CN110008185B - Cloud information classification processing system utilizing processing redundancy - Google Patents
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- CN110008185B CN110008185B CN201910254144.2A CN201910254144A CN110008185B CN 110008185 B CN110008185 B CN 110008185B CN 201910254144 A CN201910254144 A CN 201910254144A CN 110008185 B CN110008185 B CN 110008185B
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- G06—COMPUTING; CALCULATING OR COUNTING
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- G06F16/10—File systems; File servers
- G06F16/13—File access structures, e.g. distributed indices
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- G—PHYSICS
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F21/60—Protecting data
- G06F21/602—Providing cryptographic facilities or services
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F21/60—Protecting data
- G06F21/62—Protecting access to data via a platform, e.g. using keys or access control rules
- G06F21/6218—Protecting access to data via a platform, e.g. using keys or access control rules to a system of files or objects, e.g. local or distributed file system or database
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2221/00—Indexing scheme relating to security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F2221/21—Indexing scheme relating to G06F21/00 and subgroups addressing additional information or applications relating to security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F2221/2107—File encryption
Abstract
The invention relates to a cloud information classification processing system utilizing processing redundancy, which comprises a control end, a classification module and an index module, wherein the classification module is provided with a classification strategy, the classification strategy is used for classifying data files, and the classification strategy comprises a file classification step, a format classification step, a redundancy characteristic group definition step and a group classification induction step; the index module is configured with a plurality of index information, each index information corresponds to a data file and comprises a file group number, a format group number and a redundancy group number; the control end is provided with a calling module, and the calling module calls the corresponding data file from the classification module through the index information; and when the data file is called from the redundancy characteristic group where the data file is located, restoring the data file according to the corresponding deleted data position. The method has a better processing effect, ensures that the data redundancy simplifies the storage to the maximum extent, and reduces the space occupation of data storage.
Description
Technical Field
The present invention relates to data processing systems, and more particularly, to a cloud information classification processing system using processing redundancy.
Background
Data (Data) is a representation of facts, concepts or instructions that can be processed by either manual or automated means. After the data is interpreted and given a certain meaning, it becomes information. Data processing (data processing) is the collection, storage, retrieval, processing, transformation, and transmission of data. Particularly in the field of monitoring and the like, the data redundancy is large, so that the waste of storage space is large, and the waste is caused by the need of regularly cleaning the database, so that the data classification system for processing the data redundancy is provided.
Disclosure of Invention
The present invention is directed to a cloud information classification system using processing redundancy to solve the above problems.
In order to solve the technical problems, the technical scheme of the invention is as follows: a cloud information classification processing system utilizing processing redundancy comprises a control end, a classification module and an index module, wherein the classification module is provided with a classification strategy, the classification strategy is used for classifying data files, and the classification strategy comprises a file classification step, a format classification step, a redundancy characteristic group definition step and a group classification induction step;
a file classification step, namely dividing the data files into a plurality of file groups according to the types of the data files so as to enable the formats of the data files in one file group to be the same, and generating a file group type number according to the number of the file group in which the data files are positioned;
a format classification step, which is to divide each file group into a plurality of format groups according to the format of the data files in each file group so as to enable the formats of the data files in one format group to be the same, and generate a format group class number according to the number of the format group in which the data file is positioned;
a redundant feature group defining step, namely configuring a plurality of redundant data information in each file group and configuring a redundant feature group for each redundant data information;
the group class induction step comprises dividing the data files in each format group into the redundant feature groups according to the redundant dividing strategy, wherein the redundant dividing strategy comprises deleting data from the data files and generating corresponding deleted data positions if the data files have the data which is the same as the redundant data information, dividing the data files into the redundant feature groups corresponding to the redundant data information, and generating a redundant group class number according to the number of the redundant feature group where the data files are located;
the index module is configured with a plurality of index information, each index information corresponds to a data file and comprises a file group number, a format group number and a redundancy group number; the control end is provided with a calling module, and the calling module calls the corresponding data file from the classification module through the index information; and when the data file is called from the redundancy feature group where the data file is located, restoring the data file according to the corresponding deleted data position.
Further: the file classification step comprises a first encryption algorithm, and when the data files are divided into a file group, the data files are encrypted according to the serial numbers of the file group and the first encryption algorithm;
the calling module is configured with a first decryption algorithm corresponding to the first encryption algorithm, and when the data file is called, the data file is decrypted according to the index information and the first decryption algorithm.
Further: the format classification step comprises a second encryption algorithm, and when the data file is divided into a format group, the data file is encrypted according to the serial number of the format group and the second encryption algorithm;
and the calling module is configured with a second decryption algorithm corresponding to the second encryption algorithm, and when the data file is called, the data file is decrypted according to the index information and the second decryption algorithm.
