Centralized monitoring management method and system for special software license

Abstract

The invention discloses a centralized monitoring management method and system for special software licensing, and the method comprises the steps: collecting a source data sample used by the special software licensing, obtaining the basic data of the use state of the special software licensing, and storing the basic data of the use state of the special software licensing in the centralized monitoring management system for the special software licensing, according to the centralized monitoring and management system for the special software licenses, the monitoring and management system carries out statistical analysis and visual presentation on historical basic data, the use rule of the software licenses is mined, instructive suggestions are provided for increasing and decreasing work of the future licenses, and the centralized monitoring and management system for the special software licenses provides a flexible and elastic grouping authorization management strategy; and an idle permission elastic release mechanism based on authorization use activeness can effectively improve the use efficiency of the software and realize rapid, centralized and efficient management of the existing software authorization.

Description

Technical Field

[0001] The present invention relates to the field of software management, and more specifically, to a centralized monitoring management method and system for special software licenses. Background Art

[0002] With the country's vigorous promotion of software legalization, more and more companies are on the road to software legalization, but the high cost of purchasing genuine software and the centralized management of genuine software have become a difficult problem facing enterprises. How to manage these genuine software, grasp the use of R&D personnel, improve the efficiency of software use, and provide guidance for subsequent software procurement has become an important task for system managers. From the purchase, deployment, operation and maintenance management of a software to the use of the software, different functional departments and personnel are involved. As an intangible asset, software lacks efficient management methods from cost, operation and maintenance to actual use, and often relies on manual management. When the number of software is large, even if a large amount of manpower costs are invested, it is difficult to meet the efficient software management needs of enterprises. Therefore, there is an urgent need for a centralized monitoring and management method for special software licenses. Summary of the invention

[0003] The present invention overcomes the defects of the prior art and proposes a centralized monitoring management method and system for special software licenses.

[0004] A first aspect of the present invention provides a centralized monitoring and management method for dedicated software licenses, comprising:

[0005] S101: deploying an additional module to the authorization server, monitoring the network communication data of the authorization server through the additional module, collecting basic data and historical usage data of users using the dedicated software, and pre-processing and storing the basic data and historical usage data;

[0006] S102: The collected basic data and historical usage data are saved in a database corresponding to the system, the basic data and the historical usage data are associated with each other, and usage feature analysis of the software license is performed based on different user departments to generate software usage feature data, and the usage feature data is serialized and used for prediction;

[0007] S103: Taking user departments as units, and according to the usage prediction results, setting license scheduling management for different user departments, wherein the license scheduling management includes setting of license allocation, license authorization, license borrowing, license reservation, and license restriction;

[0008] S104: In the authorization server, based on the additional module, the communication information between the server and the client is monitored and whether the client has idle license resources, a recycling cycle is set, and if there are idle license resources, a recycling instruction is sent to the authorization server for resource recycling.

[0009] In this solution, the S101 is specifically:

[0010] For the authorized server of the special software, set the corresponding additional module, which is used to collect, analyze and store data;

[0011] Through additional modules and preset collection strategies, basic data and historical usage data of users using special software are collected from the authorized server;

[0012] Basic data includes the remaining points of dedicated software licenses and the usage status data of licenses in use;

[0013] Historical usage data includes the user's software license usage frequency, usage time, and license status data within a historical period;

[0014] The preset collection strategy includes setting data sampling points, which are set based on preset time intervals, preset user operations, and specific events;

[0015] Perform data cleaning and deduplication preprocessing on basic data and historical usage data, and store the basic data and historical usage data in the system database.

[0016] In this solution, the S102 is specifically:

[0017] Analyze the collected basic data and historical usage data, save them to the system database, and establish corresponding data management strategies, including authority control strategies, backup strategies, and data archiving strategies;

[0018] The basic data and the historical usage data are associated with the usage information and the user department, and information statistics are performed through data association to generate the first characteristic data and the second characteristic data respectively;

[0019] The first characteristic data includes the total amount, usage rate and remaining quantity information of the licenses;

[0020] The second characteristic data includes the license utilization rate of each user department, peak usage period, and department license usage distribution;

[0021] Integrate the first characteristic data and the second characteristic data to form software usage characteristic data;

[0022] Build a GAN-based generative model, which includes a generator and a discriminator;

[0023] Import the software usage feature data as real data into the generation model, perform feature learning on the real data through the generator and cyclically generate virtual feature data;

[0024] Import the virtual feature data into the discriminator for discrimination, perform prediction model training and evaluation through the preset loss function, and adjust the generator and discriminator parameters in real time;

[0025] The adversarial training of the generator and the discriminator is repeated until the generator and the discriminator reach Nash equilibrium.

[0026] Generate a preset amount of simulated usage characteristic data by generating a model.

