A hierarchical optical disc storage management system

Abstract

This invention relates to the field of optical disc storage technology, specifically to a hierarchical optical disc cartridge storage management system. The system includes a data analysis module, a weight calculation module, a strategy formulation module, a media selection module, a dynamic adjustment module, and a performance evaluation module. In this invention, by deeply analyzing optical disc data and recording data access frequency, file quantity, and modification frequency, changes in storage needs and data access patterns can be more effectively identified. This enables precise recording of data attributes, weight allocation, and sensitivity analysis of optical disc files, allowing for the construction of more detailed storage management strategies. The system can adjust storage locations and priorities based on actual data usage, responding to real-time data demands. The real-time adjustment mechanism improves system response speed and operational efficiency, while regular performance evaluation ensures the continuous adaptability and efficiency of the storage strategy, guaranteeing the reliability and security of long-term data preservation.

Description

Technical Field

[0001] This invention relates to the field of optical disc storage technology, and in particular to an optical disc cartridge storage management system based on hierarchical management. Background Technology

[0002] Optical disc storage technology involves using optical discs (such as CDs, DVDs, and Blu-rays) as a medium for data storage and retrieval. The core concept is the optical disc reading and writing method, which uses a laser beam to read and record data. An optical disc storage system includes an optical drive, optical discs, and related software for data management and access. Due to its relatively low cost, high data security, and stable storage lifespan, it is widely used in personal data storage, business data backup, and multimedia content distribution.

[0003] Among them, the tiered management-based optical disc storage management system aims to optimize the efficiency of optical disc storage and retrieval through a tiered management strategy. This includes an automated optical disc swapping mechanism and a software control system that can automatically manage the physical location and access priority of optical discs based on data access frequency and importance. Its main purpose is to improve data retrieval speed and storage efficiency in large-scale data storage environments, and it is particularly suitable for datasets that require long-term preservation and have uneven access frequencies, such as archives, libraries, and enterprise backup data centers.

[0004] While existing optical disc storage technology is widely used in various data storage environments, it has significant shortcomings when handling large-scale datasets with uneven access frequencies. Optical disc storage systems fix the physical location and access priorities of the discs, lacking dynamic management capabilities based on the actual access and modification frequency of the data. This results in data retrieval speeds being limited by physical location, hindering the rapid retrieval of frequently accessed data. Especially in archives or enterprise backup data centers, inefficient data access leads to operational delays, impacting real-time data use and decision-making. For example, in emergency recovery scenarios, the inability to quickly access backup data prolongs the recovery process, affecting business continuity. Fixed storage strategies also lead to resource waste, as infrequently accessed data occupies easily accessible storage locations, reducing cost-effectiveness. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of existing technologies and propose a hierarchical management system for optical disc cartridge storage.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: a hierarchical optical disc cartridge storage management system includes:

[0007] The data analysis module identifies the stored CD data from the CD cartridge, records the access frequency, number of files, and modification frequency of each data item, calculates the distribution and variability of multiple CD data items, and generates data attribute records.

[0008] The weight calculation module uses the data attribute records to assign weights to the factors affecting the storage of the optical disc cartridge, and combines this with the sensitivity of the files stored in the optical disc cartridge to obtain the weight distribution result.

[0009] Based on the weight distribution results, the strategy formulation module evaluates the priority of the data stored in the optical disc cartridge, adjusts the optical disc cartridge storage strategy according to the priority order through hierarchical management, and outputs a storage optimization plan.

[0010] The media selection module uses the storage optimization scheme to analyze the resource usage of the optical disc cartridge storage, selects storage media for different data types, and generates media matching results through hierarchical management.

[0011] Based on the media matching results, the dynamic adjustment module monitors the load and data access patterns of the optical disc cartridge storage, responds to real-time data access needs, verifies storage efficiency, and creates adjustment feedback records.

[0012] Based on the adjustment feedback records, the performance evaluation module periodically checks the operating status of the optical disc cartridge storage, analyzes the execution effect of the storage strategy, evaluates the adaptability and efficiency of the storage strategy, and generates storage management evaluation results.

[0013] As a further aspect of the present invention, the data attribute record includes the access frequency, number of files, and modification frequency of optical disc data; the weight distribution result includes the weight values ​​of influencing factors and the sensitivity assessment of files stored in the optical disc cartridge; the storage optimization scheme includes storage strategies adjusted according to data priority and tiered management guidelines; the media matching result includes storage media selection and tiered management strategies for differentiated data types; the adjustment feedback record includes load monitoring data, data access patterns, and storage efficiency verification results for optical disc cartridge storage; and the storage management evaluation result includes periodic checks on the execution effect, adaptability, and efficiency of the storage strategy.

[0014] As a further aspect of the present invention, the data analysis module includes:

[0015] The data recognition submodule identifies and classifies the file information in each CD based on the CD data in the CD cartridge, identifies the file types associated with the CD, performs file classification, and generates a file classification list.