Further: the file group comprises an audio file group, and when the type of the data file is an audio file, the data file is divided into the audio file group;
the redundancy feature group defining step comprises an audio redundancy defining sub-step, wherein the audio redundancy defining sub-step is used for defining data files under an audio file group, the audio redundancy defining sub-step comprises the steps of selecting reference redundancy audio according to the control end and generating a first redundancy range according to the reference redundancy audio, the reference redundancy information comprises the first redundancy range and the reference redundancy audio, and when data with an error between the data files and the reference redundancy audio in the reference redundancy range exists in the data files, the data files are divided into the redundancy feature group in which the reference redundancy range exists.
Further: the reference redundancy ranges include an audio range, a volume range, and a timbre range.
Further: the file group comprises a video file group, and when the type of the data file is a video file, the data file is divided into the video file group;
the redundancy feature group defining step comprises a video redundancy defining sub-step, wherein the video redundancy defining sub-step is used for defining data files under a video file group, the video redundancy defining sub-step comprises the steps of selecting a reference redundancy map area according to the control end and generating a second redundancy range according to the reference redundancy map area, the reference redundancy information comprises the second redundancy range and the reference redundancy map area, and when data with the error of the reference redundancy map area within the second redundancy range exists in the data files, the data files are divided into the redundancy feature group in which the reference redundancy range is located.
Further: the second redundancy range includes an RGB range and a luminance range.
Further: the file classification step comprises a file data structure optimization sub-step, the file data structure optimization sub-step is used for configuring a corresponding file optimization strategy for each file group, the file data structure optimization sub-step comprises executing the corresponding file optimization strategy according to the file group when the data files are divided into the file groups, and the file optimization strategy is used for optimizing the data files according to the types of the data files.
Further: the format classification step comprises a format data structure optimization sub-step, the format data structure optimization sub-step is used for configuring a corresponding format optimization strategy for each format group, the format data structure optimization sub-step comprises executing the corresponding format optimization strategy according to the format group when the data formats are divided into the format groups, and the format optimization strategy is used for optimizing the data formats according to the types of the data formats.
Further: the file group further comprises a document file group and a picture file group.
The technical effects of the invention are mainly reflected in the following aspects: through the arrangement, a better processing effect is achieved, the data redundancy is guaranteed, the storage is simplified to the maximum extent, and the occupied space of the data storage is reduced.
Drawings
FIG. 1: the invention relates to a framework schematic diagram of a cloud information classification processing system utilizing processing redundancy;
FIG. 2: the invention utilizes a grouping schematic diagram of a cloud information classification processing system for processing redundancy;
FIG. 3: the invention relates to a classification strategy flow chart of a cloud information classification processing system for processing redundancy.
Reference numerals: 1. a database; 2. a control end; 3. a classification module; 4. an indexing module; 10. a file group; 20. a format group; 30. a set of redundant features.
Detailed Description
The following detailed description of the embodiments of the present invention is provided in order to make the technical solution of the present invention easier to understand and understand.
Referring to fig. 1, a cloud information classification processing system using processing redundancy includes a control end 2, a classification module 3 and an index module 4, where the classification module 3 is configured with a classification policy, the classification policy is used to classify data files, and the classification policy includes a file classification step, a format classification step, a redundancy feature group 30 definition step and a group classification induction step; the control end 2 can be a server for serving the database 1, and the classification module 3 and the index module 4 are functional modules configured by the system.
Referring to fig. 3, a file classification step, which divides the data files into a plurality of file groups 10 according to the types of the data files, so that the formats of the data files in a file group 10 are the same, and generates a file group 10 type number according to the number of the file group 10 in which the data file is located; the file classification step is simple, and the files of all the databases 1 are reclassified according to the file types, such as video files, audio files, picture files, document files, table files, installation package files and the like, and are respectively grouped, so that the safety and reliability of the data are ensured.
A format classification step, which is to divide each file group 10 into a plurality of format groups 20 according to the format of the data file in each file group 10, so that the formats of the data files in one format group 20 are the same, and generate a format group 20 type number according to the number of the format group 20 in which the data file is located; the format classification step classifies audio files according to formats, such as MP3 format, MP4 format, WAM format, etc., so that the redundant formats are different according to the formats (due to the files of different formats).
A redundant feature group 30 defining step, configuring a plurality of redundant data information in each file group 10, and configuring a redundant feature group 30 for each redundant data information; as a core point of the present invention, the configuration of redundant data information is very critical, for example, two files have the same redundant data, and the data can be stored only once.
