CN115686379A - Method and system for optimizing management of blank data area in flash memory - Google Patents
Method and system for optimizing management of blank data area in flash memory Download PDFInfo
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Abstract
The invention provides a method and a system for optimizing management of a blank data area in a flash memory, which are applied to the technical field of semiconductor storage. The method comprises the following steps: acquiring blank data area information, blank area quantity and blank area space; determining block cluster division information based on the blank space number and the blank space; performing cluster division on the blank data area information according to the block cluster division information to obtain a blank block division cluster; setting response parameters according to the blank block partition cluster, and determining a block response parameter mapping table; and comparing the storage parameter information based on the information to be stored in the block response parameter mapping table, determining the matched blank area information, and controlling the matched blank area to respond, so that the space optimization of the blank data area in the flash memory is achieved, the classified management of the storage content is facilitated, the response speed of the blank data area in the flash memory is improved through the setting of the response priority, and the technical effect of improving the storage performance of the flash memory is further improved.
Description
Technical Field
The invention relates to the technical field of semiconductor storage, in particular to a processing method and a processing system for optimizing management of a blank data area in a flash memory.
Background
Flash memories can retain stored information for long periods of time in the event of a power failure.
In recent years, in memory devices, flash memories have been popular among researchers and production applications due to their characteristics of being able to retain stored information even when power is off, and being highly integrated, and are often used in electronic products such as digital cameras, digital televisions, and mobile phones.
In the prior art, most attention is paid to improvement or design of a flash memory structure, and in the data storage process, data to be stored enter which storage unit is random, space optimization among the storage units is not considered, and further flash memory efficiency is influenced.
Disclosure of Invention
The application provides a method and a system for optimizing management of a blank data area in a flash memory, which are used for solving the technical problem that space optimization is lacked among storage units in a flash memory chip in the prior art, so that the efficiency of the flash memory is influenced, and the technical effects of automatically performing space optimization on a flash memory storage space and further improving the response speed of the blank data area in the flash memory are achieved.
In view of the foregoing, the present application provides a method and system for optimizing management of blank data areas in a flash memory.
In a first aspect of the present application, there is provided a method for optimizing management of blank data areas in a flash memory, the method comprising: acquiring blank data area information; obtaining the blank area quantity and the blank area space according to the blank data area information; determining block cluster division information based on the blank space number and the blank space; performing cluster division on the blank data area information according to the block cluster division information to obtain blank block division clusters; setting response parameters according to the blank block division clusters, and determining a block response parameter mapping table, wherein the block response parameter mapping table comprises blank information, response parameter information and response priority; obtaining information to be stored, and extracting storage parameters of the information to be stored to obtain storage parameter information; and performing response parameter information and response priority ratio comparison in the block response parameter mapping table based on the storage parameter information, determining matched blank area information, and generating a response instruction for controlling the matched blank area to respond.
In a second aspect of the present application, there is provided a system for optimizing management of blank data areas in a flash memory, the system comprising: a first obtaining unit configured to obtain blank data area information; a first processing unit, configured to obtain a blank area number and a blank area space according to the blank data area information; a second processing unit configured to determine block cluster division information based on the blank area number and the blank area space; a third processing unit, configured to perform cluster division on the blank data area information according to the block cluster division information, so as to obtain blank block division clusters; a fourth processing unit, configured to perform response parameter setting according to the blank block partition cluster, and determine a block response parameter mapping table, where the block response parameter mapping table includes blank information, response parameter information, and a response priority; the fifth processing unit is used for obtaining information to be stored and extracting storage parameters of the information to be stored to obtain storage parameter information; and the first execution unit is used for performing response parameter information and response priority ratio comparison in the block response parameter mapping table based on the storage parameter information, determining matched blank area information, and generating a response instruction for controlling the matched blank area to respond.
In a third aspect of the present application, a system for optimizing management of blank data areas in a flash memory is provided, including: a processor coupled to a memory for storing a program that, when executed by the processor, causes a system to perform the steps of the method according to the first aspect.
In a fourth aspect of the present application, a computer-readable storage medium is provided, on which a computer program is stored, which computer program, when being executed by a processor, carries out the steps of the method according to the first aspect.
One or more technical solutions provided in the present application have at least the following technical effects or advantages:
the method comprises the steps of clustering blank data areas in a flash memory according to block clustering division information to obtain blank block clustering division, setting response parameters according to the blank block clustering division to determine a block response parameter mapping table, wherein the block response parameter mapping table comprises the blank information, the response parameter information and the response priority, comparing the response priority ratio of information to be stored and a block influence parameter mapping table to determine the priority response matching blank area, realizing the fast storage matching with the information to be stored, and simultaneously carrying out the parameter matching on the blank area information based on the storage parameters of the information to be stored to realize the classified storage management, so that the space optimization of the blank data areas in the flash memory is achieved, the classified management of storage contents is facilitated, the response speed of the blank data areas in the flash memory is improved through the setting of the response priority, and the technical effect of the storage performance of the flash memory is further improved.
The foregoing description is only an overview of the technical solutions of the present application, and the present application can be implemented according to the content of the description in order to make the technical means of the present application more clearly understood, and the following detailed description of the present application is given in order to make the above and other objects, features, and advantages of the present application more clearly understandable.
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FIG. 1 is a flow chart illustrating a method for optimizing white data area management in a flash memory according to the present invention;
FIG. 2 is a schematic flow chart illustrating the determination of block cluster partition information in a method for optimizing white data area management in a flash memory according to the present application;
FIG. 3 is a schematic flow chart illustrating obtaining storage parameter information in a method for optimizing management of blank data areas in a flash memory according to the present invention;
FIG. 4 is a block diagram illustrating a system for optimizing management of blank data areas in a flash memory according to the present invention;
fig. 5 is a schematic structural diagram of an exemplary electronic device of the present application.