[0016] The data statistics submodule uses the file classification list to count the access frequency, number of files, and modification frequency of the data stored in the CD-ROM cartridge, and calculates the distribution and variability of the data to obtain statistical analysis results.

[0017] The attribute recognition submodule uses the statistical analysis results to integrate information on the frequency of data access, the number of files, and the frequency of modification of the optical disc storage, constructs archives based on data attributes, and generates data attribute records.

[0018] As a further aspect of the present invention, the weight calculation module includes:

[0019] The factor analysis submodule analyzes the factors affecting the storage performance of the optical disc cartridge through the data attribute records, and classifies the differentiated factors by data sorting and priority evaluation, generating a factor influence classification diagram.

[0020] Based on the factor influence hierarchy diagram, the sensitivity analysis submodule uses the support vector machine algorithm to analyze the sensitivity of files stored in the optical disc cartridge, and uses the feature vectors of file access and modification records to obtain a file sensitivity evaluation table.

[0021] The weight allocation submodule uses the document sensitivity assessment table and the factor influence classification diagram to calculate the weights of differentiated influencing factors, adjust the weights of differentiated factors, process and review documents according to their sensitivity, and generate weight distribution results.

[0022] As a further aspect of the present invention, the formula for the support vector machine algorithm is as follows:

[0023] ;

[0024] in, Let be the decision function. For the input feature vector, The number of vectors, For support vectors, For the class labels of support vectors, The decision function for support vectors, For Lagrange multipliers, For Gaussian kernel function, This is the bandwidth parameter of the kernel function. For regularization parameters, The weights of the error term, This is a bias term.

[0025] As a further aspect of the present invention, the strategy formulation module includes:

[0026] The priority evaluation submodule evaluates the priority of the optical disc cartridge storage data based on the weight distribution results, sorts the optical disc cartridge storage data according to the weight priority, and generates a data priority list.

[0027] The hierarchical management submodule uses the data priority list and hierarchical management strategy to divide the data stored in the optical disc cartridge into hierarchical levels, allocate resources and configure storage space according to priority, check the priority of data and access it first, and obtain the hierarchical management strategy.

[0028] The strategy adjustment submodule adopts the hierarchical management strategy to adjust the optical disc cartridge storage strategy. By dynamically adjusting the storage location and resource configuration, it optimizes storage performance, verifies the response speed and data security of the optical disc cartridge storage, and outputs a storage optimization solution.

[0029] As a further aspect of the present invention, the medium selection module includes:

[0030] Based on the storage optimization scheme, the resource analysis submodule analyzes the resource usage of the optical disc cartridge storage, measures real-time resource utilization through hierarchical management, performs resource demand analysis, and generates resource usage analysis results.

[0031] The attribute analysis submodule identifies multiple types of storage data based on the resource usage analysis results, performs attribute analysis on the optical disc cartridge storage data, classifies the data according to the access frequency and modification frequency, and obtains a data type classification table.

[0032] The media matching submodule uses the data type classification table to select storage media with different data types. By comparing the performance indicators and cost-effectiveness of the media, it verifies the efficiency and cost of storage of different optical disc cartridges and outputs the media matching results.

[0033] As a further aspect of the present invention, the dynamic adjustment module includes:

[0034] Based on the media matching results, the load assessment submodule monitors the real-time load status of the optical disc cartridge storage, records the optical disc cartridge storage frequency and data traffic, performs load analysis on the optical disc cartridge storage, and generates load monitoring and analysis results.

[0035] The pattern recognition submodule uses the load monitoring analysis results and the K-means clustering algorithm to analyze the access patterns of data stored in the optical disc cartridge. By aggregating data requests into the target category, it optimizes data access speed and efficiency and obtains access pattern analysis results.

[0036] The efficiency verification submodule uses the access mode analysis results to respond to real-time data access requirements, verifies the response time and processing capability of the optical disc cartridge storage through simulation testing, examines the performance of the storage medium, verifies that the storage efficiency meets expectations, and creates adjustment feedback records.

[0037] As a further aspect of the present invention, the formula for the K-means clustering algorithm is as follows:

[0038] ;

[0039] in, For the first The center of each cluster, For the first Each cluster includes a set of points. For a single data point in a point set, For data points The weighting coefficients, This is the variance adjustment factor. For the first The variance of each cluster, This is the skewness adjustment factor. For the first The skewness of each cluster, This is the kurtosis adjustment factor. For the first The kurtosis of each cluster.

[0040] As a further aspect of the present invention, the performance evaluation module includes:

[0041] Based on the adjustment feedback records, the status check submodule periodically checks the operating status of the optical disc cartridge storage, records the operating parameters and performance indicators of the optical disc cartridge, extracts the key performance indicators that affect the optical disc cartridge storage, and generates operating status monitoring results.

[0042] The effect comparison submodule analyzes the execution effect of the storage strategy based on the running status monitoring results, compares the performance data before and after the execution of the storage strategy, performs effect comparison analysis, verifies that the execution of the storage strategy matches the expected goal, and obtains the execution effect analysis results.

