Photoelectromagnetic storage method and system based on hierarchical management

Abstract

The invention relates to the technical field of hierarchical storage, in particular to a photo-electromagnetic storage method and system based on hierarchical management, and the method comprises the following steps: collecting read-write speed, error rate, durability and cost data of optical storage and electromagnetic storage media, carrying out the sorting and grading processing of the data according to the read-write speed and the error rate, and carrying out the sorting and grading processing of the data; and performing score calculation on each storage medium to obtain a medium performance score. According to the method and the device, the data is effectively distributed to the most suitable storage medium by accurately scoring the performance of the storage medium and combining specific requirements of the to-be-stored data, so that the data access speed and efficiency are improved, the total storage cost is reduced, and particularly, when a large amount of data is processed, the data compression level and the encoding format are dynamically adjusted, and the data compression efficiency is improved. The storage efficiency of the data is further optimized, data redundancy is reduced, the overall performance of data storage and access is remarkably improved through optimization measures, and meanwhile long-term safety and integrity of the data are ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of hierarchical storage, and in particular to an optical and electromagnetic storage method and system based on hierarchical management. Background Art

[0002] The field of tiered storage technology aims to improve storage efficiency and data access speed by allocating data to different storage media (such as SSD, HDD or tape) according to usage frequency, importance or standards, so as to achieve effective data management. Each layer of storage media has different access speeds and cost-effectiveness, allowing data center operators to store data according to specific needs and cost budgets. Tiered storage is used in large-scale data centers, cloud storage services, and enterprise IT environments that require efficient data backup and recovery. By realizing automatic data classification and migration, tiered storage can optimize data processing performance and reduce overall storage costs.

[0003] Among them, the optical-electromagnetic storage method based on hierarchical management is an advanced data storage solution that combines optical and electromagnetic storage technologies. It is suitable for application scenarios that need to process batch data, such as large data centers or high-performance computing environments. By using different storage technologies (optical storage and electromagnetic storage) at different storage levels, storage performance and cost efficiency can be optimized while providing high-speed data access and reliable data protection. The main uses include data backup, long-term data archiving, and business operations that support high-frequency data reading and writing, making full use of the characteristics of various storage media to meet diverse data storage needs.

[0004] Although existing tiered storage technologies can optimize the use of storage media based on the frequency and importance of data, they lack flexibility and automation and cannot adapt quickly when processing sudden batch data or data that needs to be updated frequently. Existing systems fail to fully utilize the potential performance of all storage media, especially in terms of read and write speed and error rate. This leads to data access bottlenecks, affecting the response time and service quality of data centers. Due to the lack of highly automated and intelligent data management strategies, existing technologies show certain limitations in large-scale data processing and real-time data demand response. Due to the lack of effective data compression and encoding optimization mechanisms, data storage efficiency is low, resulting in unnecessary increases in storage costs. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose an optical and electromagnetic storage method and system based on hierarchical management.

[0006] In order to achieve the above object, the present invention adopts the following technical solution, an optical electromagnetic storage method based on hierarchical management, comprising the following steps: S1: Collect the read / write speed, error rate, durability and cost data of optical storage and electromagnetic storage media, sort and grade the data according to the read / write speed and error rate, and calculate the score for each storage medium to obtain the medium performance score; S2: According to the medium performance score, the size, access frequency and urgency of the data to be stored are evaluated, and the data is divided into differentiated storage requirement categories by sorting and assigning priorities to the parameters to obtain a data performance requirement table; S3: Through the data performance requirement table, matching analysis is performed on data categories and medium performance, the optimal storage medium is selected, data backup is performed and a temporary cache is created, and a data storage decision table is generated; S4: using the data storage decision table to check the integrity of the backup data and verify the cache response speed, optimizing the encoding format by using the statistical characteristics of the optical and electromagnetic storage data, and dynamically adjusting the compression level according to the real-time changes of the data to generate an encoding compression configuration; S5: According to the coding compression configuration, the validity of the data is detected, the storage layout is adjusted by regularly scanning the optical and electromagnetic storage data, and redundant data is automatically identified and cleaned to obtain redundant data management records; S6: Analyze the optical and electromagnetic storage distribution from the redundant data management records, track and locate the data storage location, optimize the data migration path through hierarchical management, and establish the dynamic adjustment result of the optical and electromagnetic storage.

[0007] As a further solution of the present invention, the media performance score is based on a weighted calculation of read and write speed, error rate, durability and cost; the data performance requirement table includes the size of the data to be stored, the access frequency and the urgency classification; the data storage decision table includes the strategy for selecting the optimal storage medium, data backup and temporary cache; the encoding compression configuration includes the encoding rule selection for each data stream, the ratio of original to compressed data and the compression efficiency index; the redundant data management record includes the identified redundant data type, the redundant data volume and the storage efficiency after processing; the dynamic adjustment result of the optical and electromagnetic storage includes the data storage location before and after adjustment, the data migration path optimization, the migration efficiency evaluation and the performance optimization index.

[0008] As a further solution of the present invention, the read / write speed, error rate, durability and cost data of optical storage and electromagnetic storage media are collected, the data are sorted and graded according to the read / write speed and error rate, and a score is calculated for each storage medium. The specific steps of obtaining the medium performance score are as follows: S101: Collect the read and write speed, error rate, durability and cost data of optical storage and electromagnetic storage media, input the data into a spreadsheet, initialize and classify the data, organize the basic performance parameters of the differentiated media, and generate a storage media data set; S102: sorting the storage medium data set in descending order using a spreadsheet function, calculating the average read and write speed and average error rate of each medium, dividing the performance level by numerical range, and obtaining sorted and graded data; S103: Calculate the score of each storage medium according to the sorted and graded data, set the weights of the read and write speed and the error rate, output the performance score of the medium according to the weighted result, and obtain the medium performance score.

