CN116126593A - Data backup system and method in cloud platform environment - Google Patents
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- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/07—Responding to the occurrence of a fault, e.g. fault tolerance
- G06F11/14—Error detection or correction of the data by redundancy in operation
- G06F11/1402—Saving, restoring, recovering or retrying
- G06F11/1446—Point-in-time backing up or restoration of persistent data
- G06F11/1448—Management of the data involved in backup or backup restore
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Abstract
The invention discloses a data backup system and method in a cloud platform environment, and belongs to the technical field of data backup. The data backup system comprises a data acquisition module, a data transmission module, a data backup analysis module and an alarm module; the data acquisition module is used for acquiring the operation data information of the computer and the data information backed up by the cloud platform and monitoring the state of the computer; the data transmission unit transmits the collected data information to the database for storage; the data backup analysis module is used for analyzing the data operated by the computer and the data needed to be backed up by the cloud platform; when the alarm module is in fault, detecting the fault of the computer and alarming and prompting the system terminal according to the security level of the cloud platform storage data; according to the method and the device for the data backup, the data operated by the computer are ordered, important data can be backed up preferentially during data backup, and the problem that the cloud platform backs up invalid data is solved.
Description
Technical Field
The invention relates to the technical field of data backup, in particular to a data backup system and method in a cloud platform environment.
Background
Important data, files or histories in the computer are critical for enterprise users and personal users, immeasurable losses can be caused when the important data, files or histories are carelessly lost, heart blood accumulated in a light way is reduced to east, normal operation of the enterprise can be seriously influenced, and huge losses are caused for scientific research and production. Data backup is the basis of disaster recovery, which is the process of copying all or part of data sets from the hard disk or array of an application host to other storage media in order to prevent the data loss caused by misoperation or system failure of the system.
Under the prior art, the cloud platform stores data indiscriminately under the condition that a computer fails, and the cloud platform stores invalid data under the condition that the computer fails due to limited memory capacity of the cloud platform, so that effective data is lost.
Disclosure of Invention
The invention aims to provide a data backup system and method in a cloud platform environment, so as to solve the problems in the background technology.
In order to solve the technical problems, the invention provides the following technical scheme: a data backup method in cloud platform environment comprises the following specific steps:
s100, grading the security of the data which can be stored by the cloud platform according to the data size of the computer running under the condition that the computer fails and the historical data of the data backup capacity which can be backed up by the cloud platform, and building a prediction model to predict the capacity of the data which can be backed up by the cloud platform under the computer failure state by monitoring the data which can be run by the computer in real time;
s200, counting the number of operation behaviors executed by a user on computer data, and sequencing the priority of the data running in different areas of the computer;
s300, according to the priority ordering of the data operated in different areas and the predicted value of the backup capacity of the cloud platform for the operated data in the computer fault state, the data needed to be backed up by the cloud platform are ordered again.
Further, the specific method for grading the security of the data that can be stored by the cloud platform in S100 is as follows:
s111, according to the data size of the computer running under the condition that the computer fails and the historical data of the backup capacity of the cloud platform, the FM classification model is utilized to obtain:
s112, all quadratic parameters W nj A symmetrical matrix W can be formed, and the weight coefficient W of the cross terms can be obtained through matrix decomposition nj Is decomposed into
Wherein v is n As hidden vector of nth dimension feature, feature component x n And x j The cross term coefficient of (2) is equal to x n Corresponding hidden vector and x j The inner product of the corresponding hidden vectors, i.e. each parameter W nj ＝<v n ，v j >The method comprises the steps of carrying out a first treatment on the surface of the By transformation +.>
Because of the existence of cross terms, the complexity of directly computing the model is O (kN 2 ) The complexity is reduced to O (kN) by changing the formula to obtain
Wherein v is n，δ Is the hidden vector v n Delta element, v j，δ Is the hidden vector v j Delta element of->
The number of elements of the one-dimensional hidden vector;
s113, multiplying the eigenvalue of the running data of the computer before the failure and the hidden vector of the eigenvalue of the data which can be backed up by the cloud platform after the failure by two to obtain the coefficient value of the cross item characteristic of the running data of the computer before the failure and the data which can be backed up by the cloud platform after the failure; the computer off-line training samples are used for obtaining coefficients of all characteristic values; the security level of the cloud platform capable of storing data can be calculated, wherein the security level of the cloud platform capable of storing data is divided into the security level of data security, data security critical, data danger and data destruction of the data stored by the four cloud platforms.
