A data management method and management system for cloud computing system

Abstract

The present invention discloses a data management method and management system for a cloud computing system. The present invention relates to the field of data management technology and solves the technical problems that it is difficult to meet the needs of large-scale data storage and rapid processing, and data storage chaos, slow reading speed, and insufficient security are prone to occur. The present invention classifies computer data of the same type based on the data format, so as to better manage data of different formats and improve the efficiency and accuracy of data management. Preselected nodes are screened according to factors such as the free load, processing speed, processing capacity, and number of missing values ​​of storage nodes, and priority values ​​are calculated to generate a standard data format. The most suitable storage node can be selected to store specific data, so as to improve storage efficiency and data processing performance. Regular storage blocks are generated, data is segmented and stored and sorted according to binary numbers, and character extraction and encryption processing is performed based on the parity of data capacity, so as to ensure the security of data.

Description

Technical Field

[0001] The present invention relates to the technical field of data management, and in particular to a data management method and management system for a cloud computing system. Background Art

[0002] With the continuous development of cloud computing technology, the amount of data has exploded. How to efficiently manage the large amount of data in the cloud computing system has become a key issue. In the cloud computing environment, the data formats are diverse and the performance of storage nodes is also different.

[0003] According to the publication number CN117997819B, a data security management method based on cloud computing and its system are disclosed, which relate to the field of data transmission technology. The data security management method based on cloud computing includes the following steps: S1: receiving a data management request from a management user terminal; S2: creating a transmission map according to the data management request; S3: receiving a transmission request from a user sub-node, automatically analyzing the transmission request according to the transmission map, obtaining a transmission path, and transmitting the transmission data in the transmission request according to the transmission path.

[0004] The above patent automatically analyzes and transmits transmission requests through the constructed transmission graph, thereby avoiding under-transmission and / or data leakage due to mis-transmission, and improving the accuracy and security of data transmission. However, traditional data management methods often fail to meet the needs of large-scale data storage and rapid processing, and are prone to problems such as data storage confusion, slow reading speed, and insufficient security. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention provides a data management method and management system for a cloud computing system, which solves the problems of difficulty in meeting the needs of large-scale data storage and rapid processing, and prone to data storage confusion, slow reading speed, and insufficient security.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: a data management method for a cloud computing system, the method specifically comprising the following steps:

[0007] Step S001, obtaining computer data, and classifying the computer data into the same type based on the data format to obtain data of the same type and format;

[0008] Step S002, screening storage nodes based on the data capacity of the same type of data to obtain pre-selected nodes, and calculating the corresponding priority values ​​based on the basic information of the pre-selected nodes, while analyzing the data format based on the capacity of the comprehensive node to process the data format and generating a standard data format;

[0009] Step S003, performing storage analysis on the computer data corresponding to the pre-selected node and generating a regular storage block, and segmenting the computer data based on the regular storage block to obtain segmented packets, and then storing the binary numbers in the segmented packets in order to generate storage information;

[0010] Step S004, based on the generated storage information, character extraction and encryption processing are performed according to the conversion data packets corresponding to different storage spaces, and encryption information is generated by combining the extracted characters.

[0011] As a further solution of the present invention: the specific method of obtaining the same type of painting data in step S001 is:

[0012] Computer data and corresponding data formats are obtained, and computer data belonging to the same type of data formats are classified to obtain data of the same type of formats, and data capacity corresponding to the data of the same type of formats is obtained at the same time.

[0013] As a further solution of the present invention: the specific method of screening and obtaining the pre-selected nodes in step S002 is:

[0014] Get all the storage nodes and label them as i, where i=1, 2, ..., j, where j represents the number of storage nodes. Then get the free load corresponding to the storage node i, which is labeled as Fi. Compare the free load Fi with the preset value Fy. Filter the storage nodes whose free load Fi is greater than the preset value Fy and label them as pre-selected nodes a, where a=1, 2, ..., b, where b represents the number of pre-selected nodes.