[0009] As a further solution of the present invention, the size, access frequency and urgency of the data to be stored are evaluated according to the medium performance score, and the data is divided into differentiated storage requirement categories by sorting and assigning priorities to the parameters. The steps of obtaining the data performance requirement table are specifically as follows: S201: According to the medium performance score, information on the size, access frequency and urgency of the data to be stored is collected and entered into a data table, and the data is initialized and sorted according to the urgency to generate an initialized data sorting table; S202: Based on the initialized data sorting table, using the sorting function of a spreadsheet, iteratively sorting the data size and access frequency, classifying the data according to the access frequency and data size, and obtaining a data access classification table; S203: Using the data access classification table, assigning differentiated storage medium priorities, classifying data into multiple storage requirement categories, assigning the best storage medium to each category of data, and obtaining a data performance requirement table.

[0010] As a further solution of the present invention, the data performance requirement table is used to match and analyze the data category and the medium performance, select the optimal storage medium, perform data backup and create a temporary cache, and generate the data storage decision table in the following steps: S301: using the data performance requirement table, comparing data categories and medium performance, evaluating storage efficiency and cost, performing matching analysis, setting data backup time and frequency, and generating a matching analysis table; S302: Based on the matching analysis table, select the optimal storage medium, plan the data backup strategy, determine the data backup time and backup frequency, and generate a backup operation table; S303: extracting a backup strategy from the backup operation table, creating a temporary cache to optimize data access, setting a cache time and update frequency, implementing a temporary cache strategy, and obtaining a data storage decision table.

[0011] As a further solution of the present invention, the data storage decision table is used to check the integrity of the backup data and verify the cache response speed, the statistical characteristics of the optical and electromagnetic storage data are used to optimize the encoding format, and the compression level is dynamically adjusted according to the real-time changes of the data. The steps of generating the encoding compression configuration are specifically as follows: S401: Based on the data storage decision table, analyze the statistical characteristics of the optical and electromagnetic storage data, identify the normal mode and volatility of the data stream, adjust the encoding parameters according to the differentiated data types and frequencies, optimize the processing efficiency of the optical and electromagnetic storage, and generate data statistical analysis results; S402: According to the data statistical analysis results, monitor the changes of the optical and electromagnetic storage data stream in real time, dynamically adjust the encoding format and compression parameters, match the requirements of data storage efficiency and transmission speed, optimize the performance of data storage and transmission, and perform compression testing to obtain compression parameter adjustment records; S403: Use the compression parameter adjustment record to identify and record the encoding and compression configuration of the optical and electromagnetic storage data stream, check that the encoding format and compression level are optimally set, match the real-time network status and data characteristics, and establish the encoding compression configuration.

[0012] As a further solution of the present invention, according to the coding compression configuration, the validity of the data is detected, the storage layout is adjusted by regularly scanning the optical and electromagnetic storage data, and the redundant data is automatically identified and cleaned up, and the steps of obtaining the redundant data management record are specifically as follows: S501: Using the coding compression configuration, detecting the validity of optical electromagnetic data storage, classifying and scanning the data stored in the differentiated levels, evaluating the frequency of use and update time of the data, identifying obsolete and unaccessed data, and generating data validity detection results; S502: According to the data validity detection result, an entropy weight method is used to perform weighted calculation of data access frequency and criticality, and the storage structure is adjusted to optimize access efficiency and response speed, thereby obtaining a storage layout adjustment record; S503: Use the storage layout adjustment record to clean up redundant data in the optical and electromagnetic storage, automatically detect and delete duplicate data entries, check the integrity and validity of the data, and establish redundant data management records.

[0013] As a further solution of the present invention, the formula of the entropy weight method is as follows: ; in, For the The weight of the data indicator, For the The information entropy of the data indicators is For custom adjustment coefficient, is the data update frequency indicator, The total number of data indicators.

[0014] As a further solution of the present invention, the steps of analyzing the optical and electromagnetic storage distribution from the redundant data management records, tracking and locating the data storage location, optimizing the data migration path through hierarchical management, and establishing the optical and electromagnetic storage dynamic adjustment result are specifically as follows: S601: Analyze the distribution of the overall optical and electromagnetic storage data using the redundant data management records, identify the data storage area and the space utilization area, track the optical and electromagnetic storage location, identify key data nodes, and generate data distribution analysis results; S602: According to the data distribution analysis result, optimize the storage area with low efficiency, adjust the optical and electromagnetic storage data to the differentiated storage level, check the balance of data flow and the optimal use of resources, and plan the migration path to obtain the data migration strategy; S603: Use the data migration strategy to execute data migration of optical and electromagnetic storage, monitor data migration, avoid factors that affect data integrity and access speed, dynamically adjust data location, integrate hierarchical management information, verify migration effect, and generate dynamic adjustment results of optical and electromagnetic storage.

