Uniform calling and computing application mechanism for model data of integrated platform of cloud side end data center

Abstract

The invention discloses a cloud side end data center integration platform model data unified calling calculation application mechanism. The system has the beneficial effects that various management and application problems of an existing data platform of a new energy enterprise are solved through services and capabilities of unified data architecture, unified database management, unified database monitoring, database service management, data storage management, data exchange management, data sharing management and the like; a headquarter, regional and station three-level data center collaborative application system is constructed for enterprises, deep integration and efficient utilization of resources of each regional and station data center are integrated, collaborative application of the three-level data center is enhanced, information islands are broken, and seamless joint and efficient collaborative application of data are realized; the headquarters data center plays a role of core overall planning global, provides strategic guidance and data support for the regional and station data centers, and supports the regional and station data centers to carry out deep analysis and practical application on data according to own characteristics and business requirements.

Description

Technical Field

[0001] The present invention relates to the field of data application technology in the energy field, and in particular to a unified calling computing application mechanism for model data of a cloud-edge-end data center integration platform. Background Art

[0002] In the field of new energy, the centralized control center plays a vital role. It is not only the core management department of equipment operation, but also the key to ensure the efficient and stable operation of equipment. With the rapid development and widespread application of new energy technologies, the management of equipment operation data and equipment indicator data has become increasingly complex and critical. These data are not only related to the operating status and performance evaluation of equipment, but also an important basis for corporate decision-making and strategic planning.

[0003] In order to improve the efficiency and accuracy of data management and solve various problems encountered in the process of data application, building a unified data management platform for stations, regions, and headquarters to carry out unified planning, storage, and application management of core equipment data has become the core demand for data management of new energy companies.

[0004] The existing data management and control platform of the new energy company has solved the problem of data management from scratch. However, in the face of the growing demand for data application and business management, there are obvious deficiencies in application management, which are mainly reflected in: 1. No unified data planning and lack of unified management; 2. The business system database runs independently, and it is difficult to connect the data; 3. The database model is single and the storage model is difficult to expand; 4. There is no unified planning and management, and it is difficult to unify the supervision of stations in various regions; 5. Multi-level database application deployment, weak database maintenance management, etc. Summary of the invention

[0005] The purpose of the present invention is to provide a unified calling computing application mechanism for model data of a cloud-edge-end data center integration platform in order to solve the above-mentioned problems.

[0006] The present invention achieves the above-mentioned purpose through the following technical solutions:

[0007] The cloud-edge-end data center integration platform model data unified call computing application mechanism, which includes the following contents: unified data architecture, unified database management, unified database monitoring, database service management, data storage management, data exchange management, and data sharing management.

[0008] Furthermore, the unified data architecture specifically builds a unified data storage framework to realize the data storage and application of the unified architecture of site, regional and headquarters data, provide an overall data storage solution, realize the unified planning of time series data, structured data and object data storage; and provide unified application management of databases.

[0009] Furthermore, the unified database management specifically provides unified management of all different types of databases at the headquarters, regional, and station levels, realizes the unified registration and maintenance management functions of databases in each region and station, provides a unified database access policy, provides the ability to finely manage and operate and maintain database instances, provides unified management and allocation of database resources, and realizes the overview and monitoring of database resources.

[0010] Furthermore, the unified database monitoring specifically refers to the overview and monitoring of database resources: providing a comprehensive view for real-time monitoring and overview of the status of the entire data resource pool and key metrics of individual databases.

[0011] Furthermore, the database service management specifically provides the ability to finely manage and operate and maintain database instances.

[0012] Furthermore, the data storage management specifically classifies and stores data according to different policies, realizing the ability of unified data management.

[0013] Furthermore, the data exchange management specifically provides unified management of data exchanges such as real-time data, relational data, and unstructured data according to different data migration and transmission policies.

[0014] Furthermore, the data sharing management specifically breaks down data barriers within the organization, supports the establishment of a unified data sharing mechanism, realizes the unified sharing ability of the data management platform to access real-time data, structured data, and object data in all regions and stations, and realizes data sharing service monitoring and data security control.