[0015] As a further solution of the present invention: the specific method of generating the standard data format in step S002 is:

[0016] Get the storage data format corresponding to the pre-selected node a, and also get the processing speed S, processing capacity C, and number of missing values ​​M corresponding to the data format, and substitute the obtained parameters into the formula The priority value Q of the pre-selected node a for processing different data formats is calculated, where Cmin and Cmax represent the minimum and maximum values ​​of data capacity, Smin and Smax represent the minimum and maximum values ​​of processing speed, respectively. The specific formula is represents the normalized data capacity, represents the normalized processing speed, Indicates the impact factor of missing values;

[0017] Similarly, the priority values ​​of all different data formats in the pre-selected node a are calculated, and the priority values ​​are summed up to calculate the mean. Then, the priority values ​​of different data formats are compared with the mean to obtain the format weight ratio. At the same time, the data format corresponding to the largest format weight ratio is selected as the standard storage format, and the number of data formats corresponding to the largest format weight ratio is identified and judged, and standard data format information is generated.

[0018] As a further solution of the present invention: the specific method of storing and analyzing the computer data corresponding to the pre-selected node in step S003 is:

[0019] Select any node as the target object, then obtain the computer data corresponding to the target object, and generate two regular storage blocks according to the data format of the computer data, and at the same time divide the storage gap between the two regular storage blocks into multiple groups of storage spaces with equal distances, and label the storage spaces in a clockwise direction starting from the top storage space as A1, A2, ..., A12;

[0020] Obtain computer data and the data capacity corresponding to the computer data, and divide the computer data equally according to the data capacity to obtain multiple groups of segmentation packages, which are recorded as n, and n=1, 2, ..., m, and the specific value of m is 12, which is the same as the number of storage spaces. Then, perform binary conversion on the segmentation packages to obtain conversion segmentation package n, and obtain the number of binary numbers 1 and binary numbers 0 in the conversion segmentation package n. At the same time, sort the packages from small to large according to the number of binary numbers 1, determine whether there is an identical number of binary numbers in the sorting process, and analyze the existence and non-existence of the identical number respectively.

[0021] As a further solution of the present invention: the specific method of analyzing the existence and non-existence of the same number of items in step S003 is:

[0022] In the case where there is the same number of binary numbers, the corresponding conversion segmentation package is obtained, and the number of binary numbers 0 in the conversion segmentation package is compared, and the conversion segmentation package with a smaller number is prioritized, and storage information is generated at the same time;

[0023] In case that there is no identical binary number, the sorted conversion segmentation packets are sorted into storage spaces with corresponding labels, and storage information is generated at the same time.

[0024] As a further solution of the present invention: the specific method of performing character extraction and encryption processing according to the conversion data packets corresponding to different storage spaces in step S004 is:

[0025] Obtain the conversion segmentation package corresponding to the storage space, and generate the encryption interval based on the rule storage block. At the same time, perform binary character extraction based on the relationship between the rule storage block and the edge mapping. The specific extraction method is:

[0026] The side lengths of regular storage blocks are labeled as 1, 2, 3 and 4 respectively, and the storage space corresponding to the side length 1 and the side length 3 is marked as the mapping space. Similarly, the storage space corresponding to the side length 2 and the side length 3 is marked as the mapping space. Then, the data capacity corresponding to the conversion segmentation package is obtained, and characters are extracted based on the parity of the data capacity.

[0027] As a further solution of the present invention: the specific method of extracting characters based on the parity of data capacity in step S004 is:

[0028] When the data capacity of the conversion segmentation packet is an odd number, the binary characters of the odd-numbered bits in the conversion segmentation packet are obtained, and the corresponding number of binary characters are extracted according to the extraction standard value, and are recorded as the extracted characters; when the number capacity of the conversion segmentation packet is an even number, the binary characters of the even-numbered bits in the conversion segmentation packet are obtained, and the corresponding number of binary characters are extracted according to the extraction standard value, and are recorded as the extracted characters;

[0029] At the same time, the extracted characters of the conversion segmentation package are exchanged with the extracted characters of the segmentation package of the mapping relationship, and all the extracted characters are reorganized according to the original conversion segmentation package to obtain a reorganized string, and then the reorganized string is reversed to generate encrypted information.