[0015] An optical electromagnetic storage system based on hierarchical management, the optical electromagnetic storage system based on hierarchical management is used to execute the optical electromagnetic storage method based on hierarchical management, the system comprises: The data analysis and scoring module collects the read and write speed, error rate, durability and cost data of optical storage and electromagnetic storage media, analyzes the parameters, arranges and grades them according to the read and write speed and error rate, calculates the score for each storage medium, and obtains the media performance score; The data demand classification module analyzes the size, access frequency and urgency of the data to be stored based on the medium performance score, sorts and prioritizes the data attributes, divides the data into categories according to differentiated storage requirements, and establishes a data performance requirement table; The medium selection and matching module uses the data performance requirement table to perform matching analysis on the data category and the performance of the storage medium, selects the optimal storage medium for data backup and temporary cache creation, and forms a data storage decision table; The encoding adjustment module adopts the data storage decision table to perform data backup integrity inspection and cache response speed verification, optimize the encoding format, dynamically adjust the compression level according to the change of data flow, and generate the encoding compression configuration; The data management module periodically scans the optical and electromagnetic storage data according to the coding compression configuration, adjusts the storage layout, identifies the optical and electromagnetic storage distribution density, optimizes the data migration path, and obtains the dynamic adjustment result of the optical and electromagnetic storage.

[0016] Compared with the prior art, the advantages and positive effects of the present invention are: In the present invention, by collecting and analyzing the performance data of various optical storage and electromagnetic storage media in detail (such as read and write speed, error rate, durability and cost), in-depth scoring and classification of storage media are achieved, and the configuration of storage resources is optimized. By accurately scoring the performance of storage media and combining the specific needs of the data to be stored (such as data size, access frequency and urgency), data can be effectively allocated to the most suitable storage medium. Not only does it improve data access speed and efficiency, it also reduces overall storage costs, especially when processing large amounts of data. By dynamically adjusting the data compression level and encoding format, the storage efficiency of data is further optimized and data redundancy is reduced. The optimization measures significantly improve the overall performance of data storage and access, while ensuring the long-term security and integrity of data. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a schematic diagram of the workflow of the present invention; Figure 2 This is a detailed flow chart of S1 of the present invention; Figure 3 This is a detailed flow chart of S2 of the present invention; Figure 4 This is a detailed flow chart of S3 of the present invention; Figure 5 This is a detailed flow chart of S4 of the present invention; Figure 6 This is a detailed flow chart of S5 of the present invention; Figure 7 This is a detailed flow chart of S6 of the present invention; Figure 8 It is a system flow chart of the present invention. DETAILED DESCRIPTION

[0018] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0019] In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, in the description of the present invention, "multiple" means two or more, unless otherwise clearly and specifically defined.

[0020] Embodiment 1 See also Figure 1 The present invention provides a technical solution, an optical electromagnetic storage method based on hierarchical management, comprising the following steps: S1: Collect the read / write speed, error rate, durability and cost data of optical storage and electromagnetic storage media, sort and grade the data according to the read / write speed and error rate, and calculate the score for each storage medium to obtain the medium performance score; S2: Based on the media performance score, the size, access frequency and urgency of the data to be stored are evaluated. By sorting and assigning priorities to the parameters, the data is divided into differentiated storage demand categories to obtain a data performance demand table. S3: Through the data performance requirement table, the data category and medium performance are matched and analyzed, the optimal storage medium is selected, data is backed up and a temporary cache is created, and a data storage decision table is generated; S4: Use data storage decision tables to check the integrity of backup data and verify cache response speed. Use the statistical characteristics of optical and electromagnetic storage data to perform information entropy analysis and optimize the encoding format. Dynamically adjust the compression level according to real-time changes in data, match network and storage conditions, and generate encoding compression configurations. S5: According to the coding compression configuration, the data validity and redundancy detection is implemented, the storage layout is adjusted by regularly scanning the optical and electromagnetic storage data, the redundant data is automatically identified and cleaned, the storage resource utilization is optimized, and the redundant data management record is obtained; S6: Analyze the storage distribution of optical and electromagnetic storage data from redundant data management records, track and locate data storage locations, optimize data migration paths through hierarchical management, avoid access delays, verify data access efficiency, and establish dynamic adjustment results for optical and electromagnetic storage.

[0021] The media performance score is based on a weighted calculation of read and write speed, error rate, durability and cost. The data performance requirement table includes the size of the data to be stored, access frequency and urgency classification. The data storage decision table includes strategies for selecting the optimal storage medium, data backup and temporary cache. The encoding and compression configuration includes the selection of encoding rules for each data stream, the ratio of original to compressed data and compression efficiency indicators. The redundant data management records include the identified redundant data types, the amount of redundant data and the storage efficiency after processing. The dynamic adjustment results of optical and electromagnetic storage include the data storage location before and after adjustment, data migration path optimization, migration efficiency evaluation and performance optimization indicators.

[0022] See also Figure 2 , collect the read and write speed, error rate, durability and cost data of optical storage and electromagnetic storage media, sort and grade the data according to the read and write speed and error rate, and calculate the score for each storage medium. The specific steps to obtain the media performance score are as follows: S101: Collect the read and write speed, error rate, durability and cost data of optical storage and electromagnetic storage media, input the data into a spreadsheet, initialize and classify the data, organize the basic performance parameters of the differentiated media, and generate the storage media data set. The execution process is as follows; Collect the read and write speed, error rate, durability and cost data of optical storage and electromagnetic storage media. The collection of this data requires detailed planning to ensure the accuracy and completeness of the data. Determine the samples of various types of storage media, such as optical disks, hard disks, etc., and perform multiple tests using standard test software to obtain the read and write speed and error rate data. During the data collection process, repeat the measurement to reduce errors. At the same time, record the use environment and test conditions of the storage media to ensure data consistency. After the data is sorted, enter it into a spreadsheet. Through data cleaning and processing, remove outliers and smooth the data for subsequent data analysis and comparison. The data classification in the spreadsheet will be based on the type of storage media, such as optical storage or electromagnetic storage, and its performance parameters, such as read and write speed and error rate, in order to conduct a preliminary performance evaluation and generate a storage media data set.

