A data center platform based on centralized management of multi-layer architecture

Abstract

The application discloses a kind of data center platforms based on multi-layer architecture centralized management, it is related to data management technical field, including: basic resource layer, data resource layer, data platform layer, application platform layer and front-end business interaction layer;Basic resource layer is connected with data resource layer, data resource layer is connected with data platform layer, data platform layer is connected with application platform layer, and application platform layer is connected with front-end business interaction layer;Data platform layer divides application program into multiple independent service units by microservice architecture, and each independent service unit communicates by RESTful API;Supporting system includes system mechanism system, standard specification system, operation and maintenance guarantee system and security protection system.The application adopts multi-layer architecture and microservice design, and realizes the efficient management and safe application of large-scale energy data by the organic combination of intelligent data processing, hierarchical storage, multiple security protection and personalized service and the like technical features.

Description

Technical Field

[0001] This invention relates to the field of data management technology, specifically to a data center platform based on a multi-layered architecture for centralized management. Background Technology

[0002] With the continuous growth of energy consumption, the scale and complexity of energy data are also expanding. To address this challenge, traditional data center management models are no longer sufficient to meet the current large-scale and diverse energy data management needs. Against the backdrop of surging energy data volumes and diversified data sources, traditional centralized data centers are proving inadequate in terms of processing power and flexibility, making it difficult to adapt to the new requirements of data management.

[0003] To address the challenges of centralized energy data management, improve the efficiency of data sharing and integration, ensure system security and reliability, and enhance system scalability and flexibility, the Guizhou Energy Data Center Scenario Construction Project proposed an innovative technical solution. This solution constructs a comprehensive energy data center platform that not only centrally manages and processes large-scale energy data but also enables effective data sharing and integration, improving data availability and value. Simultaneously, the platform employs advanced security technologies and measures to protect the security and privacy of the data center when processing sensitive data. Furthermore, the platform's design considers the needs of business growth and change, ensuring rapid adaptation and scalability through a microservice architecture and modular design to address potential future challenges. This technological background provides a solid foundation for the implementation of the Guizhou Energy Data Center Scenario Construction Project. Summary of the Invention

[0004] In view of the above-mentioned problems, the present invention is proposed.

[0005] Therefore, the present invention provides a data center platform based on a multi-layer architecture for centralized management, which can solve the problems mentioned in the background art.

[0006] To address the aforementioned technical problems, this invention provides the following technical solution: a data center platform based on a multi-layered architecture for centralized management, comprising: a basic resource layer, a data resource layer, a data platform layer, an application platform layer, and a front-end business interaction layer; wherein,

[0007] The basic resource layer is connected to the data resource layer, the data resource layer is connected to the data platform layer, the data platform layer is connected to the application platform layer, and the application platform layer is connected to the front-end business interaction layer.

[0008] The data platform layer divides the application into multiple independent service units through a microservice architecture, and each independent service unit communicates through a RESTful API;

[0009] The supporting system includes a system of rules and regulations, a system of standards and specifications, a system of operation and maintenance support, and a system of security protection. The supporting system is connected to the basic resource layer, the data resource layer, the data platform layer, the application platform layer, and the front-end business interaction layer, respectively.

[0010] As a preferred embodiment of the data center platform based on multi-layer architecture centralized management described in this invention, a data acquisition unit is provided between the basic resource layer and the data resource layer, and the data acquisition unit includes a data extraction module and a data preprocessing module.

[0011] When the data extraction module collects data, the data preprocessing module cleans the collected data and transmits the cleaned data to the data resource layer.

[0012] As a preferred embodiment of the data center platform based on multi-layer architecture centralized management described in this invention, the data platform layer includes a data storage module and a data analysis module;

[0013] If a data storage request is received, the data storage module stores the data in the structured data area or the unstructured data area according to the data type.

[0014] If a data analysis request is received, the data analysis module retrieves the data to be analyzed from the data storage module.

[0015] As a preferred embodiment of the data center platform based on multi-layer architecture centralized management described in this invention, each of the independent service units includes a first API interface, and the first API interfaces of two adjacent independent service units establish a communication connection through a RESTful API.

[0016] If the first independent service unit sends a service call request to the second independent service unit, the second independent service unit returns service response data.

[0017] As a preferred embodiment of the data center platform based on multi-layer architecture centralized management described in this invention, the standard specification system includes a data resource display specification unit, a data classification and storage specification unit, and a data application specification unit; if the data platform layer receives new data, the data classification and storage specification unit performs hierarchical classification of the data; if data needs to be displayed, the data resource display specification unit selects the corresponding display template according to the display scenario.

[0018] As a preferred embodiment of the data center platform based on multi-layer architecture centralized management described in this invention, the standard specification system includes a data resource display specification unit, a data classification and storage specification unit, and a data application specification unit.

[0019] The data classification and storage specification unit establishes a three-level classification system for data, specifically:

[0020] If the data belongs to the first level, it corresponds to the basic business data storage area;

[0021] If the data belongs to the second level, then the corresponding data storage area should be analyzed and mined.