[0030] A data management system for a cloud computing system, comprising:

[0031] A data acquisition unit, which is used to acquire computer data and storage node information and transmit them to the comprehensive screening processing unit;

[0032] A comprehensive screening processing unit, which is used to analyze the acquired computer data and storage node information, classify the computer data based on the data format of the computer data to obtain classified data of the same type, and obtain pre-selected nodes according to the free load of the storage node, and calculate the data format priority value corresponding to the pre-selected node, and generate standard data format information according to the priority value, and then transmit the standard data format information to the data storage analysis unit;

[0033] A data storage and analysis unit, which is used to perform storage analysis on computer data according to the acquired standard data format information, the system generates a regular storage block, and divides the regular storage block into multiple groups of storage spaces, and at the same time divides the computer data based on the number of storage spaces to obtain a divided package, then performs base conversion on the divided package to obtain a converted divided package, and sorts and stores the converted divided package in different ways according to the number of different base numbers in the converted divided package to generate storage information, and then transmits the storage information to the encryption storage unit;

[0034] An encryption storage unit, which is used to extract binary characters from conversion data packets in different storage spaces according to the acquired storage information, and the extraction method is based on the parity of the data capacity, and the extracted characters are mapped and replaced in combination with the corresponding mapping space, and the extracted characters are reorganized and reversed to generate a reorganized character string, and further generate encrypted information;

[0035] A management information output unit is used to generate corresponding decryption information according to the acquired encryption information and store the decryption information.

[0036] The present invention provides a data management method and management system for a cloud computing system. Compared with the prior art, it has the following beneficial effects:

[0037] The present invention can better manage data of different formats by classifying computer data of the same type based on the data format, improve the efficiency and accuracy of data management, screen pre-selected nodes according to factors such as the free load, processing speed, processing capacity and number of missing values ​​of the storage node, calculate the priority value to generate a standard data format, select the most suitable storage node to store specific data, improve storage efficiency and data processing performance, generate regular storage blocks, segment data and perform storage sorting according to binary numbers, and perform character extraction and encryption processing based on the parity of data capacity, so as to ensure the security of data and prevent data leakage and tampering. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 It is a step diagram of the method of the present invention;

[0039] Figure 2 The storage space partition diagram of the present invention;

[0040] Figure 3 This is the principle framework of the system of the present invention. DETAILED DESCRIPTION

[0041] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0042] For example, see Figure 1 and Figure 2 The present application provides a data management method for a cloud computing system, the method specifically comprising the following steps:

[0043] First, in step S001, computer data is acquired, and computer data is classified into the same type based on the data format to obtain data of the same type and format.

[0044] First, computer data is acquired, and the computer data acquired here includes data of different format types, such as NTFS, EXT4, ZFS and other file data. Then, the data format corresponding to the computer data is analyzed, and computer data belonging to the same type of data format is classified to obtain data of the same type of format, and the data capacity corresponding to the data of the same type of format is acquired.

[0045] Next, in step S002, the storage nodes are screened based on the data capacity of the same type of data to obtain pre-selected nodes, and the corresponding priority values ​​are calculated based on the basic information of the pre-selected nodes. At the same time, the data format is analyzed based on the capacity of the comprehensive node to process the data format and a standard data format is generated.

[0046] Obtain all storage nodes, and label the storage nodes as i, where i=1, 2, ..., j, where j represents the number of storage nodes. Then obtain the free load corresponding to the storage node i as Fi, and compare the free load Fi with a preset value Fy, and the specific value of the preset value is set by the operator. Filter the storage nodes whose free load Fi is greater than the preset value Fy and record them as pre-selected nodes a, where a=1, 2, ..., b, where b represents the number of pre-selected nodes.