[0027] Based on the time dimension, the simulation usage characteristic data and the software usage characteristic data are serialized to obtain first sequence data and second sequence data;

[0028] Based on the PCA analysis method, feature analysis and sequence splicing are performed on the first sequence data and the second sequence data to generate fusion sequence data;

[0029] Build a prediction model based on LSTM, import the fused sequence data into the prediction model, set the prediction period, and generate prediction sequence data;

[0030] Perform data analysis on the prediction sequence data and generate usage prediction data.

[0031] In this solution, the S102 further includes:

[0032] Conduct statistical analysis on basic data, historical usage data, and usage forecast data, and display data through visualization tools, including statistical reports, charts, and graphical interface conversion tools.

[0033] Set up visual data import and export interfaces, and import or export visual data through user visual interaction.

[0034] In this solution, S103 includes:

[0035] Determine the management priorities of different user departments based on the software usage demand status and usage forecast data of user departments. The management priorities include the priority of specific user categories, the priority of business needs, and the priority of working hours.

[0036] After determining the management priority, licenses are allocated to different user departments. License allocation includes setting the license quantity, specifying the license start and end dates, and handling changes and adjustments to license management.

[0037] In this solution, S103 includes:

[0038] Through the authorization server, user data of users using special software is collected in real time. The user data includes the user's login information, access frequency, usage time, department-related parameters, and license allocation data.

[0039] Authentication and user matching based on user data;

[0040] After successful identity authentication, the user data is stored in the system database, and the users are grouped and identified by department.

[0041] In this solution, S103 includes:

[0042] According to the license usage requirements and license allocation of each user department, a corresponding license authorization strategy is formulated. The license authorization strategy includes the authority to access different professional software licenses and the access permission level, and the license authorization strategy is stored in the system database.

[0043] In this solution, the S103 further includes:

[0044] Formulate license borrowing, license reservation, and license restriction strategies for different user departments based on the software usage demand status and usage forecast data of the user departments;

[0045] License reservation strategies involve reserving a certain number of licenses for specific departments, ensuring sustainable access;

[0046] The license borrowing strategy includes setting the conditions, deadlines and procedures for borrowing licenses for different departments;

[0047] The license restriction strategy includes information on setting restrictions on the number and time of license usage for different departments.

[0048] In this solution, the S104 is specifically:

[0049] The communication information between the server and the client is monitored through the additional module on the authorization server. The monitoring process is to establish bypass communication between the professional software license centralized monitoring and management platform and the license server to monitor the usage of the client license in real time;

[0050] The platform determines whether the client user's license is idle by analyzing the communication pattern and time interval between the user and the authorization server;

[0051] The system marks the identified restricted license resources and sends instructions to the authorization server to reclaim the idle licenses from the users and provide the reclaimed license resources to new license usage requests.

[0052] The second aspect of the present invention further provides a centralized monitoring and management system for dedicated software licenses, the system comprising: a memory and a processor, the memory comprising a centralized monitoring and management program for dedicated software licenses, the centralized monitoring and management program for dedicated software licenses implementing the following steps when executed by the processor:

[0053] S101: deploying an additional module to the authorization server, monitoring the network communication data of the authorization server through the additional module, collecting basic data and historical usage data of users using the dedicated software, and pre-processing and storing the basic data and historical usage data;

[0054] S102: The collected basic data and historical usage data are saved in a database corresponding to the system, the basic data and the historical usage data are associated with each other, and usage feature analysis of the software license is performed based on different user departments to generate software usage feature data, and the usage feature data is serialized and used for prediction;

[0055] S103: Taking user departments as units, and according to the usage prediction results, setting license scheduling management for different user departments, wherein the license scheduling management includes setting of license allocation, license authorization, license borrowing, license reservation, and license restriction;

[0056] S104: In the authorization server, based on the additional module, the communication information between the server and the client is monitored and whether the client has idle license resources, a recycling cycle is set, and if there are idle license resources, a recycling instruction is sent to the authorization server for resource recycling.

[0057] The present invention solves the technical difficulties in monitoring and managing the software asset usage process. Through the method provided by the present invention, it is possible to centrally monitor the usage of professional software licenses distributed on different servers; it is possible to perform in-depth analysis of the software license usage history records, thereby providing accurate usage statistics and demand forecasts, and helping enterprises to optimize software license assets; it is possible to implement permission setting and resource allocation scheduling for software license assets, thereby meeting the multi-layer flexible authorization management needs of enterprise users; it is possible to implement idle identification and adaptive recycling of software licenses, thereby meeting the efficient allocation and utilization needs of enterprise software license assets.