[0015] Furthermore, the cloud-edge architecture in the unified call and computing application mechanism of the cloud-edge-end data center integration platform model data provides technical support for the three-level data management centers at the headquarters, regional, and station levels, realizes the close connection between the cloud, edge, and end, enables the cloud capabilities to extend to the edge side, including data sharing, data storage, data computing, etc., and at the same time provides service hosting capabilities for the edge side, solving the problem that individual regions and stations have small scales and limited resources, resulting in the inability of the region to have management service capabilities.

[0016] Furthermore, when the unified call and computing application mechanism of the cloud-edge-end data center integration platform model is specifically used, it constructs a collaborative application system for the three-level data centers at the headquarters, regional, and station levels for enterprises, deeply integrates and efficiently utilizes the resources of data centers in each region and station, strengthens the collaborative application of the three-level data centers, breaks information silos, and realizes seamless docking and efficient collaborative application of data; while the headquarters data center mainly plays a core overall planning role, providing strategic guidance and data support for the regional and station data centers. At the same time, it supports the regional and station data centers to conduct in-depth analysis and practical application of data according to their own characteristics and business needs.

[0017] The beneficial effects of the present invention are as follows:

[0018] Through services and capabilities such as unified data architecture, unified database management, unified database monitoring, database service management, data storage management, data exchange management, and data sharing management, the present invention solves various management and application problems of the existing data platforms of new energy enterprises, constructs a collaborative application system for the headquarters, regional, and station-level data centers for the enterprise, deeply integrates and efficiently utilizes the resources of the data centers in each region and station, strengthens the collaborative application of the three-level data centers, breaks information silos, and realizes seamless docking and efficient collaborative application of data; the headquarters data center will play a core overall coordinating role, providing strategic guidance and data support for the regional and station-level data centers. At the same time, it supports the regional and station-level data centers to deeply analyze and practically apply the data according to their own characteristics and business needs. Brief Description of the Drawings

[0019] Figure 1 It is the overall cloud-edge-end architecture diagram of the cloud-edge-end data center integration platform model data unified call calculation application mechanism of the present invention;

[0020] Figure 2 It is the timing data (operation data) storage architecture diagram of the cloud-edge-end data center integration platform model data unified call calculation application mechanism of the present invention;

[0021] Figure 3 It is the structured data storage architecture diagram of the cloud-edge-end data center integration platform model data unified call calculation application mechanism of the present invention;

[0022] Figure 4 It is the object data storage architecture diagram of the cloud-edge-end data center integration platform model data unified call calculation application mechanism of the present invention;

[0023] Figure 5 It is the data sharing service flow chart of the cloud-edge-end data center integration platform model data unified call calculation application mechanism of the present invention. Detailed Embodiments

[0024] In order to enable those skilled in the art to better understand the solution of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0025] The following explains some parts in the embodiments of the present application to facilitate the understanding of those skilled in the art.

[0026] The following further describes the content of the present invention in detail in conjunction with the accompanying drawings:

[0027] Combined Figure 1 Describe the overall architecture of the cloud-edge-end:

[0028] The cloud-edge architecture provides technical support for the three-level data management centers of the headquarters, regions, and stations, realizing the close connection of the cloud-edge-end, enabling the cloud capabilities to extend to the edge side, including data sharing, data storage, data computing, etc., and at the same time providing service hosting capabilities for the edge side, solving the problem that individual regional stations are small in scale and limited in resources, resulting in the lack of management and service capabilities in the region.

[0029] The cloud platform is built based on the CGN private cloud. The K8S cluster, edge agent, kafka, sftp, and ETL jointly build the basic services of the cloud platform; the cloud platform services mainly include the monitoring center, model development, model design, application management, data center, image center, automatic scheduling, edge-cloud collaboration, log / alarm, operation monitoring, etc. In terms of business, it integrates the device collection data and data persistence with the Internet of Things platform and data warehouse; and details the main services, mainly including image display, dashboard display, application display, device display, alarm display, and log display.