[0047] Then, the storage data format corresponding to the pre-selected node a is obtained, and the processing speed S, processing capacity C and number of missing values ​​M corresponding to the data format are obtained, and the obtained parameters are substituted into the formula The priority value Q of the pre-selected node a for processing different data formats is calculated, where Cmin and Cmax represent the minimum and maximum values ​​of data capacity, Smin and Smax represent the minimum and maximum values ​​of processing speed, respectively. The specific formula is represents the normalized data capacity, represents the normalized processing speed, Indicates the impact factor of missing values;

[0048] Similarly, calculate the priority values ​​of all different data formats in the pre-selected node a, and sum the priority values ​​to calculate the mean, then calculate the ratio of the priority values ​​of different data formats to the mean to obtain the format weight ratio, and select the data format corresponding to the largest format weight ratio as the standard storage format, and identify and judge the number of data formats corresponding to the largest format weight ratio, and generate standard data format information at the same time, and here it is assumed that there is only one data format with the largest format weight ratio. Specifically, for example, the data formats corresponding to one of the pre-selected nodes a include NTFS, EXT4, and ZFS, where the format weights corresponding to NTFS, EXT4, and ZFS are 0.4, 0.45, and 0.51, respectively. Further, the ZFS format corresponding to the largest format weight ratio, that is, 0.51, is selected as the standard data format.

[0049] Next, in step S003, the computer data corresponding to the pre-selected node is stored and analyzed, and a regular storage block is generated. At the same time, the computer data is segmented based on the regular storage block to obtain segmented packages, and then the storage information is generated by sequentially storing the binary numbers in the segmented packages.

[0050] First, any node is selected as the target object, and then the computer data corresponding to the target object is obtained, and two regular storage blocks are generated according to the data format of the computer data. The regular storage blocks here are square, and the regular storage blocks are nested and automatically generated by the system, as shown in the attached figure. Figure 2 As shown, the storage gap between two regular storage blocks is divided into multiple groups of storage spaces at equal distances. Specifically, the number of storage spaces generated is 12 groups, and the storage spaces are numbered clockwise starting from the top storage space as A1, A2, ..., A12;

[0051] Obtain computer data and the data capacity corresponding to the computer data, and divide the computer data equally according to the data capacity to obtain multiple groups of split packages, which are recorded as n, and n=1, 2, ..., m, and the specific value of m is 12, which is the same as the number of storage spaces. Assume that there is a group of computer data, and its data capacity is 1200 units. Divide it equally into 12 split packages, then perform binary conversion on the split packages to obtain conversion split package n, and obtain the number of binary numbers 1 and binary numbers 0 in conversion split package n, and sort them from small to large according to the number of binary numbers 1, determine whether there is the same number of binary numbers in the sorting process, and analyze the situation of the same number and the situation of not having the same number respectively;

[0052] In a specific example, after binary conversion, split packet 1 is 101010101010, wherein the number of binary 1s is 6 and the number of binary 0s is 6;

[0053] After the split packet 2 is converted, it becomes 101101101101, the number of binary 1s is 6, and the number of binary 0s is 6.

[0054] After the split packet 3 is converted, it becomes 100010001000, the number of binary 1s is 4, and the number of binary 0s is 8.

[0055] …

[0056] After the split packet 12 is converted, it becomes 111100001111, the number of binary 1s is 8, and the number of binary 0s is 4.

[0057] For the case where there are the same number of binary numbers, that is, there are two or more conversion split packages corresponding to the same number of binary numbers 1, obtain the corresponding conversion split packages, and compare the number of binary numbers 0 in the conversion split packages, and give priority to the conversion split packages with smaller numbers, and generate storage information at the same time; first sort according to the number of binary numbers 1, and then find that the number of binary numbers 1 in split package 1 and split package 2 is the same, then compare their number of binary numbers 0, both are 6, and the priority order cannot be determined. Additional rules can be used, such as comparing the number size of the original split packages, etc. It is assumed that here according to the number size, split package 1 takes precedence over split package 2.

[0058] For the case where there is no identical number of binary numbers, that is, it is equivalent to being able to sort from small to large according to the number of binary numbers 1, sorting the sorted conversion split packets into storage spaces with corresponding labels, and generating storage information at the same time; for the case where there is no identical number of binary numbers 1, such as split packets 3 to split packets 12, they are sequentially allocated to storage spaces with corresponding labels in the sorted order, and storage information is generated, such as "segment packet 3 is stored in storage space A3, and conversion split packets are stored in storage space A12.

