阅读说明：本技术 一种磁盘设备寿命预测方法及装置 (A kind of disk unit life-span prediction method and device ) 是由 张振广 苏楠 李辉 于 2019-08-23 设计创作，主要内容包括：本发明提供一种磁盘设备寿命预测方法及装置,该方法包括：基于待测磁盘设备中的N个SMART特征值在预设时间阈值内的变异系数进行计算,得到待测特征值；分别计算待测特征值分别与M个预设的训练样本值的权重,并构建权重矩阵；基于权重矩阵进行线性回归计算,得到回归系数；基于回归系数,确定待测特征值对应的待测磁盘设备的寿命状态。在本发明中,通过确定待测特征值对应的回归系数,能够确定待测磁盘设备的寿命状态,从而提高存储系统的安全性及可靠性较低。(The present invention is provided a kind of disk unit life-span prediction method and device and obtains characteristic value to be measured this method comprises: being calculated based on the coefficient of variation of N number of SMART characteristic value in preset time threshold in disk unit to be measured；Weight of the characteristic value to be measured respectively with M preset training sample values is calculated separately, and constructs weight matrix；Linear regression calculating is carried out based on weight matrix, obtains regression coefficient；Based on regression coefficient, the service life state of the corresponding disk unit to be measured of characteristic value to be measured is determined.In the present invention, by the corresponding regression coefficient of determination characteristic value to be measured, can determine the service life state of disk unit to be measured, thus improve storage system safety and reliability it is lower.)

1. a kind of disk unit life-span prediction method, which is characterized in that the described method includes:

It is calculated, is obtained based on the coefficient of variation of N number of SMART characteristic value in preset time threshold in disk unit to be measured Characteristic value to be measured, wherein N is the integer more than or equal to 1；

The weight of the characteristic value to be measured and M preset training sample values is calculated separately, and constructs weight matrix, the training Sample value includes the characteristic value of the disk unit of preset quantity, and M is the integer more than or equal to 1；

Linear regression calculating is carried out based on the weight matrix, obtains regression coefficient；

Based on the regression coefficient, the service life state of the corresponding disk unit to be measured of the characteristic value to be measured is determined.

2. the method according to claim 1, wherein the default process of the training sample value includes:

Obtain the SMART characteristic value of training disk unit record；

The n SMART characteristic values high with default life characteristic data correlation are selected, the N is used to indicate preset want The number of the SMART characteristic value of selection, n are the integer more than or equal to 1；

The coefficient of variation based on N number of SMART characteristic value in preset time threshold is calculated, and training sample value is obtained, wherein N is the integer more than or equal to 1.

3. the method according to claim 1, wherein described special based on N number of SMART in disk unit to be measured The coefficient of variation of the value indicative in preset time threshold is calculated, before obtaining characteristic value to be measured, further includes:

Obtain the SMART characteristic value of disk unit record to be predicted；

N number of SMART characteristic value high with default life characteristic data correlation is selected, the N is used to indicate preset want The number of the SMART characteristic value of selection.

4. determining the spy to be measured the method according to claim 1, wherein described be based on the regression coefficient The service life state of the corresponding disk unit to be measured of value indicative, comprising:

It is calculated based on the regression coefficient, obtains the corresponding prediction data of the characteristic value to be measured；

Judge whether the corresponding prediction data of the characteristic value to be measured is greater than preset threshold value；

When the prediction data is more than or equal to preset threshold value, the corresponding disk unit to be measured of the characteristic value to be measured is determined Service life state be it is available, the service life that the available service life state is used to indicate disk unit is more than or equal to the day that marks in advance Number；

When the prediction data is less than preset threshold value, the service life of the corresponding disk unit to be measured of the characteristic value to be measured is determined State is damage, and the service life that the service life state of the damage is used to indicate disk unit is less than the number of days marked in advance.

5. the method according to claim 1, wherein the method also includes:

After the service life state for determining the corresponding disk unit to be measured of the characteristic value to be measured, prompt information is exported.

6. a kind of disk unit life predication apparatus, which is characterized in that described device includes:

First computing unit, for based on variation of N number of SMART characteristic value in preset time threshold in disk unit to be measured Coefficient is calculated, and characteristic value to be measured is obtained, wherein N is the integer more than or equal to 1；

Second computing unit for calculating separately the weight of the characteristic value to be measured and M preset training sample values, and constructs Weight matrix, the training sample include the characteristic value of the disk unit of preset quantity, and M is the integer more than or equal to 1；

Third computing unit obtains regression coefficient for carrying out linear regression calculating based on the weight matrix；

Determination unit determines the service life of the corresponding disk unit to be measured of the characteristic value to be measured for being based on the regression coefficient State.