[0030] The hardware basis of the intelligent edge end includes edge devices, intelligent gateways, and intrusion prevention systems. On the basis of the hardware basic devices, the Kylin operating system and firewall are built, and the edge end EMQ, IOTDB / TDengine time series database, and MQTT communication protocol are built; the intelligent edge end applications include data collection, data storage, joint training, edge-cloud collaboration, container management, application orchestration, automatic scheduling, and log / alarm systems. Based on advanced design concepts and big data, cloud platform, and mobile Internet technologies, integrating advanced data fusion technologies and data mining algorithms in the industry, and leading by the intelligent centralized control requirements, a cloud-edge-end collaborative management platform for the data management center application is constructed.

[0031] Combined Figure 2 、 Figure 3 、 Figure 4 、 Figure 5 Further describe in detail the services and capabilities such as unified data architecture, unified database management, unified database monitoring, database service management, data storage management, data exchange management, data sharing management, etc.:

[0032] 1) Unified data architecture

[0033] Build a unified data storage framework to achieve data storage and application with a unified architecture for data from stations, regions, and headquarters, provide an overall data storage solution, and realize the unified planning of the storage of time-series data, structured data, and object data; provide unified application management for the database.

[0034] 1. Storage of time-series data

[0035] Time-series data mainly includes equipment operation data, power data, etc. Based on the overall plan, in the form of an IOTDB time-series database, a three-layer storage architecture is adopted. The data is mainly stored in the three zones of the station and the three zones of the region. The headquarters can, as needed, extract part of the data within a certain range to the headquarters for data application through data extraction.

[0036] The database adopts a variety of fusion architectures, which can be selected according to the data volume of each region. For example, if there are many stations and a large amount of data in a region, a cluster can be adopted at the regional layer to meet the data storage and application requirements. If there are few stations and little data in a region, a single-node mode is deployed (with the ability to expand horizontally and vertically). In addition, if data cannot be stored at the station in a region, the data can be directly collected and stored in the region. For the specific structure, see Figure 2 。

[0037] The time-series data in the three zones of the station will temporarily store data for half a year or one year according to the plan. The three zones of the region will store all the data of each station under that region, and use the MQTT method or data collection service to store the data in the database. The headquarters can call the data of each station from each region and use the data extraction service to extract the data to the headquarters for storage and application in the form of kafka.

[0038] The table structure of each station data point stored in the headquarters, region, and station adopts a unified data information model, and a unified data information model change process is set. The headquarters data center will, in the form of a data asset catalog, realize the distribution display of data point tables and data in each region and station. Headquarters users can perform statistics, retrieval, search according to needs, and realize data extraction and call according to application requirements.

[0039] When users enter the platform, they will enter different levels according to their personnel permissions. For example, regional and station personnel enter the data platforms of each region and can view the equipment operation data under the current region and station, and can perform operations such as online query, statistics, application, and export of data.

[0040] 2. Storage of structured data

[0041] Structured data mainly includes station ledger data, business data, indicator data, and application data, and is mainly stored in the OceanBese database; the headquarters is deployed in a cluster mode + regional cluster mode (which can be set as a single node according to the data volume); for the specific architecture, see Figure 3 。

[0042] The data of the equipment asset ledger is uniformly managed by the headquarters and distributed to the regional database in the way of message bus; for the index data, the headquarters can set a unified index data model, develop a data index calculation module, and the region calculates and reports the data to the headquarters database; for the application data, according to the function of actively uploading data developed within the unified monitoring of the platform, the application data of the stations and regions is reported; for the business data, according to the application requirements of the headquarters, it is regularly synchronized and extracted to the headquarters structured database through ETl.

[0043] 3. Object data storage

[0044] The object data mainly includes object data such as regional and station CMS vibration data, fault recording data, pictures, and files. The overall platform plan is to store them in the MinIo lightweight object database, design a multi-layer same-structure storage mode, deploy the headquarters and regions in a cluster mode, and deploy the stations in a single-node mode (the region can choose to deploy in a single-node mode according to the actual business volume); for the specific architecture, see Figure 4 。

[0045] The object data of the station or region is collected through the object data collection program, and the data forwarding program synchronously transmits it to the MinIo object libraries of the station and region in the way of RESF message bus for full-volume storage; based on the application requirements or business requirements of the object data, the headquarters regularly synchronizes the object data of each station under the region in the way of SFTP or RESF.

