Organizational management system based on cloud computing architecture

Abstract

The application belongs to the technical field of cloud computing organization management, and discloses an organization management system based on a cloud computing architecture, which adjusts the cloud server specification in advance by combining historical data with an organization business load prediction model to avoid system collapse during peak periods; the master-standby-disaster three available area architecture and multi-specification micro cloud instance meet the high concurrency and high stability requirements of provincial organizations, are suitable for low-cost and low-concurrency scenarios of township-level organizations, and avoid the plight of small organizations pulling large carts; compared with traditional systems, the resource utilization rate is significantly improved, and the stable operation of subsequent business modules is supported, thereby reducing operation and maintenance costs and business interruption risks caused by improper resource adaptation; through inter-module coordination and linkage, the module data of organization management, learning, organization fees and the like are automatically synchronized, so that when the organization relationship is transferred, learning permission can be opened and a payment base can be generated without manual repeated input, thereby greatly reducing the operation burden of grassroots organizations.

Description

Technical Field

[0001] This invention belongs to the field of cloud computing organization management technology, specifically an organization management system based on cloud computing architecture. Background Technology

[0002] Currently, the nation is continuously promoting the digital transformation of organizational work, and information technology has been widely applied to scenarios such as organizational management and member learning. Existing organizational systems are mostly built on traditional architectures, achieving basic online functionality, but as business complexity increases, various adaptation issues are gradually being exposed. With the deepening of the digital transformation of organizational work, the technical limitations and insufficient business adaptability of traditional organizational management systems are becoming increasingly apparent, specifically exhibiting the following technical problems:

[0003] During peak access periods such as the deadline for organizational fee payment, traditional systems with statically configured resources either experience congestion and crashes during peak hours or have idle resources during off-peak hours. Furthermore, the organizational structure varies greatly across multiple levels, from "province-city-county-township-branch," making it difficult for a general architecture to adapt to the needs of low-cost, low-concurrency grassroots organizations and high-stability, high-concurrency provincial organizations.

[0004] In terms of data collaboration and security, the isolated data of each module in traditional systems forms information barriers. Cross-module business such as organizational relationship transfers requires manual and repetitive data entry, which increases the burden on grassroots staff. Organizational data is sensitive, but existing systems lack hierarchical protection, have simple encryption and ambiguous permissions, making them vulnerable to attacks and leaks, and lack audit and traceability capabilities.

[0005] In terms of high availability and decision support, traditional systems are often deployed on single nodes, making it easy for hardware failures to disrupt services. Under extreme network conditions, critical services such as organizational fee payments are difficult to carry out. Organizational assessments rely on manual statistics, resulting in data lag, limited dimensions, and difficulty in identifying pain points such as organizational member participation and activity effectiveness, thus failing to provide support for decision-making. Summary of the Invention

[0006] The purpose of this invention is to provide an organization management system based on a cloud computing architecture to solve the problems mentioned in the background art.

[0007] To achieve the above objectives, the present invention provides the following technical solution: an organization management system based on a cloud computing architecture, the system comprising:

[0008] Scenario-based cloud architecture module: Build the platform infrastructure, predict changes in resource demand by analyzing historical data, design a three-availability zone architecture of primary availability zone, backup availability zone and disaster recovery availability zone, and provide micro-cloud implementation options to adapt to the organization's business scale;

[0009] Inter-module collaboration module: The organization management sub-module is used to synchronize organization member information to the learning management module and the organization fee management module; the activity management sub-module synchronizes activity data to the data analysis module; and a one-click business package function is designed to simplify the operation process of grassroots organizations.

[0010] Sensitive data security module: Core sensitive data is encrypted and stored, while non-core data is dynamically de-identified; operation permissions are assigned according to hierarchy and responsibility, and all critical operations of all modules generate tamper-proof audit logs;

[0011] Intelligent load balancing module: Based on the differences in the characteristics of the organization's business, it is divided into three core business types. Different load balancing schemes are designed for different business types, and load balancing weights are set according to business priority.

[0012] High Availability Module for Critical Business: Based on the availability zone of the scenario-based cloud architecture module and combined with the load data of the business intelligent load balancing module, a fault tolerance mechanism is established; for core business data, a dual backup strategy of multiple replicas and scheduled snapshots is adopted; for critical business, an offline emergency mode is set up.