[0023] S102: Storage medium data set, using the spreadsheet function to sort the read and write speed and error rate data in descending order, respectively calculating the average read and write speed and average error rate of each medium, dividing the performance level by the numerical range, and obtaining the execution process of sorting and grading data is as follows; Sort the read / write speed and error rate data in descending order according to the formula , calculate the average read and write speed and average error rate. In the formula, Represents the read and write speed of a single storage medium. represents the error rate, and is the corresponding weight, Represents the total number of storage media.

[0024] Detailed explanation of the formula and the process of formula calculation and derivation: Consider the read and write speed of the storage medium and error rate , using weight and , weighted to reflect that read and write speeds are more important in performance scoring than error rates.

[0025] There are five types of storage media, the specific data are as follows: Storage medium A: MB / s,

[0026] Storage medium B: MB / s,

[0027] Storage medium C: MB / s,

[0028] Storage medium D: MB / s,

[0029] Storage medium E: MB / s,

[0030] The calculation formula is as follows:

[0031] The calculation results are simplified and averaged to obtain a score, which represents the storage medium performance evaluation after comprehensively considering the read and write speed and error rate.

[0032] S103: Calculate the score of each storage medium according to the sorted and graded data, set the weights of the read and write speed and the error rate, and output the performance score of the medium according to the weighted result. The execution process of obtaining the medium performance score is as follows; Based on the sorted and graded data, the score of each storage medium is calculated. The calculation process includes setting appropriate weights for each medium to ensure that the impact of read and write speeds and error rates in the total score is properly reflected. When setting weights, the actual usage scenarios of the storage medium and the performance requirements must be considered. For example, high-speed storage media focus more on read and write speeds, while high-reliability storage media focus more on low error rates. The comprehensive score of each medium is calculated by weighted average based on the read and write speeds and error rates of each medium. The score helps users make decisions based on specific needs when selecting storage media. The score is calculated not only based on the original data, but also based on industry standards and performance data to adjust the weights to ensure the fairness and accuracy of the score and obtain a medium performance score.

[0033] See also Figure 3 , according to the media performance score, evaluate the size, access frequency and urgency of the data to be stored, and classify the data into differentiated storage demand categories by sorting and prioritizing the parameters. The specific steps to obtain the data performance requirement table are as follows: S201: According to the medium performance score, the size, access frequency and urgency of the data to be stored are collected and entered into a data table, and the data is initialized and sorted according to the urgency. The execution process of generating the initialization data sorting table is as follows; According to the media performance score, collect information on the size, access frequency and urgency of the data to be stored. During the entire data collection process, determine the specific type of data, such as documents, pictures or videos. The type directly affects the size of the data. Obtain data access frequency information by querying system logs or user feedback. The urgency is assessed based on business needs and the time sensitivity of the data. After collection, enter the data into a data table and use automated tools to verify the integrity and accuracy of the data to prevent entry errors. Initial sorting is based on urgency to ensure that urgent data can be processed first. Sorting uses the automatic sorting function of spreadsheets to make data management more efficient and facilitate subsequent processing and analysis. It reflects the priority of different data items and provides a basis for subsequent data processing and storage allocation to generate an initialization data sorting table.

[0034] S202: Based on the initialized data sorting table, the sorting function of the spreadsheet is used to iteratively sort the data size and access frequency, and the data is classified according to the access frequency and data size. The execution process of obtaining the data access classification table is as follows; Based on the initialized data sorting table, the spreadsheet sorting function is used to sort the data size and put the large data items in the front row to give priority to the configuration of storage space in subsequent processing. The access frequency is iteratively sorted. The system will sort the data from high to low according to the access frequency to ensure that high-frequency data can be quickly reached. The iterative sorting process ensures that the data is optimized not only according to the urgency, but also according to the access requirements and storage space occupied. The classification of each data item is clearly displayed, such as frequently accessed small files or infrequently accessed large files, which helps to more accurately plan data storage and allocate resources, and obtain a data access classification table.

[0035] S203: Using the data access classification table, assigning differentiated storage medium priorities, classifying data into multiple storage requirement categories, assigning the best storage medium to each category of data, and obtaining the data performance requirement table. The execution process is as follows; Using the data access classification table, differentiated storage media priorities are assigned. During the allocation process, data is classified into multiple storage demand categories, such as temporary data, long-term storage data, high-frequency access data, etc. The optimal storage medium is assigned to each type of data. Considering the performance score of the medium, high-performance media is assigned to data with high access frequency first, while less frequently accessed data can consider lower-cost storage solutions. Data with high urgency should be stored on media with high fault tolerance to prevent data loss. The entire data allocation process is supported by an automated system to ensure the timeliness and accuracy of the allocation. The storage media, performance requirements and expected costs of each type of data are listed in detail to provide guidance for actual storage operations and obtain a data performance requirement table.