[0046] The region stores all the object data of each station in full volume. The station can store in full volume or periodically according to the requirements. The headquarters will regularly synchronize the data required by the business according to the business application requirements; the platform will adopt a unified data asset catalog to realize the unified asset catalog management of the station, region, and headquarters, and realize the unified management and application of object data assets.

[0047] 2) Unified database management

[0048] The data management platform provides unified management of all different types of databases of the headquarters, regions, and stations. It realizes the unified registration and maintenance management functions of the databases of each region and station, provides a unified database access policy, provides the ability to finely manage and operate and maintain the database instances, provides unified management and allocation of database resources, and realizes the overview and monitoring of database resources.

[0049] Multi-source database access: Realize the integration and fusion of different data sources, including structured data, unstructured data, and data from different systems and applications, to establish a comprehensive data asset library.

[0050] Unified Database Management: Provide database management functions such as adding new regional databases to the data resource pool to achieve unified management and allocation of resources. During the registration process, detailed server information needs to be collected and recorded, including but not limited to: basic server information (IP address, hostname, operating system type and version); geographical location information (physical location or the region where the data center is located, which helps with geographical load balancing and fault location); hardware resource configuration (number of CPU cores, memory size, storage medium type and total capacity); network configuration (internal and external network IPs, bandwidth limits, security group rules, etc.).

[0051] 3) Unified Database Monitoring

[0052] Database Resource Overview and Monitoring: Provide a comprehensive view for real-time monitoring and overview of the status of the entire data resource pool and key metrics of individual databases:

[0053] Resource Overview: Display the overall health status of the data resource pool, including the total number of all databases, total storage capacity, average load, etc.

[0054] Database Status Monitoring: Real-time display the running status of each database instance (such as running, stopped, under maintenance, etc.).

[0055] Load and Utilization: Dynamically display charts of CPU utilization rate, memory occupancy rate, and I / O read and write speed of each database to help identify performance bottlenecks.

[0056] Storage Size and Data Increment: Track the usage of database storage space, including total size, remaining space, and daily or weekly data growth, in order to perform capacity planning in a timely manner.

[0057] 4) Database Service Management

[0058] Database Service Management provides the ability to finely manage and operate and maintain database instances, including:

[0059] Database Access Control: Provide access entrances to the headquarters database, regional databases, and station databases, with functions such as querying data, data display, and data analysis.

[0060] Database Start / Stop: Support one-key start or stop of the database service, facilitating maintenance operations or resource scheduling.

[0061] Parameter Adjustment: Provide an interface or API to allow administrators to adjust database configuration parameters according to business needs, such as connection number limits, cache size, automatic backup frequency, etc., without directly logging in to the database server for operation.

[0062] Scheduled Task Management: Support setting up regular tasks, such as automatic backups, data cleaning, and execution of performance optimization scripts, to automate daily maintenance work and improve operation and maintenance efficiency.

[0063] 5) Database Storage Management

[0064] Data Storage: According to the data classification of real-time data, relational data, and object data, classify and store data according to different strategies to achieve the ability to uniformly manage data.

[0065] Data Backup and Recovery: Implement data backup and recovery strategies to ensure data security and reliability, and be able to quickly recover data in case of data loss and disasters.

[0066] 6) Data Exchange Management

[0067] 1. Real-time Data Transmission

[0068] Message Queue Data Transmission Support: The system supports data transmission through message queues to ensure efficient, reliable, and asynchronous data transmission. This includes not only common message queue systems but also supports various data formats such as CSV, JSON, AVRO, DEBEZIUM-JSON, CANAL-JSON, MAXWELL-JSON, etc., as well as user-defined data formats.

[0069] Dimensional Table Access and Real-time Data Mapping: The system also supports the access of dimensional tables, which usually contain dimension information of data; by mapping these dimensional tables with real-time data, the system can provide users with a more complete and rich data view to help users better understand the context and background of the data.

[0070] Real-time Data Access: To meet application scenarios with high real-time requirements, the system supports accessing data from various real-time data sources, such as IOTDB (Internet of Things Database), TAOSI, etc.; these data sources can generate and send data in real time, and the system can capture and process this data in real time to ensure that users can obtain the latest data as soon as possible.