[0013] Intelligent analysis and decision-making module: It calculates a comprehensive score of organizational member participation through weighted calculation, sets up four levels of customized reports according to the management needs of different levels of organizations, and intuitively displays the analysis results through data visualization technology.

[0014] Preferably, the scenario-based cloud architecture module is as follows:

[0015] The platform infrastructure is built around cloud servers, cloud storage, and cloud databases. An organizational business load prediction model is established to address the cyclical characteristics of organizational business. This model analyzes data including historical activity participation and peak payment periods to predict changes in resource demand and automatically adjust cloud servers in advance.

[0016] The architecture is designed with three availability zones: the primary availability zone is used to deploy core business modules including organization management and organization fee payment; the backup availability zone is used to synchronize data with the primary availability zone in real time; and the disaster recovery availability zone is used to store historical archived data.

[0017] Based on the different resource needs of organizations at the provincial, municipal, county, and township levels, we offer multiple micro-cloud instance options to adapt to the business scale of organizations at different levels.

[0018] Organizational workload forecasting formula:

[0019] ;

[0020] In the formula: This indicates the predicted business load value for the target time period, expressed in "concurrent requests per minute";

[0021] n represents the number of historical data samples;

[0022] This represents the weighting coefficient for the i-th historical period, with a value range of... ;

[0023] This represents the actual business load value for the i-th historical period, expressed in "concurrent requests per minute";

[0024] This represents the organizational business cycle coefficient, which is adjusted according to the business type.

[0025] This indicates the trend correction term, with the unit being "concurrent requests per minute".

[0026] Preferably, the inter-module collaborative linkage module is specifically as follows:

[0027] The organization management submodule is used to manage organizational hierarchy information and personal information of organizational members, including information entry, query, and update functions; when an organizational relationship is transferred, the system will automatically synchronize the organizational member information to the learning management module and the organization fee management module;

[0028] The event management submodule has full-process functions, including event planning, online registration, on-site check-in, and feedback collection. After the event, it automatically synchronizes the data of event participation rate, feedback score, and list of participating members to the data analysis module and generates a related report that includes an evaluation of the event's effectiveness.

[0029] The one-click business package feature simplifies the operational process of grassroots organizations, integrating multiple steps in the new member onboarding scenario, including organizational information entry, initial learning task allocation, and organization fee account activation.

[0030] Preferably, the sensitive data security module is specifically as follows:

[0031] Establish a tiered data security protection system. For core and sensitive data, including the ID numbers of organization members and proof of organizational relationship, use the national cryptographic SM4 algorithm for encrypted storage and set up dual authentication of TLS1.3 protocol and national cryptographic SM2 certificate in the data transmission process. For non-core data, including learning progress and activity registration records, use dynamic desensitization processing to display only necessary information and limit the scope of data visibility.

[0032] Based on the five-level hierarchical system of provincial, municipal, county, township and branch organizations, a five-dimensional permission matrix is ​​established; operational permissions are allocated according to level and responsibility.

[0033] Establish a full-process operation audit mechanism. All critical operations in all modules generate tamper-proof audit logs. The logs include key information such as the operator, operation time, operation IP address, and operation content. It also supports penetrating audits of subordinate units by higher-level organizations.

[0034] Preferably, the intelligent load balancing module is as follows:

[0035] Employing core technologies including reverse proxy and traffic distribution, and based on the differences in the characteristics of organizational businesses, they are divided into three core business types: high-concurrency real-time, high-bandwidth, and high-security, and differentiated load strategies are formulated for each type.

[0036] High-concurrency real-time services adopt a proximity access and queue buffering mechanism, which distributes user requests to the nearest node and combines queue sorting; high-bandwidth services use edge node caching technology to preload popular courses to the city edge nodes.

[0037] Load balancing weights are set according to business priorities, with high-security businesses such as organizational fee payment and organizational relationship transfer having the highest weights; at the same time, it is linked with the high availability module of critical businesses to synchronize the load status of each server node in real time.

[0038] Load balancing service weight allocation formula:

[0039] ;

[0040] In the formula: This represents the load balancing weight of the j-th type of organizational business;

[0041] j and k represent the business type number. Corresponding to high security class, For high-concurrency real-time classes, Corresponding to the high-bandwidth class; k is the traversal variable for all service types;

[0042] The total number of business types in the organization is fixed at 3.