Further, the specific method for predicting the capacity of the cloud platform capable of backing up data in S100 is as follows:
s121, through the data size of the computer running under the condition that the computer fails and the historical data of the backup capacity of the cloud platform, the predicted value of the memory capacity of the data which can be actually stored by the cloud platform after the computer fails can be obtained
A is a coefficient between the memory capacity of the cloud platform actually capable of storing data and the data memory operated by the computer before the fault occurs, x is the data memory operated by the computer before the fault occurs, and b is an error term;
s122, enabling the cloud platform to store the memory capacity of the data actually
And x is the time before the computer failsThe running data memory is substituted into the FM classification model, so that the grade of data security when the cloud platform backs up the data under the condition of failure of the computer can be obtained; when the cloud platform is detected to carry out backup on data, the alarm unit alarms the terminal equipment, the backup data sequencing unit sequences the priority of the data operated by the computer, and the priority sequencing is performed according to the importance degree of the data operated by the computer.
Further, the S200 includes:
s201, marking data of operation behaviors executed by a user of data operated in different areas of a computer, and sequencing the areas of the computer according to the marked quantity of the data in the areas from large to small according to the marked quantity of the data in the areas; such as: in the process that a user uses a computer, various interaction behaviors occur between the user and the computer, wherein data in different areas of the computer are provided with an interaction ID, the interaction ID in the computer is triggered when the user executes operation behaviors, and when the user triggers the interaction ID which is provided with the data in different areas of the computer, the data matched with the interaction ID according to the interaction ID triggered by the user is marked;
s202, counting the number of times accumulated values marked by the operation behaviors executed by the user in the data operated in different areas of the computer, and eliminating the data with the number of times accumulated values marked by the operation behaviors executed by the user in the data operated in different areas of the computer being zero; and sequencing the data running in different areas of the computer from large to small according to the sequencing of the areas of the computer from large to small according to the accumulated marked times.
Further, the S300 includes:
s301, acquiring the memory of data operated in different areas of the computer, and predicting the memory capacity of the computer operated data to be backed up by the cloud platform through the ordering of the computer areas and the data in the areas
Reordering the data to be backed up of the cloud platform;
s302, the cloud platform performs backup according to the ordering of the data in the computer area, and when the cloud platform performs backup on the (h+1) th data in the computer area, the cloud platform backup memory M is enabled to be smaller than zero; analyzing the h+1th data and the memory of the h data in the computer area; h=1, 2, 3, H, H, M are constants;
s303, when the cloud platform is backing up the h data, the memory capacity of the cloud platform
Is larger than zero, and when the cloud platform is backing up the (h+1) th data, the memory capacity of the cloud platform is +.>
Less than zero, reordering the h+1th data stored by the cloud platform such that +.>
Wherein the method comprises the steps of
Is any one of the running data after the h+1 in the computer area.
The data backup system comprises a data acquisition module, a data transmission module, a data backup analysis module and an alarm module; the data acquisition module is used for acquiring the operation data information of the computer and the data information backed up by the cloud platform and monitoring the state of the computer; the data transmission unit is used for transmitting the collected operation data information of the computer and the data information backed up by the cloud platform to the database for storage; the data backup analysis module is used for analyzing data operated by the computer and data needed to be backed up by the cloud platform; the alarm module detects the faults of the computer after the computer has faults and alarms and prompts the system terminal according to the security level of the cloud platform storage data; the output end of the data acquisition module is connected with the input end of the data transmission module, the output end of the data transmission module is connected with the input end of the data backup analysis module, and the output end of the data backup analysis module is connected with the input end of the alarm module.