[0058] The present invention discloses a method and system for centralized monitoring and management of special software licenses. By collecting source data samples of special software license usage, basic data of the usage status of special software licenses are obtained, and the basic data of the usage status of software licenses are saved in a centralized monitoring and management system for special software licenses. The monitoring and management system performs statistical analysis and visual presentation on historical basic data, mines the usage patterns of software licenses, and provides guiding opinions on the increase and decrease of future licenses. The centralized monitoring and management system for special software licenses of the present invention provides a flexible and elastic group authorization management strategy, as well as an elastic release mechanism for idle licenses based on the activeness of authorized usage, which can effectively improve the usage efficiency of software and realize fast, centralized and efficient management of existing software authorizations. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 A flow chart showing a centralized monitoring and management method for special software licenses of the present invention is shown;

[0060] Figure 2 A block diagram of the data collection process of the present invention is shown;

[0061] Figure 3 A block diagram showing the strategy implementation process of the present invention is shown;

[0062] Figure 4 A schematic diagram of the licensing resource allocation method of the present invention is shown;

[0063] Figure 5 A schematic diagram of the adaptive allocation function of licensed resources of the present invention is shown;

[0064] Figure 6 A block diagram of a centralized monitoring and management system for dedicated software licensing according to the present invention is shown. DETAILED DESCRIPTION

[0065] In order to more clearly understand the above-mentioned purpose, features and advantages of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other without conflict.

[0066] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited to the specific embodiments disclosed below.

[0067] Figure 1 A flow chart of a centralized monitoring and management method for special software licenses of the present invention is shown.

[0068] like Figure 1 As shown, the first aspect of the present invention provides a centralized monitoring and management method for dedicated software licenses, comprising:

[0069] S101: deploying an additional module to the authorization server, monitoring the network communication data of the authorization server through the additional module, collecting basic data and historical usage data of users using the dedicated software, and pre-processing and storing the basic data and historical usage data;

[0070] S102: The collected basic data and historical usage data are saved in a database corresponding to the system, the basic data and the historical usage data are associated with each other, and usage feature analysis of the software license is performed based on different user departments to generate software usage feature data, and the usage feature data is serialized and used for prediction;

[0071] S103: Taking user departments as units, and according to the usage prediction results, setting license scheduling management for different user departments, wherein the license scheduling management includes setting of license allocation, license authorization, license borrowing, license reservation, and license restriction;

[0072] S104: In the authorization server, based on the additional module, the communication information between the server and the client is monitored and whether the client has idle license resources, a recycling cycle is set, and if there are idle license resources, a recycling instruction is sent to the authorization server for resource recycling.

[0073] It should be noted that the authorization server is a software authorization server, which includes corresponding additional modules, and the additional modules are used for collecting and analyzing data and policy analysis and implementation.

[0074] According to an embodiment of the present invention, the S101 is specifically:

[0075] For the authorized server of the special software, set the corresponding additional module, which is used to collect, analyze and store data;

[0076] Through additional modules and preset collection strategies, basic data and historical usage data of users using special software are collected from the authorized server;

[0077] Basic data includes the remaining points of dedicated software licenses and the usage status data of licenses in use;

[0078] Historical usage data includes the user's software license usage frequency, usage time, and license status data within a historical period;

[0079] The preset collection strategy includes setting data sampling points, which are set based on preset time intervals, preset user operations, and specific events;

[0080] Perform data cleaning and deduplication preprocessing on basic data and historical usage data, and store the basic data and historical usage data in the system database.

[0081] It should be noted that after obtaining the data, the system first cleans and deduplicates the historical usage data. The cleaning operation can detect and repair errors, missing or abnormal values ​​in the data to ensure the accuracy of the data. The deduplication operation can remove duplicate data records to avoid duplicate impact on the analysis results.

[0082] It should be noted that the system can obtain user usage data (i.e. basic data) of the relevant special software through the additional module deployed on the authorization server, including basic data of license points and license usage status, etc. By collecting this data, the system can fully understand the usage of the software.

[0083] Figure 2 A block diagram of the data collection process of the present invention is shown;

[0084] The preset collection strategy includes setting data sampling points, which are set based on preset time intervals, preset user operations, and specific events, including: Figure 2 The process shown:

[0085] S201: The system samples the software authorization status by setting data sampling points, and collects and stores data on the use of professional software licenses within a predetermined time period;

[0086] S202: Data sampling points can be set based on time intervals, user operations, specific events, etc. to ensure the comprehensiveness and timeliness of data. At each sampling point, the system automatically records the detailed usage of professional software licenses, including the license usage status (used, idle, expired), user identity information, specific usage time period, and license details (license type, version number, etc.);

[0087] S203: Analyze, filter and organize the original data, remove invalid and duplicate data, and unify its naming rules and formats; classify and organize the original data according to different dimensions such as license category, department and time, and store it in the system database.

[0088] It should be noted that data storage and management use industry-standard database management systems to ensure data stability and reliability.

[0089] Raw data refers to basic data and historical usage data.

