A Centralized Monitoring and Management Method and System for Special Software Licenses

Abstract

The present invention discloses a method and system for centralized monitoring and management of dedicated software licenses. By collecting source data samples of the use of dedicated software licenses, basic data on the usage status of dedicated software licenses is obtained, and the basic data on the software license usage status is saved into the dedicated software license centralized monitoring and management system. The monitoring and management system performs statistical analysis and visual presentation on the historical basic data, mines the usage rules of software licenses, and provides guiding opinions on the increase and decrease of future licenses. The dedicated software license centralized monitoring and management system of the present invention provides a flexible and elastic grouping authorization management strategy, as well as an idle license elastic release mechanism based on the activity of authorized use, which can effectively improve the usage efficiency of software and achieve fast, centralized, and efficient management of existing software authorizations.

Description

Technical Field

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

[0002] With the strong promotion of software legalization by the state, more and more enterprises have embarked on the path of software legalization. However, the high procurement cost of legal software and the centralized management of legal software have become a difficult problem for enterprises. How to manage these legal software, master the usage of R & D personnel, improve the software usage efficiency, and provide guiding opinions for subsequent software procurement has become an important task for system administrators. A software involves different functional departments and personnel from purchase, deployment, operation and maintenance management to software usage. As an intangible asset, there is a lack of efficient methods for management in the prior art in terms of cost, operation and maintenance, and actual usage. It often relies on manual management. When the number of software is large, it is difficult to meet the high-efficiency software management needs of enterprises even with a large amount of human cost input. Therefore, there is an urgent need for a method for centralized monitoring and management of dedicated software licenses at present. Summary of the Invention

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

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

[0005] S101: Deploy an additional module to the authorization server, monitor the network communication data of the authorization server through the additional module, collect the basic data and historical usage data of users using the dedicated software, and preprocess and store the basic data and historical usage data;

[0006] S102: Save the collected basic data and historical usage data into the corresponding database of the system, perform data association on the basic data and historical usage data, and perform usage feature analysis on the software license based on different user departments to generate software usage feature data, and serialize and predict the usage of the usage feature data;

[0007] S103: Taking the user department as a unit, set the license scheduling management for different user departments according to the usage prediction result. The license scheduling management includes the setting of license allocation, license authorization, license borrowing, license reservation, and license restriction;

[0008] S104: In the authorization server, based on the additional module, listen to the communication information between the server and the client and identify whether there are idle license resources on the client, set the recycling period, and if there are idle license resources, send a recycling instruction to the authorization server for resource recycling.

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

[0010] For the authorization server of the dedicated software, set corresponding additional modules, which are used to collect, analyze, and store data;

[0011] Through the additional modules and the preset collection strategy, collect the basic data and historical usage data of users using the dedicated software from the authorization server;

[0012] The basic data includes the remaining points of the dedicated software license and the usage status data of the in-use license;

[0013] The historical usage data includes the software license usage frequency, usage time, and license status data of users within the historical time period;

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

[0015] Perform data cleaning and deduplication preprocessing on the 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 as follows:

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

[0018] Associate the usage information of the basic data and historical usage data with the user departments using them, and perform information statistics through data association to generate first characteristic data and 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, peak usage period, and department license usage distribution of each user department;

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

[0022] Construct a GAN-based generation model, which includes a generator and a discriminator;

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

[0024] Import virtual feature data into the discriminator for discrimination, and train and evaluate the prediction model through a preset loss function, and adjust the parameters of the generator and discriminator in real time;

[0025] Perform adversarial training on the generator and discriminator in a loop until the generator and discriminator reach Nash equilibrium;

[0026] Through the generation model, generate simulated usage feature data of a preset data volume,

[0027] Based on the time dimension, serialize the simulated usage feature data and the software usage feature data to obtain the first sequence data and the second sequence data;

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

[0029] Construct an LSTM-based prediction model, import the fused sequence data into the prediction model, set the prediction period, and generate prediction sequence data;

[0030] Parse the prediction sequence data and generate usage prediction data.