Description of reference numerals: a first obtaining unit 11, a first processing unit 12, a second processing unit 13, a third processing unit 14, a fourth processing unit 15, a fifth processing unit 16, a first execution unit 17, an electronic device 300, a memory 301, a processor 302, a communication interface 303, and a bus architecture 304.
Detailed Description
The application provides a method and a system for optimizing management of a blank data area in a flash memory, which are used for solving the technical problem that in the prior art, space optimization is lacked among storage units in a flash memory chip, and further the flash memory efficiency is influenced.
In view of the above technical problems, the technical solution provided by the present application has the following general idea:
the method provided by the embodiment of the application carries out cluster division on a blank data area in a flash memory according to block cluster division information to obtain a blank block division cluster, carries out response parameter setting according to the blank block division cluster, and determines a block response parameter mapping table, wherein the block response parameter mapping table comprises blank information, response parameter information and response priority, and the extracted storage parameter information of the information to be stored is compared with the information in the block response parameter mapping table to further determine the matched blank area and respond.
Having described the basic principles of the present application, the technical solutions in the present application will be described clearly and completely with reference to the accompanying drawings, and it should be understood that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments of the present application, and the present application is not limited to the exemplary embodiments described herein. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present application without making any creative effort, shall fall within the protection scope of the present application. It should be further noted that, for the convenience of description, only some but not all of the elements relevant to the present application are shown in the drawings.
Example one
As shown in fig. 1, the present application provides a method for optimizing management of a blank data area in a flash memory, the method comprising:
s100: acquiring blank data area information;
specifically, the blank data area information is an unoccupied area in the flash memory, optionally, the total storage information of the flash memory and the existing storage information in the flash memory are obtained, and then the blank data area information is obtained, or according to the attribute code of each block in the flash memory, the attribute code is a code used for identifying the storage state in the flash memory, when the flash memory is subjected to storage operation, the attribute code can be updated in real time according to the storage occupation condition, so that the occupation condition of the flash memory block can be grasped in real time through the attribute code, and the blank area is determined by traversing and comparing the code characteristics of the blank area in the attribute code, wherein the blank data area can include a storage blank area and a storage redundant area; the storage blank block is a storage block which does not store data in the flash memory; the storage redundancy area is a storage block in which part of data is stored and the rest is not occupied in the flash memory.
S200: obtaining the blank area quantity and the blank area space according to the blank data area information;
specifically, after the blank data area information is obtained, the number of blank areas and the blank space are further obtained, and for the blank information obtained from the blank data area information, the number of blank blocks and the size of the corresponding blank space are extracted, where the number of the blank areas is the number of all blank areas of the current flash memory, and the size of the storage space of each blank area corresponding to the number of the blank areas is the blank space.
Illustratively, the blank data area information comprises a storage blank block and a storage redundant area, the storage blank block and the storage redundant area are obtained according to the blank data area information, and the number of the blank data areas and the space of the blank data areas are obtained according to the storage blank block; obtaining the number of redundant areas and the storage space of the redundant areas according to the storage redundant areas; the blank area number is the sum of the blank data number and the redundant area number; the blank space is the sum of a blank data area space and a redundant area storage space, for example, the number of blocks in the flash memory that do not store any data is 30, the size of each block space is 100M, or the spaces may be different in size, the number of storage blocks in the flash memory that store part of data and remain part of data and are not occupied is 10, the size of each remaining part of storage blocks that are not occupied is 50M, or the spaces may be different in size, then the number of blank spaces is 40, and the blank space is 3500M.
S300: determining block cluster division information based on the blank space number and the blank space;
s400: performing cluster division on the blank data area information according to the block cluster division information to obtain blank block division clusters;
specifically, the block cluster division information is information required by a hierarchical feature rule established for the blank area, for example, the storage redundant area and the storage blank area in the blank area may be classified hierarchically to form two large groups of the storage redundant area and the storage blank area, and then the two large groups of the storage redundant area and the storage blank area may be further subdivided.
In the process of subdividing the large group of storage redundant areas, the unoccupied space in the block for storing the information is the storage redundant area, and for example, the storage attribute of the storage redundant area (for example, different attributes such as video images, pictures, documents, and the like) may be divided according to the attribute of the stored information, or the size of the space of the storage redundant area may be divided; in the process of subdividing the large group of memory space blocks, the memory space blocks can be divided by adopting a space size method.
Optionally, when the blank block division clustering is performed, the machine learning model is used to improve the operation efficiency and reliability, specifically, each hierarchical feature is determined based on the hierarchical requirement in the block cluster division information, a hierarchical model is constructed by using each hierarchical feature, the blank data area information is input into the hierarchical model after the construction training to obtain each hierarchical result, and the blank block division clustering is established according to the hierarchical management among each hierarchical result.
Further, cluster division is performed on the blank data area information according to the block cluster division information, so as to obtain blank block division clusters.
The blank data area information is subjected to cluster division to obtain blank block division clusters, so that corresponding areas respond to the blank data when the data are stored subsequently, space optimization of the blank areas of the flash memory is achieved, the blank areas are stored into corresponding storage areas according to different attributes and/or sizes of the data to be stored, the corresponding speed of the corresponding storage areas is further improved, and the storage efficiency of the flash memory is improved.
S500: setting response parameters according to the blank block partition cluster, and determining a block response parameter mapping table, wherein the block response parameter mapping table comprises blank information, response parameter information and response priority;
specifically, in order to classify the flash memory storage space to optimize the flash memory storage space and improve the utilization rate of the flash memory storage space, a block response parameter mapping table needs to be obtained.