[0043] This represents the priority coefficient of the j-th type of business;

[0044] This represents the real-time load impact factor, which is fixed at 0.01.

[0045] This represents the real-time load value of the j-th type of service, in units of "concurrent requests per second";

[0046] This represents the unit resource demand coefficient for the j-th type of business.

[0047] Preferably, the critical business high availability module is as follows:

[0048] Based on the availability zones of the scenario-based cloud architecture module, and combined with the real-time load data provided by the business intelligent load balancing module, a fault tolerance mechanism is established. When the server in the primary availability zone experiences problems such as hardware failure or network interruption, the system automatically switches to the backup availability zone, and any unfinished critical business is restored through the breakpoint resume function.

[0049] For core business data, a dual backup strategy of multiple replicas and timed snapshots is adopted. Core data is stored in replicas in the primary and backup availability zones respectively. At the same time, data snapshots are generated at fixed intervals and stored in the disaster recovery availability zone. The snapshots include business data and system configuration.

[0050] For critical business operations that cannot be interrupted, such as payment of organizational fees and transfer of organizational affiliation, an offline emergency mode is set up. When grassroots organizations encounter extreme scenarios such as network interruption or temporary system failure, they can export offline forms through secure media and collect organizational member information and business data offline.

[0051] Formula for calculating data replica availability:

[0052] ;

[0053] In the formula: Indicates the availability of core organizational data;

[0054] This represents the probability of failure of a single data replica, with a value of [value missing]. ;

[0055] n represents the number of data replicas, which is fixed at 3;

[0056] This indicates the average recovery time for data failures, in minutes.

[0057] This indicates the total duration of the statistical period, in minutes.

[0058] Preferably, the intelligent analysis and decision-making module is as follows:

[0059] Integrate all business data from the learning management, organization fee management, and activity management sub-modules to establish an organization member participation model. This model uses the organization member's learning time, activity participation rate, and timeliness of organization fee payment as core indicators, and generates a comprehensive score through weighted calculation.

[0060] Based on the management needs of different organizational levels, customized reports are provided at four levels: branch, county / district, prefecture / city, and province. Branch-level reports focus on micro-level data, while provincial-level reports focus on macro-level summaries. The reports support drill-down queries.

[0061] The analysis results are presented intuitively through data visualization technology, and at the same time, the analysis results are fed back to the learning management module and the activity management sub-module.

[0062] Formula for comprehensive scoring of organization member participation:

[0063] ;

[0064] In the formula: This represents the overall score of organization members' participation, ranging from 0 to 100.

[0065] This represents the base score, which is fixed at 40 points.

[0066] , , This represents the weight coefficients for each dimension, with a total of 1.

[0067] This represents the score for the learning dimension, with a value range of 0-100.

[0068] This represents the score for the activity dimension, with a value range of 0-100.

[0069] This represents the score for the organization fee dimension, with a value ranging from 0 to 100.

[0070] This indicates a deduction item, with a value range of 0-20 points.

[0071] The beneficial effects of this invention are as follows:

[0072] 1. This invention uses an organizational business load prediction model and historical data to adjust cloud server specifications in advance, avoiding system crashes during peak periods such as payment deadlines. The primary-backup-disaster three-availability zone architecture and multi-specification micro-cloud instances not only meet the high concurrency and high stability requirements of provincial organizations, but also adapt to low-cost and low-concurrency scenarios at the township level. Compared with traditional systems, resource utilization is significantly improved, while providing underlying support for the stable operation of subsequent business modules and reducing maintenance costs and business interruption risks caused by improper resource adaptation.

[0073] 2. This invention achieves automatic synchronization of data between modules such as organizational management, learning, and organizational fees through inter-module collaboration. For example, when an organizational relationship is transferred, learning permissions can be activated and payment bases can be generated without manual re-entry, significantly reducing the operational burden on grassroots organizations. At the same time, the hierarchical data security system (national cryptographic encryption for core data and dynamic desensitization for non-core data) and the "five-dimensional permission matrix" precisely control the scope of data visibility. The tamper-proof audit logs comply with the requirements of the Personal Information Protection Law, effectively preventing data leakage and malicious operation risks, and ensuring the security of sensitive organizational data throughout its entire lifecycle.