[0043] The strategy adaptability assessment submodule uses the execution effect analysis results to evaluate the adaptability and efficiency of the storage strategy. By analyzing the processing time and resource utilization of data stored in the optical disc cartridge, it analyzes the effectiveness and adaptability of the storage strategy and outputs the storage management assessment results.

[0044] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0045] This invention, through in-depth analysis of optical disc data, records data access frequency, file quantity, and modification frequency, enabling more accurate calculation of data distribution and variability. It also allows for more effective identification of changes in storage needs and data access patterns, achieving precise recording of data attributes. Weight allocation and sensitivity analysis of optical disc files construct a more detailed storage management strategy, adjusting storage location and priority based on actual data usage. This not only improves data retrieval efficiency but also optimizes resource allocation, ensuring faster access to high-frequency and high-sensitivity data while reducing unnecessary data migration and storage redundancy. Dynamic monitoring of the optical disc drive's load and data access patterns responds to real-time data demands, and real-time adjustment mechanisms enhance system response speed and operational efficiency. Regular performance evaluations ensure the continuous adaptability and efficiency of the storage strategy, guaranteeing the reliability and security of long-term data preservation. Attached Figure Description

[0046] Figure 1 This is a system flowchart of the present invention;

[0047] Figure 2 This is a schematic diagram of the system framework of the present invention;

[0048] Figure 3 This is a flowchart of the data analysis module of the present invention;

[0049] Figure 4 This is a flowchart of the weight calculation module of the present invention;

[0050] Figure 5 Flowchart of the strategy formulation module of this invention;

[0051] Figure 6 This is a flowchart of the media selection module of the present invention;

[0052] Figure 7 This is a flowchart of the dynamic adjustment module of the present invention;

[0053] Figure 8 This is a flowchart of the performance evaluation module of the present invention. Detailed Implementation

[0054] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to 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.

[0055] In the description of this invention, it should be understood that the terms "length," "width," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicating orientation or positional relationships, are based on the orientation or positional relationships shown in the accompanying drawings and are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. Furthermore, in the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0056] Example 1

[0057] Please see Figures 1 to 2 A hierarchical optical disc cartridge storage management system includes:

[0058] The data analysis module identifies the stored CD data from the CD cartridge, records the access frequency, number of files, and modification frequency of each data item, calculates the distribution and variability of multiple CD data items, and generates data attribute records.

[0059] The weight calculation module records data attributes and assigns weights to factors affecting CD-ROM storage based on the frequency of CD-ROM data access and modification. Combined with the sensitivity of files stored in the CD-ROM, the weight distribution result is obtained.

[0060] Based on the weight distribution results, the strategy formulation module evaluates the priority of the data stored in the optical disc cartridge, configures the physical location of the data according to the priority order, adjusts the optical disc cartridge storage strategy using hierarchical management, optimizes the access speed and security of the data stored in the optical disc cartridge, and outputs a storage optimization plan.

[0061] The media selection module uses storage optimization schemes to analyze the resource usage of optical disc cartridges, selects matching storage media based on different data types and access frequencies, verifies the cost-effectiveness through hierarchical management, and generates media matching results.

[0062] The dynamic adjustment module adjusts the storage location based on the media matching results, monitors the load and data access patterns of the optical disc cartridge storage, responds to real-time data access needs, verifies storage efficiency and response speed through cyclic adjustment, and creates adjustment feedback records.

[0063] The performance evaluation module, based on adjustment feedback records, periodically checks the operational status of optical disc cartridge storage, analyzes the execution effect of storage strategies, extracts key performance indicators, evaluates the adaptability and efficiency of storage strategies, and generates storage management evaluation results.

[0064] Data attribute records include the access frequency, number of files, and modification frequency of optical disc data; weight distribution results include the weight values ​​of influencing factors and sensitivity assessment of files stored in optical disc cartridges; storage optimization schemes include storage strategies adjusted according to data priority and tiered management guidelines; media matching results include storage media selection and tiered management strategies for differentiated data types; adjustment feedback records include load monitoring data, data access patterns, and storage efficiency verification results for optical disc cartridge storage; and storage management evaluation results include periodic checks on the implementation effect, adaptability, and efficiency of storage strategies.

[0065] Please see Figure 2 , 3 The data analysis module includes:

[0066] The data recognition submodule identifies and classifies the file information in each CD based on the CD data in the CD case, identifies the file types associated with the CD, classifies the files, and generates a file classification list. The execution flow is as follows:

[0067] The data recognition submodule automatically identifies and categorizes file information based on the data on the CD-ROM disc in the disc cartridge. It employs advanced recognition algorithms to parse various file formats on the disc, ranging from basic text documents to multimedia files. Using the identified file types, the system sorts and categorizes files according to preset classification criteria (such as documents, images, and videos) to enable users to manage and access data more efficiently. This not only improves data retrieval efficiency but also optimizes the data storage structure, making subsequent data access faster. The generated file classification list uses the following formula:

[0068] ;

[0069] in, This represents a list of file categories. This is the total number of files on the CD. Indicates the first The weight of each file It is the first The type identifier of a file.