7. device according to claim 6, which is characterized in that further include:

Acquiring unit, for obtaining the SMART characteristic value of disk unit record to be predicted；

Selecting unit, for selecting N number of SMART characteristic value high with default life characteristic data correlation, the N is used to indicate The number of the preset SMART characteristic value to be chosen.

8. device according to claim 6, which is characterized in that the determination unit includes:

Computation subunit obtains the corresponding prediction data of the characteristic value to be measured for being calculated based on the regression coefficient；

Judging unit, for judging whether the corresponding prediction data of the characteristic value to be measured is greater than preset threshold value；

First determines subelement, for determining the characteristic value to be measured when the prediction data is more than or equal to preset threshold value The service life state of corresponding disk unit to be measured be it is available, the service life that the available service life state is used to indicate disk unit is big In equal to the number of days marked in advance；

Second determines subelement, for when the prediction data is less than preset threshold value, determining that the characteristic value to be measured is corresponding The service life state of disk unit to be measured be damage, the service life that the service life state of the damage is used to indicate disk unit is less than pre- The number of days first marked.

9. device according to claim 6, which is characterized in that further include:

Prompt unit, for after the service life state for determining the corresponding disk unit to be measured of the characteristic value to be measured, output to be prompted Information.

Technical field

The present invention relates to technical field of data processing more particularly to a kind of disk unit life-span prediction method and device.

Background technique

With the continuous development of computer technology, the data for needing to store are increasing, to storage system storage performance Demand is also increasing, and can storage system provide reliable and stable data access capabilities, directly affects entire storage system Reliability.It is counted based on data center, the disk unit in storage system is the highest component of failure rate.

Summary of the invention

In view of this, the embodiment of the present invention provides a kind of disk unit life-span prediction method and device, to solve existing skill The safety of storage system and the lower problem of reliability in art.

To achieve the above object, the embodiment of the present invention provides the following technical solutions:

On the one hand the embodiment of the present invention discloses a kind of disk unit life-span prediction method, which comprises

It is calculated based on the coefficient of variation of N number of SMART characteristic value in preset time threshold in disk unit to be measured, Obtain characteristic value to be measured, wherein N is the integer more than or equal to 1；

The weight of the characteristic value to be measured and M preset training sample values is calculated separately, and constructs weight matrix, it is described Training sample value includes the characteristic value of the disk unit of preset quantity, and M is the integer more than or equal to 1；

Linear regression calculating is carried out based on the weight matrix, obtains regression coefficient；

Based on the regression coefficient, the service life state of the corresponding disk unit to be measured of the characteristic value to be measured is determined.

Optionally, the default process of the training sample value includes:

Obtain the SMART characteristic value of training disk unit record；

The n SMART characteristic values high with default life characteristic data correlation are selected, the N, which is used to indicate, to be preset The SMART characteristic value to be chosen number, n is integer more than or equal to 1；

The coefficient of variation based on N number of SMART characteristic value in preset time threshold is calculated, and training sample value is obtained, Wherein, N is the integer more than or equal to 1.

Optionally, described based on variation of N number of SMART characteristic value in preset time threshold in disk unit to be measured Coefficient is calculated, before obtaining characteristic value to be measured, further includes:

Obtain the SMART characteristic value of disk unit record to be predicted；

N number of SMART characteristic value high with default life characteristic data correlation is selected, the N, which is used to indicate, to be preset The SMART characteristic value to be chosen number.

Optionally, described to be based on the regression coefficient, determine the longevity of the corresponding disk unit to be measured of the characteristic value to be measured Life state, comprising:

It is calculated based on the regression coefficient, obtains the corresponding prediction data of the characteristic value to be measured；

Judge whether the corresponding prediction data of the characteristic value to be measured is greater than preset threshold value；

When the prediction data is more than or equal to preset threshold value, determine that the corresponding disk to be measured of the characteristic value to be measured is set Standby service life state be it is available, the service life that the available service life state is used to indicate disk unit is more than or equal to be marked in advance Number of days；

When the prediction data is less than preset threshold value, the corresponding disk unit to be measured of the characteristic value to be measured is determined Service life state is damage, and the service life that the service life state of the damage is used to indicate disk unit is less than the number of days marked in advance.