[0071] Data Change Synchronization Capture: The system also provides the function of data change synchronization capture, supporting the capture of data change operations from multiple database systems. This includes MongoDB CDC, MysqlCDC, sqlserverCDC, postgresqlCDC, etc. By capturing these change operations, the system can update data in real time to ensure data accuracy and consistency.

[0072] 2. Relational Data Transmission

[0073] Support structured data migration: The system supports various types of structured data migration, including migrating massive amounts of data between various databases such as Mysql, Oracle, DB2, Hive, etc. Whether it is a common relational database or a big data processing platform, the system can easily handle it to ensure the integrity and accuracy of the data.

[0074] FTP / SFTP server data migration: In addition to database migrations, the system also supports parsing, mapping, and migrating structured data files from FTP / SFTP servers; users can complete these operations in one step without switching between multiple tools or systems, greatly improving work efficiency.

[0075] Flexible configuration of migration conditions: During the data migration process, the system supports flexible configuration of preconditions and postconditions.

[0076] Support incremental and full - volume migrations: To meet the needs of different users, the system supports two migration methods: incremental migration and full - volume migration; incremental migration only transfers data that has changed since the last migration, while full - volume migration transfers all data; users can choose the appropriate migration method according to the actual situation.

[0077] Resume - interrupted transfer function: During data transfer, if the transfer is interrupted due to certain reasons (such as network interruption, server failure, etc.), the system supports the resume - interrupted transfer function; this means that users do not need to start the data transfer from the beginning but can continue from the breakpoint, greatly saving time and bandwidth resources.

[0078] Resource configuration for migration tasks: Users can configure the resources for migration tasks according to the actual situation and needs, including parallelism and traffic, etc.; by reasonably configuring resources, the efficiency and stability of data migration can be ensured.

[0079] Dirty data handling: During data migration, there may be some data that does not meet the requirements or expectations, that is, so - called "dirty data"; the system supports the configuration and handling of dirty data, and users can set limits on the number of dirty data or the proportion of dirty data. When these limits are reached, the system can take corresponding handling measures, such as stopping the migration, recording logs, or sending alerts, etc.; this can ensure the accuracy and quality of data migration.

[0080] 3. Unstructured data

[0081] Automatic migration of unstructured data: The system supports the automatic migration of a wide range of unstructured data, including but not limited to various types of files (such as documents, spreadsheets, presentations, etc.), pictures, videos, audio files, etc.; regardless of where the data is stored, the system can automatically migrate it to the target location without manual intervention.

[0082] Single / Batch File Migration: To meet the needs and scenarios of different users, the system supports both single-file migration and batch-file migration. Users can selectively migrate specific files or migrate an entire folder or multiple files at once, greatly enhancing the flexibility and efficiency of data migration.

[0083] Automatic Processing of Migrated Files: After file migration is completed, the system also supports automatic processing of the migrated files, including operations such as file renaming, classification, and storage format conversion, ensuring that the files meet the actual needs and usage habits of users at the target location.

[0084] Full and Incremental Migration: Similar to structured data migration, the system also supports full and incremental migration of unstructured data. Full migration migrates all selected files at once, while incremental migration only migrates files that have been newly added or modified since the last migration. This allows for the selection of an appropriate migration method according to actual needs, ensuring both data integrity and time and resource savings.

[0085] 7) Data Sharing Management

[0086] Data sharing mainly breaks down data barriers within the organization, supports the establishment of a unified data sharing mechanism, realizes the unified sharing ability of the data management platform to access real-time data, structured data, and object data in all regions and stations, and realizes data sharing service monitoring and data security control.

[0087] Implement the construction of a unified data sharing process, including capabilities such as data application, data approval, data security management, and data interface provision. The core of data sharing ensures data security and realizes data sharing security control based on data ownership confirmation and data classification levels. For the data sharing management process, see Figure 5 .

[0088] 1. Service Construction

[0089] Provide two construction methods: data resource directory application construction and data resource directory construction.

[0090] Data resource directory application construction supports basic information settings, service data, data extraction logic, configuration parameters, field mapping, value mapping, and data desensitization capabilities to ensure data security.

[0091] Data resource directory construction supports construction and release in the form of new additions, provides management functions for the data resource directory system, and can manage the directory system by level and node, including adding, deleting, and modifying the directory system.