[0090] According to an embodiment of the present invention, the S102 is specifically:

[0091] Analyze the collected basic data and historical usage data, save them to the system database, and establish corresponding data management strategies, including authority control strategies, backup strategies, and data archiving strategies;

[0092] The basic data and the historical usage data are associated with the usage information and the user department, and information statistics are performed through data association to generate first characteristic data and second characteristic data respectively;

[0093] The first characteristic data includes the total amount, usage rate and remaining quantity information of the licenses;

[0094] The second characteristic data includes the license utilization rate of each user department, peak usage period, and department license usage distribution;

[0095] Integrate the first characteristic data and the second characteristic data to form software usage characteristic data;

[0096] Build a GAN-based generative model, which includes a generator and a discriminator;

[0097] Import the software usage feature data as real data into the generation model, perform feature learning on the real data through the generator and cyclically generate virtual feature data;

[0098] Import the virtual feature data into the discriminator for discrimination, perform prediction model training and evaluation through the preset loss function, and adjust the generator and discriminator parameters in real time;

[0099] The adversarial training of the generator and the discriminator is repeated until the generator and the discriminator reach Nash equilibrium.

[0100] Generate a preset amount of simulated usage characteristic data by generating a model.

[0101] Based on the time dimension, the simulation usage characteristic data and the software usage characteristic data are serialized to obtain first sequence data and second sequence data;

[0102] Based on the PCA analysis method, feature analysis and sequence splicing are performed on the first sequence data and the second sequence data to generate fusion sequence data;

[0103] Build a prediction model based on LSTM, import the fused sequence data into the prediction model, set the prediction period, and generate prediction sequence data;

[0104] Perform data analysis on the prediction sequence data and generate usage prediction data.

[0105] It should be noted that the data management strategy is used to ensure the security and availability of data and to ensure the long-term preservation and reliability of data. The LSTM-based prediction model includes an input layer, a hidden layer, and an output layer. The prediction model is used to implement training and prediction of serialized data. The prediction data includes prediction data on the total number of licenses, usage rate, remaining number, license utilization rate, peak usage period, and user department license usage distribution. By using the prediction data, efficient licensing policy setting and management can be achieved in the future.

[0106] It is worth mentioning here that in traditional technologies, effective predictions of license usage are often lacking, and in the collection of software license usage data, there are small amounts of data and high prediction difficulty. Especially for feature learning prediction models, the lack of existing preserved feature data often leads to low model prediction accuracy. Based on this, the present invention extracts features from existing software usage data, and based on the GAN model, performs feature learning on relevant real usage data and generates simulated data, and serializes and fuses real data with simulated data. In the future, it can effectively improve the prediction accuracy of the LSTM model, achieve effective extraction of software usage features of user departments and accurate analysis of usage predictions, improve the effectiveness and applicability of policy configuration, and thus improve the efficiency of centralized monitoring and management of software licenses.

[0107] It should be noted that the system carries out various data processing and management operations based on the collected and stored data. Associate and integrate historical user usage data with other relevant data to obtain a more comprehensive view. For example, historical usage data can be associated with license basic data to obtain information such as the total license amount, usage rate, and remaining number. Historical usage data can also be associated with other data such as user departments and projects to obtain more in-depth business analysis; common data analysis indicators include license utilization, peak usage hours, department / team distribution of license usage, etc. Users can view the usage of dedicated software, the allocation of license points, usage trends, etc. in real time according to their needs.

[0108] The system of the present invention provides a wealth of automated functions, such as automatic discovery, automatic configuration, automatic alarm, etc. It effectively reduces the workload of manual operations and improves management efficiency. The system provides various reporting and analysis functions, which can generate detailed performance reports, trend analysis, etc. This helps administrators better understand the usage and performance of the software, so as to make more accurate decisions and optimization measures.

[0109] According to an embodiment of the present invention, the S102 further includes:

[0110] Conduct statistical analysis on basic data, historical usage data, and usage forecast data, and display data through visualization tools, including statistical reports, charts, and graphical interface conversion tools.

[0111] Set up visual data import and export interfaces, and import or export visual data through user visual interaction.

[0112] It should be noted that users can use visualization tools to view the usage of special software, the allocation of license points, usage trends, etc. in real time according to their needs. The results of historical data analysis are displayed and reported through visualization charts and reports.

[0113] The report can summarize the analysis results and provide relevant suggestions and decision support. At the same time, the system can also provide optional data export and import functions to facilitate users to conduct more in-depth data analysis and cross-system data integration.

[0114] At the same time, through centralized monitoring and management, administrators can manage and configure software distributed on different servers on a central console. Administrators can monitor the license usage of professional software in real time through an intuitive visual tool interface. Through the unified and real-time view provided by the system, administrators can clearly understand the current license allocation, usage and remaining number, and which users are using which licenses. This helps administrators better understand and manage resource allocation. In addition, the centralized monitoring and management system can help administrators promptly discover software authorization failures distributed on different servers and provide detailed fault diagnosis and troubleshooting functions.

[0115] Using forecast data means using forecast results.

[0116] According to an embodiment of the present invention, the S103 includes:

[0117] Determine the management priorities of different user departments based on the software usage demand status and usage forecast data of user departments. The management priorities include the priority of specific user categories, the priority of business needs, and the priority of working hours.