Optionally, the method also includes:

After the service life state for determining the corresponding disk unit to be measured of the characteristic value to be measured, prompt information is exported.

On the other hand the embodiment of the present invention discloses a kind of disk unit life predication apparatus, described device includes:

First computing unit, for based on N number of SMART characteristic value in disk unit to be measured in preset time threshold The coefficient of variation is calculated, and characteristic value to be measured is obtained, wherein N is the integer more than or equal to 1；

Second computing unit, for calculating separately the weight of the characteristic value to be measured and M preset training sample values, and Weight matrix is constructed, the training sample includes the characteristic value of the disk unit of preset quantity, and M is the integer more than or equal to 1；

Third computing unit obtains regression coefficient for carrying out linear regression calculating based on the weight matrix；

Determination unit determines the corresponding disk unit to be measured of the characteristic value to be measured for being based on the regression coefficient Service life state.

Optionally, further includes:

Acquiring unit, for obtaining the SMART characteristic value of disk unit record to be predicted；

Selecting unit, for selecting N number of SMART characteristic value high with default life characteristic data correlation, the N is used for Indicate the number of the preset SMART characteristic value to be chosen.

Optionally, the determination unit includes:

Computation subunit obtains the corresponding prediction of the characteristic value to be measured for being calculated based on the regression coefficient Data；

Judging unit, for judging whether the corresponding prediction data of the characteristic value to be measured is greater than preset threshold value；

First determines subelement, for determining the spy to be measured when the prediction data is more than or equal to preset threshold value The service life state of the corresponding disk unit to be measured of value indicative be it is available, the available service life state is used to indicate the longevity of disk unit Life is more than or equal to the number of days marked in advance；

Second determines subelement, for determining the characteristic value to be measured when the prediction data is less than preset threshold value The service life state of corresponding disk unit to be measured is damage, and the service life that the service life state of the damage is used to indicate disk unit is small In the number of days marked in advance.

Optionally, further includes:

Prompt unit, for exporting after the service life state for determining the corresponding disk unit to be measured of the characteristic value to be measured Prompt information.

Based on a kind of disk unit life-span prediction method and device that the embodiments of the present invention provide, this method comprises: It is calculated, is obtained to be measured based on the coefficient of variation of N number of SMART characteristic value in preset time threshold in disk unit to be measured Characteristic value；The weight of characteristic value to be measured and M preset training sample values is calculated separately, and constructs weight matrix；Based on weight Matrix carries out linear regression calculating, obtains regression coefficient；Based on regression coefficient, determine that the corresponding disk to be measured of characteristic value to be measured is set Standby service life state.In embodiments of the present invention, by the corresponding regression coefficient of determination characteristic value to be measured, it can determine magnetic to be measured The service life state of disc apparatus, thus improve storage system safety and reliability it is lower.

Detailed description of the invention

In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, to embodiment or will show below There is attached drawing needed in technical description to be briefly described, it should be apparent that, the accompanying drawings in the following description is only this The embodiment of invention for those of ordinary skill in the art without creative efforts, can also basis The attached drawing of offer obtains other attached drawings.

Fig. 1 is a kind of flow diagram of disk unit life-span prediction method provided in an embodiment of the present invention；

Fig. 2 is the flow diagram of the balance rate of precision and recall rate under different hyper parameters provided in an embodiment of the present invention；

Fig. 3 is a kind of flow diagram of disk unit life-span prediction method provided in an embodiment of the present invention；

Fig. 4 is the flow diagram of the service life state of determination provided in an embodiment of the present invention disk unit to be measured；

Fig. 5 is a kind of block diagram of disk unit life predication apparatus provided in an embodiment of the present invention；

Fig. 6 is the block diagram of another disk unit life predication apparatus provided in an embodiment of the present invention；

Fig. 7 is the block diagram of another disk unit life predication apparatus provided in an embodiment of the present invention.

Specific embodiment

Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete Site preparation description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts every other Embodiment shall fall within the protection scope of the present invention.