In the embodiment of the present application, a response parameter is set for an obtained blank block partition cluster, and a block response parameter mapping table is determined, where the block response parameter mapping table includes blank information, response parameter information, and a response priority, where the blank information, the response parameter information, and the response priority form a one-to-one correspondence relationship, and the obtained block response parameter mapping table classifies and summarizes blank areas, where the blank information includes a size of a blank storage space and a port link for performing block storage, the response parameter information is parameter information matched when the blank area responds, and the response priority is a response level of each parameter corresponding to the response parameter.
Illustratively, any variable in the block response parameter mapping table can implement fast mapping with other two variables, each blank area information corresponds to a response setting priority relationship of its respective parameter, when the response parameter information is successfully matched and the priority of the matched parameter set in the blank area is first, the block performs fast response to obtain the corresponding blank area information, implement fast matching with the blank area, thereby implementing optimization of the storage space and facilitating data management; on the other hand, the obtained block response parameter mapping table can be used for comparing with information to be stored, so that an optimal response area is obtained for storing the information to be stored, the response speed of the flash memory is improved, and the use performance of the flash memory is further improved.
S600: obtaining information to be stored, and extracting storage parameters of the information to be stored to obtain storage parameter information;
specifically, the information to be stored is information that needs to be stored in the flash memory, and may include videos, pictures, and the like, the storage parameter information of the information to be stored is extracted by using an existing data feature reading method, and the storage parameter information may include attribute parameter information, size parameter information, and the like.
S700: and performing response parameter information and response priority ratio comparison in the block response parameter mapping table based on the storage parameter information, determining matched blank area information, and controlling the matched blank area to respond.
Specifically, the obtained parameter information of the information to be stored is compared with the response parameter information and the response priority in the block response parameter mapping table, the matched blank area information is determined according to the one-to-one correspondence relationship among the blank area information, the response parameter information and the response priority, the response instruction is generated to control the matched blank area to respond to the information to be stored, and therefore the information to be stored is rapidly stored.
The method comprises the steps of carrying out cluster division on a blank data area in a flash memory according to block cluster division information to obtain a blank block division cluster, carrying out response parameter setting according to the blank block division cluster to determine a block response parameter mapping table, wherein the block response parameter mapping table comprises blank information, response parameter information and response priority, comparing the extracted storage parameter information of the information to be stored with the information in the block response parameter mapping table to further determine a matched blank area and respond, so that space optimization of the blank area of the flash memory is realized, the blank area is stored into a corresponding storage area according to different attributes and/or sizes of the data to be stored, the response speed of the corresponding storage area is further improved, and the storage efficiency of the flash memory is improved.
Step S100 in the method provided in the embodiment of the present application includes:
step S110: obtaining the storage information of the flash memory;
step S120: obtaining a stored block and a storage blank block according to the storage information of the flash memory;
step S130: obtaining a storage redundant area according to the stored block;
step S140: and acquiring the blank data area information according to the storage blank block and the storage redundant area.
Specifically, total storage information of the flash memory and existing storage information in the flash memory are obtained, and blank data area information of the flash memory is obtained according to the total storage information of the flash memory and the existing storage information in the flash memory, wherein the blank data area information in the flash memory is storage block information of data which is not stored in the flash memory and storage block information of the remaining part of the stored part of the data which is not occupied.
Preferably, the storage information of the flash memory is obtained, and the block and the storage blank block of which the information is stored are obtained according to the stored information in the flash memory; according to the stored block, obtaining a storage redundant area, namely, the stored information only occupies part of the space of the block, the rest space of the block is not occupied, and the unoccupied space in the block for storing the information is the storage redundant area; and the obtained storage blank block and the storage redundant area jointly form the blank data area, so that blank data area information is obtained, and a basis is provided for cluster division of the subsequent blank data area.
Step S200 in the method provided in the embodiment of the present application includes:
s210: acquiring the storage blank blocks from the blank data area information, and acquiring the number of blank data areas and blank storage space, wherein each blank block in the number of blank data areas has a first corresponding relation with the blank storage space;
s220: according to the storage redundant area, obtaining the number of redundant areas and the storage space of the redundant area, wherein each redundant area in the number of redundant areas and the redundant storage space have a second corresponding relation;
s230: and obtaining the blank space number based on the blank data area number and the redundant area number, and obtaining the blank space based on the blank storage space and the redundant storage space.
Specifically, in order to obtain the blank space number and the blank space, the storage blank block and the storage redundant area are obtained from the blank data area information, the storage blank block is used to obtain the blank data area number, the blank data area includes one or more blank blocks, the size of the storage space of each blank block, that is, the blank storage space, is obtained, and each blank block included in the blank data area has a first corresponding relationship with the size of the storage space of the blank block, that is, each blank block in the blank data area number corresponds to the blank storage space one by one; obtaining the number of redundant areas and the storage space of the redundant areas by using the storage redundant areas, wherein each redundant area in the number of the redundant areas has a second corresponding relation with the redundant storage space, namely, each redundant area in the number of the redundant areas corresponds to the redundant storage space one by one; the blank area number is the sum of the blank data area number and the redundant area number; the blank storage space is the sum of the blank storage space and the redundant storage space; through the technical characteristics, all the spaces not occupied by the data in the flash memory are counted, and a stable data basis is provided for the subsequent optimization management of the blank data area in the flash memory.