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

[0032] Perform statistical analysis on the basic data, historical usage data, and usage prediction data, and display the data through a visualization tool. The visualization tool includes statistical reports, charts, and graphical interface conversion tools,

[0033] Set the import and export interfaces for the visualization data, and perform import or export operations on the visualization data through user visualization interaction.

[0034] In this solution, the S103 includes:

[0035] Determine the management priorities of different user departments based on the software usage requirement status and usage prediction data of the user department. The management priorities include the priorities of specific user categories, business requirements, and working hours;

[0036] After determining the management priorities, perform license allocation for different user departments. The license allocation includes setting the license quantity, specifying the start and end dates of the license, and handling changes and adjustments to the license management.

[0037] In this solution, the S103 includes:

[0038] Through the authorization server, collect user data of users using the dedicated software in real time. The user data includes the login information, access frequency, usage time, department association parameters, and license allocation data of the users;

[0039] Perform authentication and user matching based on user data;

[0040] After successful authentication, store the user data in the system database, and group and identify the users by department.

[0041] In this solution, the S103 includes:

[0042] According to the licensing usage requirements and licensing allocation of each user department, formulate corresponding licensing authorization policies, where the licensing authorization policies include the permissions to access different professional software licenses, access permission levels, and store the licensing authorization policies in the system database.

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

[0044] According to the software usage requirement status and usage prediction data of the user department, formulate licensing borrowing, licensing reservation, and licensing restriction policies for different user departments;

[0045] The licensing reservation policy includes reserving a certain number of licenses for a specific department to ensure sustainable access rights;

[0046] The licensing borrowing policy includes setting conditions, terms, and procedures for borrowing licenses for different departments;

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

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

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

[0050] The platform judges whether the license of the client user is in an idle state by analyzing the communication mode and time interval between the user and the authorization server;

[0051] The system marks the identified restricted license resources, sends an instruction to the authorization server to recycle the idle licenses from the user, and provides the recycled license resources to new license usage requests.

[0052] The second aspect of the present invention also provides a centralized monitoring and management system for professional software licenses, which includes: a memory, a processor. The memory includes a centralized monitoring and management program for professional software licenses. When the centralized monitoring and management program for professional software licenses is executed by the processor, the following steps are implemented:

[0053] S101: Deploy an additional module to the authorization server. Monitor the network communication data of the authorization server through the additional module, collect the basic data and historical usage data of users using the dedicated software, and preprocess and store the basic data and historical usage data;

[0054] S102: Save the collected basic data and historical usage data to the corresponding database of the system. Perform data association on the basic data and historical usage data, and conduct usage feature analysis on software licenses based on different user departments to generate software usage feature data. Serialize and perform usage prediction on the usage feature data;

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

[0056] S104: In the authorization server, based on the additional module, monitor the communication information between the server and the client and identify whether there are idle license resources on the client. Set the recycling period. If there are idle license resources, send a recycling instruction to the authorization server for resource recycling.

[0057] The present invention solves the technical problems of monitoring and management in the process of using software assets. 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 conduct in-depth analysis of the historical records of software license usage, thereby providing accurate usage rate statistics and demand prediction to help enterprises optimize software license assets; it is possible to set permissions and allocate and schedule resources for software license assets, thereby meeting the multi-level flexible authorization management needs of enterprise users; it is possible to identify idle software licenses and perform adaptive recycling, thereby meeting the needs of efficient allocation and utilization of enterprise software license assets.

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

[0059] Figure 1 Shows the flowchart of a centralized monitoring and management method for a special software license of the present invention;

[0060] Figure 2 Shows the block diagram of the data acquisition process of the present invention;

[0061] Figure 3 Shows the block diagram of the strategy implementation process of the present invention;

[0062] Figure 4 Shows the schematic diagram of the license resource allocation method of the present invention;

[0063] Figure 5 Shows the schematic diagram of the license resource adaptive allocation function of the present invention;

[0064] Figure 6 Shows the block diagram of a centralized monitoring and management system for a special software license of the present invention. Detailed implementation manners

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

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

[0067] Figure 1 Shows the flowchart of a centralized monitoring and management method for a special software license of the present invention.