In this application, the terms "include", "comprise" or any other variant thereof is intended to cover non-exclusive inclusion, So that the process, method, article or equipment for including a series of elements not only includes those elements, but also including not having The other element being expressly recited, or further include for elements inherent to such a process, method, article, or device.Do not having There is the element limited in the case where more limiting by sentence "including a ...", it is not excluded that in the mistake including the element There is also other identical elements in journey, method, article or equipment.

It can be seen from background technology that be merely able to test and analyze and reporting techniques (Self-Monitoring by self at present Analysis And Reporting Technology, SMART) the intact situation of automatic monitoring magnetic disk device driver and report Potential problems, the failure of look-ahead disk unit.But once there is continuous muti-piece equipment fault, user data still can be lost It loses, and decay state is presented in the performance that will lead to its disk unit.

Therefore, the embodiment of the invention provides a kind of disk unit life-span prediction method and devices, pass through determination spy to be measured The smallest training sample value of the difference of value indicative and training sample value, determines characteristic value pair to be measured based on the corresponding weight of training sample value The regression coefficient answered, can determine the service life state of disk unit to be measured, to improve the safety and reliability of storage system It is lower.

It is a kind of flow diagram of disk unit life-span prediction method provided in an embodiment of the present invention, the party with reference to Fig. 1 Method the following steps are included:

Step S101: based on the coefficient of variation of N number of SMART characteristic value in preset time threshold in disk unit to be measured It is calculated, obtains characteristic value to be measured.

In step s101, N is the integer more than or equal to 1.

It should be noted that the SMART characteristic value include SMART1, SMART2, SMART3, SMART4, SMART5, SMART7, SMART8, SMART183, SMART184 etc., the SMART characteristic value be used to indicate the equipment process status, The device datas such as space storage, data processing performance, it is without restriction to this application.

During implementing step S101, N number of SMART characteristic value based on the selection calculates every SMART The standard deviation of characteristic value and the coefficient of variation of this feature value in preset time threshold, and divided by N number of SMART characteristic value Mean value obtains characteristic value to be measured, wherein the preset time threshold may be configured as 7 days, to this can according to the actual situation depending on, The application is without restriction.

In order to preferably illustrate the above-mentioned characteristic value to be measured being related to, illustrate below by the content in table 1 Explanation.

In the table 1, shows selected 14 and existed by N number of SMART characteristic value in disk unit to be measured The field for the characteristic value to be measured that the coefficient of variation in preset time threshold is calculated.

Table 1:

Serial number	The field of SMART characteristic value	Serial number	The field of SMART characteristic value
				1	SMART_5_RAW_CV	8	SMART_5_NORM_CV
2	SMART_183_RAW_CV	9	SMART_183_NORM_CV
				3	SMART_184_RAW_CV	10	SMART_184_NORM_CV
4	SMART_187_RAW_CV	11	SMART_187_NORM_CV
				5	SMART_188_RAW_CV	12	SMART_188_NORM_CV
6	SMART_197_RAW_CV	13	SMART_197_NORM_CV
				7	SMART_198_RAW_CV	14	SMART_188_NORM_CV

Step S102: the weight of the characteristic value to be measured and M preset training sample values is calculated separately, and constructs weight Matrix.

In step s 102, the training sample value includes the characteristic value of the disk unit of preset quantity, M be more than or equal to 1 integer.

During implementing step S102, core is passed through based on characteristic value to be measured and M preset training sample values The corresponding weights omega (i, i) of M training sample value is calculated in function formula (1), and constructs matrix based on the weight.

It should be noted that the kernel function can be gaussian kernel function.

Formula (1):

Wherein, x⁽ⁱ⁾For i-th of training sample value, the i is less than or equal to M, and x is characteristic value to be measured, and k needs are adjusted Parameter.

It should be noted that is, hyper parameter gives the mesh to M training sample value weight assignment by adjustment parameter k It marks training sample and assigns higher weight.

It should be noted that k can balance feature to be measured based on the difference between the training sample value and sample to be tested value It is worth the balance rate of precision and recall rate of corresponding prediction data, as shown in Figure 2, wherein the abscissa of Fig. 2 is for indicating taking for k Value, ordinate are used for the balance rate of precision and recall rate for indicating to survey the corresponding prediction data of characteristic value.

It should be noted that the default process of the training sample value includes:

Obtain the SMART characteristic value of training disk unit record.

Wherein, by training disk unit carry built-in SMART System to the process status of each trained disk, deposit The detection such as space and data processing performance is stored up, the SMART characteristic value of each trained disk unit record is obtained.