[0074] 3. The rapid switching and breakpoint resumption mechanism of the primary and backup availability zones in this invention ensures that critical businesses such as organizational fee payment and organizational relationship transfer are not interrupted; the offline emergency mode is adapted to grassroots scenarios with unstable networks to avoid business stagnation; in addition, the organizational member participation model and four-level customized reports replace manual statistics, generate comprehensive scores and multi-dimensional data visualization results in real time, accurately identify organizational member participation shortcomings and activity effectiveness problems, provide data support for organizations to formulate learning plans and optimize activity strategies, and promote organizational management from experience-driven to data-driven. Attached Figure Description

[0075] Figure 1 This is a flowchart of the organization management system based on cloud computing architecture of the present invention. Detailed Implementation

[0076] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0077] like Figure 1 As shown, this embodiment of the invention provides an organization management system based on a cloud computing architecture, the system comprising:

[0078] Scenario-based cloud architecture module: Build the platform infrastructure, predict changes in resource demand by analyzing historical data, design a three-availability zone architecture of primary availability zone, backup availability zone and disaster recovery availability zone, and provide micro-cloud implementation options to adapt to the organization's business scale;

[0079] Inter-module collaboration module: The organization management sub-module is used to synchronize organization member information to the learning management module and the organization fee management module; the activity management sub-module synchronizes activity data to the data analysis module; and a one-click business package function is designed to simplify the operation process of grassroots organizations.

[0080] Sensitive data security module: Core sensitive data is encrypted and stored, while non-core data is dynamically de-identified; operation permissions are precisely allocated according to hierarchy and responsibility, and all critical operations of all modules generate tamper-proof audit logs;

[0081] Intelligent load balancing module: Based on the differences in the characteristics of the organization's business, it is divided into three core business types. Different load balancing schemes are designed for different business types, and load balancing weights are set according to business priority.

[0082] High Availability Module for Critical Business: Based on the availability zone of the scenario-based cloud architecture module and combined with the load data of the business intelligent load balancing module, a fault tolerance mechanism is established; for core business data, a dual backup strategy of multiple replicas and scheduled snapshots is adopted; for critical business, an offline emergency mode is set up.

[0083] Intelligent analysis and decision-making module: It calculates a comprehensive score of organizational member participation through weighted calculation, sets up four levels of customized reports according to the management needs of different levels of organizations, and intuitively displays the analysis results through data visualization technology.

[0084] The specific details of the scenario-based cloud architecture module are as follows:

[0085] The platform infrastructure is built around cloud servers, cloud storage, and cloud databases. Targeting the cyclical characteristics of organizational business, such as peak scenarios like the "July 1st" themed activities and organizational fee payment deadlines, an organizational business load prediction model is established. This model analyzes data including historical activity participation and peak payment periods to predict changes in resource demand and automatically adjusts the specifications of cloud servers such as CPU and memory in advance, achieving dynamic resource allocation and elastic expansion to avoid resource idleness or overload during peak periods.

[0086] The architecture is designed with three availability zones. The primary availability zone is used to deploy core business modules, including organization management and organization fee payment, to ensure efficient operation of daily business. The backup availability zone is used to synchronize data with the primary availability zone in real time to form a hot backup of business. The disaster recovery availability zone is used to store historical archived data, such as learning records and activity archives of organization members over the years, and the data synchronization delay across availability zones is controlled within a reasonable range.

[0087] Based on the different resource needs of organizations at the provincial, municipal, county, and township levels, we offer multiple micro-cloud instance options, ranging from basic lightweight configurations to high-performance configurations that meet the needs of organizations at the municipal level and above, adapting to the business scale of different levels of organizations and ensuring accurate resource matching under the distributed architecture.

[0088] Organizational workload forecasting formula:

[0089] ;

[0090] In the formula: This represents the predicted business load value for the target time period, expressed in "concurrent requests per minute," and is used to determine the need for cloud server resource adjustments, such as the predicted registration concurrency before the "July 1st" event.

[0091] n represents the number of historical data samples, which are usually selected from the last three similar periods (such as the "July 1st" activities in the last three years) to ensure the accuracy of the prediction;

[0092] This represents the weighting coefficient for the i-th historical period, with a value range of... The weighting of recent cycles is higher, such as the past year cycle. In the past two years In the past three years This reflects the timeliness of the data;

[0093] This represents the actual business load value for the i-th historical period, expressed in "concurrent requests per minute," such as the peak concurrent registration volume for the "July 1st" event in the past year.