[0068] As Figure 1 shown, the first aspect of the present invention provides a centralized monitoring and management method for a special software license, including:

[0069] S101: Deploy an additional module to the authorization server, monitor the network communication data of the authorization server through the additional module, collect the basic data and historical usage data of users using the special software, and preprocess and store the basic data and historical usage data;

[0070] S102: Save the collected basic data and historical usage data into the corresponding database of the system, perform data association on the basic data and historical usage data, perform usage feature analysis on the software license based on different user departments, generate software usage feature data, and serialize and predict the usage of the usage feature data;

[0071] S103: Taking the user department as a unit, set the license scheduling management for different user departments according to the usage prediction results. The license scheduling management includes the setting of license allocation, license authorization, license borrowing, license reservation, and license restriction.

[0072] S104: In the authorization server, based on the additional module, monitor the communication information between the server and the client and identify whether there are idle license resources on the client. Set the recovery period. If there are idle license resources, send a recovery instruction to the authorization server for resource recovery.

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

[0074] According to the embodiments of the present invention, the S101 is specifically as follows:

[0075] For the authorization server of the dedicated software, set the corresponding additional module, which is used for data collection, analysis, and storage.

[0076] Through the additional module and the preset collection strategy, collect the basic data and historical usage data of the user using the dedicated software from the authorization server.

[0077] The basic data includes the remaining points of the dedicated software license and the usage status data of the in-use license.

[0078] The historical usage data includes the software license usage frequency, usage time, and license status data of the user within the historical time period.

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

[0080] Perform data cleaning and duplicate removal preprocessing on the 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 the system obtains the data, it first performs cleaning and duplicate removal processing on the historical usage data. The cleaning operation can detect and repair errors, missing values, or outliers in the data to ensure the accuracy of the data. The duplicate removal operation can remove duplicate data records to avoid duplicate impacts on the analysis results.

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

[0083] Figure 2 The block diagram showing the data acquisition process of the present invention is presented;

[0084] The preset acquisition strategy includes setting data sampling points, which are set based on a preset time interval, preset user operations, and specific events, including, for example Figure 2 the process shown as follows:

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

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

[0087] The original data is analyzed, filtered, and sorted out, removing invalid and duplicate data, and unifying its naming rules and formats; the original data is classified and sorted according to different dimensions such as license category, department, and time, and stored in the system database.

[0088] It should be noted that the data storage and management adopt an industry-standard database management system to ensure the stability and reliability of the data.

[0089] The original data is the basic data and historical usage data.

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

[0091] The collected basic data and historical usage data are parsed and saved to the system database, and corresponding data management strategies are established. The data management strategies include permission control strategies, backup strategies, and data archiving strategies;

[0092] The basic data and historical usage data are associated with usage information and the user departments using them, 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 number of licenses, the usage rate, and the remaining quantity information;

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

[0095] The first characteristic data and the second characteristic data are integrated to form software usage characteristic data;

[0096] Construct a GAN-based generation model, where the generation model includes a generator and a discriminator;

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

[0098] Import the virtual feature data into the discriminator for discrimination, and use a preset loss function to train and evaluate the prediction model and adjust the parameters of the generator and discriminator in real time;

[0099] Perform adversarial training on the generator and the discriminator in a loop until the generator and the discriminator reach Nash equilibrium;

[0100] Generate simulated usage feature data of a preset data volume through the generation model,

[0101] Based on the time dimension, serialize the simulated usage feature data and the software usage feature data to obtain the first sequence data and the second sequence data;

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

[0103] Construct an LSTM-based prediction model, import the fused sequence data into the prediction model, set the prediction period, and generate prediction sequence data;

[0104] Parse 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, and the prediction model is used to implement the training and prediction of serialized data. The usage prediction data includes prediction data on information such as the total amount of licenses, the usage rate, the remaining quantity, the license utilization rate, the peak usage period, and the distribution of license usage by user departments. Through the use of the usage prediction data, efficient license policy setting and management can be achieved subsequently.