The n SMART characteristic values high with default life characteristic data correlation are selected, the N, which is used to indicate, to be preset The SMART characteristic value to be chosen number.

Wherein, n is the integer more than or equal to 1.In the SMART characteristic value of each trained disk unit record, into Row screening, chooses N number of SMART characteristic value high with default life characteristic data correlation.

The coefficient of variation based on N number of SMART characteristic value in preset time threshold is calculated, and training sample value is obtained.

Wherein, the N is the integer more than or equal to 1.The value of the N and n may be the same or different, to this Apply without restriction.

Step S103: linear regression calculating is carried out based on the weight matrix, obtains regression coefficient.

During implementing step S103, it is based on the weight matrix, mesh is determined in the M training sample Mark training sample.And solve regression coefficientCorresponding matrix expression (2), and pass through regression coefficientCorresponding expression matrix Formula (2) carries out linear regression calculating to the corresponding weight of the target training sample value, wherein the X in matrix^TThe determinant of WX It is 0, obtains regression coefficient

Formula (2):

Wherein, W is the corresponding weight of training sample value, and y is the product of weight matrix, and X is the corresponding parameter of matrix.

It should be noted that the target training sample is used to indicate the training sample nearest with the characteristic value size to be measured This.

Step S104: it is based on the regression coefficient, determines the service life of the corresponding disk unit to be measured of the characteristic value to be measured State.

In embodiments of the present invention, based on N number of SMART characteristic value in disk unit to be measured in preset time threshold The coefficient of variation is calculated, and characteristic value to be measured is obtained；Calculate separately the power of characteristic value to be measured and M preset training sample values Weight, and construct weight matrix；Linear regression calculating is carried out based on weight matrix, obtains regression coefficient；Based on regression coefficient, determine The service life state of the corresponding disk unit to be measured of characteristic value to be measured, it can be seen that disk unit disclosed by the embodiments of the present invention Life-span prediction method can determine the service life of disk unit to be measured by determining the corresponding regression coefficient of characteristic value to be measured State, to improve the safety and reliability of storage system.

Based on embodiments of the present invention disk unit life-span prediction method shown in fig. 1, it is based on executing step S101 The coefficient of variation of N number of SMART characteristic value in preset time threshold in disk unit to be measured is calculated, and feature to be measured is obtained Before value, as shown in Figure 3, further includes:

Step S301: the SMART characteristic value of disk unit record to be predicted is obtained.

During implementing step S301, by carrying built-in SMART System to institute in disk unit to be measured The detection such as process status, memory space and data processing performance of disk to be predicted is stated, disk unit record to be predicted is obtained SMART characteristic value.

Step S302: the N number of SMART characteristic value high with default life characteristic data correlation of selection.

In step s 302, the N is used to indicate the number of the preset SMART characteristic value to be chosen.

During implementing step S302, in the SMART characteristic value of the disk unit record to be predicted, into Row screening, chooses N number of SMART characteristic value high with default life characteristic data correlation.

It should be noted that the default life characteristic data includes at least the working time of disk, the secondary head of disk The throughput performance of number and disk the processing data of addressing failure, in embodiments of the present invention, for the life characteristic data It is not limited to that, can also include the life characteristic data in other influences disk unit service life, N may be configured as 14.

It is above-mentioned being related to the high SMART characteristic value of default life characteristic data correlation in order to preferably illustrate, It is illustrated below by the content in table 2.

In the table 2, selected 14 and the high SMART characteristic value of default life characteristic data correlation are shown Initial field.

Table 2:

Serial number	The field of SMART characteristic value	Serial number	The field of SMART characteristic value
				1	SMART_5_RAW	8	SMART_5_NORM
2	SMART_183_RAW	9	SMART_183_NORM
				3	SMART_184_RAW	10	SMART_184_NORM
4	SMART_187_RAW	11	SMART_187_NORM
				5	SMART_188_RAW	12	SMART_188_NORM
6	SMART_197_RAW	13	SMART_197_NORM
				7	SMART_198_RAW	14	SMART_188_NORM

In embodiments of the present invention, N number of SMART characteristic value high with default life characteristic data correlation is selected, is obtained Characteristic value to be measured, can be avoided that SMART characteristic value data is excessive, and caused by data processing speed it is slow.