As shown in fig. 2, step S300 in the method provided in the embodiment of the present application includes:
s310: performing first classification on redundant areas and blank blocks in the blank area quantity, and taking attribute characteristics of the redundant areas and the blank blocks as first classification characteristics to obtain a first cluster and a second cluster, wherein the first cluster corresponds to the redundant areas, and the second cluster corresponds to the blank blocks;
s320: performing second classification on the second cluster according to preset storage space classification information based on the blank space, and taking space classification characteristics as second classification characteristics of the second cluster;
s330: acquiring storage area information corresponding to a redundant area, and performing data characteristic analysis according to the redundant area storage area information to acquire storage data attribute characteristics;
s340: performing second classification on the first cluster according to the stored data attribute characteristics, and taking the stored data attribute characteristics as second classification characteristics of the first cluster;
s350: performing attribute residual grading on the redundant area of the first cluster based on the blank space, and taking an attribute residual grading characteristic as a third grading characteristic of the first cluster;
s360: determining the block cluster partitioning information based on the first, second, and third ranking features.
Specifically, based on the number of blank areas, classifying the features of the blank areas according to the attributes of redundant areas and blank data areas in the blank areas to obtain a first cluster and a second cluster, wherein the first cluster corresponds to the redundant areas, and the second cluster corresponds to blank areas in the blank data areas to form first classification features; that is, the blank area includes a blank data area and a redundant area storing data but having a remaining unoccupied space, and the blank area is divided into a redundant area cluster and a blank block cluster according to attributes of the blank data area and the redundant area; the redundant area cluster and the blank block cluster are then further divided.
And performing secondary division on the second cluster according to preset storage space division information based on the blank space, and taking the space division characteristics as second classification characteristics of the second cluster, wherein the preset storage space division information can be a super-large storage space, a large storage space and a general storage space, for example, the space size of more than or equal to 200M is the super-large storage space, the space size between 200 and 100M belongs to the large storage space, and the space size of less than or equal to 100M is the general storage space.
And performing data characteristic analysis on the stored area information where the redundant area is located to obtain attribute characteristics of stored partial data, such as video images, pictures, documents and the like, grading the first cluster, namely the redundant area cluster, according to the attributes of the stored information, and taking the stored data attribute characteristics as second grading characteristics of the first cluster.
And dividing the redundant area of the first cluster, namely, the redundant area of the space which stores partial data and is not occupied by the rest part based on the blank space to form a third classification characteristic of the first cluster, namely, dividing the redundant area by the space size.
And combining the obtained first grading characteristic, second grading characteristic and third grading characteristic to determine the block cluster division information. According to the method and the device, the classification features which are possibly many are obtained to construct block cluster division information, the cushion is made for division of a subsequent blank data area, and when the information to be stored is stored, the appropriate area can be rapidly matched, so that space optimization of a flash memory area is achieved, and the corresponding storage area is enabled to respond rapidly.
Optionally, the first hierarchical feature, the second hierarchical feature, and the third hierarchical feature are used to determine block cluster division information, a hierarchical model is constructed through each hierarchical feature, the hierarchical model is a computer processing model learned through a machine and includes a three-layer processing structure, the first layer uses the first hierarchical feature as a classification feature to classify input blank information to obtain an output result, the output first cluster and the output second cluster are used as input data to enter a second processing layer, the second processing layer uses the second hierarchical feature as a classification feature, wherein, the blank type of a cluster is matched with the corresponding secondary hierarchical feature, the cluster of blank block features uses the second hierarchical feature of the first cluster as a classification feature to perform subgroup division, and is established in a sub-relationship of the first cluster, information with redundant zone features uses the second hierarchical feature of the second cluster as a classification feature to classify the second cluster to obtain a sub-set of the second cluster, and is established in a sub-relationship of the second cluster, the output result of the second processing layer is input as an attribute of the third processing layer, the classification feature is directly established in a classification function of the third hierarchical feature, and the classification information is directly established in a classification process, and the third hierarchical feature is directly established in the third hierarchical relationship of the third hierarchical feature, and the classification of the third hierarchical feature, the output of the hierarchical model, and the hierarchical model is established.
Step S500 in the method provided in the embodiment of the present application includes:
s510: establishing a space code according to the second cluster and the space division characteristics;
s520: establishing a space matching priority based on the space coding, taking the space matching priority as a first cluster response priority, taking the space coding as response parameter information, and establishing a first mapping relation with blank space information in the second cluster;
s530: establishing attribute codes according to the attribute characteristics of the first cluster and the stored data;
s540: establishing a residual grade code according to the first cluster and the attribute residual grade dividing characteristics;
s550: the attribute codes are used as first cluster first priority, the residual grade codes are used as first cluster second priority, response priority of the first clusters is determined based on the first priority and the second priority, response parameter information of the first clusters is coded based on the attribute codes and the residual grade codes, and a second mapping relation with the blank area information in the second clusters is established;
s560: and determining the block response parameter mapping table based on the first mapping relation and the second mapping relation.
Specifically, for a second cluster formed by blank blocks, spatial features are preferentially taken as division features, spatial codes are established, spatial matching priorities are established based on the spatial codes, the spatial matching priorities are taken as first cluster response priorities, that is, corresponding spatial codes are established according to the sizes of the blank blocks, one blank block corresponds to one spatial code, then corresponding matching priorities are established according to the spatial sizes of the blank blocks based on the spatial codes, and the spatial codes are taken as response parameter information, wherein the response parameter information, the blank block information and the priorities are in one-to-one correspondence, for example, the space size of 100M is required, the corresponding spatial codes are found from the second cluster, and blank areas corresponding to the spatial codes respond.