[0106] It is worth mentioning here that in traditional technologies, there is often a lack of effective prediction for license usage, and in the collection of software license usage data, there are problems such as a small amount of data and high prediction difficulty. Especially for the prediction model of feature learning, the lack of existing saved feature data often leads to low prediction accuracy of the model. Based on this, the present invention extracts features from existing software usage data, and based on the GAN model, conducts feature learning on relevant real usage data and generates simulated data. By serially fusing real data and simulated data, in the follow-up, it can effectively improve the prediction accuracy of the LSTM model, realize the effective extraction of software usage features of user departments and the precise analysis of usage prediction, improve the effectiveness and applicability of policy configuration, and further improve the centralized monitoring and management efficiency of software licenses.

[0107] It should be noted that the system conducts various data processing and management operations based on the collected and stored data. Associates and integrates 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 amount, usage rate, and remaining quantity of licenses. 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 rate, peak usage period, department / team distribution of license usage, etc. Users can, according to their own needs, view the usage situation of dedicated software, the allocation of license points, the trend of usage situation, etc. in real time.

[0108] The system of the present invention provides rich automation functions, such as automatic discovery, automatic configuration, automatic alarm, etc. It effectively reduces the workload of manual operations and improves the management efficiency. The system provides various report and analysis functions, and can generate detailed performance reports, trend analysis, etc. This helps administrators better understand the usage situation and performance status of 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] Statistically analyze the basic data, historical usage data, and usage prediction data, and display the data through visualization tools. The visualization tools include statistical reports, charts, and graphical interface conversion tools.

[0111] Set the import and export interfaces for visualization data, and through user visualization interaction, perform import or export operations on the visualization data.

[0112] It should be noted that users can, according to their own needs, view the usage situation of dedicated software, the allocation of license points, the trend of usage situation, etc. in real time through visualization tools. Display and report the results of historical data analysis through visualization charts and reports.

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

[0114] Meanwhile, through centralized monitoring and management, the administrator can manage and configure the software distributed on different servers on a central console. The administrator 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, the administrator can clearly master the current license allocation situation, the number of licenses in use and the remaining number, as well as which users are using which licenses. This helps the administrator better understand and manage the resource allocation situation. In addition, the centralized monitoring and management system can help the administrator promptly detect software authorization failures distributed on different servers and provide detailed fault diagnosis and troubleshooting functions.

[0115] Use the prediction data, that is, use the prediction results.

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

[0117] Determine the management priorities of different user departments based on the software usage requirement status and usage prediction data of the user departments. The management priorities include the priorities of specific user categories, business requirements, and working hours;

[0118] After determining the management priorities, perform license allocation for different user departments. The license allocation includes setting the license quantity, specifying the start and end dates of the license, and handling changes and adjustments to license management.

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

[0120] The administrator needs to determine the management priorities of different users or teams. For example: the priorities of specific user categories (such as senior management), the priorities of business requirements (such as key project teams), or the priorities of working hours (such as full-day use and non-full-day use). License quantity management: Based on the license demand assessment, the administrator needs to determine the license quantity required for each user or team. According to the company's policies and actual situations, the administrator assigns a fixed number of licenses to each user, or dynamically adjusts the license quantity based on real-time needs.

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

[0122] Changes and adjustments to license management: As business requirements change, administrators need to promptly process change requests for 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 specific license usage permissions. Through authorization, the system can clearly specify which users can access and use specific licenses to ensure the legal and secure use of licenses. When a license is no longer needed or expires, the system can recycle the license. The recycled license can be rescheduled and allocated to other users or departments to avoid the idle and waste of licenses.