Referring to fig. 2, the group class summarization step includes dividing the data files in each format group 20 into the redundant feature group 30 according to the redundancy division policy, where the redundancy division policy includes, if there is a data in the data file that is the same as the redundant data information, deleting the data from the data file and generating a corresponding deleted data position, dividing the data file into the redundant feature group 30 corresponding to the redundant data information, and generating a redundant group class number according to the number of the redundant feature group 30 where the data file is located; therefore, the classification of the data is completed, any data can be extracted through the corresponding index, the data can be deleted by recording the position of the data with the same redundant data information, and the data can be added again when the data is called, so that the position information of the data only needs to be stored, and a data encryption function can be realized.
The index module 4 is used for acquiring data files, the index module 4 is configured with a plurality of index information, each index information corresponds to a data file, and the index information comprises file group 10 type numbers, format group 20 type numbers and redundancy group type numbers; the control end 2 is configured with a calling module, and the calling module calls a corresponding data file from the classification module 3 through the index information; when the data file is called from the redundancy feature set 30 in which it is located, the data file is restored according to the corresponding deleted data location. The index information points to the storage position of the data, and when the data needs to be called, the original data file is restored after the corresponding redundant data information is added, so that the data can be normally used. In another embodiment, the file classifying step includes a first encryption algorithm, and when the data file is divided into a file group 10, the data file is encrypted according to the number of the file group 10 and the first encryption algorithm; the calling module is configured with a first decryption algorithm corresponding to the first encryption algorithm, and when the data file is called, the data file is decrypted according to the index information and the first decryption algorithm. In another embodiment, the format classifying step includes a second encryption algorithm, and when the data file is divided into a format group 20, the data file is encrypted according to the number of the format group 20 and the second encryption algorithm; and the calling module is configured with a second decryption algorithm corresponding to the second encryption algorithm, and when the data file is called, the data file is decrypted according to the index information and the second decryption algorithm. The security of the file is guaranteed.
For audio files, details are given. The file group 10 includes an audio file group 10, and when the type of the data file is an audio file, the data file is divided into the audio file group 10; the redundant feature group 30 defining step includes an audio redundancy defining sub-step, the audio redundancy defining sub-step is used for defining data files under the audio file group 10, the audio redundancy defining sub-step includes selecting reference redundant audio according to the control end 2, generating a first redundant range according to the reference redundant audio, the reference redundant information includes the first redundant range and the reference redundant audio, and when data with an error between the data files and the reference redundant audio in the reference redundant range exists in the data files, dividing the data files into the redundant feature group 30 in which the reference redundant range exists. The reference redundancy ranges include an audio range, a volume range, and a timbre range. Specifically, a reference redundant audio is obtained through manual or algorithm screening, that is, the audio appears in a data file which does not pass through, and an audio range, a volume range and a tone range are defined.
For the details of the video files, the file group 10 includes a video file group 10, and when the type of the data file is a video file, the data file is divided into the video file group 10; the step of defining the redundancy feature group 30 includes a video redundancy definition sub-step, the video redundancy definition sub-step is used for defining the data file under the video file group 10, the video redundancy definition sub-step includes selecting a reference redundancy region according to the control end 2, and generating a second redundancy range according to the reference redundancy region, the reference redundancy information includes the second redundancy range and the reference redundancy region, and when data with an error within the second redundancy range from the reference redundancy region exists in the data file, the data file is divided into the redundancy feature group 30 in which the reference redundancy range exists. The second redundancy range includes an RGB range and a luminance range. Generally, for a monitoring video, the background of a video file basically does not change, so that the background can be extracted and stored uniformly by using single-frame data, and the time can be obtained by the above way.
In another embodiment, the file classification step includes a file data structure optimization sub-step, the file data structure optimization sub-step configures a corresponding file optimization policy for each file group 10, and the file data structure optimization sub-step includes executing the corresponding file optimization policy according to the file group 10 when the data file is divided into the file groups 10, and the file optimization policy optimizes the data file according to the type of the data file. In another embodiment, the format classifying step includes a format data structure optimizing sub-step, the format data structure optimizing sub-step configures a corresponding format optimizing policy for each format group 20, and the format data structure optimizing sub-step includes executing a corresponding format optimizing policy according to the format group 20 where the data format is located when the data format is divided into the format groups 20, and the format optimizing policy optimizes the data format according to the type of the data format. And optimizing the file according to the data format through the optimization step, so that the storage effect is improved.
The above are only typical examples of the present invention, and besides, the present invention may have other embodiments, and all the technical solutions formed by equivalent substitutions or equivalent changes are within the scope of the present invention as claimed.