[0036] See also Figure 4 , through the data performance requirement table, match and analyze the data category and medium performance, select the optimal storage medium, perform data backup and create a temporary cache, and generate the data storage decision table in the following steps: S301: Using the data performance requirement table, comparing data categories and media performance, evaluating storage efficiency and cost, performing matching analysis, setting the data backup time and frequency, and generating a matching analysis table, the execution process is as follows; Using the data performance requirement table, we begin to compare the performance of data categories with storage media. The comparative analysis is performed through automated tools to ensure that the data classification matches the performance characteristics of the media. Storage efficiency and cost evaluation are calculated through an algorithm model. The model considers factors such as the read and write speed, error rate, durability and cost of the storage media. The evaluation results will guide the setting of data backup time and frequency, and set appropriate backup strategies for each data category to maximize the use of storage resources and reduce costs. The matching degree of each data with the recommended storage media, backup time and frequency, and expected storage cost are listed in detail to ensure the economy and efficiency of the storage solution and generate a matching analysis table.

[0037] S302: Based on the matching analysis table, the optimal storage medium is selected, the data backup strategy is planned, the data backup time and backup frequency are determined, and the execution process of generating the backup operation table is as follows; Based on the matching analysis table, select the optimal storage medium. During the selection process, pay special attention to matching the access frequency and size of the data with the performance of the medium to ensure efficient use of storage resources. When planning data backup strategies, refer to the access frequency and modification frequency of the data, and set a higher backup frequency for data that is frequently modified or accessed. At the same time, consider the security and recovery requirements of the data, determine the backup time and frequency of the data, include detailed backup time plans and frequency settings, provide clear guidance for actual backup operations, ensure the continuity and recoverability of data, and generate a backup operation table.

[0038] S303: Extract the backup strategy from the backup operation table, create a temporary cache to optimize data access, set the cache time and update frequency, implement the temporary cache strategy, and obtain the execution process of the data storage decision table as follows; Extract the backup strategy from the backup operation table, create a temporary cache to optimize data access, set the cache time and update frequency according to the data access mode and frequency. For example, set a shorter cache update cycle for frequently accessed data to provide fast access. For infrequently accessed data, you can set a longer cache time to reduce the system load. The implemented temporary cache strategy is managed by an automated system to ensure the real-time and effectiveness of the cache, including cache strategies, update frequencies and corresponding data categories, to provide optimized solutions for data access, improve the system's response speed and efficiency, and obtain a data storage decision table.

[0039] See also Figure 5 ,Using the data storage decision table, we can check the integrity of the backup data and verify the cache response speed.,We can use the statistical characteristics of the optical and electromagnetic storage data to optimize the encoding format, and dynamically adjust the compression level according to the real-time changes of the data.,The steps to generate the encoding compression configuration are as follows: S401: Based on the data storage decision table, the statistical characteristics of the optical and electromagnetic storage data are analyzed, the normal mode and volatility of the data stream are identified, the encoding parameters are adjusted according to the differentiated data types and frequencies, the processing efficiency of the optical and electromagnetic storage is optimized, and the execution process of generating the data statistical analysis results is as follows; Sub-step S401 is a crucial step to conduct statistical analysis on the optical and electromagnetic storage data based on the data storage decision table. By analyzing and evaluating the results, the normal patterns and volatility of the data stream can be identified, which helps to understand the performance of different data types in the optical and electromagnetic storage system. According to the statistical characteristics, the system will adjust the encoding parameters for differentiated data types and frequencies to optimize the processing efficiency of the optical and electromagnetic storage. The adjustment process includes optimizing the data storage structure and access algorithm to ensure that the data processing process is efficient and accurate, and generate data statistical analysis results. The formula used is: ; in, represents the variance of the data, is the total number of data points, It is The value of the data point, is the mean of the data.

[0040] S402: According to the data statistical analysis results, the changes of the optical and electromagnetic storage data stream are monitored in real time, the encoding format and compression parameters are dynamically adjusted to match the requirements of data storage efficiency and transmission speed, the performance of data storage and transmission is optimized, and compression testing is performed to obtain the execution process of the compression parameter adjustment record as follows; Sub-step S402 monitors the changes of the optical electromagnetic storage data stream in real time based on the data statistical analysis results, and dynamically adjusts the encoding format and compression parameters to match the requirements of data storage efficiency and transmission speed. By analyzing the real-time changes of the data stream, the encoding and compression settings that need to be optimized are identified to improve the storage density and transmission efficiency of the data. Dynamic adjustment includes algorithm selection and parameter configuration to adapt to the characteristics of the data stream and changes in network conditions, and compression tests are performed to verify the effect of the adjustment, ensure the integrity and access speed of the data during storage and transmission, and obtain compression parameter adjustment records.

[0041] S403: Using compression parameter adjustment records, identifying and recording the encoding and compression configuration of the optical electromagnetic storage data stream, checking the optimal settings of the encoding format and compression level, matching the real-time network status and data characteristics, and establishing the execution flow of the encoding compression configuration is as follows; Substep S403 uses compression parameter adjustment records to systematically identify and record the encoding and compression configuration of the optical and electromagnetic storage data stream. Through detailed records and analysis, it verifies whether the settings of the encoding format and compression level are optimal, ensuring that the configuration can match the real-time network conditions and data characteristics. It provides a clear reference framework for managing and optimizing the storage and transmission of data streams, and establishes an encoding compression configuration table using the formula: ; in, Indicates the adaptability of the configuration, is the total number of configurations, It is The performance response of each configuration, It is the strictness of the network and data conditions that the configuration needs to meet.