For a first cluster formed by the redundant area, the attribute feature of the stored data is preferentially taken as a division feature, corresponding attribute codes are established, then the spatial feature is taken as a division feature, and residual level codes are established, namely, for the redundant area, the attribute code established by the attribute feature of the stored data is taken as a first priority of the first cluster, and the residual level code is taken as a second priority of the first cluster. And taking the first priority and the second priority as response priorities of the first cluster, and taking attribute coding and residual level coding as response parameter information of the first cluster, wherein the response parameter information, the redundant area information and the priorities are in one-to-one correspondence. For example, when data is stored, whether the type of the stored data is consistent with the stored information attribute is preferentially judged, if so, a consistent redundant area is preferentially considered for responding, and if a plurality of redundant areas with the same attribute exist, the redundant areas are distributed according to the size of the redundant area space, so that the classification and optimization of the flash memory space are realized, and the utilization rate of the flash memory space is improved.
As shown in fig. 3, step S600 in the method provided in the embodiment of the present application includes:
s610: obtaining the size of stored data according to the information to be stored;
s620: judging whether the size of the stored data meets the requirement of a preset super-large file or not;
s630: if the storage parameter information meets the requirement, obtaining a spatial matching code, and taking the spatial matching code as the storage parameter information;
s640: when the information does not meet the requirement, carrying out data characteristic analysis on the information to be stored to obtain data attribute characteristics;
s650: and obtaining an attribute matching code according to the data attribute characteristics, and taking the attribute matching code and the size of the stored data as the storage parameter information.
Specifically, for the storage information to be stored, firstly, the size of the data to be stored is obtained, whether the size of the storage data meets the preset requirement of an oversized file is judged, if the size of the data to be stored exceeds the preset requirement of the oversized file, the data to be stored is directly matched with the large space and the small space of a blank block, a corresponding space matching code is obtained, the space matching code is used as the storage parameter information of the data to be stored, and then the blank block corresponding to the space matching code responds to the information to be stored.
If the size of the data to be stored does not meet the requirement of a preset super-large file, performing characteristic attribute analysis on the data to be stored to obtain attribute characteristics of the data to be stored, judging whether the attribute characteristics of the data to be stored are consistent with the attributes of the stored data containing a redundant area or not according to the attribute characteristics of the data to be stored to further obtain attribute matching codes, using the attribute matching codes and the size of the data to be stored as the storage parameter information, and if the size of the data to be stored does not meet the requirement of the preset super-large file, performing matching according to the space size.
Furthermore, in the corresponding data reading stage, the data response priority in the block response parameter mapping table is also applied, matching is preferentially performed according to the spatial priority when the read data is the super-large data characteristic, and the response speed of reading is accelerated according to the data attribute preferential matching when the read data does not meet the super-large data requirement. Correspondingly, after data storage, the blank area information in the block response parameter mapping table is adjusted to be storage information, the position of the storage information and the interface information are stored, a read block response parameter mapping table during reading application is constructed, the read block response parameter mapping table and the read block response parameter mapping table during storage have the same mapping structure, and the response priority and the response parameters are the same.
For example, when a file is read, firstly, attribute judgment is carried out on the read file, a primary attribute is determined, the primary attribute is an attribute with the highest identification degree of the file, for example, for an oversized file, the number of the oversized file is small, and for the oversized file, the primary attribute is a space attribute of the oversized file, so that the storage information, namely storage area information, with priority space response parameters according to the oversized attribute in a block response parameter mapping table corresponds to blank area information during storage, the response search range is narrowed, further matching is carried out in a storage space with successful priority matching, and the matching range is reduced, so that the matching process is shortened, and the reading response speed is accelerated.
After step S650 in the method provided in the embodiment of the present application, the method further includes:
s651: matching the attribute matching code with the block response parameter mapping table to obtain a matching result;
s652: when the matching result is matching failure, determining the attribute of the information to be stored according to the attribute matching code;
s653: performing information expansion characteristic analysis according to the attribute of the information to be stored to obtain storage information expansion characteristics;
s654: acquiring a space storage requirement based on the storage information expansion characteristics and the attribute of the information to be stored;
s655: and generating a space matching code according to the space storage requirement to match in the block response parameter mapping table to obtain the matching blank space information.
Specifically, the attribute matching code of the information to be stored is matched with the block response parameter mapping table to obtain a matching result, and when the attribute matching code is matched with the block response parameter mapping table, the matched blank block is controlled to respond.
When the matching of the attribute matching code and the block response parameter mapping table fails, the file with the same attribute as the information to be stored does not exist in the currently stored file, a blank block needs to be newly opened for storing the information to be stored, the attribute of the information to be stored is determined according to the attribute matching code, information expansion characteristic analysis is carried out according to the attribute of the information to be stored, and the expansion characteristic of the stored information is obtained; for example, by obtaining the attribute of the information to be stored, and determining whether the attribute of the information to be stored has expandability according to the historical information attribute database, for example, the information to be stored is a bill file, and as time goes on, the file capacity is continuously increased, the expandability of the file is considered, and the file is stored in a blank block with a large space, and if the file is only a storage document and the content is not updated as time goes on, the corresponding blank block can be matched according to the size of the file for storage.
Furthermore, for the analysis of the expansion characteristics of the stored information, the information to be stored can be input into the supervised learning model trained by using the historical data by means of the supervised learning model, the expansion characteristics of the information to be stored are output, the accurate determination of the expansion characteristics of the information to be stored is ensured by using the supervised learning model, and then the response of the corresponding blank block to the information to be stored is ensured.
Furthermore, the method and the device for obtaining the matching blank area information obtain a space storage requirement based on the obtained storage information expansion characteristics and the information attribute to be stored, and generate a space matching code according to the space storage requirement to match in the block response parameter mapping table to obtain the matching blank area information.