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

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

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

[0127] Based on the user data, identity verification and user matching are performed;

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

[0129] According to the collected user data, the corresponding user department information or other identifiers can be obtained, and the system can group the users. The grouping can be classified according to departments, job levels, project teams, etc. This can better understand the needs of users and the license allocation situation, and formulate corresponding license scheduling management strategies for different groups of users. To simplify license management operations, the system can defaultly assign all users to a default group. 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 the license can be set based on the administrator or system platform automation. The administrator can allocate licenses to users through system settings. The administrator first specifies different user groups according to the organizational structure or project structure, such as departments, teams, or individuals. Then, they can allocate appropriate numbers and types of licenses to each user department. For example, for a department, the administrator can allocate multiple licenses to meet the needs of each member of the department to use professional software. For a team or an individual, the administrator can allocate an appropriate amount of licenses according to their responsibilities and project requirements.

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

[0132] According to the license usage requirements and license allocation situations of each user department, formulate corresponding license authorization policies. The license authorization policies include the permissions to access different professional software licenses and the access permission levels, and store the license authorization policies in the system database.

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

[0134] It should be noted that administrators can set the usage permissions and restrictions of licenses to ensure that only authorized users can access and use specific types of licenses. In addition, administrators can also set the priorities and time limits of licenses. For some urgent or important projects, administrators can increase the license priorities of relevant users to ensure that they can obtain the usage permissions of licenses first. Administrators can also set the time limit for specific licenses to be automatically returned after the completion of the project, so as to release the license resources in a timely manner after the project ends. Furthermore, it ensures that project teams and individuals can obtain the required license resources, helping to improve work efficiency and project success rates.

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

[0136] According to the software usage requirement status and usage prediction data of user departments, formulate license borrowing, license reservation, and license restriction policies for different user departments;

[0137] The license reservation policy includes reserving a certain number of licenses for a specific department to ensure sustainable access permissions;

[0138] The license borrowing policy includes setting conditions, terms, and procedures for borrowing licenses for different departments;

[0139] The license restriction policy includes setting restriction information on the license usage quantity and usage time for different departments.

[0140] It should be noted that in some cases, a department may need to temporarily borrow the licenses of other departments to meet special needs. Administrators should formulate license borrowing policies, including setting conditions, terms, and procedures for borrowing licenses.

[0141] Administrators should promptly review and examine the records of license reservation and borrowing operations. This helps to evaluate the effectiveness of reservation and borrowing policies and the compliance of license usage. Administrators can adjust the reservation and borrowing policies to adapt to the changing needs of different departments.

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

[0143] As Figure 3 shown, the centralized management platform performs policy configuration through the administrator or system setting method, and assigns it to relevant modules and user groups (i.e., user departments), saves the configured settings analyzed to the database in the platform. After the policy is formulated, the platform communicates with the additional module on the authorization server to issue the above-mentioned formulated policy. Finally, under the joint control of the platform and the additional module, the authorization server completes the implementation of the policy.

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

[0145] As Figure 4 shown, in an embodiment of the present invention, if a unit has departments A and B jointly using a software with 10 authorization licenses ( Figure 4 on the left), where department A is an important R & D department and department B is an assisting department. Without resource allocation, if department B first occupies most or even all of the licenses, it will cause department A to have no licenses available, and thus the people undertaking the main work cannot work.

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

[0147] Now the authorization policy is optimized to Figure 4 shown on the right: After resource allocation, according to the importance of the work, 4 licenses can be reserved for department A and 8 licenses are restricted; 1 license is reserved for department B and 6 licenses are restricted. This can ensure that the department with more important work has more software usage rights.

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

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

[0150] The platform analyzes the communication mode and time interval between the user and the authorization server to determine whether the license of the client user is in an idle state;

[0151] The system marks the recognized restricted license resources, sends an instruction to the authorization server to recycle the idle licenses from the user, and provides the recycled license resources to new license usage requests.

[0152] Specifically, S104 is an automatic recognition and adaptive recycling process for idle authorizations (i.e., the recycling policy process).