[0094] This represents the organizational business cycle coefficient, which is adjusted according to the business type, such as the deadline for organizational fee payment. Regular activities This reflects the load fluctuation characteristics of different services;

[0095] This indicates a trend correction, measured in "concurrent requests per minute," calculated based on organizational growth (e.g., new members) and business expansion (e.g., adding online learning courses). For example, when 500 new members are added... This compensates for incremental changes not covered by historical data.

[0096] The specific inter-module collaborative linkage modules are as follows:

[0097] Supported by the resources of the scenario-based cloud architecture module, the organization management submodule is used to manage organizational hierarchy information and personal information of organizational members, including information entry, query, and update functions. When an organizational relationship is transferred, the system will automatically synchronize the organizational member information to the learning management module (which opens corresponding learning permissions according to the organizational member's level) and the organization fee management module (which generates the payment base based on the organizational member's job level, salary, and other information), realizing seamless cross-module flow of core data.

[0098] The event management submodule has full-process functions, covering event planning, online registration, on-site check-in, and collection of participation feedback. After the event, the system automatically synchronizes data such as event participation rate, feedback scores, and list of participating members to the data analysis module without manual intervention, and generates a related report that includes an evaluation of the event's effectiveness.

[0099] The one-click business package function simplifies the operation process of grassroots organizations. It integrates multiple steps in the new member onboarding scenario, including organizational information entry, initial learning task assignment, and organization fee account opening. Grassroots staff only need to operate once to complete the series of processes, greatly reducing repetitive operations.

[0100] The sensitive data security module is specifically as follows:

[0101] A tiered data security protection system has been established. For core and sensitive data such as organizational member ID numbers and organizational relationship certificates, the national cryptographic SM4 algorithm is used for encrypted storage. During data transmission, dual authentication using TLS1.3 protocol and national cryptographic SM2 certificate is set up to ensure the security of core data throughout the entire chain from storage to transmission. For non-core data such as learning progress and activity registration records, dynamic de-identification processing is adopted, and only necessary information, such as organizational member name + de-identified ID number, is displayed to limit the scope of data visibility.

[0102] Based on the five-level hierarchical system of provincial, municipal, county, township and branch organizations, a five-dimensional permission matrix is ​​established; operation permissions are allocated according to level and responsibility. For example, branch administrators only have basic permissions such as querying information on members of their own branch and initiating activities, but no permissions to export data or view information across branches; administrators at the municipal level and above can obtain aggregated data permissions within their respective jurisdictions as needed, thereby achieving minimal permission control and preventing unauthorized access to data.

[0103] A full-process operation audit mechanism has been established. All critical operations in all modules (such as modification of organizational member information, export of organizational fee data, and permission changes) generate tamper-proof audit logs. The logs contain key information such as the operator, operation time, operation IP address, and operation content. The log retention period strictly complies with the requirements of laws and regulations such as the Personal Information Protection Law. It also supports the penetrating audit of subordinate organizations by superior organizations, real-time tracing of operational behavior, and comprehensive protection of the security of data flow and operation in all modules.

[0104] The intelligent load balancing module for business operations is specifically as follows:

[0105] Employing core technologies such as reverse proxy and traffic distribution, and based on the differences in the characteristics of organizational businesses, they are divided into three core business types: "high-concurrency real-time" (such as event registration and online check-in, with a surge in access during peak hours), "high-bandwidth" (such as video learning and live courses, which have high bandwidth requirements), and "high-security" (such as organizational fee payment and organizational relationship transfer, which have strict requirements for stability and security), and differentiated load balancing strategies are formulated for each type.

[0106] High-concurrency real-time services adopt a proximity access and queue buffering mechanism. By allocating user requests to the nearest node and combining queue sorting, congestion caused by concentrated access by members of the same organization in the same region is avoided. High-bandwidth services use edge node caching technology to preload popular courses to the edge nodes of cities and prefectures, reducing bandwidth pressure in core areas and improving video loading speed.