[0042] See also Figure 6 , according to the coding compression configuration, the validity of the data is detected, the storage layout is adjusted by regularly scanning the optical and electromagnetic storage data, and the redundant data is automatically identified and cleaned. The specific steps of obtaining the redundant data management record are: S501: Using the coding compression configuration, detecting the validity of optical electromagnetic data storage, classifying and scanning the data stored in the differentiated levels, evaluating the frequency of use and update time of the data, identifying obsolete and unaccessed data, and generating the execution flow of the data validity detection result are as follows; Substep S501 uses the coding compression configuration to detect the validity of optical and electromagnetic data storage, which is a key process to ensure optimal storage and management of data. It involves classifying and scanning the data stored in differentiated levels, including evaluating the frequency of use and update time of the data. The system can identify outdated and unaccessed data, which is crucial to maintaining storage efficiency and data quality. The data validity test results are generated using the formula: ; in, Indicates the validity index of the data. is the total number of data entries, is the current time, It is The last access time of each data entry, is the frequency of use of the data entry.

[0043] S502: Based on the data validity test result, the entropy weight method is used to perform weighted calculation of data access frequency and criticality, and the storage structure is adjusted to optimize access efficiency and response speed. The execution process of obtaining the storage layout adjustment record is as follows; Substep S502 uses the entropy weight method to perform weighted calculations of data access frequency and criticality based on the data validity test results, which is an important step in optimizing the storage structure. The entropy weight method determines the weight of each data attribute by analyzing the distribution characteristics of the data, which helps to identify data characteristics that are more critical to the decision-making process. Allowing the system to adjust the storage structure, optimize access efficiency and response speed, and generate storage layout adjustment records.

[0044] The formula of the entropy weight method is as follows: ; in, For the The weight of the data indicator, For the The information entropy of the data indicators is For custom adjustment coefficient, is the data update frequency indicator, The total number of data indicators.

[0045] The execution flow is as follows: Based on the data validity test results, calculate the information entropy of each data indicator and update frequency , set a custom adjustment factor for each indicator The coefficient is set by the data administrator based on the importance and sensitivity of the data, and the weight of each indicator is calculated. It not only considers the frequency of data use and criticality, but also integrates the frequency of data updates and the administrator's subjective assessment of the importance of data to perform more accurate storage structure optimization.

[0046] S503: Use the storage layout adjustment record to clean up redundant data in the optical and electromagnetic storage, automatically detect and delete duplicate data entries, check the integrity and validity of the data, and establish the execution process of the redundant data management record as follows; Substep S503 uses the storage layout adjustment record to clean up redundant data in the optical and electromagnetic storage, which is a key operation to ensure data storage efficiency and quality. By automatically detecting and deleting duplicate data entries, the system can maintain the neatness and accuracy of the data. It involves a thorough review of the optical and electromagnetic storage system to ensure that all data is the latest and most relevant. The system will check the data integrity and validity and generate redundant data management records.

[0047] See also Figure 7 ,Analyzing the distribution of optical and electromagnetic storage from redundant data management records, tracking and locating data storage locations, optimizing data migration paths through hierarchical management, and establishing the steps of dynamic adjustment results of optical and electromagnetic storage are as follows: S601: Analyze the distribution of the overall optical and electromagnetic storage data using redundant data management records, identify data storage areas and space utilization areas, track the optical and electromagnetic storage locations, identify key data nodes, and generate data distribution analysis results. The execution process is as follows; Substep S601 uses redundant data management records to analyze the distribution of the overall optical and electromagnetic storage data to optimize the storage structure, help identify data storage areas and space utilization, and provide basic data for further optimization. By tracking the optical and electromagnetic storage locations in detail, the system can identify key data nodes that contain frequently accessed or critical business data, and describe the usage of each storage area in detail, including storage density, access frequency, and space efficiency, and generate data distribution analysis results using the formula: ; in, Indicates the average space utilization of the storage area. is the total number of storage areas, It is The space used by the storage area, It is The total space of the storage area.

[0048] S602: According to the data distribution analysis results, optimize the storage area with low efficiency, adjust the optical and electromagnetic storage data to the differentiated storage level, check the balance of data flow and the optimal use of resources, and plan the migration path. The execution process of the data migration strategy is as follows; Substep S602 optimizes the storage areas with low efficiency based on the data distribution analysis results and adjusts the optical and electromagnetic storage data to differentiated storage levels. The process includes re-evaluating the balance of data flow and the optimal use of resources to ensure that data is distributed to the appropriate storage layer according to demand and importance. Migration path planning is key, which involves calculating the best path and method for data migration to reduce the impact on existing operations and obtain a data migration strategy using the formula: ; in, Indicates the overall data migration efficiency, is the total amount of data being migrated, It is The access frequency of data, is the importance score of the data, It is the migration The cost of data.

[0049] S603: Use the data migration strategy to perform data migration of the optical and electromagnetic storage, monitor data migration, avoid factors that affect data integrity and access speed, dynamically adjust the data location, integrate hierarchical management information, verify the migration effect, and generate the execution process of the dynamic adjustment result of the optical and electromagnetic storage as follows; Substep S603 uses the data migration strategy to perform data migration of optical and electromagnetic storage and monitors the entire migration process. This is a key step to ensure that data integrity and access speed are not affected. By dynamically adjusting the data location and integrating the information of hierarchical management, the system can continuously adjust and optimize the data storage strategy. Monitoring and verifying the migration effect is crucial to ensure that the data performs as expected in the new storage environment and generate the dynamic adjustment results of optical and electromagnetic storage. The formula used is: ; in, represents the ratio of post-migration to pre-migration performance, is the total number of data entries, and Respectively represent The access speed of each data entry before and after migration.

