the lifetime consumption ratio of the system region.

[0141] In one possible implementation, the lifetime consumption assessment result is calculated using the following formula:

[0142]

[0143] Among them, Result LifeConsumed This represents the lifetime consumption evaluation result; UserLifeConsumed represents the lifetime consumption percentage of the user area; SysLifeConsumed represents the lifetime consumption percentage of the system area; MIN{} indicates taking the minimum value; β represents the boundary value. In practical applications, β can be 0.01, indicating that a 1% difference is allowed, meaning that the lifetime consumption percentage of the system area is allowed to be at most 1% higher than the lifetime consumption percentage of the user area. This lifetime consumption evaluation result indicates that if the lifetime consumption rate of the system area is faster than that of the user area, it suggests that the flash memory device may be malfunctioning.

[0144] In another possible implementation, the lifetime consumption assessment result is obtained using a ternary operator and calculated through the following formula:

[0145]

[0146] In the formula above, ? represents the ternary operator, also known as the conditional operator, which is an operator with three operands. For example, in A? B:C, A? is the condition, B is the operation where condition A is true, and C is the operation where condition A is false. Therefore, in calculating Result... LifeConsumed At that time, it can be determined Is it true or false? If true, then the lifespan assessment result is Result. A If false, the lifespan consumption assessment result is Result. B Here, Result AResult can be 1. B Depending on the actual application scenario and project requirements, a constant less than 1 can be used, such as 0.3.

[0147] After obtaining the lifetime consumption evaluation results, they can be compared with preset values ​​to determine whether the storage device is abnormal: if the lifetime consumption evaluation result is not less than the preset value, the storage device is determined to be normal; if the lifetime 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: This method can be seen as a combination of obtaining reliability evaluation information using methods 1 and 2, and using that information to determine 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; device status information also includes: nominal capacity, power-on usage time, nominal DWPD, remaining erase / write cycles for the user area, remaining erase / write cycles for 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; reliability evaluation information also includes: data write overhead ratio.

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

[0150] The runtime DWPD is calculated based on the nominal number of superblock erase / write cycles, the number of superblocks in the user area, the global write amplification factor, the nominal capacity, and the power-on usage time. The remaining lifetime of the user area is calculated based on the remaining number of erase / write cycles and the write amplification factor of the user area. The remaining lifetime of the system area is calculated based on the remaining number of erase / write cycles 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] For details on how to calculate the runtime DWPD, please refer to the relevant description in Method 1. For details on how to calculate the remaining lifetime of the user area, the remaining lifetime of the system area, and the data write overhead ratio, please refer to the relevant description in Method 2. These details will not be repeated here.

[0152] The runtime DWPD, remaining lifetime of the user area, remaining lifetime of the system area, and data write overhead ratio are used as reliability evaluation information; and based on the above reliability evaluation information, it is determined whether the storage device has any anomalies, including:

[0153] If the runtime DWPD is greater than the nominal DWPD, and / or if the product between the remaining lifetime of the user area and the data write overhead ratio is not greater than the remaining lifetime of the system area, then the storage device is considered to be functioning normally.

[0154] If the runtime DWPD is not greater than the nominal DWPD, and / or if the product between the remaining lifetime of the user area and the data write overhead ratio is greater than the remaining lifetime of the system area, then the storage device is determined to be faulty.

[0155] For example, it can be based on runtime DWPD (i.e., DWPD) runtime ) and nominal DWPD (i.e. DWPD) spec Substituting into the following formula, we get Result1:

[0156]

[0157] Substituting the remaining lifespan of the system zone (SysZone Lifetime) and the remaining lifespan of the user zone (UserZone Lifetime) into the following formula yields Result2:

[0158]

[0159] Based on Result1 and Result2 obtained above, we obtain Result3:

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

[0161] Result3 combines Result1 and Result2. If either result indicates an anomaly (i.e., Result1 < 1 or Result2 < 1), then Result3 = 0, indicating that there is an anomaly in the storage device.

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

[0163] Method 5: This method can be considered a combination of obtaining reliability evaluation information using methods 1 and 3, and using that information to determine the health status of the storage device. In Method 5, the write amplification factor includes the global write amplification factor; device status information also includes: nominal capacity, power-on usage time, nominal DWPD, erase / write cycles for the user area, and erase / write cycles for the system area.

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

[0165] The runtime DWPD is calculated based on the nominal number of erase / write cycles of the superblock, the number of superblocks in the user area, the global write amplification factor, the nominal capacity, and the power-on usage time. The lifetime consumption percentage of the user area is calculated based on the number of erase / write cycles of the user area, the nominal number of erase / write cycles of the superblock, and the number of superblocks in the user area. The lifetime consumption percentage of the system area is calculated based on the number of erase / write cycles of the system area, the nominal number of erase / write cycles of the superblock, and the number of superblocks in the system area.