Claims (10)
1. The utility model provides a utilize and handle redundant high in clouds information classification processing system which characterized in that: the system comprises a control terminal, a classification module and an index module, wherein the classification module is configured with a classification strategy, the classification strategy is used for classifying data files, and the classification strategy comprises a file classification step, a format classification step, a redundancy feature group definition step and a group class induction step;
a file classification step, namely dividing the data files into a plurality of file groups according to the types of the data files so as to enable the types of the data files in one file group to be the same, and generating a file group type number according to the number of the file group in which the data files are positioned;
a format classification step, which is to divide each file group into a plurality of format groups according to the format of the data files in each file group so as to enable the formats of the data files in one format group to be the same, and generate a format group class number according to the number of the format group in which the data file is positioned;
a redundant feature group defining step, namely configuring a plurality of redundant data information in each file group and configuring a redundant feature group for each redundant data information;
the group class induction step comprises dividing the data files in each format group into the redundant feature groups according to the redundant dividing strategy, wherein the redundant dividing strategy comprises deleting data from the data files and generating corresponding deleted data positions if the data files have the data which is the same as the redundant data information, dividing the data files into the redundant feature groups corresponding to the redundant data information, and generating a redundant group class number according to the number of the redundant feature group where the data files are located;
the index module is configured with a plurality of index information, each index information corresponds to a data file and comprises a file group number, a format group number and a redundancy group number; the control end is provided with a calling module, and the calling module calls the corresponding data file from the classification module through the index information; and when the data file is called from the redundancy feature group where the data file is located, restoring the data file according to the corresponding deleted data position.
2. The cloud-based information classification processing system using processing redundancy of claim 1, wherein: the file classification step comprises a first encryption algorithm, and when the data files are divided into a file group, the data files are encrypted according to the serial numbers of the file group and the first encryption algorithm;
the calling module is configured with a first decryption algorithm corresponding to the first encryption algorithm, and when the data file is called, the data file is decrypted according to the index information and the first decryption algorithm.
3. The cloud-based information classification processing system using processing redundancy of claim 1, wherein: the format classification step comprises a second encryption algorithm, and when the data file is divided into a format group, the data file is encrypted according to the serial number of the format group and the second encryption algorithm;
and the calling module is configured with a second decryption algorithm corresponding to the second encryption algorithm, and when the data file is called, the data file is decrypted according to the index information and the second decryption algorithm.
4. The cloud-based information classification processing system using processing redundancy of claim 1, wherein: the file group comprises an audio file group, and when the type of the data file is an audio file, the data file is divided into the audio file group;
the redundancy feature group defining step comprises an audio redundancy defining sub-step, wherein the audio redundancy defining sub-step is used for defining data files under an audio file group, the audio redundancy defining sub-step comprises the steps of selecting reference redundancy audio according to the control end and generating a first redundancy range according to the reference redundancy audio, the reference redundancy information comprises the first redundancy range and the reference redundancy audio, and when data with an error between the data files and the reference redundancy audio in the reference redundancy range exists in the data files, the data files are divided into the redundancy feature group in which the reference redundancy range exists.
5. The cloud-based information classification processing system using processing redundancy of claim 4, wherein: the reference redundancy ranges include an audio range, a volume range, and a timbre range.
6. The cloud-based information classification processing system using processing redundancy of claim 1, wherein: the file group comprises a video file group, and when the type of the data file is a video file, the data file is divided into the video file group;
the redundancy feature group defining step comprises a video redundancy defining sub-step, wherein the video redundancy defining sub-step is used for defining data files under a video file group, the video redundancy defining sub-step comprises the steps of selecting a reference redundancy map area according to the control end and generating a second redundancy range according to the reference redundancy map area, the reference redundancy information comprises the second redundancy range and the reference redundancy map area, and when data with the error of the reference redundancy map area within the second redundancy range exists in the data files, the data files are divided into the redundancy feature group in which the reference redundancy range is located.
7. The cloud-based information classification processing system using processing redundancy of claim 6, wherein: the second redundancy range includes an RGB range and a luminance range.
8. The cloud-based information classification processing system using processing redundancy of claim 1, wherein: the file classification step comprises a file data structure optimization sub-step, the file data structure optimization sub-step is used for configuring a corresponding file optimization strategy for each file group, the file data structure optimization sub-step comprises executing the corresponding file optimization strategy according to the file group when the data files are divided into the file groups, and the file optimization strategy is used for optimizing the data files according to the types of the data files.
9. The cloud-based information classification processing system using processing redundancy of claim 1, wherein: the format classification step comprises a format data structure optimization sub-step, the format data structure optimization sub-step is used for configuring a corresponding format optimization strategy for each format group, the format data structure optimization sub-step comprises executing the corresponding format optimization strategy according to the format group when the data formats are divided into the format groups, and the format optimization strategy is used for optimizing the data formats according to the types of the data formats.
10. The cloud-based information classification processing system using processing redundancy of claim 1, wherein: the file group further comprises a document file group and a picture file group.
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