Based on embodiments of the present invention disk life-span prediction method shown in fig. 1, step S104 is being executed based on described Regression coefficient, during the service life state for determining the corresponding disk unit to be measured of the characteristic value to be measured, as shown in figure 4, packet Include following steps:

Step S401: being calculated based on the regression coefficient, obtains the corresponding prediction data of the characteristic value to be measured.

During implementing step S401, it is based on the regression coefficientIt is calculated, is obtained by formula (3) The corresponding prediction data of the characteristic value to be measured

Formula (3):

Wherein, x is characteristic value to be measured, the prediction dataValue range be 0 to 1.

Step S402: judging whether the corresponding prediction data of the characteristic value to be measured is greater than preset threshold value, when described pre- When measured data is more than or equal to preset threshold value, step S403 is executed: when the prediction data is less than preset threshold value, executing step Rapid S404.

It should be noted that the preset threshold value may be configured as 0.5, it is without restriction to this application.

Step S403: determine that the service life state of the corresponding disk unit to be measured of the characteristic value to be measured is available.

In step S403, the service life that the available service life state is used to indicate disk unit is more than or equal to label in advance Number of days.

Step S404: determine the service life state of the corresponding disk unit to be measured of the characteristic value to be measured for damage.

In step s 404, the service life that the service life state of the damage is used to indicate disk unit is less than the day marked in advance Number.

Before the process for realizing above-mentioned steps S403 and step S404, need to the corresponding disk unit of training sample Output prompt information re-flagged.

Specifically, the output prompt information that the disk unit service life is less than the disk unit of the number of days marked in advance is labeled as 0, i.e. disk unit has damaged, and the disk unit service life is greater than to the output prompt information of the disk unit of the number of days marked in advance Labeled as 1, i.e. disk unit can also use.

It should be noted that can be set the number of days marked in advance to 14 days according to many experiments, the application is not limited System.

In embodiments of the present invention, it by the service life state of determination disk unit to be measured, is prompted in order to be exported to user Information, can be avoided occur disk unit damage caused by various data failures, thus improve storage system safety and Reliability.

Optionally, on the basis of present invention disk unit life-span prediction method disclosed above, further includes:

After the service life state for determining the corresponding disk unit to be measured of the characteristic value to be measured, prompt information is exported.

It should be noted that if the output prompt information is 1, then illustrate the corresponding disk unit of the characteristic value to be measured It can also use, if the output prompt information is 0, illustrate that the corresponding disk unit of the characteristic value to be measured has damaged.

Compared with present invention disk unit life-span prediction method disclosed above, determining that characteristic value to be measured is corresponding to be measured After the service life state of disk unit, prompt information is exported, reminds the user that the disk unit whether there is high risk, so as to Disk unit is replaced in user or starts other safeguard measures, to avoid that various numbers caused by disk unit damages occur According to failure.

Corresponding with disk unit life-span prediction method disclosed in the embodiments of the present invention, the embodiment of the present invention is also corresponding A kind of disk unit life predication apparatus is disclosed, as shown in figure 5, the disk unit life predication apparatus includes:

First computing unit 501, for based on N number of SMART characteristic value in disk unit to be measured in preset time threshold The interior coefficient of variation is calculated, and characteristic value to be measured is obtained.

It should be noted that N is the integer more than or equal to 1.

Second computing unit 502, for calculating separately the power of the characteristic value to be measured and M preset training sample values Weight, and construct weight matrix.

It should be noted that the training sample includes the characteristic value of the disk unit of preset quantity, M is more than or equal to 1 Integer.

Third computing unit 503 obtains regression coefficient for carrying out linear regression calculating based on the weight matrix.

Determination unit 504 determines the corresponding disk unit to be measured of the characteristic value to be measured for being based on the regression coefficient Service life state.

It should be noted that each unit in disk unit life predication apparatus disclosed in the embodiments of the present invention has The principle and implementation procedure of body, it is identical as the disk unit life-span prediction method shown in aforementioned present invention implementation, reference can be made to above-mentioned Corresponding part in disk unit life-span prediction method disclosed by the embodiments of the present invention, is not discussed here.