To sum up, the embodiment of the present application has at least the following technical effects:
1. the method comprises the steps of clustering blank data areas in a flash memory according to block clustering division information, setting response parameters according to the blank block clustering division, determining a block response parameter mapping table, wherein the block response parameter mapping table comprises blank area information, response parameter information and response priority, comparing the information to be stored with a block influence parameter mapping table according to the response priority, determining the priority response matching blank area, realizing the fast storage matching with the information to be stored, and simultaneously carrying out parameter matching on the blank area information based on the storage parameters of the information to be stored to realize the classified storage management, so that the space optimization of the blank data areas in the flash memory is achieved, the classified management of storage contents is facilitated, the response speed of the blank data areas in the flash memory is improved through the setting of the response priority, and the technical effect of improving the storage performance of the flash memory is further achieved.
2. When the first grading characteristic, the second grading characteristic and the third grading characteristic are carried out to determine the block clustering division information, each grading characteristic is utilized to construct a grading model, the grading model is a computer processing model which is learned through a machine, clustering is carried out on the blank area information through the grading model, the block clustering division efficiency is improved, the intelligent degree is high, and the technical effect that the reliability of a clustering division result is ensured by carrying out data grading operation through the computer model is achieved.
3. The method comprises the steps of setting response parameters, blank information and response priorities in a block response parameter mapping table, similarly applying the data response priorities in the block response parameter mapping table in a data reading stage, matching the priorities in the block response parameter mapping table for the first identification attribute of data to be read, and responding corresponding blocks according to matching results, so that the matching range is reduced, the matching process is shortened, the reading response speed is increased, priority matching is performed according to the response parameters of a storage space during storage and reading, the storage response process is optimized, and the storage management intelligence level and the response speed of the flash memory can be effectively improved.
4. Performing information expansion characteristic analysis according to the attribute of the information to be stored in the blank block matching process by storing data without the same attribute to obtain the stored information expansion characteristic; and based on the storage information expansion characteristics and the attribute of the information to be stored, obtaining the space storage requirement, matching in the block response parameter mapping table, and obtaining the matched blank area information. The technical effects of pertinently matching the storage capacity space according to the expansion characteristics of the storage data to ensure the classification management of the subsequent files and improve the expansibility requirement of the blank block storage classification management are achieved.
Example two
Based on the same inventive concept as the method for optimizing management of blank data areas in the flash memory in the foregoing embodiment, as shown in fig. 4, the present application provides a system for optimizing management of blank data areas in the flash memory, wherein the system includes:
a first obtaining unit 11 for obtaining blank data area information;
a first processing unit 12, configured to obtain a blank area number and a blank area space according to the blank data area information;
a second processing unit 13, configured to determine block cluster division information based on the blank space amount and the blank space;
a third processing unit 14, configured to perform cluster division on the blank data area information according to the block cluster division information, so as to obtain blank block division clusters;
a fourth processing unit 15, configured to perform response parameter setting according to the blank block partition cluster, and determine a block response parameter mapping table, where the block response parameter mapping table includes blank information, response parameter information, and response priority;
the fifth processing unit 16 is configured to obtain information to be stored, and perform storage parameter extraction on the information to be stored to obtain storage parameter information;
a first executing unit 17, configured to perform a response parameter information and response priority ratio comparison in the block response parameter mapping table based on the storage parameter information, determine matching blank information, and generate a response instruction for controlling a response of a matching blank block.
Further, the system further comprises:
a second obtaining unit that obtains flash memory storage information;
a third obtaining unit, for obtaining the stored block and the storage blank block according to the storage information of the flash memory;
a fourth obtaining unit configured to obtain a storage redundancy area according to the stored block;
and the fifth obtaining unit is used for obtaining the blank data area information according to the storage blank block and the storage redundant area.
Further, the system further comprises:
a sixth obtaining unit, configured to obtain the storage blank blocks from the blank data area information, and obtain the number of blank data areas and a blank storage space, where each blank block in the number of blank data areas and the blank storage space have a first corresponding relationship;
a seventh obtaining unit, configured to obtain, according to the redundant area, a number of redundant areas and a redundant area storage space, where each redundant area in the number of redundant areas and the redundant storage space have a second correspondence relationship;
an eighth obtaining unit that obtains the blank area number based on the blank data area number and the redundant area number, and obtains the blank area space based on the blank storage space and the redundant storage space.
Further, the system further comprises:
a sixth processing unit, configured to perform first classification based on a redundant area and a blank area in the blank area number, and obtain a first cluster and a second cluster by using attribute features of the redundant area and the blank area as first classification features, where the first cluster corresponds to the redundant area and the second cluster corresponds to the blank area;
a seventh processing unit, configured to perform second classification on the second cluster according to preset storage space division information based on the empty space, and use a space division feature as a second classification feature of the second cluster;
the eighth processing unit is used for acquiring the storage area information corresponding to the redundant area and carrying out data characteristic analysis according to the storage area information of the redundant area to acquire the attribute characteristics of the stored data;
a ninth processing unit, configured to perform second classification on the first cluster according to the stored data attribute feature, and use the stored data attribute feature as a second classification feature of the first cluster;
a tenth processing unit that performs attribute remaining ranking on the redundant area of the first cluster based on the blank space, and takes an attribute remaining ranking feature as a third ranking feature of the first cluster;
an eleventh processing unit that determines the block cluster division information based on the first, second, and third ranking features.
Further, the system further comprises:
the twelfth processing unit is used for establishing a space code according to the second cluster and the space division characteristics;
a thirteenth processing unit, configured to construct a spatial matching priority based on the spatial coding, use the spatial matching priority as a first cluster response priority, use the spatial coding as response parameter information, and perform first mapping relationship establishment with blank space information in the second cluster;
a fourteenth processing unit, for establishing attribute codes according to the attribute features of the first cluster and the stored data;
a fifteenth processing unit, for establishing a residual grade code according to the first cluster and the attribute residual grade dividing feature;
a sixteenth processing unit configured to encode the attribute as a first cluster first priority, encode the remaining level as a first cluster second priority, determine a response priority of the first cluster based on the first priority and the second priority, encode the remaining level as response parameter information of the first cluster based on the attribute encoding, and establish a second mapping relationship with blank area information in the second cluster;
a seventeenth processing unit, configured to determine the block response parameter mapping table based on the first mapping relationship and the second mapping relationship.