[0118] After determining the management priority, licenses are allocated to different user departments. License allocation includes setting the license quantity, specifying the license start and end dates, and handling changes and adjustments to license management.

[0119] The system of the present invention integrates the scheduling management function of software licenses, allowing administrators to achieve flexible control over the use of licenses. License scheduling management should first determine the management strategy in the management system, including:

[0120] Administrators need to determine the management priorities of different users or teams. For example, the priority of specific user categories (such as senior management), the priority of business needs (such as key project groups), or the priority of work periods (such as full-day use and part-time use). License quantity management: Based on the license demand assessment, administrators need to determine the number of licenses required for each user or team. According to company policies and actual conditions, administrators assign a fixed number of licenses to each user, or dynamically adjust the number of licenses based on real-time needs.

[0121] Specify license start and end dates: Administrators need to specify the license start and end dates for each user or team to ensure the validity period of the license. Administrators can also adjust and update the license start and end dates as needed.

[0122] Changes and adjustments to license management: As business needs change, administrators need to promptly handle requests for changes to license usage, including adding or reducing the number of licenses, changing start and end dates or permissions, etc.

[0123] It should be noted that the system has the function of authorizing and managing licenses, that is, determining the specific license usage rights. Through authorization, the system can clearly specify which users can access and use specific licenses to ensure the legal and safe use of licenses. When a license is no longer needed or expires, the system can recycle the license. The reclaimed license can be reassigned to other users or departments to avoid idleness and waste of licenses.

[0124] The software usage demand status can be obtained through basic data and historical usage data.

[0125] According to an embodiment of the present invention, the S103 includes:

[0126] Through the authorization server, user data of users using special software is collected in real time. The user data includes the user's login information, access frequency, usage time, department-related parameters, and license allocation data.

[0127] Authentication and user matching based on user data;

[0128] After successful identity authentication, the user data is stored in the system database, and the users are grouped and identified by department.

[0129] Based on the collected user data, the system can obtain the corresponding user department information or other identification, and the users can be grouped. The groups can be classified according to departments, job levels, project groups, etc. This can better understand the needs of users and the allocation of licenses, and formulate corresponding license scheduling management strategies for users in different groups. In order to simplify the license management operation, the system can assign all users to a default group by default. The default group can be a group of users with basic license permissions, which is convenient for future license allocation operations.

[0130] It should be noted that setting permissions can be automated based on administrators or system platforms, and administrators can assign permissions to users through system settings. Administrators first specify different user groups, such as departments, teams, or individuals, based on the organizational structure or project structure. They can then assign the appropriate number and type of permissions to each user department. For example, for a department, an administrator can assign multiple licenses to it to meet the needs of various members of the department to use professional software. For a team or individual, an administrator can assign the right amount of permissions based on their responsibilities and project needs.

[0131] According to an embodiment of the present invention, the S103 includes:

[0132] According to the license usage requirements and license allocation of each user department, a corresponding license authorization strategy is formulated. The license authorization strategy includes the authority to access different professional software licenses and the access permission level, and the license authorization strategy is stored in the system database.

[0133] It should be noted that by establishing precise authorization policies, administrators can ensure the reasonable allocation of licenses and control of access rights. This helps to protect the security and effectiveness of software licenses while meeting the license usage needs of various departments. Administrators should closely monitor the authorization process and license usage to ensure the implementation and optimization of policies.

[0134] It should be noted that administrators can set permissions and restrictions for licenses to ensure that only authorized users can access and use specific types of licenses. In addition, administrators can also set the priority and time limit of licenses. For certain urgent or important projects, administrators can increase the license priority of related users to ensure that they can obtain the use rights of the licenses first. Administrators can also set a time limit for the automatic return of specific licenses after the project is completed, so that license resources can be released in time after the project is completed. This ensures that project teams and individuals can obtain the required license resources, helping to improve work efficiency and project success rate.

[0135] According to an embodiment of the present invention, the S103 further includes:

[0136] Formulate license borrowing, license reservation, and license restriction strategies for different user departments based on the software usage demand status and usage forecast data of the user departments;

[0137] License reservation strategies involve reserving a certain number of licenses for specific departments, ensuring sustainable access;

[0138] The license borrowing strategy includes setting the conditions, deadlines and procedures for borrowing licenses for different departments;

[0139] The license restriction strategy includes information on setting restrictions on the number and time of license usage for different departments.

[0140] It should be noted that in some cases, a department may need to temporarily borrow licenses from other departments to meet special needs. Administrators should develop a license borrowing strategy, including the conditions, deadlines, and procedures for borrowing licenses.

[0141] Administrators should review and audit license reservation and borrowing operation records in a timely manner. This helps evaluate the effectiveness of reservation and borrowing policies and the compliance of license usage. Administrators can adjust reservation and borrowing policies to adapt to the changing needs of different departments.