Further, the data acquisition module comprises a cloud platform backup data information acquisition unit, a computer operation data information acquisition unit and a computer state monitoring unit; the cloud platform backup data information acquisition unit is used for acquiring historical data of data information backed up by the cloud platform; the computer operation data information acquisition unit is used for acquiring data memory information of computer operation; the computer state monitoring unit monitors the working state of the computer.
Further, the data transmission module comprises a data transmission unit and a data storage unit; the data transmission unit is used for transmitting the collected operation data information of the computer and the data information backed up by the cloud platform to the database; the data storage unit is used for storing the collected operation data information of the computer and the data information backed up by the cloud platform in a database.
Further, the data backup analysis module comprises a cloud platform backup memory prediction unit, a user operation behavior marking unit and a backup data ordering unit; the cloud platform backup memory prediction unit predicts the data memory capacity of the cloud platform, which can be backed up when the computer fails, according to the historical information of the cloud platform backup data when the computer fails; the user operation behavior marking unit marks the data operated in different areas of the computer according to the operation behaviors executed by the user; the backup data sorting unit sorts the backup data according to the accumulated values of times marked by the data running in different areas of the computer for executing the operation behaviors of the user.
Further, the alarm module comprises a computer fault detection unit and an alarm unit; the computer fault detection unit is used for detecting faults of a computer; the alarm unit is used for carrying out alarm prompt on the terminal equipment when the security level of the data stored by the cloud platform is dangerous and damaged after the computer fails.
Compared with the prior art, the invention has the following beneficial effects: according to the method and the device for the data backup, the data operated by the computer are marked according to the operation behaviors of the user, the data are ordered according to the accumulated number of the data marks, important data can be backed up preferentially when the data are backed up, and the problem that the cloud platform backs up invalid data is solved.
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The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
fig. 1 is a schematic structural diagram of a data backup system in a cloud platform environment.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, the present invention provides the following technical solutions:
a data backup method in cloud platform environment comprises the following specific steps:
s100, grading the security of the data which can be stored by the cloud platform according to the data size of the computer running under the condition that the computer fails and the historical data of the data backup capacity which can be backed up by the cloud platform, and building a prediction model to predict the capacity of the data which can be backed up by the cloud platform under the computer failure state by monitoring the data which can be run by the computer in real time;
s200, counting the number of operation behaviors executed by a user on computer data, and sequencing the priority of the data running in different areas of the computer;
s300, according to the priority ordering of the data operated in different areas and the predicted value of the backup capacity of the cloud platform for the operated data in the computer fault state, the data needed to be backed up by the cloud platform are ordered again.
The specific method for grading the security of the cloud platform capable of storing data in S100 is as follows:
s111, according to the data size of the computer running under the condition that the computer fails and the historical data of the backup capacity of the cloud platform, the FM classification model is utilized to obtain:
s112, all quadratic parameters W nj A symmetrical matrix W can be formed, and the weight coefficient W of the cross terms can be obtained through matrix decomposition nj Is decomposed into
Wherein v is n As hidden vector of nth dimension feature, feature component x n And x j The cross term coefficient of (2) is equal to x n Corresponding hidden vector andx j the inner product of the corresponding hidden vectors, i.e. each parameter W nj ＝<v n ，v j >The method comprises the steps of carrying out a first treatment on the surface of the By transformation +.>
Because of the existence of cross terms, the complexity of directly computing the model is O (kN 2 ) The complexity is reduced to O (kN) by changing the formula as follows:
can then obtain
Wherein v is n，δ Is the hidden vector v n Delta element, v j，δ Is the hidden vector v j Delta element of->
The number of elements of the one-dimensional hidden vector;
s113, multiplying the eigenvalue of the running data of the computer before the failure and the hidden vector of the eigenvalue of the data which can be backed up by the cloud platform after the failure by two to obtain the coefficient value of the cross item characteristic of the running data of the computer before the failure and the data which can be backed up by the cloud platform after the failure; the computer off-line training samples are used for obtaining coefficients of all characteristic values; the security level of the cloud platform capable of storing data can be calculated, wherein the security level of the cloud platform capable of storing data is divided into the security level of data security, data security critical, data danger and data destruction of the data stored by the four cloud platforms.