[0166] The specific methods for calculating the runtime DWPD mentioned above can be found in the relevant description in Method 1. The specific methods for calculating the lifetime consumption ratio of the user area, the lifetime consumption ratio of the system area, and the subsequent calculation of lifetime consumption evaluation results can be found in the relevant description in Method 3. They will not be repeated here.

[0167] The runtime DWPD, user area lifetime consumption percentage, and system area lifetime consumption percentage are used as reliability evaluation information; based on the above reliability evaluation information, it is determined whether the storage device has any anomalies, including:

[0168] The lifetime consumption evaluation results are determined based on the lifetime consumption ratio of the user region and the lifetime consumption ratio of the system region.

[0169] If the DWPD during operation is greater than the nominal DWPD, and / or if the lifetime consumption evaluation result is not less than the preset value, then the storage device is determined to be normal.

[0170] If the runtime DWPD is not greater than the nominal DWPD, and / or if the lifetime consumption evaluation result is less than the preset value, then the storage device is determined to be abnormal. In practical applications, the preset value can be 1.

[0171] For example, it can be based on runtime DWPD (i.e., DWPD) runtime ) and nominal DWPD (i.e. DWPD) spec Substituting into the following formula, we get Result1:

[0172]

[0173] Substituting the system region's lifetime consumption percentage (i.e., SysLifeConsumed) and the user region's lifetime consumption percentage (i.e., UserLifeConsumed) into any of the following formulas yields Result2:

[0174]

[0175] or

[0176]

[0177] Based on Result1 and Result2 obtained above, we obtain Result3:

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

[0179] Result3 combines Result1 and Result2. If either result indicates an anomaly (i.e., Result1 < 1 or Result2 < 1), then Result3 = 0, indicating that there is an anomaly in the storage device.

[0180] The embodiments of this application provide methods one through five, which, through joint analysis of various device status parameters, can accurately identify potential problems in storage devices and improve the accuracy of reliability prediction for storage devices. After identifying an anomaly in a storage device, the final determined storage device status can be reported promptly, and corresponding maintenance measures can be taken based on the reliability evaluation information obtained through different methods, reducing the possibility of data loss and device failure.

[0181] To implement the storage device reliability prediction method of this application embodiment, this application embodiment also provides a storage device reliability prediction apparatus, such as... Figure 2 As shown, the device includes:

[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: nominal number of superblock erase / write cycles, number of superblocks in the user area of ​​the storage space of the storage device, number of superblocks in the system area of ​​the storage space of the storage device, and write amplification factor;

[0183] The determining unit 202 is used to determine the reliability evaluation information of the storage device based on the device status information; the reliability evaluation information includes at least one of the following: daily disk writes (DWPD) during operation, remaining lifetime of the user area, remaining lifetime of the system area, lifetime consumption percentage of the user area, and lifetime consumption percentage of the system area.

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

[0185] In one embodiment, the device further includes: a processing unit; the processing unit is configured to calculate the runtime DWPD based on the nominal number of superblock erase / write cycles, the number of superblocks in the user area, the global write amplification factor, the nominal capacity, and the power-on usage time, and use it as reliability evaluation information for 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 the storage device is abnormal if the runtime DWPD is not greater than the nominal DWPD.

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

[0189]

[0190] Among them, DWPD runtime The runtime DWPD is represented by EPcycle, the nominal number of erase / write cycles for the superblock is represented by PhyUserSblkCnt, the number of superblocks in the user area is represented by WA, the global write amplification factor is represented by DeviceVol, the nominal capacity is represented by usedTime, and the power-on usage time is represented by T. g This indicates the warranty period for the storage device.

[0191] The processing unit is further configured to, in one embodiment, calculate the remaining lifetime of the user region based on the remaining erasable / rewrite cycles of the user region and the write amplification factor of the user region;

[0192] The processing unit is further configured to calculate the remaining lifetime of the system region based on the remaining erasable / rewrite cycles of the system region and the write amplification factor of the system region;

[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 lifetime of the user area, the remaining lifetime 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 between the remaining lifetime of the user area and the data write overhead ratio is not greater than the remaining lifetime of the system area;

[0196] The determining unit 202 is further configured to determine that the storage device is abnormal if the product between the remaining lifetime of the user area and the data write overhead ratio is greater than the remaining lifetime of the system area.