[0107] Load balancing weights are set according to business priorities, with high-security businesses such as organizational fee payments and organizational relationship transfers having the highest weights. This ensures that critical businesses receive priority resource support in high-concurrency scenarios, guaranteeing business continuity. At the same time, it works in conjunction with the high-availability modules of critical businesses to synchronize the load status of each server node in real time, such as CPU utilization and memory usage, providing accurate load data support for subsequent failover and ensuring that each business module can still operate stably in high-concurrency scenarios.

[0108] Load balancing service weight allocation formula:

[0109] ;

[0110] In the formula: This represents the load balancing weight of the j-th type of organizational service, which determines the traffic allocation ratio, such as the organizational fee payment service. =40%, meaning 40% of server resources are allocated to this service;

[0111] j and k represent the business type number. Corresponding to the high-security category (organizational fee payment), For high-concurrency real-time applications (event registration), Corresponding to the high-bandwidth class (video learning); k is the traversal variable for all business types;

[0112] The total number of business types in the organization is fixed at 3, corresponding to the three business types mentioned above;

[0113] This represents the priority coefficient of the j-th type of service, high security class. =1.5, high-concurrency real-time class =1.2, High Bandwidth Class =1.0, reflecting the difference in business importance;

[0114] This represents the real-time load impact coefficient, which is fixed at 0.01. It is used to amplify the impact of real-time load on weights and prevent low-load services from consuming too many resources.

[0115] This represents the real-time load value of the j-th type of service, expressed in "concurrent requests per second", such as the real-time load of the event registration service. =80;

[0116] This represents the unit resource demand coefficient for the j-th type of service, high bandwidth class. =1.5, video learning consumes bandwidth, the other two types This reflects the differences in resource consumption.

[0117] The specific high-availability modules for critical business operations are as follows:

[0118] Based on the availability zones of the scenario-based cloud architecture module and combined with the real-time load data provided by the business intelligent load balancing module, a fault tolerance mechanism is established. When the server in the primary availability zone experiences problems such as hardware failure or network interruption, the system automatically switches to the backup availability zone. Unfinished critical business processes (such as the organization fee payment process) are restored through the "breakpoint resume" function, without requiring users to repeat operations, thus ensuring the continuity of business processes.

[0119] For core business data, such as organizational fee payment records and organizational relationship data, a dual backup strategy of multiple replicas and scheduled snapshots is adopted. Multiple replicas of core data are stored in the primary and backup availability zones, respectively. Simultaneously, data snapshots are generated at fixed intervals and stored in the disaster recovery availability zone. These snapshots contain complete business data and system configurations. In the event of data corruption or accidental deletion, a rapid rollback to the most recent snapshot version is supported within one hour to minimize data loss.

[0120] For critical business operations that cannot be interrupted, including organizational fee payments and organizational relationship transfers, an offline emergency mode is set up. When grassroots organizations encounter extreme scenarios such as network outages or temporary system failures, offline forms can be exported through secure media to collect organizational member information and business data offline. After the system is restored, the data can be imported in batches to ensure that organizational business is not interrupted under extreme conditions.

[0121] Formula for calculating data replica availability:

[0122] ;

[0123] In the formula: This indicates the availability of core organizational data (such as organizational expense records and organizational relationships), expressed as a percentage, with a target value. That is, the total downtime throughout the year. ,minute;

[0124] This represents the probability of failure of a single data replica, with a value of [value missing]. Based on cloud storage hardware failure rate statistics, approximately 1 out of 100,000 copies fails.

[0125] n represents the number of data replicas, which is fixed at 3, corresponding to the "multiple replicas and scheduled snapshots" strategy, with one replica each in the primary, backup, and disaster recovery availability zones;

[0126] This indicates the average recovery time for data failures, expressed in minutes, and is controlled to within 10 minutes through an automated recovery mechanism.

[0127] This indicates the total duration of the statistical period, in minutes, and is calculated on an annual basis. =525600 minutes, ensuring uniformity of calculation dimensions.

[0128] The intelligent analysis and decision-making module is specifically as follows:

[0129] Integrate all business data from the learning management, organization fee management, and activity management sub-modules to establish an organization member participation model. This model uses the organization member's learning time, activity participation rate, and timeliness of organization fee payment as core indicators, and generates a comprehensive score through weighted calculation. It automatically identifies organization members with low participation and pushes personalized learning tasks, such as branch activity reminders, according to their positions and levels to improve the organization member's participation enthusiasm.