Further, the specific method for predicting the capacity of the cloud platform capable of backing up data in S100 is as follows:
s121, the computer runs with large data under the condition of faults through the computerThe small cloud platform can backup the historical data of the data capacity, and the predicted value of the memory capacity of the data which can be actually stored by the cloud platform after the computer fails can be obtained
A is a coefficient between the memory capacity of the cloud platform actually capable of storing data and the data memory operated by the computer before the fault occurs, x is the data memory operated by the computer before the fault occurs, and b is an error term;
s122, enabling the cloud platform to store the memory capacity of the data actually
And x is the data memory running before the computer fails and is substituted into the FM classification model, so that the grade of data security when the cloud platform backs up the data under the condition of the computer failure can be obtained; when the cloud platform is detected to carry out backup on data, the alarm unit alarms the terminal equipment, the backup data sequencing unit sequences the priority of the data operated by the computer, and the priority sequencing is performed according to the importance degree of the data operated by the computer.
Further, the S200 includes:
s201, marking data of operation behaviors executed by a user of data operated in different areas of a computer, and sequencing the areas of the computer according to the marked quantity of the data in the areas from large to small according to the marked quantity of the data in the areas;
s202, counting the number of times accumulated values marked by the operation behaviors executed by the user in the data operated in different areas of the computer, and eliminating the data with the number of times accumulated values marked by the operation behaviors executed by the user in the data operated in different areas of the computer being zero; and sequencing the data running in different areas of the computer from large to small according to the sequencing of the areas of the computer from large to small according to the accumulated marked times.
Further, the S300 includes:
s301, acquiring the memory of data operated in different areas of the computer, and predicting the memory capacity of the computer operated data to be backed up by the cloud platform through the ordering of the computer areas and the data in the areas
Reordering the data to be backed up of the cloud platform;
s302, the cloud platform performs backup according to the sequence of the data in the computer area, and when the cloud platform performs backup on the 10 th data in the computer area, the residual backup memory M of the cloud platform is enabled to be smaller than zero; analyzing the memory of the 10 th data and the 9 th data in the computer area; the data running in different areas of the computer are sequenced from large to small according to the sequence from large to small of the areas of the computer, and the data memory size can be obtained by sequencing the accumulated marked times:
{18、10、15、9、5、4、3、10、20、17、10、18、15、10、6、18}
s303, when the cloud platform is backing up the 9 th data, the memory capacity m=100-94=6 of the cloud platform is greater than zero, and when the cloud platform is backing up the 10 th data, the memory capacity m=100-111= -11 of the cloud platform is less than zero, and the 10 th data stored in the cloud platform is reordered so that
Wherein the method comprises the steps of
For any one of the operation data after 10 th in the computer area, it is possible to learn +.>
15 th run data in the computer area.
The data backup system comprises a data acquisition module, a data transmission module, a data backup analysis module and an alarm module; the data acquisition module is used for acquiring the operation data information of the computer and the data information backed up by the cloud platform and monitoring the state of the computer; the data transmission unit is used for transmitting the collected operation data information of the computer and the data information backed up by the cloud platform to the database for storage; the data backup analysis module is used for analyzing data operated by the computer and data needed to be backed up by the cloud platform; the alarm module detects the faults of the computer after the computer has faults and alarms and prompts the system terminal according to the security level of the cloud platform storage data; the output end of the data acquisition module is connected with the input end of the data transmission module, the output end of the data transmission module is connected with the input end of the data backup analysis module, and the output end of the data backup analysis module is connected with the input end of the alarm module.