[0022] If the data belongs to the third level, then it corresponds to the derived application data storage area;

[0023] The data resource display specification unit allocates different data display templates according to the data level, and the data application specification unit establishes a data mapping table for cross-regional data access.

[0024] As a preferred embodiment of the data center platform based on multi-layer architecture centralized management described in this invention, the security protection system includes a data encryption unit and an access control unit; the data encryption unit includes multiple encryption mechanisms.

[0025] If the data is structured, field-level encryption is used; if the data is unstructured, file-level encryption is used.

[0026] The access control unit establishes a multi-dimensional access control matrix, which includes user dimension, data dimension and time dimension, and determines data access permissions based on the calculation results of the access control matrix.

[0027] As a preferred embodiment of the data center platform based on multi-layer architecture centralized management described in this invention, the security protection system further includes a security monitoring unit; the security monitoring unit establishes a user access behavior model, which includes time characteristics, frequency characteristics, and data association characteristics.

[0028] If the deviation between the detected user access behavior and the user access behavior model exceeds a first preset threshold, the security monitoring unit generates an abnormal warning signal; if the density of the abnormal warning signal exceeds a second preset threshold, the access control unit automatically adjusts the permission level of the access control matrix.

[0029] As a preferred embodiment of the data center platform based on multi-layer architecture centralized management described in this invention, the operation and maintenance support system includes a system monitoring unit and a fault handling unit; the system monitoring unit establishes a system health assessment model, which includes resource utilization indicators, performance indicators, and stability indicators.

[0030] If the evaluation result of the system health assessment model is lower than the third preset threshold, the self-healing mechanism of the fault handling unit is triggered; the self-healing mechanism includes dynamic resource adjustment and service degradation processing.

[0031] As a preferred embodiment of the data center platform based on multi-layer architecture centralized management described in this invention, the front-end business interaction layer includes a data display module and a user interaction module; the user interaction module establishes a user profile model, which includes user role characteristics, data access characteristics, and business operation characteristics.

[0032] The data display module automatically adjusts the data display strategy based on the user profile model. If the user profile model displays user preference data analysis, the data analysis results are displayed first. If the user profile model displays raw user preference data, the raw dataset is displayed first.

[0033] The beneficial effects of this invention are as follows: This invention achieves hierarchical management and processing of energy data through a multi-layered architecture design; the microservice architecture design improves the system's flexibility and scalability; automated data acquisition and preprocessing mechanisms, combined with a three-level classification storage strategy, enhance data management efficiency; differentiated encryption strategies and multi-dimensional access control, combined with user behavior monitoring, construct a comprehensive security protection system; system health assessment and self-healing mechanisms improve system stability; and personalized display strategies based on user profiles optimize the user experience. The organic combination of these technical features enables this invention to effectively solve the management challenges of large-scale energy data, providing efficient data services while ensuring data security. Attached Figure Description

[0034] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0035] Figure 1 This is an overall structural diagram of a data center platform based on a multi-layered architecture and centralized management proposed in this invention. Detailed Implementation

[0036] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0037] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0038] Example 1, referring to Figure 1 As an embodiment of the present invention, a data center platform based on a multi-layer architecture and centralized management is provided.

[0039] The system adopts a layered architecture, including a basic resource layer, a data resource layer, a data platform layer, an application platform layer, and a front-end business interaction layer, and is equipped with corresponding supporting systems. Each layer is interconnected through standardized interfaces, forming a complete data management ecosystem.

[0040] The system is structured as follows: the basic resource layer connects to the data resource layer; the data resource layer connects to the data platform layer; the data platform layer connects to the application platform layer; and the application platform layer connects to the front-end business interaction layer. The data platform layer uses a microservice architecture to divide the application into multiple independent service units, which communicate with each other via RESTful APIs. Supporting systems include institutional mechanisms, standards and specifications, operation and maintenance support, and security protection, which connect to the basic resource layer, data resource layer, data platform layer, application platform layer, and front-end business interaction layer, respectively.

[0041] Specifically, the basic resource layer is primarily responsible for the collection and storage of raw data, including operational data from various energy devices, environmental monitoring data, and user consumption data. These data sources are diverse, including but not limited to smart meters, environmental sensors, and energy trading systems. The basic resource layer employs a distributed storage architecture to ensure efficient storage and rapid access to massive amounts of data.

[0042] A data acquisition unit is set up between the data resource layer and the basic resource layer. This data acquisition unit includes a data extraction module and a data preprocessing module. The data extraction module is responsible for extracting raw data from the basic resource layer. After the data extraction module acquires the data, the data preprocessing module cleans and processes the data, including removing noise, filling in missing values, and standardizing the data. The preprocessed data is then transmitted to the data resource layer for further management and storage.