In embodiments of the present invention, the first computing unit is based on N number of SMART characteristic value in disk unit to be measured default The coefficient of variation in time threshold is calculated, and characteristic value to be measured is obtained；Second computing unit calculates separately characteristic value to be measured and M The weight of a preset training sample value, and construct weight matrix；Third computing unit is based on weight matrix and carries out linear regression It calculates, obtains regression coefficient；Determination unit is based on regression coefficient, determines the service life of the corresponding disk unit to be measured of characteristic value to be measured State, it can be seen that the life-span prediction method of disk unit disclosed by the embodiments of the present invention, it is corresponding by determination characteristic value to be measured Regression coefficient, can determine the service life state of disk unit to be measured, thus improve storage system safety and reliability compared with It is low.

Based on the disk unit life predication apparatus shown in above-mentioned Fig. 5, shown of the invention real in conjunction with Fig. 5 with reference to Fig. 6 A kind of structural block diagram of disk unit life predication apparatus of example offer, described device are provided further include:

Acquiring unit 601, for obtaining the SMART characteristic value of disk unit record to be predicted.

Selecting unit 602, for selecting N number of SMART characteristic value high with default life characteristic data correlation, the N It is used to indicate the number of the preset SMART characteristic value to be chosen.

In embodiments of the present invention, N number of SMART characteristic value high with default life characteristic data correlation is selected, is obtained Characteristic value to be measured, can be avoided that SMART characteristic value data is excessive, and caused by data processing rate it is slow.

Based on the disk unit life predication apparatus shown in above-mentioned Fig. 5, the determination unit 504 includes:

Computation subunit obtains the corresponding prediction of the characteristic value to be measured for being calculated based on the regression coefficient Data.

Judging unit, for judging whether the corresponding prediction data of the characteristic value to be measured is greater than preset threshold value.

First determines subelement, for determining the spy to be measured when the prediction data is more than or equal to preset threshold value The service life state of the corresponding disk unit to be measured of value indicative is available.

It should be noted that the service life that the available service life state is used to indicate disk unit is more than or equal to label in advance Number of days.

Second determines subelement, for determining the characteristic value to be measured when the prediction data is less than preset threshold value The service life state of corresponding disk unit to be measured is damage.

It should be noted that the service life that the service life state of the damage is used to indicate disk unit is less than the day marked in advance Number.

In embodiments of the present invention, it by the service life state of determination disk unit to be measured, is prompted in order to be exported to user Information, can be avoided occur disk unit damage caused by various data failures, thus improve storage system safety and Reliability.

Based on the disk unit life predication apparatus shown in above-mentioned Fig. 5, shown of the invention real in conjunction with Fig. 5 with reference to Fig. 7 A kind of structural block diagram of disk unit life predication apparatus of example offer, described device further include: prompt unit 505 are provided.

Prompt unit 505, after the service life state for determining the corresponding disk unit to be measured of the characteristic value to be measured, output is mentioned Show information.

In embodiments of the present invention, after the service life state for determining the corresponding disk unit to be measured of characteristic value to be measured, output Prompt information reminds the user that the disk unit with the presence or absence of high risk, in order to which user replaces disk unit or starting Other safeguard measures, to avoid that various data failures caused by disk unit damages occur.

All the embodiments in this specification are described in a progressive manner, same and similar portion between each embodiment Dividing may refer to each other, and each embodiment focuses on the differences from other embodiments.Especially for system or For system embodiment, since it is substantially similar to the method embodiment, so describing fairly simple, related place is referring to method The part of embodiment illustrates.System and system embodiment described above is only schematical, wherein the conduct The unit of separate part description may or may not be physically separated, component shown as a unit can be or Person may not be physical unit, it can and it is in one place, or may be distributed over multiple network units.It can root According to actual need that some or all of the modules therein is selected to achieve the purpose of the solution of this embodiment.Ordinary skill Personnel can understand and implement without creative efforts.

Professional further appreciates that, unit described in conjunction with the examples disclosed in the embodiments of the present disclosure And algorithm steps, can be realized with electronic hardware, computer software, or a combination of the two, in order to clearly demonstrate hardware and The interchangeability of software generally describes each exemplary composition and step according to function in the above description.These Function is implemented in hardware or software actually, the specific application and design constraint depending on technical solution.Profession Technical staff can use different methods to achieve the described function each specific application, but this realization is not answered Think beyond the scope of this invention.

The foregoing description of the disclosed embodiments enables those skilled in the art to implement or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, as defined herein General Principle can be realized in other embodiments without departing from the spirit or scope of the present invention.Therefore, of the invention It is not intended to be limited to the embodiments shown herein, and is to fit to and the principles and novel features disclosed herein phase one The widest scope of cause.