[0070] The data statistics submodule uses a file classification list to count the access frequency, number of files, and modification frequency of data stored in the CD-ROM cartridge, and calculates the distribution and variability of the data to obtain the statistical analysis results. The execution flow is as follows:

[0071] The data statistics submodule performs detailed statistical analysis on the files within the CD-ROM using a file classification list. It calculates the access frequency, file count, and modification frequency of the CD-ROM data, using these metrics to evaluate data usage patterns and storage efficiency. For example, files with high access frequency require more frequent backups or optimized storage solutions. The statistical results also include data distribution and variability, helping to identify potential problems or areas for improvement in data storage. This provides crucial information for data management decisions, contributing to improved overall data system performance and reliability. The statistical analysis results are obtained using the following formula:

[0072] ;

[0073] in, This indicates the results of the statistical analysis. It is an adjustment factor. , and These represent access frequency, number of files, and file modification frequency, respectively.

[0074] The attribute recognition submodule uses statistical analysis results to integrate information on the frequency of data access, the number of files, and the frequency of modification of data stored in the CD-ROM drive. The execution flow for building archives and generating data attribute records based on data attributes is as follows:

[0075] The attribute identification submodule uses statistical analysis results to conduct in-depth analysis and recording of various data attributes, integrating information on data access frequency, file quantity, and modification frequency to construct a detailed data attribute profile. Through this profile, administrators can quickly obtain a detailed description of the dataset, including data usage frequency, change history, and storage distribution. Attribute identification is crucial for implementing advanced data management strategies, such as data migration, backup, and security policies. By analyzing data attributes, data storage structure can also be optimized, data access efficiency improved, and data attribute records generated using the formula:

[0076] ;

[0077] in, Represents data attribute records, These are weight parameters. These represent access frequency, number of files, and modification frequency, respectively.

[0078] Please see Figure 2 , 4 The weight calculation module includes:

[0079] The factor analysis submodule analyzes the factors affecting the storage performance of optical disc cartridges through data attribute records, and classifies the differentiated factors by data sorting and priority evaluation to generate a factor influence classification diagram. The execution flow is as follows:

[0080] The factor analysis submodule comprehensively evaluates and analyzes key factors affecting optical disc drive storage performance through data attribute records. Using advanced data analysis techniques, it deeply mines data attributes to identify the main variables influencing storage performance. Through data sorting and prioritization methods, factors are categorized, effectively distinguishing those with the greatest impact on storage performance. This helps management implement targeted optimization measures, such as improving hardware performance or adjusting data storage strategies, and generates a factor impact hierarchy chart using the following formula:

[0081] ;

[0082] in, Indicates the influence of factors on the classification. For the total number of factors, For the first The influence value of each factor Priority rating for factors.

[0083] The sensitivity analysis submodule, based on the factor influence hierarchy diagram, uses the support vector machine algorithm to analyze the sensitivity of files stored in the optical disc cartridge, and uses the feature vectors of file access and modification records to obtain the file sensitivity evaluation table. The execution flow is as follows:

[0084] The sensitivity analysis submodule, based on a factor influence hierarchy map, uses a Support Vector Machine (SVM) algorithm to analyze the sensitivity of files stored on optical disc drives. It generates feature vectors based on file access and modification records, and uses these feature vectors to train an SVM model to accurately predict the sensitivity level of files. Sensitivity analysis identifies sensitive files requiring special attention and protection, which is crucial for complying with data protection regulations and optimizing data security strategies, resulting in a file sensitivity assessment table.

[0085] The formula for the Support Vector Machine algorithm is as follows:

[0086] ;

[0087] in, Let be the decision function. For the input feature vector, The number of vectors, For support vectors, For the class labels of support vectors, The decision function for support vectors, For Lagrange multipliers, For Gaussian kernel function, This is the bandwidth parameter of the kernel function. For regularization parameters, The weights of the error term, This is a bias term.

[0088] The execution process is as follows:

[0089] Introducing the Gaussian kernel function To replace the original dot product operation, the bandwidth parameter of the kernel function is used to enhance the model's nonlinear classification ability in high-dimensional spaces. To ensure optimal generalization performance, the optimal value is selected through cross-validation, and a regularization parameter is introduced. By adjusting the regularization parameter, the complexity of the model is balanced with the fit to the training data, and error term weights are added. By minimizing the weighted sum of error terms, the robustness of the model to noise and outliers is improved. The decision function is then recalculated by integrating the parameters. To obtain a more accurate and robust document sensitivity assessment table.

[0090] The weight allocation submodule uses a document sensitivity assessment table, combined with a factor influence hierarchy diagram, to calculate the weights of differentiated influencing factors, adjust the weights of differentiated factors, process and review documents according to their sensitivity, and generate weight distribution results. The execution flow is as follows:

[0091] The weight allocation submodule uses a file sensitivity assessment table combined with a factor influence hierarchy diagram to calculate the weights of differentiated influencing factors. By comprehensively considering the sensitivity of the file and the importance of the influencing factors, it adjusts the weights of the factors to ensure the effectiveness and rationality of data storage and processing strategies. Through dynamic weight allocation, highly sensitive files receive more attention and protection, while regular files are processed according to actual needs, generating a weight distribution result using the following formula:

[0092] ;

[0093] in, This represents the weight distribution result. It is the number of sensitivity ratings. It is the first Sensitivity score of each file These are factors that influence the score.