[0197] In one embodiment, the processing unit is further configured to calculate the lifetime consumption percentage of the user region based on the number of times the user region has been erased and written, the nominal number of times the superblock has been erased and written, and the number of superblocks in the user region;

[0198] The processing unit is also used to calculate the lifetime consumption percentage of the system region based on the number of times the system region has been erased and written, the nominal number of times the superblock has been erased and written, and the number of superblocks in the system region;

[0199] The processing unit is also used to use the lifetime consumption ratio of the user area and the lifetime consumption ratio of the system area as reliability evaluation information.

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

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

[0202] The determining unit 202 is further configured to determine that the storage device is abnormal if the lifetime consumption evaluation result is less than a preset value.

[0203] In one embodiment, the runtime DWPD is calculated based on the nominal number of erase / write cycles of the superblock, the number of superblocks in the user area, the global write amplification factor, the nominal capacity size, and the power-on usage duration.

[0204] The processing unit is further configured to calculate the remaining lifetime of the user region based on the remaining erasable / rewrite cycles of the user region and the write amplification factor of the user region;

[0205] The processing unit is further configured to calculate the remaining lifetime of the system region based on the remaining erasable / rewrite cycles of the system region and the write amplification factor of the system region;

[0206] The processing unit is also used 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 lifetime of the user area, the remaining lifetime 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 between the remaining lifetime of the user area and the data write overhead ratio is not greater than the remaining lifetime of the system area;

[0209] The determining unit 202 is further configured to determine that the storage device is abnormal if the runtime DWPD is not greater than the nominal DWPD, and / or if the product between the remaining lifetime of the user area and the data write overhead ratio is greater than the remaining lifetime of the system area.

[0210] In one embodiment, the processing unit is further configured to calculate the runtime DWPD based on the nominal number of erase / write cycles of the superblock, the number of superblocks in the user area, the global write amplification factor, the nominal capacity size, and the power-on usage duration;

[0211] The processing unit is also used to calculate the lifetime consumption percentage of the user region based on the number of times the user region has been erased and written, the nominal number of times the superblock has been erased and written, and the number of superblocks in the user region.

[0212] The processing unit is also used to calculate the lifetime consumption percentage of the system region based on the number of times the system region has been erased and written, the nominal number of times the superblock has been erased and written, and the number of superblocks in the system region.

[0213] The processing unit is also used to use the runtime DWPD, the lifetime consumption ratio of the user area, and the lifetime consumption ratio of the system area as reliability evaluation information.

[0214] The determining unit 202 is further configured to determine the lifetime consumption evaluation result based on the lifetime consumption ratio of the user area and the lifetime consumption ratio 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 lifetime consumption evaluation result is not less than a preset value;

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

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

[0218] The first formula includes:

[0219]

[0220] Among them, Result LifeConsumed This represents the lifetime consumption evaluation result; UserLifeConsumed represents the lifetime consumption percentage of the user region; SysLifeConsumed represents the lifetime consumption percentage of the system region; MIN{} represents taking the minimum value; β is a constant representing the boundary value;

[0221] The second formula includes:

[0222]

[0223] Where, ?: represents the conditional operator; Result A Result B For different values ​​of constants; the second formula represents if If true, then the lifespan consumption evaluation result is Result. A ;like If the result is false, then the lifespan consumption evaluation result is Result. B .

[0224] In practical applications, the processing unit can be implemented by the processor in the storage device combined with the communication interface, and the acquisition unit 201 and the determination unit 202 can be implemented by the communication interface in the storage device reliability prediction device.

[0225] It should be noted that the storage device reliability prediction device provided in the above embodiments is only illustrated by the division of the above-described program modules. In practical applications, the above processing can be assigned to different program modules as needed, that is, the internal structure of the device can be divided into different program modules to complete all or part of the processing described above. In addition, the storage device reliability prediction device and the storage device reliability prediction method embodiments provided in the above embodiments belong to the same concept, and their specific implementation process can be found in the method embodiments, which will not be repeated here.

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

[0227] Central processing unit 301, memory 302, and input / output interface 303;

[0228] The memory 302 is a short-term storage memory or a persistent storage memory;

[0229] The central processing unit 301 is configured to communicate with the memory 302 and execute instructions in the memory 302 to perform any of the above-described storage device reliability prediction methods.

[0230] Of course, in practical applications, the various components in the storage device 300 are coupled together through a bus system 304. It is understood that the bus system 304 is used to realize communication between these components. In addition to a data bus, the bus system 304 also includes a power bus, a control bus, and a status signal bus. However, for clarity, in... Figure 3 The general designated all buses as Bus System 304.