[0130] Based on the management needs of organizations at different levels, customized reports are provided at four levels: branch, county / district, prefecture / city, and province. Branch-level reports focus on micro-level data, such as the weekly learning completion rate of branch members, the number of members with outstanding organizational fees, and activity registration details. Provincial-level reports focus on macro-level summaries, such as the province's organizational coverage rate, cross-regional collaboration efficiency, and the progress of learning activities in various cities and counties. The reports support drill-down queries; for example, clicking on "Low Participation Rate in a Certain City" allows you to drill down to view specific county / district and branch data, meeting the needs of multi-level management.

[0131] Data visualization techniques (such as bar charts, heatmaps, and trend curves) are used to visually present the analysis results, providing clear data support for organizational management decisions. For example, activity formats can be adjusted based on participation rate data, and organizational fee collection strategies can be optimized based on payment statistics. At the same time, the analysis results are fed back to the learning management module and activity management sub-module, such as optimizing course recommendations based on organizational members' learning preferences and adjusting activity plans based on activity effectiveness data.

[0132] Formula for comprehensive scoring of organization member participation:

[0133] ;

[0134] In the formula: This represents the overall score of organization members' participation, ranging from 0 to 100 points. It is used to identify organization members with low participation and push personalized tasks to them. 60 points is the passing score.

[0135] This represents the base score, which is fixed at 40 points. This ensures that organization members can earn the base score simply by engaging in basic activities (such as completing identity verification), thus preventing the score from being too low.

[0136] , , This represents the weight coefficients of each dimension, which sum to 1, where the learning dimension... =0.4, reflecting learning priority and activity dimension. =0.3, Organizational cost dimension =0.3;

[0137] This represents the learning dimension score, ranging from 0 to 100, based on monthly learning time / specified time. Calculations: If the monthly study period is stipulated as 4 hours, but the actual study time is 6 hours, then... =150, capped at 100;

[0138] This represents the activity dimension score, ranging from 0 to 100 points, calculated as the number of activities participated in per year / the required number of times. Calculations: If the rule is to participate in 6 activities per year, and the actual participation is 4, then... ;

[0139] The score represents the organization fee dimension, with a value range of 0-100 points. It is calculated based on timeliness: 100 points are awarded for payments made in the current month, 80 points for payments made in the following month, and 0 points for payments made more than 3 months overdue.

[0140] This indicates the deduction items, with a value range of 0-20 points. These are for violations (e.g., 10 points for cheating in studies, 5 points for unexcused absence from activities), reflecting the seriousness of the scoring.

[0141] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0142] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. An organization management system based on a cloud computing architecture, characterized by: This includes a scenario-based cloud architecture module, an inter-module collaboration module, a sensitive data security module, a business intelligent load balancing module, a critical business high availability module, and an intelligent analysis and decision-making module. Scenario-based cloud architecture module: Build the platform infrastructure, predict changes in resource demand by analyzing historical data, design a three-availability zone architecture of primary availability zone, backup availability zone and disaster recovery availability zone, and provide micro-cloud implementation options to adapt to the organization's business scale; The inter-module collaboration module includes an organization management submodule and an activity management submodule. The organization management submodule is used for the management of organizational hierarchy information and personal information of organizational members, including information input, query and update functions. When an organizational affiliation is transferred, the system will automatically synchronize the organizational member information to the learning management module and the organization fee management module. The event management submodule has full-process functions, including event planning, online registration, on-site check-in, and feedback collection. After the event, it automatically synchronizes the data of event participation rate, feedback score, and list of participating members to the data analysis module and generates a related report that includes an evaluation of the event's effectiveness. The one-click business package function simplifies the operation process of grassroots organizations and integrates multiple steps in the new organization member onboarding scenario, including organization information entry, initial learning task allocation, and organization fee account opening. Sensitive data security module: Core sensitive data is encrypted and stored, while non-core data is dynamically de-identified; operation permissions are assigned according to hierarchy and responsibility, and all critical operations of all modules generate tamper-proof audit logs; The intelligent load balancing module for business adopts core technologies including reverse proxy and traffic distribution. Based on the differences in the characteristics of the organization's business, it divides them into three core business types: high-concurrency real-time, high-bandwidth, and high-security, and formulates differentiated load strategies for different types. High-concurrency real-time services adopt a proximity access and queue buffering mechanism, which distributes user requests to the nearest node and combines queue sorting; high-bandwidth services use edge node caching technology to preload popular courses to the city edge nodes. Load balancing weights are set according to business priorities, with high-security businesses such as organizational fee payment and organizational relationship transfer having the highest weights; at the same time, it is linked with the high availability module of critical businesses to synchronize the load status of each server node in real time. High Availability Module for Critical Business: Based on the availability zone of the scenario-based cloud architecture module and combined with the load data of the business intelligent load balancing module, a fault tolerance mechanism is established; for core business data, a dual backup strategy of multiple replicas and scheduled snapshots is adopted; for critical business, an offline emergency mode is set up. Intelligent analysis and decision-making module: It calculates a comprehensive score of organizational member participation through weighted calculation, sets up four levels of customized reports according to the management needs of different levels of organizations, and intuitively displays the analysis results through data visualization technology.