[0092] The platform supports relational data sharing, real-time data service sharing, and object data sharing.

[0093] Relational data sharing enables users to drag and drop data tables and fields according to their data acquisition requirements to quickly generate data sharing service interfaces; it supports quickly configuring data sharing service interfaces based on single tables, wide tables, or multiple tables; it also supports constructing services in the form of flexible SQL.

[0094] Real-time data sharing supports two sharing methods: Kafka and MQTT. Kafka performs real-time sharing through parameter information such as address, topic name, partition selection, region selection, and station selection, while MQTT performs real-time data sharing through address, port, client ID, topic name, region, and station.

[0095] Object data sharing supports file sharing, picture sharing, and CMS data sharing.

[0096] 2. Service Go-live

[0097] The platform has a service go-live module, and service go-live supports service catalog management functions, online / offline approval functions, forced offline functions, and modified offline functions.

[0098] Catalog management supports adding service catalogs, renaming, deleting, and modifying.

[0099] Online / offline approval supports viewing service applications and performing online / offline approvals; selecting approval opinions: approve, reject; and completing the approval after confirmation.

[0100] The forced offline function forcibly takes an online service offline. After confirmation, the service will enter the offline state.

[0101] The modified offline function modifies an online service to an offline state. After confirmation, the service will enter the offline modification state; after modifying a service in the "offline modification" state, the service will enter the "construction completed" state and can be re-submitted for an online application operation.

[0102] 3. Service Approval

[0103] The platform has a service approval module that manages the approval information of data services; it has functions for applying for approval, awaiting my approval, and I have approved.

[0104] Applying for approval supports service approval by the administrator of the confirmation department and the data management specialist after they log in to the system.

[0105] Awaiting my approval supports functions such as viewing applications, approval opinions, and entering approval opinions for approval.

[0106] The I have approved function has the ability to view the service information that I have approved.

[0107] 4. Service Monitoring

[0108] It provides the ability of service monitoring for the operation and maintenance of data services, automatically monitors the running status of data services, identifies anomalies, locates problems, and ensures the normal operation of data services on the platform.

[0109] Service monitoring statistics: It provides the ability of data service monitoring, including functions such as the running status of data services, anomaly identification, and problem location.

[0110] Service monitoring log: It supports the display of all data service call logs and enables data service administrators and business personnel to view the monitoring logs of corresponding services.

[0111] 5. Service authorization

[0112] Requirement analysis and role definition: Understand its business requirements and define different user roles accordingly; each role is granted corresponding data access permissions based on its responsibilities and requirements.

[0113] Permission configuration and management: Our permission management system supports flexible permission configuration, and can customize the level, scope, and restrictions of data access according to the needs of different roles.

[0114] Audit and monitoring: To ensure the compliance and security of data access, we provide powerful audit and monitoring functions. The system can record all user data access behaviors and generate detailed audit reports; in addition, we also provide real-time monitoring functions, enabling administrators to promptly discover and handle any abnormal access behaviors.

[0115] Permission change and adjustment: As the business develops and changes, user roles and permissions may also need to be adjusted accordingly; our service authorization mechanism supports flexible permission changes and adjustments to meet the ever-changing business needs of customers.

[0116] 6. Service security

[0117] To securely control access to data sharing services, the platform provides a function to set an exception list for data sharing services. It sets the access defense line for users on the exception list to avoid malicious attacks; it supports the normal list mode to ensure more secure data usage within the enterprise.

[0118] The platform supports setting exception and normal lists in the way of IP addresses and IP address segments.

[0119] 7. Service control

[0120] During the application of data sharing services, there is often a peak period when users concentrate on invoking services in a certain time period, which affects the performance of the platform; in response to this phenomenon, the platform provides the ability of traffic control strategies.

[0121] Support flexible traffic control policies for data sharing services in the system, provide traffic control solutions such as by time period and frequency, and support restricting the number of times a service is accessed and the number of times an IP accesses the service to control system access traffic; the flow control policy of the platform provides a series of solutions to reduce the system load pressure, can simply handle the load problems brought by the possible service access peak period, and enhances the security and availability of data sharing service management.