Further, the data acquisition module comprises a cloud platform backup data information acquisition unit, a computer operation data information acquisition unit and a computer state monitoring unit; the cloud platform backup data information acquisition unit is used for acquiring historical data of data information backed up by the cloud platform; the computer operation data information acquisition unit is used for acquiring data memory information of computer operation; the computer state monitoring unit monitors the working state of the computer.
Further, the data transmission module comprises a data transmission unit and a data storage unit; the data transmission unit is used for transmitting the collected operation data information of the computer and the data information backed up by the cloud platform to the database; the data storage unit is used for storing the collected operation data information of the computer and the data information backed up by the cloud platform in a database.
Further, the data backup analysis module comprises a cloud platform backup memory prediction unit, a user operation behavior marking unit and a backup data ordering unit; the cloud platform backup memory prediction unit predicts the data memory capacity of the cloud platform, which can be backed up when the computer fails, according to the historical information of the cloud platform backup data when the computer fails; the user operation behavior marking unit marks the data operated in different areas of the computer according to the operation behaviors executed by the user; the backup data sorting unit sorts the backup data according to the accumulated values of times marked by the data running in different areas of the computer for executing the operation behaviors of the user.
Further, the alarm module comprises a computer fault detection unit and an alarm unit; the computer fault detection unit is used for detecting faults of a computer; the alarm unit is used for carrying out alarm prompt on the terminal equipment when the security level of the data stored by the cloud platform is dangerous and damaged after the computer fails.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Finally, it should be noted that: the foregoing description is only a preferred embodiment of the present invention, and the present invention is not limited thereto, but it is to be understood that modifications and equivalents of some of the technical features described in the foregoing embodiments may be made by those skilled in the art, although the present invention has been described in detail with reference to the foregoing embodiments. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A data backup method in a cloud platform environment is characterized by comprising the following steps: the data backup method comprises the following specific steps:
s100, grading the security of the data which can be stored by the cloud platform according to the data size of the computer running under the condition that the computer fails and the historical data of the data backup capacity which can be backed up by the cloud platform, and building a prediction model to predict the capacity of the data which can be backed up by the cloud platform under the computer failure state by monitoring the data which can be run by the computer in real time;
s200, counting the number of operation behaviors executed by a user on computer data, and sequencing the priority of the data running in different areas of the computer;
s300, according to the priority ordering of the data operated in different areas and the predicted value of the backup capacity of the cloud platform for the operated data in the computer fault state, the data needed to be backed up by the cloud platform are ordered again.
2. The method for backing up data in a cloud platform environment according to claim 1, wherein: the specific method for grading the security of the cloud platform capable of storing data in S100 is as follows:
s111, according to the data size of the computer running under the condition that the computer fails and the historical data of the backup capacity of the cloud platform, utilizing an FM classification model:
s112, obtaining through matrix decomposition
The formula transformation can be obtained>
Simplifying the formula to obtain
s113, offline training samples are used for obtaining coefficients of all the characteristic values, and the security level of the cloud platform storage data is calculated.
3. The method for backing up data in a cloud platform environment according to claim 2, wherein: the specific method for predicting the capacity of the cloud platform capable of backing up data in S100 is as follows:
s121, obtaining a predicted value of the memory capacity of the data which can be actually stored by the cloud platform after the computer is in failure through the data size of the computer running under the condition that the computer is in failure and the historical data of the data which can be backed up by the cloud platform
A is a coefficient between the memory capacity of the cloud platform actually capable of storing data and the data memory operated by the computer before the fault occurs, x is the data memory operated by the computer before the fault occurs, and b is an error term;
s122, predicting actual capability of cloud platformMemory capacity for storing data
And substituting the data memory x operated by the computer before the failure into the FM classification model, so that the grade of data security when the cloud platform backs up the data under the condition of the failure of the computer can be obtained.