[0231] The memory 302 in this embodiment 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 understood that when the processor in the storage device 300 described above executes the computer program, it can also implement the functions of each unit 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 a memory, and executed by the processor to complete the various embodiments of this application. One or more modules / units can be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program in the storage device 300. For example, the computer program can be divided into units in the storage device 300 described above, and each unit can implement the specific functions described in the corresponding storage device 300 above.

[0233] Storage device 300 may include, but is not limited to, processors and memory. Those skilled in the art will understand that processors and memory are merely examples of storage device 300 and do not constitute a limitation on storage device 300. It may include more or fewer components, or combinations of certain components, or different components, such as error correction modules (ECC), interface controllers (such as SATA, NVMe, PCIe interfaces), etc.

[0234] The processor can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor. The processor is the control center of the storage device 300, connecting all parts of the storage device 300 via various interfaces and lines.

[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 by accessing data stored in the memory. The memory may mainly include a program storage area and a data storage area. The program storage area may store the operating system, applications required for at least one function, etc.; the data storage area may store data created according to the use of the terminal, etc. In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as small-capacity non-volatile memory (such as NOR flash memory).

[0236] This application also provides a computer-readable storage medium storing a computer program thereon, wherein when the computer program is executed by a processor, it performs any of the above-described storage device reliability prediction methods.

[0237] This application also provides a computer program product storing a computer program / instruction, which, when executed by a processor, is used to implement the storage device reliability prediction method described in the first aspect or any specific implementation of the first aspect of this application.

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

[0239] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection between apparatuses or units through some interfaces, and may be electrical, mechanical, or other forms.

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

[0241] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0242] If the integrated unit is implemented as 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 this application, in essence, 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. This computer software product is stored in a storage medium and includes several instructions to cause a storage device to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

Claims

1. A storage device reliability prediction method characterized by comprising: The method comprises: obtaining device state information of a storage device; the device state information at least comprises one of the following: superblock nominal erase times, the number of superblocks of a user area in the storage space of the storage device, the number of superblocks of a system area in the storage space of the storage device, a write amplification coefficient; based on the device state information, determining the reliability evaluation information of the storage device; the determination method of the reliability evaluation information at least comprises one of the following: calculating the runtime daily whole-disk write times DWPD and determining it as the reliability evaluation information of the storage device; calculating the remaining life of the user area, the remaining life of the system area, and the data write overhead ratio and determining them as the reliability evaluation information of the storage device; calculating the life consumption proportion of the user area, the life consumption proportion of the system area and determining them as the reliability evaluation information of the storage device; determining whether the storage device has an abnormality according to the reliability evaluation information.

2. The storage device reliability prediction method of claim 1, wherein The write amplification coefficient comprises a global write amplification coefficient; The device state information further comprises: nominal capacity size, power-on use duration, nominal DWPD; the determination of the reliability evaluation information of the storage device based on the device state information comprises: based on the superblock nominal erase times, the number of superblocks of the user area, the global write amplification coefficient, the nominal capacity size, and the power-on use duration, the runtime DWPD is calculated and used as the reliability evaluation information of the storage device; The determination of whether the storage device has an abnormality according to the reliability evaluation information comprises: if the runtime DWPD is greater than the nominal DWPD, it is determined that the storage device is normal; if the runtime DWPD is not greater than the nominal DWPD, it is determined that the storage device has an abnormality.

3. The storage device reliability prediction method of claim 2, wherein The runtime DWPD is calculated by the following formula: wherein, characterizing a runtime DWPD, characterizing a nominal erase count of the superblock, characterizing a number of superblocks of the user area, characterizing a global write amplification factor, characterizing a nominal capacity size, characterizing a power-on usage duration, characterizing a warranty period of the storage device.

4. The storage device reliability prediction method of claim 1, wherein, The write amplification coefficient comprises a user area write amplification coefficient and a system area write amplification coefficient; the device state information further comprises: the remaining erasable times of the user area, the remaining erasable times of the system area, the write data amount of the system area per unit time, and the write data amount of the user area per unit time; The determination of the reliability evaluation information of the storage device based on the device state information comprises: based on the remaining erasable times of the user area and the user area write amplification coefficient, the remaining life of the user area is calculated; based on the remaining erasable times of the system area and the system area write amplification coefficient, the remaining life of the system area is calculated; based on the write data amount of the system area per unit time and the write data amount of the user area per unit time, the data write overhead ratio is calculated; the remaining life of the user area, the remaining life of the system area, and the data write overhead ratio are used as the reliability evaluation information; The determination of whether the storage device has an abnormality according to the reliability evaluation information comprises: determining that the storage device is normal if a 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 abnormal 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.