2. The organization management system based on cloud computing architecture according to claim 1, characterized in that: The specific modules of the scenario-based cloud architecture are as follows: The platform infrastructure is built around cloud servers, cloud storage, and cloud databases. An organizational business load prediction model is established to address the cyclical characteristics of organizational business. This model analyzes data including historical activity participation and peak payment periods to predict changes in resource demand and automatically adjust cloud servers in advance. The architecture is designed with three availability zones: the primary availability zone is used to deploy core business modules including organization management and organization fee payment; the backup availability zone is used to synchronize data with the primary availability zone in real time; and the disaster recovery availability zone is used to store historical archived data. Based on the different resource needs of organizations at the provincial, municipal, county, and township levels, we offer multiple micro-cloud instance options to adapt to the business scale of organizations at different levels.

3. The organization management system based on cloud computing architecture according to claim 2, characterized in that: The sensitive data security module is as follows: Establish a tiered data security protection system. For core and sensitive data, including the ID numbers of organization members and proof of organizational relationship, use the national cryptographic SM4 algorithm for encrypted storage and set up dual authentication of TLS1.3 protocol and national cryptographic SM2 certificate in the data transmission process. For non-core data, including learning progress and activity registration records, use dynamic desensitization processing to display only necessary information and limit the scope of data visibility. Based on the five-level hierarchical system of provincial, municipal, county, township and branch organizations, a five-dimensional permission matrix is ​​established; operational permissions are allocated according to level and responsibility. Establish a full-process operation audit mechanism. All critical operations in all modules generate tamper-proof audit logs. The logs include key information such as the operator, operation time, operation IP address, and operation content. It also supports penetrating audits of subordinate units by higher-level organizations.

4. The organization management system based on cloud computing architecture according to claim 3, characterized in that: The specific high-availability modules for critical business operations are as follows: Based on the availability zones of the scenario-based cloud architecture module, and combined with the real-time load data provided by the business intelligent load balancing module, a fault tolerance mechanism is established. When the server in the primary availability zone experiences problems such as hardware failure or network interruption, the system automatically switches to the backup availability zone, and any unfinished critical business is restored through the breakpoint resume function. For core business data, a dual backup strategy of multiple replicas and timed snapshots is adopted. Core data is stored in replicas in the primary and backup availability zones respectively. At the same time, data snapshots are generated at fixed intervals and stored in the disaster recovery availability zone. The snapshots include business data and system configuration. For critical business operations that cannot be interrupted, such as payment of organizational fees and transfer of organizational affiliation, an offline emergency mode is set up. When grassroots organizations encounter extreme scenarios such as network interruptions or temporary system failures, they can export offline forms through secure media and collect organizational member information and business data offline.

5. The organization management system based on cloud computing architecture according to claim 4, characterized in that: The intelligent analysis and decision-making module is as follows: Integrate all business data from the learning management, organization fee management, and activity management sub-modules to establish an organization member participation model. This model uses the organization member's learning time, activity participation rate, and timeliness of organization fee payment as core indicators, and generates a comprehensive score through weighted calculation. Based on the management needs of different organizational levels, customized reports are provided at four levels: branch, county / district, prefecture / city, and province. Branch-level reports focus on micro-level data, while provincial-level reports focus on macro-level summaries. The reports support drill-down queries. The analysis results are presented intuitively through data visualization technology, and at the same time, the analysis results are fed back to the learning management module and the activity management sub-module.

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