4. A method for backing up data in a cloud platform environment according to claim 3, wherein: the S200 includes:
s201, marking data of operation behaviors executed by a user of data operated in different areas of a computer, and sequencing the areas of the computer according to the marked quantity of the data in the areas from large to small according to the marked quantity of the data in the areas;
s202, counting the number of times accumulated values marked by the operation behaviors executed by the user in the data operated in different areas of the computer, and eliminating the data with the number of times accumulated values marked by the operation behaviors executed by the user in the data operated in different areas of the computer being zero; and sequencing the data running in different areas of the computer from large to small according to the sequencing of the areas of the computer from large to small according to the accumulated marked times.
5. The method for backing up data in a cloud platform environment according to claim 4, wherein: the S300 includes:
s301, acquiring the memory of data operated in different areas of the computer, and predicting the memory capacity of the computer operated data to be backed up by the cloud platform through the ordering of the computer areas and the data in the areas
Reordering the data to be backed up of the cloud platform;
s302, the cloud platform performs backup according to the ordering of the data in the computer area, and when the cloud platform performs backup on the (h+1) th data in the computer area, the cloud platform backup memory M is enabled to be smaller than zero; analyzing the h+1th data and the memory of the h data in the computer area; h=1, 2, 3, H, H, M are constants;
s303, when the cloud platform is backing up the h data, the memory capacity of the cloud platform
Is larger than zero, and when the cloud platform is backing up the (h+1) th data, the memory capacity of the cloud platform is +.>
Less than zero, reordering the h+1th data stored by the cloud platform such that +.>
Wherein->
Is any one of the running data after the h+1 in the computer area.
6. A data backup system applied to the data backup method in the cloud platform environment of any one of claims 1 to 5, which is characterized in that: the data backup system comprises a data acquisition module, a data transmission module, a data backup analysis module and an alarm module; the data acquisition module is used for acquiring the operation data information of the computer and the data information backed up by the cloud platform and monitoring the state of the computer; the data transmission unit is used for transmitting the collected operation data information of the computer and the data information backed up by the cloud platform to the database for storage; the data backup analysis module is used for analyzing data operated by the computer and data needed to be backed up by the cloud platform; the alarm module detects the faults of the computer after the computer has faults and alarms and prompts the system terminal according to the security level of the cloud platform storage data; the output end of the data acquisition module is connected with the input end of the data transmission module, the output end of the data transmission module is connected with the input end of the data backup analysis module, and the output end of the data backup analysis module is connected with the input end of the alarm module.
7. The data backup system of claim 6, wherein: the data acquisition module comprises a cloud platform backup data information acquisition unit, a computer operation data information acquisition unit and a computer state monitoring unit; the cloud platform backup data information acquisition unit is used for acquiring historical data of data information backed up by the cloud platform; the computer operation data information acquisition unit is used for acquiring data memory information of computer operation; the computer state monitoring unit monitors the working state of the computer.
8. The data backup system of claim 7, wherein: the data transmission module comprises a data transmission unit and a data storage unit; the data transmission unit is used for transmitting the collected operation data information of the computer and the data information backed up by the cloud platform to the database; the data storage unit is used for storing the collected operation data information of the computer and the data information backed up by the cloud platform in a database.
9. The data backup system of claim 8, wherein: the data backup analysis module comprises a cloud platform backup memory prediction unit, a user operation behavior marking unit and a backup data ordering unit; the cloud platform backup memory prediction unit predicts the data memory capacity of the cloud platform, which can be backed up when the computer fails, according to the historical information of the cloud platform backup data when the computer fails; the user operation behavior marking unit marks the data operated in different areas of the computer according to the operation behaviors executed by the user; the backup data sorting unit sorts the backup data according to the accumulated values of times marked by the data running in different areas of the computer for executing the operation behaviors of the user.
10. The data backup system of claim 9, wherein: the alarm module comprises a computer fault detection unit and an alarm unit; the computer fault detection unit is used for detecting faults of a computer; the alarming unit is used for alarming and prompting the terminal equipment when the memory capacity level of the cloud platform capable of storing data is data danger and data damage after the computer fails.
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