[0059] Finally, in step S004, based on the generated storage information, character extraction and encryption processing are performed according to the conversion data packets corresponding to different storage spaces, and encryption information is generated by combining the extracted characters.

[0060] Get the conversion segmentation package corresponding to the storage space, and generate the encryption interval based on the rule storage block, as shown in the attached Figure 2As shown, the encryption interval is a circle with a radius of d, with the center point of the regular storage block as the center, and the obtained circle is used as the encryption interval. The encryption interval is automatically generated by the system, and binary characters are extracted according to the relationship between the regular storage block and the edge mapping. The specific extraction method is:

[0061] The side lengths of the regular storage blocks are numbered as 1, 2, 3 and 4 respectively, and the storage space corresponding to the side length 1 and the side length 3 is marked as the mapping space, that is, the area corresponding to the side length 1 and the side length 3 is the first mapping space, and similarly, the storage space corresponding to the side length 2 and the side length 3 is marked as the mapping space, and the area corresponding to the side length 2 and the side length 4 is the second mapping space. Then, the data capacity corresponding to the conversion segmentation package is obtained, and the character is extracted based on the parity of the data capacity;

[0062] When the data capacity of the conversion segmentation package is an odd number, the binary characters of the odd-numbered bits in the conversion segmentation package are obtained, and the corresponding number of binary characters are extracted using the extraction standard value, which are recorded as extracted characters. When the number capacity of the conversion segmentation package is an even number, the binary characters of the even-numbered bits in the conversion segmentation package are obtained, and the corresponding number of binary characters are extracted using the extraction standard value, which are recorded as extracted characters. The definition of the standard extraction value here is based on the number of segmentation packages. In this application, the number of segmentation packages is 12, and the corresponding standard extraction value is 12, so the number of extracted characters obtained is 12.

[0063] At the same time, the extracted characters of the conversion segmentation package are interchanged with the extracted characters of the segmentation package of the mapping relationship. For example, the extracted characters in the conversion segmentation package corresponding to the storage space A1 are interchanged with the extracted characters in the conversion segmentation package corresponding to the storage space A9, and so on. At the same time, all the obtained extracted characters are reorganized according to the original conversion segmentation package to obtain a reorganized string, and then the reorganized string is reversed to generate encrypted information.

[0064] Embodiment 2: This embodiment is implemented on the basis of Embodiment 1, and the difference from Embodiment 1 is as follows:

[0065] In step S002, the situation where there are multiple data formats with the maximum format weight ratio is analyzed, and the corresponding data format is obtained. At the same time, the data capacity of the computer data corresponding to the data format is obtained, and the difference between the data capacity and the maximum processing capacity corresponding to the data format is calculated, and then the data format with the smallest difference is selected as the standard data format.

[0066] Embodiment 3, as the embodiment 3 of the present invention, focuses on combining the implementation processes of embodiment 1 and embodiment 2 for implementation.

[0067] Example 4, please refer to Figure 3A data management system for a cloud computing system, the system includes: a data acquisition unit, a comprehensive screening and processing unit, a data storage and analysis unit, a storage encryption and analysis unit, and a management information output unit, and all of the above functional units are unidirectionally electrically connected.

[0068] A data acquisition unit is used to acquire computer data and storage node information and transmit them to the comprehensive screening processing unit.

[0069] A comprehensive screening and processing unit is used to analyze the acquired computer data and storage node information, classify the computer data based on the data format of the computer data to obtain classified data of the same type, and obtain pre-selected nodes according to the free load of the storage node, and at the same time calculate the data format priority value corresponding to the pre-selected node, and generate standard data format information according to the priority value, and then transmit the standard data format information to the data storage analysis unit, and the processing method here is the same as the processing method of step S002 in Example 1.