[0094] Please see Figure 2 , 5 The strategy formulation module includes:

[0095] The priority evaluation submodule evaluates the priority of the data stored in the optical disc cartridge based on the weight distribution results, sorts the data stored in the optical disc cartridge according to the weight priority, and generates a data priority list. The execution flow is as follows:

[0096] The priority assessment submodule prioritizes data stored in optical disc cartridges based on weight distribution results. All stored data is sorted according to its importance and sensitivity weights. A complex algorithm analyzes the weight of each data item to determine its priority within the storage strategy. This ensures that critical data receives priority processing during hardware failures or peak data access times, enhancing the efficiency and reliability of the data management system. It not only guides daily data operations but also supports emergency management, ensuring rapid access to the most important data in critical moments. A data priority list is generated using the following formula:

[0097] ;

[0098] in, This represents a list of data priorities. An array representing the weights of each data item. Represents each data item, It is a sorting function based on weights.

[0099] The hierarchical management submodule uses a data priority list and hierarchical management strategy to divide the data stored in the optical disc cartridge into hierarchical levels, allocate resources and configure storage space according to priority, and check the priority of data for priority access. The execution flow of the hierarchical management strategy is as follows:

[0100] The hierarchical management submodule implements a hierarchical management strategy through a data priority list. It divides the data stored in the optical disc cartridge into hierarchical levels and allocates resources and configures storage space according to data priority. Hierarchical management allows the system to allocate resources on demand, optimizing storage space utilization while ensuring fast access to high-priority data. The system can improve response speed and service quality while ensuring data security, making data storage more efficient and flexible. The resulting hierarchical management strategy is expressed by the following formula:

[0101] ;

[0102] in, Indicates a hierarchical management strategy. Indicates the first The priority of each data item Represented as the first Resources configured for each data item.

[0103] The strategy adjustment submodule adopts a hierarchical management strategy to adjust the optical disc cartridge storage strategy. By dynamically adjusting the storage location and resource configuration, it optimizes storage performance, verifies the response speed and data security of the optical disc cartridge storage, and outputs the execution flow of the storage optimization scheme as follows;

[0104] The strategy adjustment submodule employs a hierarchical management strategy. Based on real-time system performance and data access requirements, it dynamically adjusts the storage location and resource configuration of the optical disc drive, continuously monitors system operating status and data access patterns, and promptly adjusts storage strategies to cope with changes, thereby improving storage efficiency and data security. By optimizing data storage location and resource allocation, the response speed of the optical disc drive and the overall system performance can be significantly improved. The resulting storage optimization solution uses the following formula:

[0105] ;

[0106] in, This indicates a storage optimization scheme. Indicates time Resource adjustment factor, Indicates time Hierarchical management strategy This indicates that the resource allocation and hierarchical strategy during the observation period are integrated.

[0107] Please see Figure 2 , 6 The media selection module includes:

[0108] The resource analysis submodule analyzes the resource usage of optical disc drive storage based on the storage optimization scheme. Through hierarchical management, it measures real-time resource utilization and performs resource demand analysis to generate resource usage analysis results. The execution flow is as follows:

[0109] The resource analysis submodule, based on storage optimization schemes, provides a detailed analysis of the resource usage of optical disc drive storage. By monitoring and measuring the resource utilization of each storage tier in real time, it offers accurate resource usage reports. This helps managers understand the efficiency of resource allocation and identifies areas of resource waste. Through tiered management strategies, resource allocation can be dynamically adjusted to optimize storage performance. Based on current resource usage, it also predicts and analyzes future resource demands to support more efficient resource planning, generating resource usage analysis results using the following formula:

[0110] ;

[0111] in, This indicates the results of the resource usage analysis. Indicates the first Total resources of the layer Indicates the first Layer resource utilization rate This represents the total amount of resources. Indicates the number of levels.

[0112] The attribute analysis submodule identifies multiple types of storage data based on resource usage analysis results, performs attribute analysis on CD-ROM storage data, and classifies the data according to access frequency and modification frequency to obtain a data type classification table. The execution flow is as follows:

[0113] The attribute analysis submodule uses resource usage analysis results to perform in-depth attribute analysis on stored data, identifying various attributes such as data type, access frequency, and modification frequency, and classifying the data. This helps optimize data management and storage strategies, ensuring that data is appropriately processed according to its importance and usage frequency. Attribute analysis can significantly improve data access efficiency and system response speed, resulting in a data type classification table using the following formula:

[0114] ;

[0115] in, Represents a data type classification table. Represents data type, Represents access frequency. Represents the frequency of modification. This is a classification function.