[0050] See also Figure 8 , an optical electromagnetic storage system based on hierarchical management, the optical electromagnetic storage system based on hierarchical management is used to execute the optical electromagnetic storage method based on hierarchical management, the system comprises: The parameter adjustment module adjusts the wavelength selection parameters according to the type and priority of the data stream, allocates target wavelengths for differentiated data streams, and generates an optical wavelength configuration table; The real-time monitoring module uses the optical wavelength configuration table to monitor the network status of the optical electromagnetic storage data flow, adjusts the frequency and phase for the differentiated wavelengths, and generates frequency and phase optimization records; The wavelength filtering module filters light waves of differentiated wavelengths based on frequency phase optimization records, monitors and verifies the isolation of data streams in real time, and creates light wave isolation effect evaluation results; The coding adjustment module uses the light wave isolation effect evaluation results to optimize the coding format, dynamically adjust the compression level according to the changes in the data stream, and generate the coding compression configuration; The data management module periodically scans the optical and electromagnetic storage data according to the coding compression configuration, adjusts the storage layout, identifies the optical and electromagnetic storage distribution density, optimizes the data migration path, and obtains the dynamic adjustment results of the optical and electromagnetic storage.

[0051] The above are only preferred embodiments of the present invention and are not intended to limit the present invention in other forms. Any technician familiar with the profession may use the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. An optical and electromagnetic storage method based on hierarchical management, characterized in that: The following steps are involved: Collect the read / write speed, error rate, durability and cost data of optical storage and electromagnetic storage media, sort and grade the data according to the read / write speed and error rate, and calculate the score for each storage medium to obtain the media performance score; According to the medium performance score, the size, access frequency and urgency of the data to be stored are evaluated, and the data is divided into differentiated storage demand categories by sorting and assigning priorities to the parameters to obtain a data performance demand table; Through the data performance requirement table, matching analysis is performed on data categories and medium performance, the optimal storage medium is selected, data backup and temporary cache are created, and a data storage decision table is generated; The data storage decision table is used to check the integrity of backup data and verify the cache response speed, the statistical characteristics of optical and electromagnetic storage data are used to optimize the encoding format, and the compression level is dynamically adjusted according to the real-time changes of the data to generate the encoding compression configuration; According to the coding compression configuration, the validity of the data is detected, the storage layout is adjusted by regularly scanning the optical and electromagnetic storage data, and redundant data is automatically identified and cleaned to obtain redundant data management records; The optical and electromagnetic storage distribution is analyzed from the redundant data management records, the data storage location is tracked and located, and through hierarchical management, the data migration path is optimized to establish the dynamic adjustment result of the optical and electromagnetic storage.

2. The optical electromagnetic storage method based on hierarchical management according to claim 1, characterized in that: The media performance score is based on a weighted calculation of read and write speed, error rate, durability and cost. The data performance requirement table includes the size of the data to be stored, the access frequency and the urgency classification. The data storage decision table includes the strategy for selecting the optimal storage medium, data backup and temporary cache. The encoding compression configuration includes the encoding rule selection for each data stream, the ratio of original to compressed data and the compression efficiency index. The redundant data management record includes the identified redundant data type, the amount of redundant data and the storage efficiency after processing. The dynamic adjustment result of the optical and electromagnetic storage includes the data storage location before and after adjustment, data migration path optimization, migration efficiency evaluation and performance optimization index.

3. The optical electromagnetic storage method based on hierarchical management according to claim 1, characterized in that: Collect the read / write speed, error rate, durability and cost data of optical storage and electromagnetic storage media, sort and grade the data according to the read / write speed and error rate, and calculate the score for each storage medium. The specific steps to obtain the media performance score are as follows: Collect the read and write speed, error rate, durability and cost data of optical storage and electromagnetic storage media, input the data into a spreadsheet, initialize and classify the data, organize the basic performance parameters of the differentiated media, and generate a storage media data set; Based on the storage medium data set, the read and write speed and error rate data are sorted in descending order using a spreadsheet function, the average read and write speed and average error rate of each medium are calculated respectively, and the performance level is divided by numerical intervals to obtain sorted and graded data; According to the sorted and graded data, the score of each storage medium is calculated, the weights of the read and write speed and the error rate are set, and the performance score of the medium is output according to the weighted result to obtain the medium performance score.

4. The optical electromagnetic storage method based on hierarchical management according to claim 1, characterized in that: According to the medium performance score, the size, access frequency and urgency of the data to be stored are evaluated, and the data is divided into differentiated storage demand categories by sorting and assigning priorities to the parameters. The steps of obtaining the data performance demand table are specifically as follows: According to the medium performance score, information on the size, access frequency and urgency of the data to be stored is collected and entered into a data table, and the data is initialized and sorted according to the urgency to generate an initialized data sorting table; Based on the initialized data sorting table, the data size and access frequency are iteratively sorted using the sorting function of the electronic spreadsheet, and the data is classified according to the access frequency and data size to obtain a data access classification table; By utilizing the data access classification table, differentiated storage medium priorities are assigned, data is classified into multiple storage requirement categories, and the optimal storage medium is assigned to each category of data, thereby obtaining a data performance requirement table.