[0142] Figure 3 A block diagram showing the strategy implementation process of the present invention is shown;

[0143] like Figure 3 As shown in the figure, the centralized management platform configures policies through administrators or system settings, and assigns them to relevant modules and user groups (i.e. user departments). The analyzed and set configurations are saved to the database in the platform. After the policy is formulated, the platform communicates with the additional module on the authorization server and issues the above-made policies. Finally, the authorization server completes the policy implementation under the joint control of the platform and the additional module.

[0144] Figure 4 A schematic diagram of the licensing resource allocation method of the present invention is shown;

[0145] like Figure 4 As shown, in one embodiment of the present invention, if a unit has departments A and B that jointly use a software with 10 licenses ( Figure 4 On the left), Department A is an important R&D department, and Department B is a supporting department. Without allocating resources, if Department B first occupies most or even all the licenses, Department A will have no licenses available, making it impossible for the people responsible for the main work to work.

[0146] After resource allocation, based on the importance of the work, 8 licenses can be allocated to Department A; 2 licenses can be allocated to Department B. However, this method will still cause some waste. If Department A does not use up all the 8 licenses and there are extra licenses on the server, Department B can only use 2 at most and cannot use the idle licenses.

[0147] The authorization strategy is now optimized to Figure 4 As shown on the right: After resource allocation, based on the importance of the work, 4 licenses can be reserved for Department A, with a limit of 8 licenses; 1 license can be reserved for Department B, with a limit of 6 licenses. This ensures that departments with more important work have more software usage rights.

[0148] According to an embodiment of the present invention, the S104 is specifically:

[0149] The communication information between the server and the client is monitored through the additional module on the authorization server. The monitoring process is to establish bypass communication between the professional software license centralized monitoring and management platform and the license server to monitor the usage of the client license in real time;

[0150] The platform determines whether the client user's license is idle by analyzing the communication pattern and time interval between the user and the authorization server;

[0151] The system marks the identified restricted license resources and sends instructions to the authorization server to reclaim the idle licenses from the users and provide the reclaimed license resources to new license usage requests.

[0152] S104 is specifically a process of automatically identifying and adaptively recovering idle authorizations (ie, a recovery strategy process).

[0153] Figure 5 The figure shows a functional schematic diagram of the adaptive allocation of licensed resources of the present invention, which is a simplified schematic diagram of the recycling process.

[0154] It should be noted that the system can determine whether the client user's license is idle by analyzing the communication mode and time interval between the user and the authorization server, thereby accurately identifying idle license resources and license resources in use. This process corresponds to Figure 5 Condition matching process.

[0155] It should be noted that, in one embodiment of the present invention, the administrator can specify the time interval for the system to scan the user occupying the authorization status. Generally speaking, due to the large number of users of software licenses in an enterprise, a too short scanning time interval will undoubtedly cause greater work pressure on the system and the authorization server. Therefore, during the implementation process, the recommended scanning time interval is no less than 3 minutes. For situations with a larger number of authorizations, it can be appropriately relaxed to 5 to 10 minutes. In addition, in the case of a large number of software licenses remaining, it is not necessary to release idle licenses. Therefore, the system can set a threshold value to start the automatic identification of idle authorizations and the adaptive authorization recovery function when the number of remaining licenses in the system is lower than this value.

[0156] According to an embodiment of the present invention, it also includes:

[0157] For a user department, based on basic data and historical usage data, the usage demand analysis of N historical usage cycles is performed to generate N historical demand degrees;

[0158] Based on the prediction model, the usage characteristics analysis and usage prediction of N usage cycles are performed on the user department, prediction data is generated in combination with the prediction model, and the obtained prediction data is subjected to demand analysis to obtain N predicted demand degrees;

[0159] The forecast data includes forecast data for N usage cycles;

[0160] Perform linear change analysis on N historical demand degrees, and calculate the average linear change rate of the data to obtain the first change rate;

[0161] Perform linear change analysis on N predicted demand degrees, and calculate the average linear change rate of the data to obtain a second change rate;

[0162] If the second change rate is greater than the first change rate, the current recycling strategy is determined to be a negative impact, and the recycling strategy is regulated, including optimizing the recycling frequency, optimizing the recycling time node, and resetting the scanning and occupying authorization interval.

[0163] It should be noted that the obtained prediction data includes usage prediction data of N usage cycles. The average linear change rate can be calculated and recorded by the change rate between adjacent data, and finally obtained by taking the average value of the change rate of the overall data. It reflects the change characteristics of N data, whether it is an increase or a decrease.

[0164] It is worth mentioning that in the process of license resource recovery, the setting of recovery frequency and recovery time point is particularly important. If the recovery frequency is too low, it will lead to less recovered resources, low license utilization rate and resource waste. If the recovery frequency is too high, it will easily affect the normal user's team building license use, causing users to perform too much interaction between software application and license acquisition. Based on this, the present invention sets N usage cycles, performs demand analysis and calculation based on N historical usage cycles and N usage cycles predicted by user usage characteristics, performs linear change analysis through the calculation of N demand degrees, and analyzes the change of user demand characteristics from the first N cycles to the second N cycles based on linear changes, so as to analyze whether the recovery strategy has a positive or negative impact on the user's use. If the second change rate is greater than the first change rate, it means that the user's demand for licenses is continuously increasing, the license usage situation is continuously tense, and the recovery strategy has brought negative effects and has not improved the corresponding utilization rate. Therefore, the strategy can be dynamically optimized based on the existing situation.