[0070] A data storage and analysis unit, the unit is used to perform storage and analysis on computer data according to the acquired standard data format information, the system generates a regular storage block, and divides the regular storage block into multiple groups of storage space, and at the same time, based on the number of storage spaces, the computer data is segmented to obtain segmentation packages, and then the segmentation packages are converted into converted segmentation packages, and storage information is generated by sorting and storing in different ways according to the number of different bases in the converted segmentation packages, and then the storage information is transmitted to the encrypted storage unit, and the specific method of generating the storage information here is the same as the processing method of step S003 in the first embodiment.

[0071] An encryption storage unit is used to extract binary characters from conversion data packets in different storage spaces according to the acquired storage information, and the extraction method is based on the parity of the data capacity, and the extracted characters are mapped and replaced in combination with the corresponding mapping space, and the extracted characters are reorganized and reversed to generate a reorganized character string, and encryption information is further generated. The processing method here is the same as the processing method of step S004 in embodiment 1, and the encrypted information is transmitted to the management information output unit.

[0072] A management information output unit is used to generate corresponding decryption information according to the acquired encryption information and store the decryption information.

[0073] Some of the data in the above formulas are dimensionless and numerically calculated. Meanwhile, the contents not described in detail in this specification belong to the prior art known to those skilled in the art.

[0074] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A data management method for a cloud computing system, characterized in that: The method specifically comprises the following steps: Step S001, obtaining computer data, and classifying the computer data into the same type based on the data format to obtain data of the same type and format; Step S002, screening storage nodes based on the data capacity of the same type of data to obtain pre-selected nodes, and calculating the corresponding priority values ​​based on the basic information of the pre-selected nodes, while analyzing the data format based on the capacity of the comprehensive node to process the data format and generating a standard data format; Step S003, performing storage analysis on the computer data corresponding to the pre-selected node, and generating a regular storage block, and segmenting the computer data based on the regular storage block to obtain segmented packets, and then storing the binary numbers in the segmented packets in order to generate storage information, and the specific method is: Select a node as the target object, obtain the computer data corresponding to the target object, generate two regular storage blocks according to the data format, and divide the storage gap between the two storage blocks into 12 groups of storage spaces with equal spacing. Starting from the top storage space, they are numbered A1, A2, ..., A12 in clockwise order. Obtain computer data and obtain its data capacity, divide the computer data into 12 split packages according to the capacity, record them as n, n=1, 2, ..., 12, convert the split packages into binary form to obtain converted split package n, count the number of binary numbers 1 and 0 in the converted split package n, sort them from small to large according to the number of binary numbers 1, determine whether there is a situation where the number of binary numbers 1 is the same during sorting, and analyze the situation where there is a same number and there is no same number; Step S004, based on the generated storage information, character extraction and encryption processing are performed according to the conversion data packets corresponding to different storage spaces, and encryption information is generated by combining the extracted characters.

2. The data management method of a cloud computing system according to claim 1, characterized in that: The specific method of obtaining the same type of format data in step S001 is: Computer data and corresponding data formats are obtained, and computer data belonging to the same type of data formats are classified to obtain data of the same type of formats, and data capacity corresponding to the data of the same type of formats is obtained at the same time.

3. The data management method of a cloud computing system according to claim 1, characterized in that: The specific method of screening and obtaining the pre-selected nodes in step S002 is: Get all the storage nodes and label them as i, where i=1, 2, …, j, where j represents the number of storage nodes. Then get the free load corresponding to the storage node i, which is recorded as Fi. Compare the free load Fi with the preset value Fy, select the storage nodes whose free load Fi is greater than the preset value Fy, and record them as pre-selected nodes a, where a=1, 2, …, b, where b represents the number of pre-selected nodes.

4. The data management method of a cloud computing system according to claim 1, characterized in that: The specific method of generating the standard data format in step S002 is: Get the storage data format corresponding to the pre-selected node a, and also get the processing speed S, processing capacity C, and number of missing values ​​M corresponding to the data format, and substitute the obtained parameters into the formula The priority value Q of the pre-selected node a for processing different data formats is calculated, where Cmin and Cmax represent the minimum and maximum values ​​of data capacity, Smin and Smax represent the minimum and maximum values ​​of processing speed, respectively. The specific formula is represents the normalized data capacity, represents the normalized processing speed, Indicates the impact factor of missing values; Similarly, the priority values ​​of all different data formats in the pre-selected node a are calculated, and the priority values ​​are summed up to calculate the mean. Then, the priority values ​​of different data formats are compared with the mean to obtain the format weight ratio. At the same time, the data format corresponding to the largest format weight ratio is selected as the standard storage format, and the number of data formats corresponding to the largest format weight ratio is identified and judged, and standard data format information is generated.