5. The optical electromagnetic storage method based on hierarchical management according to claim 1, characterized in that: Through the data performance requirement table, the matching analysis of data category and medium performance is performed, the optimal storage medium is selected, data backup and temporary cache are created, and the steps of generating the data storage decision table are as follows: Using the data performance requirement table, comparing data categories and media performance, evaluating storage efficiency and cost, performing matching analysis, setting data backup time and frequency, and generating a matching analysis table; Based on the matching analysis table, select the optimal storage medium, plan the data backup strategy, determine the data backup time and backup frequency, and generate a backup operation table; The backup strategy is extracted from the backup operation table, a temporary cache is created to optimize data access, the cache time and update frequency are set, the temporary cache strategy is implemented, and a data storage decision table is obtained.

6. The optical electromagnetic storage method based on hierarchical management according to claim 1, characterized in that: The data storage decision table is used to check the integrity of backup data and verify the cache response speed. The statistical characteristics of optical and electromagnetic storage data are used to optimize the encoding format and dynamically adjust the compression level according to the real-time changes of data. The steps of generating the encoding compression configuration are as follows: Based on the data storage decision table, the statistical characteristics of the optical and electromagnetic storage data are analyzed, the normal mode and volatility of the data stream are identified, the encoding parameters are adjusted according to the differentiated data types and frequencies, the processing efficiency of the optical and electromagnetic storage is optimized, and the data statistical analysis results are generated; According to the statistical analysis results of the data, real-time monitoring of changes in the optical and electromagnetic storage data stream, dynamic adjustment of the encoding format and compression parameters, matching the requirements of data storage efficiency and transmission speed, optimizing the performance of data storage and transmission, and performing compression testing to obtain compression parameter adjustment records; The compression parameter adjustment record is used to identify and record the encoding and compression configuration of the optical electromagnetic storage data stream, check the optimal settings of the encoding format and compression level, match the real-time network status and data characteristics, and establish the encoding compression configuration.

7. The optical electromagnetic storage method based on hierarchical management according to claim 1, characterized in that: According to the coding compression configuration, the validity of the data is detected, the storage layout is adjusted by regularly scanning the optical and electromagnetic storage data, and the redundant data is automatically identified and cleaned up to obtain the redundant data management record. Specifically, the steps are: Using the coding compression configuration, detecting the validity of optical electromagnetic data storage, classifying and scanning the data stored in the differentiated levels, evaluating the frequency of use and update time of the data, identifying obsolete and unaccessed data, and generating data validity detection results; According to the data validity detection result, the entropy weight method is used to perform weighted calculation of data access frequency and criticality, and the storage structure is adjusted to optimize access efficiency and response speed, so as to obtain a storage layout adjustment record; The storage layout adjustment record is used to clean up redundant data in optical and electromagnetic storage, automatically detect and delete duplicate data entries, check the integrity and validity of data, and establish redundant data management records.

8. The optical and electromagnetic storage method based on hierarchical management according to claim 7, characterized in that: The formula of the entropy weight method is as follows: ； in, For the The weight of the data indicator, For the The information entropy of the data indicators is For custom adjustment coefficient, is the data update frequency indicator, The total number of data indicators.

9. The optical electromagnetic storage method based on hierarchical management according to claim 1, characterized in that: The steps of analyzing the optical and electromagnetic storage distribution from the redundant data management records, tracking and locating the data storage location, optimizing the data migration path through hierarchical management, and establishing the optical and electromagnetic storage dynamic adjustment result are as follows: Utilizing the redundant data management records, analyzing the distribution of the overall optical and electromagnetic storage data, identifying data storage areas and space utilization areas, tracking the optical and electromagnetic storage locations, identifying key data nodes, and generating data distribution analysis results; According to the data distribution analysis results, optimize the storage area with low efficiency, adjust the optical and electromagnetic storage data to the differentiated storage level, check the balance of data flow and the optimal use of resources, and plan the migration path to obtain the data migration strategy; The data migration strategy is used to execute data migration of optical and electromagnetic storage, monitor data migration, avoid factors that affect data integrity and access speed, dynamically adjust data location, integrate hierarchical management information, verify migration effects, and generate dynamic adjustment results of optical and electromagnetic storage.

10. An optical electromagnetic storage system based on hierarchical management, characterized in that: According to the optical and electromagnetic storage method based on hierarchical management according to any one of claims 1 to 9, the system comprises: The data analysis and scoring module collects the read and write speed, error rate, durability and cost data of optical storage and electromagnetic storage media, analyzes the parameters, arranges and grades them according to the read and write speed and error rate, calculates the score for each storage medium, and obtains the media performance score; The data demand classification module analyzes the size, access frequency and urgency of the data to be stored based on the medium performance score, sorts and prioritizes the data attributes, divides the data into categories according to differentiated storage requirements, and establishes a data performance requirement table; The medium selection and matching module uses the data performance requirement table to perform matching analysis on the data category and the performance of the storage medium, selects the optimal storage medium for data backup and temporary cache creation, and forms a data storage decision table; The encoding adjustment module adopts the data storage decision table to perform data backup integrity inspection and cache response speed verification, optimize the encoding format, dynamically adjust the compression level according to the change of data flow, and generate the encoding compression configuration; The data management module periodically scans the optical and electromagnetic storage data according to the coding compression configuration, adjusts the storage layout, identifies the optical and electromagnetic storage distribution density, optimizes the data migration path, and obtains the dynamic adjustment result of the optical and electromagnetic storage.

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