[0116] The media matching submodule uses a data type classification table to select storage media with different data types. By comparing the performance indicators and cost-effectiveness of the media, it verifies the efficiency and cost of storage on different optical disc cartridges and outputs the media matching results. The execution flow is as follows:

[0117] The media matching submodule uses a data type classification table to select the most suitable storage medium for different types of data, comparing the performance indicators and cost-effectiveness of different media to determine the optimal storage solution. It ensures that each type of data is stored on the medium best suited to its characteristics, optimizing storage efficiency and reducing costs. The media matching result is output using the formula:

[0118] ;

[0119] in, Indicates the media matching result. For the quantity of media, Indicates the first The cost of this medium, Indicates performance metrics, It is a regulatory factor.

[0120] Please see Figure 2 , 7 The dynamic adjustment module includes:

[0121] The load assessment submodule monitors the real-time load status of optical disc cartridge storage based on media matching results, records the storage frequency and data flow of optical disc cartridges, performs load analysis on optical disc cartridge storage, and generates load monitoring and analysis results. The execution flow is as follows:

[0122] The load assessment submodule monitors and records the real-time load status of optical disc drive storage based on media matching results, tracking the storage frequency and data traffic of the drives in real time, and providing a detailed view of the current load level. By analyzing the data, it can identify load peaks, storage bottlenecks, and potential efficiency issues, helping administrators make necessary adjustments to prevent overload. It also performs trend analysis to predict future load changes, supporting more accurate resource planning and media optimization, and generates load monitoring analysis results using the following formula:

[0123] ;

[0124] in, This indicates the results of load monitoring and analysis. Indicates time storage frequency, Indicates data flow. It is the observation time window.

[0125] The pattern recognition submodule analyzes the load monitoring results and uses the K-means clustering algorithm to analyze the access patterns of data stored in the optical disc cartridge. By aggregating data requests into the target category, it optimizes data access speed and efficiency. The execution flow of the access pattern analysis results is as follows:

[0126] The pattern recognition submodule analyzes load monitoring results and uses the K-means clustering algorithm to analyze access patterns of data stored in optical disc cartridges. The clustering algorithm groups similar data requests into corresponding categories, optimizing data access speed and overall storage efficiency. By identifying common access patterns and request behaviors, data can be organized more rationally, reducing access latency and improving response speed. This also helps in designing more efficient data caching strategies and loading priorities, based on the access pattern analysis results.

[0127] The formula for the K-means clustering algorithm is as follows:

[0128] ;

[0129] in, For the first The center of each cluster, For the first Each cluster includes a set of points. For a single data point in a point set, For data points The weighting coefficients, This is the variance adjustment factor. For the first The variance of each cluster, This is the skewness adjustment factor. For the first The skewness of each cluster, This is the kurtosis adjustment factor. For the first The kurtosis of each cluster.

[0130] The execution process is as follows:

[0131] Calculate the weight of each data point The weights are determined based on the access frequency and time sensitivity of the data points, and according to the variance of each cluster. Adjust cluster centers to reflect the dispersion of data within clusters, taking into account cluster skewness. and kurtosis To assess the asymmetry and angularity of cluster shapes, a skewness adjustment coefficient is introduced. and kurtosis adjustment factor The specific values ​​of the coefficients are determined through optimization of the cross-validation dataset, and the center of each cluster is recalculated according to the formula based on the parameters and weights. This is to optimize the data access pattern.

[0132] The efficiency verification submodule uses access mode analysis results to respond to real-time data access needs. It verifies the response time and processing capability of the optical disc cartridge storage through simulation testing, examines the performance of the storage medium, verifies that the storage efficiency meets expectations, and creates the following execution flow for adjustment feedback records.

[0133] The efficiency verification submodule uses access pattern analysis results to simulate the response time and processing capacity of the optical disc cartridge storage, responding to real-time data access demands. Actual loading and access tests are used to verify the performance of the storage medium. Simulation testing helps confirm whether the storage system can meet performance expectations in real-world operation, ensuring the effectiveness of the data storage solution. Through testing, performance bottlenecks and optimization points can be identified, generating adjustment feedback records using the following formula:

[0134] ;

[0135] in, This indicates the storage efficiency verification results. It is the first Response time per access, This is the corresponding processing time. It represents the number of tests.

[0136] Please see Figure 2 , 8 The performance evaluation module includes:

[0137] The status check submodule periodically checks the operating status of the optical disc cartridge storage based on the adjustment feedback record, records the operating parameters and performance indicators of the optical disc cartridge, extracts the key performance indicators that affect the optical disc cartridge storage, and generates the operating status monitoring results. The execution flow is as follows:

[0138] The status check submodule, based on adjustment feedback records, periodically checks the operational status of the optical disc drive storage. Its main task is to monitor the drive's operating parameters and performance indicators, ensuring all system components operate according to predetermined specifications and promptly identifying potential problems or performance degradation. By analyzing the collected data, key indicators affecting storage performance, such as read / write speed, error rate, and resource utilization, are extracted. This helps determine the health status and performance level of the storage system, generating operational status monitoring results using the following formula:

[0139] ;

[0140] in, This indicates the results of the operational status monitoring. It is the first The weight of each performance metric, It refers to the number of performance indicators. These are the corresponding performance index values.