5. The data management method of a cloud computing system according to claim 1, characterized in that: The specific method of analyzing the situation of the same number and the situation of the same number in step S003 is: In the case where there is the same number of binary numbers, the corresponding conversion segmentation package is obtained, and the number of binary numbers 0 in the conversion segmentation package is compared, and the conversion segmentation package with a smaller number is prioritized, and storage information is generated at the same time; In case that there is no identical binary number, the sorted conversion segmentation packets are sorted into storage spaces with corresponding labels, and storage information is generated at the same time.

6. The data management method of a cloud computing system according to claim 1, characterized in that: The specific method of performing character extraction and encryption processing according to the conversion data packets corresponding to different storage spaces in step S004 is: Obtain the conversion segmentation package corresponding to the storage space, and generate the encryption interval based on the rule storage block. At the same time, perform binary character extraction based on the relationship between the rule storage block and the edge mapping. The specific extraction method is: The side lengths of regular storage blocks are labeled as 1, 2, 3 and 4 respectively, and the storage space corresponding to side length 1 and side length 3 is marked as mapping space. Similarly, the storage space corresponding to side length 2 and side length 4 is marked as mapping space. Then, the data capacity corresponding to the conversion segmentation package is obtained, and characters are extracted based on the parity of the data capacity.

7. A data management method for a cloud computing system according to claim 6, characterized in that: The specific method of extracting characters based on the parity of data capacity in step S004 is: When the data capacity of the conversion segmentation packet is an odd number, the binary characters of the odd-numbered bits in the conversion segmentation packet are obtained, and the corresponding number of binary characters are extracted according to the extraction standard value, and are recorded as the extracted characters; when the number capacity of the conversion segmentation packet is an even number, the binary characters of the even-numbered bits in the conversion segmentation packet are obtained, and the corresponding number of binary characters are extracted according to the extraction standard value, and are recorded as the extracted characters; At the same time, the extracted characters of the conversion segmentation package are exchanged with the extracted characters of the segmentation package of the mapping relationship, and all the extracted characters are reorganized according to the original conversion segmentation package to obtain a reorganized string, and then the reorganized string is reversed to generate encrypted information.

8. A data management system for a cloud computing system, used to execute a data management method for a cloud computing system according to any one of claims 1 to 7, characterized in that: include: A data acquisition unit, which is used to acquire computer data and storage node information and transmit them to the comprehensive screening processing unit; A comprehensive screening processing unit, which is used to analyze the acquired computer data and storage node information, classify the computer data based on the data format of the computer data to obtain classified data of the same type, and obtain pre-selected nodes according to the free load of the storage node, and calculate the data format priority value corresponding to the pre-selected node, and generate standard data format information according to the priority value, and then transmit the standard data format information to the data storage analysis unit; A data storage and analysis unit, which is used to perform storage analysis on computer data according to the acquired standard data format information, the system generates a regular storage block, and divides the regular storage block into multiple groups of storage spaces, and at the same time divides the computer data based on the number of storage spaces to obtain a divided package, then performs base conversion on the divided package to obtain a converted divided package, and sorts and stores the converted divided package in different ways according to the number of different base numbers in the converted divided package to generate storage information, and then transmits the storage information to the encryption storage unit; An encryption storage unit, which is used to extract binary characters from conversion data packets in different storage spaces according to the acquired storage information, and the extraction method is based on the parity of the data capacity, and the extracted characters are mapped and replaced in combination with the corresponding mapping space, and the extracted characters are reorganized and reversed to generate a reorganized character string, and further generate encrypted information; A management information output unit is used to generate corresponding decryption information according to the acquired encryption information and store the decryption information.

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