Further, the system further comprises:
a ninth obtaining unit, configured to obtain a size of storage data according to the information to be stored;
the first judging unit is used for judging whether the size of the stored data meets the requirement of a preset super-large file or not;
the eighteenth processing unit is used for obtaining a spatial matching code when the storage parameter information is met, and using the spatial matching code as the storage parameter information;
the nineteenth processing unit is used for carrying out data characteristic analysis on the information to be stored when the information to be stored does not meet the requirements, and obtaining data attribute characteristics;
and the twentieth processing unit is used for obtaining an attribute matching code according to the data attribute characteristics, and using the attribute matching code and the size of the stored data as the storage parameter information.
Further, the system further comprises:
the twenty-first processing unit is used for matching the attribute matching codes with the block response parameter mapping table to obtain matching results;
the twenty-second processing unit is used for determining the attribute of the information to be stored according to the attribute matching code when the matching result is that the matching fails;
the twenty-third processing unit is used for carrying out information expansion characteristic analysis according to the attribute of the information to be stored to obtain the storage information expansion characteristic;
the twenty-fourth processing unit is used for acquiring a space storage requirement based on the storage information expansion characteristic and the attribute of the information to be stored;
and the twenty-fifth processing unit is used for generating a space matching code according to the space storage requirement to match in the block response parameter mapping table to obtain the matched blank area information.
EXAMPLE III
Based on the same inventive concept as the method for optimizing management of blank data areas in a flash memory in the previous embodiment, the present application further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method as in the first embodiment.
Exemplary electronic device
The electronic device of the present application is described below with reference to figure 5,
based on the same inventive concept as the method for optimizing management of the blank data area in the flash memory in the foregoing embodiment, the present application further provides a system for optimizing management of the blank data area in the flash memory, including: a processor coupled to a memory, the memory for storing a program that, when executed by the processor, causes the system to perform the steps of the method of embodiment one.
The electronic device 300 includes: processor 302, communication interface 303, memory 301. Optionally, the electronic device 300 may also include a bus architecture 304. Wherein, the communication interface 303, the processor 302 and the memory 301 may be connected to each other through a bus architecture 304; the bus architecture 304 may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The bus architecture 304 may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, only one thick line is shown in FIG. 5, but this is not intended to represent only one bus or type of bus.
The communication interface 303 may be any device, such as a transceiver, for communicating with other devices or communication networks, such as an ethernet, a Radio Access Network (RAN), a Wireless Local Area Network (WLAN), a wired access network, and the like.
The memory 301 may be, but is not limited to, a ROM or other type of static storage device that can store static information and instructions, a RAM or other type of dynamic storage device that can store information and instructions, an electrically erasable Programmable read-only memory (EEPROM), a compact-read-only-memory (CD-ROM) or other optical disk storage, optical disk storage (including compact disk, laser disk, optical disk, digital versatile disk, blu-ray disk, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer. The memory may be self-contained and coupled to the processor through a bus architecture 304. The memory may also be integral to the processor.
The memory 301 is used for storing computer-executable instructions for executing the present application, and is controlled by the processor 302 to execute. The processor 302 is configured to execute the computer execution instructions stored in the memory 301, so as to implement the processing method for the orthoimage of the unmanned aerial vehicle provided by the above embodiment of the present application.
Those of ordinary skill in the art will understand that: the various numbers of the first, second, etc. mentioned in this application are for convenience of description and are not intended to limit the scope of this application nor to indicate the order of precedence. "and/or" describes the association relationship of the associated objects, meaning that there may be three relationships, e.g., a and/or B, which may mean: a exists alone, A and B exist simultaneously, and B exists alone. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship. "at least one" means one or more. At least two means two or more. "at least one," "any," or similar expressions refer to any combination of these items, including any combination of singular or plural items. For example, at least one (one ) of a, b, or c, may represent: a, b, c, a-b, a-c, b-c, or a-b-c, wherein a, b, c may be single or multiple.
In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the procedures or functions described in accordance with the present application are generated, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another computer readable storage medium, for example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device including one or more available media integrated servers, data centers, and the like. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid State Disk (SSD)), among others.
The various illustrative logical units and circuits described in this application may be implemented or operated upon by design of a general purpose processor, a digital signal processor, an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof. A general-purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices, e.g., a digital signal processor and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a digital signal processor core, or any other similar configuration.
The steps of a method or algorithm described in this application may be embodied directly in hardware, in a software element executed by a processor, or in a combination of the two. The software cells may be stored in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. For example, a storage medium may be coupled to the processor such the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium may be integral to the processor. The processor and the storage medium may reside in an ASIC, which may be disposed in a terminal. In the alternative, the processor and the storage medium may reside as discrete components in a terminal. These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Although the present application has been described in conjunction with specific features and embodiments thereof, it will be evident that various modifications and combinations can be made thereto without departing from the spirit and scope of the application. Accordingly, the specification and figures are merely exemplary of the application and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of the application. It will be apparent to those skilled in the art that various changes and modifications may be made in the present application without departing from the scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the present application and its equivalent technology, the present application is intended to include such modifications and variations.