[0122] 8. Service Agreement

[0123] In providing real-time sharing services, support common protocols and technologies such as IEC104, Modbus, RESTful, Kafka, MQTT, etc., to ensure the real-time and efficient forwarding of data; these technologies not only meet the real-time data requirements of multiple fields such as early warning systems, vibration analysis platforms, and other business platforms, but also ensure the reliability and stability of data transmission.

[0124] For non-real-time sharing services, the platform supports methods such as SFTP secure file transfer, API interface calls, and offline sharing. These services can meet the needs of customers in terms of data security, flexibility, and offline operations, and ensure the integrity and security of data.

[0125] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

Claims

1. The unified call and calculation application mechanism for model data of the cloud-edge-end data center integration platform, characterized in that: It includes the following: unified data architecture, unified database management, unified database monitoring, database service management, data storage management, data exchange management, and data sharing management.

2. The unified call and calculation application mechanism for cloud-edge-end data center integrated platform model data according to claim 1, characterized in that: The unified data architecture specifically constructs a unified data storage framework to realize the data storage and application of the unified data architecture of the data of stations, regions, and headquarters, provides an overall data storage solution, and realizes the unified planning of the storage of time-series data, structured data, and object data; provides unified application management of the database.

3. The unified call and calculation application mechanism for cloud-edge-end data center integrated platform model data according to claim 1, wherein: The unified database management specifically provides unified management of all different types of databases in the headquarters, regions, and stations, realizes the unified registration and maintenance management functions of the databases in each region and station, provides a unified database access policy, provides the ability to finely manage and operate and maintain the database instance, provides unified management and allocation of database resources, and realizes the overview and monitoring of database resources.

4. The unified call and calculation application mechanism for model data of the cloud-edge-end data center integration platform according to claim 1, characterized in that: The unified database monitoring specifically is the overview and monitoring of database resources: provides a comprehensive view for real-time monitoring and overview of the status of the entire data resource pool and the key indicators of individual databases.

5. The unified call and calculation application mechanism for model data of the cloud-edge-end data center integration platform according to claim 1, characterized in that: The database service management specifically provides the ability to finely manage and operate and maintain the database instance.

6. The unified call and calculation application mechanism for model data of the cloud-edge-end data center integration platform according to claim 1, characterized in that: The data storage management specifically classifies and stores data according to different policies, and realizes the ability of unified data management.

7. The unified call and calculation application mechanism for cloud-edge-end data center integrated platform model data according to claim 1, characterized in that: The data exchange management specifically uniformly manages the exchange of data such as real-time data, relational data, and unstructured data according to different data migration and transmission policies.

8. The unified call and calculation application mechanism for the model data of the cloud-edge-end data center integration platform according to claim 1, characterized in that: The data sharing management specifically breaks through the data barriers within the organization, supports the establishment of a unified data sharing mechanism, realizes the unified sharing ability of the data management platform to access the real-time data, structured data, and object data of all regions and stations, and realizes data sharing service monitoring and data security control.

9. The unified call and calculation application mechanism for model data of the cloud-edge-end data center integration platform according to claim 1, characterized in that: The cloud-edge-end data center integration platform model's data unified call computing application mechanism's cloud-edge architecture provides technical support for the three-level data management centers of the headquarters, regions, and stations, realizes the close connection of the cloud-edge-end, enables the cloud capabilities to extend to the edge side, including data sharing, data storage, data computing, etc., and at the same time provides service hosting capabilities for the edge side, solving the problem that individual regions and stations have small scales and limited resources, resulting in the lack of management service capabilities in the region.

10. The unified call and calculation application mechanism for the cloud-edge-end data center integration platform model data according to claim 1, characterized in that: When the cloud-edge-end data center integration platform model's data unified call computing application mechanism is specifically used, it constructs a collaborative application system for the three-level data centers of the headquarters, regions, and stations for the enterprise, deeply integrates and efficiently utilizes the resources of the data centers in each region and station, strengthens the collaborative application of the three-level data centers, breaks through information islands, and realizes the seamless connection and efficient collaborative application of data; while the headquarters data center mainly plays a core overall role, provides strategic guidance and data support for the data centers in regions and stations. At the same time, it supports the data centers in regions and stations to conduct in-depth analysis and practical application of data according to their own characteristics and business needs.

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