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

[0154] It should be noted that by analyzing the communication mode and time interval between the user and the authorization server, the system can determine whether the license of the client user is in an idle state, so as to accurately identify the idle license resources and the license resources in use. This process corresponds to Figure 5 the condition matching process in

[0155] It should be noted that in an embodiment of the present invention, the administrator can specify the time interval for the system to scan the authorization status occupied by the user. Generally speaking, due to the large number of software license users in the enterprise, too small a scanning time interval will undoubtedly cause greater working pressure on the system and the authorization server. Therefore, in the implementation process, the scanning time interval is recommended to be no less than 3 minutes. For situations with more authorizations, it can be appropriately relaxed to 5 - 10 minutes. In addition, in the case of a large number of remaining software licenses, there is no need to release the idle licenses. Therefore, the system can set a threshold value to start the automatic recognition of idle authorizations and the adaptive recycling function of authorizations when the remaining license quantity of the system is lower than this value.

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

[0157] For a user department, based on the basic data and historical usage data, analyze the usage demand degree for the historical N usage cycles to generate N historical demand degrees;

[0158] Based on the prediction model, conduct usage feature analysis and usage prediction for the said user department for N usage cycles, generate prediction data in combination with the prediction model, and conduct demand degree analysis on the obtained prediction data to obtain N predicted demand degrees;

[0159] The prediction data includes N usage cycle usage prediction data;

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

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

[0162] If the second rate of change is greater than the first rate of change, it is determined that the current recycling strategy has a negative impact, and the recycling strategy is regulated. The regulation includes optimizing the recycling frequency, optimizing the recycling time node, and resetting the scanning occupancy authorization interval.

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

[0164] It is worth mentioning that during the process of recycling licensed resources, the setting of the recycling frequency and the recycling time point is particularly important. If the recycling frequency is too low, it will result in less recycled resources, low license utilization rate and resource waste. If the recycling frequency is too high, it is likely to affect the normal user's group license usage and cause users to interact too much in the software application and license acquisition process. Based on this, the present invention sets N usage cycles, conducts demand analysis and calculation based on the historical N usage cycles and the N usage cycles predicting user usage characteristics, conducts 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 the linear change analysis, so as to analyze whether the recycling strategy has a positive or negative impact on user usage. If the second rate of change is greater than the first rate of change, it means that the user's demand for license usage is continuously increasing, the license usage situation is continuously tense, and the recycling strategy has a negative impact and does not improve the corresponding utilization rate. Therefore, the strategy can be dynamically optimized based on the existing situation.

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

[0166] In a second aspect of the present invention, a centralized monitoring and management system 6 for a dedicated software license is further provided. The system includes: a memory 61 and a processor 62. The memory 61 includes a centralized monitoring and management program for the dedicated software license. When the centralized monitoring and management program for the dedicated software license is executed by the processor 62, the following steps are implemented:

[0167] S101: Deploy an additional module to the authorization server, monitor the network communication data of the authorization server through the additional module, collect the basic data and historical usage data of users using the dedicated software, and preprocess and store the basic data and historical usage data;

[0168] S102: Save the collected basic data and historical usage data into the corresponding database of the system, perform data association on the basic data and historical usage data, conduct usage feature analysis on software licenses based on different user departments, generate software usage feature data, and serialize and predict the usage of the usage feature data;

[0169] S103: Taking the user department as a unit, set the license scheduling management for different user departments according to the usage prediction results. The license scheduling management includes the setting of license allocation, license authorization, license borrowing, license reservation, and license restriction;

[0170] S104: In the authorization server, listen to the communication information between the additional module monitoring server and the client based on the additional module, identify whether there are idle license resources on the client, set the recycling period, and if there are idle license resources, send a recycling instruction to the authorization server for resource recycling.

[0171] The present invention discloses a method and system for centralized monitoring and management of dedicated software licenses. By collecting the source data samples of the use of dedicated software licenses, the basic data of the use status of dedicated software licenses is obtained, and the basic data of the software license use status is saved into the dedicated software license centralized monitoring and management system. The monitoring and management system conducts statistical analysis and visual presentation on the historical basic data, discovers the usage rules of software licenses, and provides guiding opinions on the future increase and decrease of licenses. The dedicated software license centralized monitoring and management system of the present invention provides a flexible and elastic grouping authorization management strategy, as well as an idle license elastic release mechanism based on the authorization usage activity, which can effectively improve the software usage efficiency and achieve fast, centralized, and efficient management of existing software authorizations.