5. The storage device reliability prediction method of claim 1, wherein, The device state information further comprises: the number of erasures of the user area, the number of erasures of the system area; and the reliability evaluation information of the storage device is determined based on the device state information, comprising: calculating a life consumption proportion of the user area based on the number of erasures of the user area, the nominal number of erasures of the super block, and the number of super blocks of the user area; calculating a life consumption proportion of the system area based on the number of erasures of the system area, the nominal number of erasures of the super block, and the number of super blocks of the system area; taking the life consumption proportion of the user area and the life consumption proportion of the system area as the reliability evaluation information; the determination of whether the storage device is abnormal based on the reliability evaluation information comprises: determining a life consumption evaluation result based on the life consumption proportion of the user area and the life consumption proportion of the system area; determining that the storage device is normal if the life consumption evaluation result is not less than a preset value; determining that the storage device is abnormal if the life consumption evaluation result is less than the preset value.

6. The storage device reliability prediction method of claim 1, wherein, The write amplification coefficient comprises a global write amplification coefficient, a user area write amplification coefficient, and a system area write amplification coefficient; The device state information further comprises: a nominal capacity size, a power-on use duration, a nominal DWPD, a remaining erasable number of times of the user area, a remaining erasable number of times of the system area, a write data amount of the system area per unit time, and a write data amount of the user area; and the reliability evaluation information of the storage device is determined based on the device state information, comprising: calculating a runtime DWPD based on the nominal number of erasures of the super block, the number of super blocks of the user area, the global write amplification coefficient, the nominal capacity size, and the power-on use duration; calculating a remaining life of the user area based on the remaining erasable number of times of the user area and the user area write amplification coefficient; calculating a remaining life of the system area based on the remaining erasable number of times of the system area and the system area write amplification coefficient; calculating a data write overhead ratio based on the write data amount of the system area per unit time and the write data amount of the user area; taking the runtime DWPD, the remaining life of the user area, the remaining life of the system area, and the data write overhead ratio as the reliability evaluation information; the determination of whether the storage device is abnormal based on the reliability evaluation information comprises: determining that the storage device is normal if the runtime DWPD is greater than the nominal DWPD and / or if a 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; If the runtime DWPD is not greater than the nominal DWPD, and / or if a product of a remaining lifetime of the user area and a data write overhead ratio is greater than a remaining lifetime of the system area, it is determined that the storage device is abnormal.

7. The storage device reliability prediction method of claim 1, wherein The write amplification factor comprises a global write amplification factor; The device state information further comprises: a nominal capacity size, a power-on use duration, a nominal DWPD, a number of erase-write times of the user area, and a number of erase-write times of the system area; The method further comprises: The runtime DWPD is calculated based on the superblock nominal erase-write times, the number of superblocks of the user area, the global write amplification factor, the nominal capacity size, and the power-on use duration; The lifetime consumption proportion of the user area is calculated based on the number of erase-write times of the user area, the superblock nominal erase-write times, and the number of superblocks of the user area; The lifetime consumption proportion of the system area is calculated based on the number of erase-write times of the system area, the superblock nominal erase-write times, and the number of superblocks of the system area; The runtime DWPD, the lifetime consumption proportion of the user area, and the lifetime consumption proportion of the system area are taken as the reliability evaluation information; The method further comprises: The lifetime consumption evaluation result is determined based on the lifetime consumption proportion of the user area and the lifetime consumption proportion of the system area; If the runtime DWPD is greater than the nominal DWPD, and / or if the lifetime consumption evaluation result is not less than a preset value, it is determined that the storage device is normal. If the runtime DWPD is not greater than the nominal DWPD, and / or if the lifetime consumption evaluation result is less than a preset value, it is determined that the storage device is abnormal.

8. The storage device reliability prediction method according to any one of claims 5 and 7, characterized by, The lifetime consumption evaluation result is determined based on the lifetime consumption proportion of the user area and the lifetime consumption proportion of the system area, comprising: The lifetime consumption evaluation result is determined based on the lifetime consumption proportion of the user area and the lifetime consumption proportion of the system area by using a first formula or a second formula; The first formula comprises: wherein, represents a life consumption evaluation result; represents a life consumption ratio of a user area; represents a life consumption ratio of a system area; represents taking a minimum value; is a constant, and represents a boundary value; The second formula comprises: wherein? : denotes a conditional operator; , are constants for different values; the second formula indicates that if is true, the life consumption evaluation result is ; if is false, the life consumption evaluation result is .

9. A storage device, comprising: comprises: A central processing unit, a memory, and an input-output interface; The memory is a transitory 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 in any one of claims 1 to 8.

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

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