[0141] The effect comparison submodule analyzes the execution effect of the storage strategy through the running status monitoring results, compares the performance data before and after the execution of the storage strategy, and performs effect comparison analysis to verify that the execution of the storage strategy matches the expected goals. The execution flow for obtaining the execution effect analysis results is as follows:

[0142] The performance comparison submodule analyzes the execution effect of the storage strategy based on the runtime status monitoring results. It compares performance data before and after the strategy implementation, such as response time, data throughput, and system load, to assess the actual impact of the strategy change. Through comparative analysis, it verifies whether the storage strategy has achieved its expected goals, ensuring that the strategy implementation is effective and reasonable. The execution performance analysis results are obtained using the following formula:

[0143] ;

[0144] in, This indicates the results of the performance analysis. and These represent performance metrics before and after the strategy is executed, respectively.

[0145] The strategy adaptability assessment submodule uses the execution effect analysis results to evaluate the adaptability and efficiency of the storage strategy. By analyzing the processing time and resource utilization of data stored in the optical disc cartridge, it analyzes the effectiveness and adaptability of the storage strategy and outputs the storage management assessment results. The execution flow is as follows:

[0146] The strategy adaptability assessment submodule uses the execution effect analysis results to evaluate the adaptability and efficiency of the storage strategy. By deeply analyzing the processing time and resource utilization of data stored on optical disc cartridges, it assesses the performance of the storage strategy under different conditions. This helps identify the effectiveness of the strategy in specific environments, ensuring that the storage strategy can adapt to changing business needs and technical environments, and outputs the storage management assessment results using the following formula:

[0147] ;

[0148] in, This indicates the results of the storage management assessment. It is the first Processing time for each operation It refers to the number of operations. This refers to the resource utilization rate of the corresponding operation.

[0149] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments that can be applied to other fields. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A hierarchical optical disc cartridge storage management system, characterized in that, The system includes: The data analysis module identifies the stored CD data from the CD cartridge, records the access frequency, number of files, and modification frequency of each data item, calculates the distribution and variability of multiple CD data items, and generates data attribute records. The formula used is: ； in, Represents data attribute records, These are weight parameters. These represent access frequency, number of files, and modification frequency, respectively. The weight calculation module uses the data attribute records to assign weights to the factors affecting the storage of the optical disc cartridge, and combines this with the sensitivity of the files stored in the optical disc cartridge to obtain the weight distribution result. Based on the weight distribution results, the strategy formulation module evaluates the priority of the data stored in the optical disc cartridge, adjusts the optical disc cartridge storage strategy according to the priority order through hierarchical management, and outputs a storage optimization plan. The formula used is: ； in, This indicates a storage optimization scheme. Indicates time Resource adjustment factor, Indicates time Hierarchical management strategy This indicates that the resource allocation and hierarchical strategy during the observation period are integrated; The media selection module uses the storage optimization scheme to analyze the resource usage of the optical disc cartridge storage, selects storage media for different data types, and generates media matching results through hierarchical management. Based on the media matching results, the dynamic adjustment module monitors the load and data access patterns of the optical disc cartridge storage, responds to real-time data access needs, verifies storage efficiency, and creates adjustment feedback records. Based on the adjustment feedback records, the performance evaluation module periodically checks the operating status of the optical disc cartridge storage, analyzes the execution effect of the storage strategy, evaluates the adaptability and efficiency of the storage strategy, and generates storage management evaluation results.

2. The optical disc drive storage management system based on hierarchical management according to claim 1, characterized in that, The data attribute records include the access frequency, number of files, and modification frequency of optical disc data. The weight distribution results include the weight values ​​of influencing factors and the sensitivity assessment of files stored in the optical disc cartridge. The storage optimization scheme includes storage strategies adjusted according to data priority and tiered management guidelines. The media matching results include storage media selection and tiered management strategies for differentiated data types. The adjustment feedback records include load monitoring data, data access patterns, and storage efficiency verification results for optical disc cartridge storage. The storage management evaluation results include periodic checks on the execution effect, adaptability, and efficiency of the storage strategy.

3. The optical disc drive storage management system based on hierarchical management according to claim 1, characterized in that, The data analysis module includes: The data recognition submodule identifies and classifies the file information in each CD based on the CD data in the CD cartridge, identifies the file types associated with the CD, performs file classification, and generates a file classification list. The data statistics submodule uses the file classification list to count the access frequency, number of files, and modification frequency of the data stored in the CD-ROM cartridge, and calculates the distribution and variability of the data to obtain statistical analysis results. The attribute recognition submodule uses the statistical analysis results to integrate information on the frequency of data access, the number of files, and the frequency of modification of the optical disc storage, constructs archives based on data attributes, and generates data attribute records.