[0172] In several embodiments provided by 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 merely illustrative. For example, the division of the units is only a logical function division, and there may be other division methods in actual implementation. For example, 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 with each other 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 as separate components may or may not be physically separated, and the components shown as units may or may not be physical units; they can be located in one place or distributed to multiple network units; some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

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

[0175] Those 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. The foregoing program may be stored in a computer-readable storage medium. When the program is executed, it performs the steps including the above method embodiments; and the foregoing storage medium includes: removable storage devices, read-only memory (ROM), random access memory (RAM), magnetic disks or optical discs and other various 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 functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the embodiments of the present invention, in essence or the part that contributes to the prior art, may be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the methods described in the embodiments of the present invention. And the foregoing storage medium includes: removable storage devices, ROM, RAM, magnetic disks or optical discs and other various media that can store program codes.

[0177] The above is only the specific implementation manners of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can easily think of changes or substitutions, which should all be covered by the protection scope of the present invention.

Claims

1. A centralized monitoring and management method for dedicated software licenses, characterized in that, Including: S101: Deploy an additional module to the authorization server. Monitor the network communication data of the authorization server through the additional module, collect the basic data and historical usage data of users using the dedicated software, and preprocess and store the basic data and historical usage data. S102: Save the collected basic data and historical usage data to the corresponding database of the system, perform data association on the basic data and historical usage data, and conduct usage feature analysis on software licenses based on different user departments to generate software usage feature data, and serialize and predict the usage of the usage feature data. S103: Taking user departments as units, set the license scheduling management for different user departments according to the usage prediction results. The license scheduling management includes the setting of license allocation, license authorization, license borrowing, license reservation, and license restriction. S104: In the authorization server, based on the additional module, monitor the communication information between the server and the client and identify whether there are idle license resources on the client. Set the recovery period. If there are idle license resources, send a recovery instruction to the authorization server for resource recovery. Among them, it also includes: For a user department, conduct usage demand analysis on the historical N usage cycles based on the basic data and historical usage data to generate N historical demand degrees. Based on the prediction model, conduct usage feature analysis and usage prediction on the said user department for N usage cycles, generate prediction data by combining the prediction model, and conduct demand degree analysis on the obtained prediction data to obtain N predicted demand degrees. The prediction data includes usage prediction data for N usage cycles. Conduct linear change analysis on the N historical demand degrees and calculate the average linear change rate of the data to obtain the first change rate. Conduct linear change analysis on the N predicted demand degrees and calculate the average linear change rate of the data to obtain the second change rate. If the second change rate is greater than the first change rate, then determine that the current recovery strategy has a negative impact and adjust the recovery strategy. The adjustment includes optimizing the recovery frequency, optimizing the recovery time node, and resetting the scanning occupancy authorization interval. Among them, the said S102 is specifically: Parse the collected basic data and historical usage data and save them to the system database, and establish corresponding data management strategies. The data management strategies include permission control strategies, backup strategies, and data archiving strategies. Associate the basic data and historical usage data with the usage information and the user departments using them, conduct information statistics through data association, and generate the first feature data and the second feature data respectively. The first feature data includes the total amount, usage rate, and remaining quantity information of the licenses. The second feature data includes the license utilization rate, peak usage period, and department license usage distribution of each user department. Integrate the first feature data and the second feature data to form software usage feature data. Construct a GAN-based generation model. The generation model includes a generator and a discriminator. Import the software usage feature data as real data into the generation model, and let the generator conduct feature learning on the real data and cyclically generate virtual feature data. Import virtual feature data into the discriminator for discrimination, train and evaluate the prediction model through a preset loss function, and adjust the parameters of the generator and discriminator in real time; Perform adversarial training of the generator and discriminator in a loop until the generator and discriminator reach Nash equilibrium; Generate simulated usage feature data of a preset data volume through the generation model, Serialize the simulated usage feature data and the software usage feature data based on the time dimension to obtain the first sequence data and the second sequence data; Based on the PCA analysis method, perform feature analysis and sequence splicing on the first sequence data and the second sequence data to generate fused sequence data; Construct an LSTM-based prediction model, import the fused sequence data into the prediction model, set the prediction period, and generate prediction sequence data; Parse the prediction sequence data and generate usage prediction data.