Claims (10)
1. A method for optimizing white data region management in a flash memory, the method comprising:
acquiring blank data area information;
obtaining the blank area quantity and the blank area space according to the blank data area information;
determining block cluster division information based on the blank space number and the blank space;
performing cluster division on the blank data area information according to the block cluster division information to obtain blank block division clusters;
setting response parameters according to the blank block partition cluster, and determining a block response parameter mapping table, wherein the block response parameter mapping table comprises blank information, response parameter information and response priority;
obtaining information to be stored, and extracting storage parameters of the information to be stored to obtain storage parameter information;
and performing response parameter information and response priority ratio comparison in the block response parameter mapping table based on the storage parameter information, determining matched blank area information, and generating a response instruction for controlling the matched blank area to respond.
2. The method of claim 1, wherein the obtaining the blank data area information comprises:
obtaining the storage information of the flash memory;
obtaining a stored block and a storage blank block according to the storage information of the flash memory;
obtaining a storage redundant area according to the stored block;
and acquiring the blank data area information according to the storage blank block and the storage redundant area.
3. The method of claim 2, wherein the obtaining the number of white spaces and the white space according to the white data area information comprises:
acquiring the storage blank blocks from the blank data area information, and acquiring the number of blank data areas and blank storage space, wherein each blank block in the number of blank data areas has a first corresponding relation with the blank storage space;
according to the storage redundant area, obtaining the number of redundant areas and the storage space of the redundant area, wherein each redundant area in the number of redundant areas and the redundant storage space have a second corresponding relation;
and obtaining the blank space number based on the blank data area number and the redundant area number, and obtaining the blank space based on the blank storage space and the redundant storage space.
4. The method of claim 3, wherein the determining block cluster division information based on the white space amount, white space, comprises:
performing first classification on redundant areas and blank blocks in the blank area quantity, and taking attribute characteristics of the redundant areas and the blank blocks as first classification characteristics to obtain a first cluster and a second cluster, wherein the first cluster corresponds to the redundant areas, and the second cluster corresponds to the blank blocks;
performing second classification on the second cluster according to preset storage space classification information based on the blank space, and taking space classification characteristics as second classification characteristics of the second cluster;
acquiring storage area information corresponding to a redundant area, and performing data characteristic analysis according to the redundant area storage area information to acquire storage data attribute characteristics;
performing second classification on the first cluster according to the stored data attribute characteristics, and taking the stored data attribute characteristics as second classification characteristics of the first cluster;
performing attribute residual grading on the redundant area of the first cluster based on the blank space, and taking an attribute residual grading characteristic as a third grading characteristic of the first cluster;
determining the block cluster partitioning information based on the first, second, and third ranking features.
5. The method of claim 4, wherein said performing response parameter setting according to said blank block-partitioned cluster, determining a block response parameter mapping table, said block response parameter mapping table comprising blank information, response parameter information, and response priority, comprises:
establishing a space code according to the second cluster and the space division characteristics;
establishing a spatial matching priority based on the spatial coding, taking the spatial matching priority as a first cluster response priority, taking the spatial coding as response parameter information, and establishing a first mapping relation with blank space information in the second cluster;
establishing attribute codes according to the attribute characteristics of the first cluster and the stored data;
establishing a residual grade code according to the first cluster and the attribute residual grade dividing characteristics;
the attribute codes are used as first cluster first priority, the residual grade codes are used as first cluster second priority, response priority of the first clusters is determined based on the first priority and the second priority, response parameter information of the first clusters is coded based on the attribute codes and the residual grade codes, and a second mapping relation with the blank area information in the second clusters is established;
and determining the block response parameter mapping table based on the first mapping relation and the second mapping relation.
6. The method of claim 1, wherein the obtaining information to be stored and performing storage parameter extraction on the information to be stored to obtain storage parameter information comprises:
obtaining the size of stored data according to the information to be stored;
judging whether the size of the stored data meets the requirement of a preset super-large file or not;
when the storage parameter information meets the requirement, obtaining a space matching code, and taking the space matching code as the storage parameter information;
when the information does not meet the requirement, carrying out data characteristic analysis on the information to be stored to obtain data attribute characteristics;
and obtaining an attribute matching code according to the data attribute characteristics, and taking the attribute matching code and the size of the stored data as the storage parameter information.
7. The method of claim 6, wherein the method further comprises:
matching the attribute matching code with the block response parameter mapping table to obtain a matching result;
when the matching result is matching failure, determining the attribute of the information to be stored according to the attribute matching code;
performing information expansion characteristic analysis according to the attribute of the information to be stored to obtain storage information expansion characteristics;
acquiring a space storage requirement based on the storage information expansion characteristics and the attribute of the information to be stored;
and generating a space matching code according to the space storage requirement to match in the block response parameter mapping table to obtain the matching blank area information.
8. A system for optimizing management of blank data areas in a flash memory, the system comprising:
a first obtaining unit configured to obtain blank data area information;
a first processing unit, configured to obtain a blank area number and a blank area space according to the blank data area information;
a second processing unit configured to determine block cluster division information based on the blank space amount and the blank space;
a third processing unit, configured to perform cluster division on the blank data area information according to the block cluster division information, so as to obtain blank block division clusters;
a fourth processing unit, configured to perform response parameter setting according to the blank block partition cluster, and determine a block response parameter mapping table, where the block response parameter mapping table includes blank information, response parameter information, and a response priority;
the fifth processing unit is used for acquiring information to be stored and extracting storage parameters of the information to be stored to obtain storage parameter information;
and the first execution unit is used for performing response parameter information and response priority ratio comparison in the block response parameter mapping table based on the storage parameter information, determining matched blank area information, and generating a response instruction for controlling the matched blank area to respond.
9. A system for optimizing management of blank data areas in a flash memory, comprising: a processor coupled to a memory, the memory for storing a program that, when executed by the processor, causes a system to perform the steps of the method of any of claims 1 to 7.
10. A computer-readable storage medium, characterized in that the storage medium has stored thereon a computer program which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 7.
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