4. The optical disc cartridge storage management system based on hierarchical management according to claim 1, characterized in that, The weight calculation module includes: The factor analysis submodule analyzes the factors affecting the storage performance of the optical disc cartridge through the data attribute records, and classifies the differentiated factors by data sorting and priority evaluation, generating a factor influence classification diagram. The sensitivity analysis submodule analyzes the sensitivity of files stored in the optical disc cartridge based on the factor influence hierarchy diagram and uses the support vector machine algorithm. It also uses the feature vectors of file access and modification records to obtain a file sensitivity evaluation table. The weight allocation submodule uses the document sensitivity assessment table and the factor influence classification diagram to calculate the weights of differentiated influencing factors, adjust the weights of differentiated factors, process and review documents according to their sensitivity, and generate weight distribution results.

5. The optical disc drive storage management system based on hierarchical management according to claim 4, characterized in that, The formula for the support vector machine algorithm is as follows: ； in, Let be the decision function. For the input feature vector, The number of vectors, For support vectors, For the class labels of support vectors, The decision function for support vectors, For Lagrange multipliers, For Gaussian kernel function, This is the bandwidth parameter of the kernel function. For regularization parameters, The weights of the error term, This is a bias term.

6. The optical disc drive storage management system based on hierarchical management according to claim 1, characterized in that, The strategy formulation module includes: The priority evaluation submodule evaluates the priority of the optical disc cartridge storage data based on the weight distribution results, sorts the optical disc cartridge storage data according to the weight priority, and generates a data priority list. The hierarchical management submodule uses the data priority list and hierarchical management strategy to divide the data stored in the optical disc cartridge into hierarchical levels, allocate resources and configure storage space according to priority, check the priority of data and access it first, and obtain the hierarchical management strategy. The strategy adjustment submodule adopts the hierarchical management strategy to adjust the optical disc cartridge storage strategy. By dynamically adjusting the storage location and resource configuration, it optimizes storage performance, verifies the response speed and data security of the optical disc cartridge storage, and outputs a storage optimization solution.

7. The optical disc cartridge storage management system based on hierarchical management according to claim 1, characterized in that, The media selection module includes: Based on the storage optimization scheme, the resource analysis submodule analyzes the resource usage of the optical disc cartridge storage, measures real-time resource utilization through hierarchical management, performs resource demand analysis, and generates resource usage analysis results. The attribute analysis submodule identifies multiple types of storage data based on the resource usage analysis results, performs attribute analysis on the optical disc cartridge storage data, classifies the data according to the access frequency and modification frequency, and obtains a data type classification table. The media matching submodule uses the data type classification table to select storage media with different data types. By comparing the performance indicators and cost-effectiveness of the media, it verifies the efficiency and cost of storage of different optical disc cartridges and outputs the media matching results.

8. The optical disc drive storage management system based on hierarchical management according to claim 1, characterized in that, The dynamic adjustment module includes: Based on the media matching results, the load assessment submodule monitors the real-time load status of the optical disc cartridge storage, records the optical disc cartridge storage frequency and data traffic, performs load analysis on the optical disc cartridge storage, and generates load monitoring and analysis results. The pattern recognition submodule uses the load monitoring analysis results and the K-means clustering algorithm to analyze the access patterns of data stored in the optical disc cartridge. By aggregating data requests into the target category, it optimizes data access speed and efficiency and obtains access pattern analysis results. The efficiency verification submodule uses the access mode analysis results to respond to real-time data access requirements, verifies the response time and processing capability of the optical disc cartridge storage through simulation testing, examines the performance of the storage medium, verifies that the storage efficiency meets expectations, and creates adjustment feedback records.

9. The optical disc cartridge storage management system based on hierarchical management according to claim 8, characterized in that, The formula for the K-means clustering algorithm is as follows: ； in, For the first The center of each cluster, For the first Each cluster includes a set of points. For a single data point in a point set, For data points The weighting coefficients, This is the variance adjustment factor. For the first The variance of each cluster, This is the skewness adjustment factor. For the first The skewness of each cluster, This is the kurtosis adjustment factor. For the first The kurtosis of each cluster.

10. The optical disc drive storage management system based on hierarchical management according to claim 1, characterized in that, The performance evaluation module includes: Based on the adjustment feedback records, the status check submodule periodically checks the operating status of the optical disc cartridge storage, records the operating parameters and performance indicators of the optical disc cartridge, extracts the key performance indicators that affect the optical disc cartridge storage, and generates operating status monitoring results. The effect comparison submodule analyzes the execution effect of the storage strategy based on the running status monitoring results, compares the performance data before and after the execution of the storage strategy, performs effect comparison analysis, verifies that the execution of the storage strategy matches the expected goal, and obtains the execution effect analysis results. The strategy adaptability assessment submodule uses the execution effect analysis results to evaluate the adaptability and efficiency of the storage strategy. By analyzing the processing time and resource utilization of data stored in the optical disc cartridge, it analyzes the effectiveness and adaptability of the storage strategy and outputs the storage management assessment results.

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