2. The centralized monitoring and management method for a dedicated software license according to claim 1, characterized in that, The S101 is specifically: For the authorization server of the dedicated software, set corresponding additional modules, and the additional modules are used to collect, analyze, and store data; Collect the basic data and historical usage data of the user using the dedicated software from the authorization server through the additional module and the preset collection strategy; The basic data includes the remaining points of the dedicated software license and the usage status data of the in-use license; The historical usage data includes the software license usage frequency, usage time, and license status data of the user in the historical time period; The preset collection strategy includes setting data sampling points, and the data sampling points are set based on a preset time interval, preset user operations, and specific events; Perform data cleaning and deduplication preprocessing on the 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 a dedicated software license according to claim 1, characterized in that, The S102 further includes: Perform statistical analysis on the basic data, historical usage data, and usage prediction data, and display the data through a visualization tool. The visualization tool includes statistical reports, charts, and graphical interface conversion tools, Set the import and export interfaces for the visualization data, and perform import or export operations on the visualization data through user visualization interaction.

4. The centralized monitoring and management method for a dedicated software license according to claim 3, characterized in that The S103 includes: Determine the management priorities of different user departments based on the software usage requirement status and usage prediction data of the user department. The management priorities include the priorities of specific user categories, business requirements, and working hours; After determining the management priorities, perform license allocation for different user departments. The license allocation includes setting the license quantity, specifying the start and end dates of the license, and handling changes and adjustments of license management.

5. The centralized monitoring and management method for a dedicated software license according to claim 4, characterized in that The S103 includes: Real-time collect user data of the user using the dedicated software through the authorization server. The user data includes the user's login information, access frequency, usage time, department association parameters, and license allocation data; Perform identity verification and user matching based on the user data; After successful identity verification, store the user data in the system database, and group and identify the users by department.

6. The centralized monitoring and management method for a dedicated software license according to claim 5, characterized in that The S103 includes: According to the licensing usage requirements and licensing allocation situations of each user department, formulate corresponding licensing authorization policies, where the licensing authorization policies include the permissions to access different professional software licenses and the access permission levels, and store the licensing authorization policies in the system database.

7. A centralized monitoring and management method for a dedicated software license according to claim 6, characterized in that, The S103 further includes: According to the software usage requirement status and usage prediction data of user departments, formulate licensing borrowing, licensing reservation, and licensing restriction policies for different user departments; The licensing reservation policy includes reserving a certain number of licenses for specific departments to ensure sustainable access permissions; The licensing borrowing policy includes setting conditions, terms, and procedures for borrowing licenses for different departments; The licensing restriction policy includes setting restriction information on the quantity and usage time of license usage for different departments.

8. A centralized monitoring and management method for a dedicated software license according to claim 7, characterized in that The S104 is specifically: Through an additional module on the authorization server, monitor the communication information between the server and the client. The monitoring process is to establish a bypass communication between the professional software license centralized monitoring and management platform and the license server to monitor the usage of client licenses in real time; The platform determines whether the license of the client user is in an idle state by analyzing the communication mode and time interval between the user and the authorization server; The system marks the identified restricted license resources, sends an instruction to the authorization server to recycle the idle licenses from the user, and provides the recycled license resources to new license usage requests.

9. A centralized monitoring and management system for dedicated software licenses, characterized in that, The system includes: a memory and a processor. The memory includes a centralized monitoring and management program for professional software licenses. When the centralized monitoring and management program for professional software licenses is executed by the processor, it realizes the steps of a method for centralized monitoring and management of a professional software license as described in any one of claims 1.

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