[0165] Figure 6 A block diagram of a centralized monitoring and management system for dedicated software licensing according to the present invention is shown.

[0166] The second aspect of the present invention further provides a centralized monitoring and management system 6 for dedicated software licenses, the system comprising: a memory 61, a processor 62, the memory 61 comprising a centralized monitoring and management program for dedicated software licenses, the centralized monitoring and management program for dedicated software licenses when executed by the processor 62 implements the following steps:

[0167] S101: deploying an additional module to the authorization server, monitoring the network communication data of the authorization server through the additional module, collecting basic data and historical usage data of users using the dedicated software, and pre-processing and storing the basic data and historical usage data;

[0168] S102: Save the collected basic data and historical usage data to the database corresponding to the system, associate the basic data with the historical usage data, and analyze the usage characteristics of the software license based on different user departments to generate software usage characteristic data, and serialize and predict the usage characteristic data;

[0169] S103: Taking user departments as units, and according to the usage prediction results, setting license scheduling management for different user departments, wherein the license scheduling management includes setting of license allocation, license authorization, license borrowing, license reservation, and license restriction;

[0170] S104: In the authorization server, based on the additional module, the communication information between the server and the client is monitored and whether the client has idle license resources, a recycling cycle is set, and if there are idle license resources, a recycling instruction is sent to the authorization server for resource recycling.

[0171] The present invention discloses a method and system for centralized monitoring and management of special software licenses. By collecting source data samples of special software license usage, basic data of the usage status of special software licenses are obtained, and the basic data of the usage status of software licenses are saved in a centralized monitoring and management system for special software licenses. The monitoring and management system performs statistical analysis and visual presentation on historical basic data, mines the usage patterns of software licenses, and provides guiding opinions on the increase and decrease of future licenses. The centralized monitoring and management system for special software licenses of the present invention provides a flexible and elastic group authorization management strategy, as well as an elastic release mechanism for idle licenses based on the activeness of authorized usage, which can effectively improve the usage efficiency of software and realize fast, centralized and efficient management of existing software authorizations.

[0172] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0173] The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units; they may be located in one place or distributed on multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0174] In addition, all functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately used as a unit, or two or more units may be integrated into one unit; the above-mentioned integrated units may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0175] A person of ordinary skill in the art can understand that: all or part of the steps of implementing the above method embodiments can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps of the above method embodiments; and the aforementioned storage medium includes: mobile storage devices, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks or optical disks, and other media that can store program codes.

[0176] Alternatively, if the above-mentioned integrated unit of the present invention is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present invention can be essentially or partly reflected in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROM, RAM, magnetic disks or optical disks.

[0177] The above description is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A method for centralized monitoring and management of special software licenses, characterized in that: include: S101: deploying an additional module to the authorization server, monitoring the network communication data of the authorization server through the additional module, collecting basic data and historical usage data of users using the dedicated software, and pre-processing and storing the basic data and historical usage data; S102: Save the collected basic data and historical usage data to the database corresponding to the system, associate the basic data with the historical usage data, and analyze the usage characteristics of the software license based on different user departments to generate software usage characteristic data, and serialize and predict the usage characteristic data; S103: Taking user departments as units, and according to the usage prediction results, setting license scheduling management for different user departments, wherein the license scheduling management includes setting of license allocation, license authorization, license borrowing, license reservation, and license restriction; S104: In the authorization server, based on the additional module, the communication information between the server and the client is monitored and whether the client has idle license resources, a recycling cycle is set, and if there are idle license resources, a recycling instruction is sent to the authorization server for resource recycling.

2. The centralized monitoring and management method for special software licenses according to claim 1, characterized in that: The S101 is specifically: For the authorized server of the special software, set the corresponding additional module, which is used to collect, analyze and store data; Through additional modules and preset collection strategies, basic data and historical usage data of users using special software are collected from the authorized server; Basic data includes the remaining points of dedicated software licenses and the usage status data of licenses in use; Historical usage data includes the user's software license usage frequency, usage time, and license status data within a historical period; The preset collection strategy includes setting data sampling points, which are set based on preset time intervals, preset user operations, and specific events; Perform data cleaning and deduplication preprocessing on basic data and historical usage data, and store the basic data and historical usage data in the system database.

3. The centralized monitoring and management method for special software licenses according to claim 1, characterized in that: The S102 is specifically: Analyze the collected basic data and historical usage data, save them to the system database, and establish corresponding data management strategies, including authority control strategies, backup strategies, and data archiving strategies; The basic data and the historical usage data are associated with the usage information and the user department, and information statistics are performed through data association to generate the first characteristic data and the second characteristic data respectively; The first characteristic data includes the total amount, usage rate and remaining quantity information of the licenses; The second characteristic data includes the license utilization rate of each user department, peak usage period, and department license usage distribution; Integrate the first characteristic data and the second characteristic data to form software usage characteristic data; Build a GAN-based generative model, which includes a generator and a discriminator; Import the software usage feature data as real data into the generation model, perform feature learning on the real data through the generator and cyclically generate virtual feature data; Import the virtual feature data into the discriminator for discrimination, perform prediction model training and evaluation through the preset loss function, and adjust the generator and discriminator parameters in real time; The adversarial training of the generator and the discriminator is repeated until the generator and the discriminator reach Nash equilibrium. Generate a preset amount of simulated usage characteristic data by generating a model. Based on the time dimension, the simulation usage characteristic data and the software usage characteristic data are serialized to obtain first sequence data and second sequence data; Based on the PCA analysis method, feature analysis and sequence splicing are performed on the first sequence data and the second sequence data to generate fusion sequence data; Build a prediction model based on LSTM, import the fused sequence data into the prediction model, set the prediction period, and generate prediction sequence data; Perform data analysis on the prediction sequence data and generate usage prediction data.

4. A method for centralized monitoring and management of special software licenses according to claim 3, characterized in that: The S102 further includes: Conduct statistical analysis on basic data, historical usage data, and usage forecast data, and display data through visualization tools, including statistical reports, charts, and graphical interface conversion tools. Set up visual data import and export interfaces, and import or export visual data through user visual interaction.

5. A method for centralized monitoring and management of special software licenses according to claim 4, characterized in that: The S103 includes: Determine the management priorities of different user departments based on the software usage demand status and usage forecast data of user departments. The management priorities include the priority of specific user categories, the priority of business needs, and the priority of working hours. After determining the management priority, licenses are allocated to different user departments. License allocation includes setting the license quantity, specifying the license start and end dates, and handling changes and adjustments to license management.

6. A method for centralized monitoring and management of special software licenses according to claim 5, characterized in that: The S103 includes: Through the authorization server, user data of users using special software is collected in real time. The user data includes the user's login information, access frequency, usage time, department-related parameters, and license allocation data. Authentication and user matching based on user data; After successful identity authentication, the user data is stored in the system database, and the users are grouped and identified by department.

7. A method for centralized monitoring and management of special software licenses according to claim 6, characterized in that: The S103 includes: According to the license usage requirements and license allocation of each user department, a corresponding license authorization strategy is formulated. The license authorization strategy includes the authority to access different professional software licenses and the access permission level, and the license authorization strategy is stored in the system database.

8. The method for centralized monitoring and management of special software licenses according to claim 7, characterized in that: The S103 further includes: Formulate license borrowing, license reservation, and license restriction strategies for different user departments based on the software usage demand status and usage forecast data of the user departments; License reservation strategies involve reserving a certain number of licenses for specific departments, ensuring sustainable access; The license borrowing strategy includes setting the conditions, deadlines and procedures for borrowing licenses for different departments; The license restriction strategy includes information on setting restrictions on the number and time of license usage for different departments.

9. A method for centralized monitoring and management of special software licenses according to claim 8, characterized in that: The S104 is specifically: The communication information between the server and the client is monitored through the additional module on the authorization server. The monitoring process is to establish bypass communication between the professional software license centralized monitoring and management platform and the license server to monitor the usage of the client license in real time; The platform determines whether the client user's license is idle by analyzing the communication pattern and time interval between the user and the authorization server; The system marks the identified restricted license resources and sends instructions to the authorization server to reclaim the idle licenses from the users and provide the reclaimed license resources to new license usage requests.

10. A centralized monitoring and management system for special software licensing, characterized in that: The system includes: a memory and a processor, wherein the memory includes a centralized monitoring management program of a dedicated software license, and when the centralized monitoring management program of the dedicated software license is executed by the processor, the following steps are implemented: S101: deploying an additional module to the authorization server, monitoring the network communication data of the authorization server through the additional module, collecting basic data and historical usage data of users using the dedicated software, and pre-processing and storing the basic data and historical usage data; S102: The collected basic data and historical usage data are saved in a database corresponding to the system, the basic data and the historical usage data are associated with each other, and usage feature analysis of the software license is performed based on different user departments to generate software usage feature data, and the usage feature data is serialized and used for prediction; S103: Taking user departments as units, and according to the usage prediction results, setting license scheduling management for different user departments, wherein the license scheduling management includes setting of license allocation, license authorization, license borrowing, license reservation, and license restriction; S104: In the authorization server, based on the additional module, the communication information between the server and the client is monitored and whether the client has idle license resources, a recycling cycle is set, and if there are idle license resources, a recycling instruction is sent to the authorization server for resource recycling.

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