[0043] The data platform layer is the core processing layer of the entire system, comprising a data storage module and a data analysis module. The data storage module stores data in either a structured or unstructured data area based on its type. Specifically, standardized data such as equipment operating parameters and user energy consumption data are stored in the structured data area, while unstructured data such as images, videos, and documents are stored in the unstructured data area. Upon receiving a data storage request, the data storage module stores the data in either the structured or unstructured data area according to its data type. When the system receives a data analysis request, the data analysis module retrieves the corresponding data to be analyzed from the data storage module for processing.

[0044] The data platform layer adopts a microservice architecture, dividing the application into multiple independent service units. Each independent service unit is equipped with a first API interface, and adjacent independent service units establish communication connections through a RESTful API between their first API interfaces. For example, when the first independent service unit needs to call the service of the second independent service unit, it sends a service call request through the RESTful API, and the second independent service unit returns the corresponding service response data after receiving the request.

[0045] The supporting system includes a system of regulations and mechanisms, a system of standards and specifications, an operation and maintenance support system, and a security protection system. The system of standards and specifications includes data resource display specifications, data classification and storage specifications, and data application specifications. The data classification and storage specifications establish a three-level classification system: the first level corresponds to the basic business data storage area, storing basic data generated from daily business operations; the second level corresponds to the analysis and mining data storage area, storing processed and analyzed data; and the third level corresponds to the derived application data storage area, storing application data further processed based on the basic and analysis data. The data resource display specifications allocate different display templates according to the data level, while the data application specifications are responsible for establishing a data mapping table for cross-regional data access, ensuring interoperability between data at different levels.

[0046] The security protection system consists of a data encryption unit, an access control unit, and a security monitoring unit. The data encryption unit employs a multi-layered encryption mechanism, using different encryption strategies for different types of data: for structured data, field-level encryption is used, allowing for individual encryption of sensitive fields; for unstructured data, file-level encryption is used to ensure the security of the entire file. The access control unit establishes a multi-dimensional access control matrix, including user, data, and time dimensions. The system determines user data access permissions based on the calculation results of this matrix.

[0047] The security monitoring unit establishes a user access behavior model, which includes time characteristics, frequency characteristics, and data correlation characteristics. The system monitors user access behavior in real time. When the deviation between the detected behavior and the model exceeds a first preset threshold (e.g., set to 0.8), the security monitoring unit generates an anomaly warning signal. If the density of anomaly warning signals exceeds a second preset threshold (e.g., more than 3 warnings within 10 minutes), the access control unit automatically adjusts the permission level of the access control matrix to enhance security protection.

[0048] The operation and maintenance support system includes a system monitoring unit and a fault handling unit. The system monitoring unit has established a system health assessment model, which comprehensively considers resource utilization indicators (such as CPU utilization and memory usage), performance indicators (such as response time and concurrent processing capacity), and stability indicators (such as system uptime and error rate). When the assessment result of the system health assessment model falls below a third preset threshold (e.g., set to 75%), the self-healing mechanism of the fault handling unit is triggered. This mechanism includes dynamic resource adjustment (such as automatic scaling and load balancing) and service degradation handling (such as shutting down non-core services and limiting concurrent requests).

[0049] The front-end business interaction layer includes a data display module and a user interaction module. The user interaction module establishes a user profile model, which includes user role characteristics (such as administrator, regular user, etc.), data access characteristics (such as commonly used data types, access frequency, etc.), and business operation characteristics (such as frequently used functions, operating habits, etc.). The data display module automatically adjusts its data display strategy based on the user profile model: for users who prefer data analysis, the system will prioritize displaying data analysis results, statistical charts, etc.; for users who prefer raw data, the system will prioritize displaying the raw dataset and provide flexible data retrieval and export functions.

[0050] In practical applications, when the system receives a user request, it first performs identity authentication and permission verification through the user interaction module of the front-end business interaction layer. After successful verification, a personalized display strategy is determined based on the user profile model. If the user requests access to certain data, the system will determine whether the user has the corresponding permissions based on the access control matrix. Once authorized, the system uses a microservice architecture to call the corresponding service unit to retrieve the required data from the data storage module. If data analysis is needed, the data analysis module processes the data and returns the results. Throughout the entire process, the system monitoring unit continuously monitors the system status to ensure stable service operation.

[0051] Through the above technical solutions, the data center platform provided in this embodiment achieves efficient management and secure access to energy data, meets the personalized needs of different users, and has strong scalability and fault tolerance.

[0052] In summary, this invention achieves hierarchical management and processing of energy data through a multi-layered architecture design; the microservice architecture design improves the system's flexibility and scalability; automated data acquisition and preprocessing mechanisms, combined with a three-level classification storage strategy, enhance data management efficiency; differentiated encryption strategies and multi-dimensional access control, combined with user behavior monitoring, construct a comprehensive security protection system; system health assessment and self-healing mechanisms improve system stability; and personalized display strategies based on user profiles optimize the user experience. The organic combination of these technical features enables this invention to effectively solve the management challenges of large-scale energy data, providing efficient data services while ensuring data security.

[0053] Example 2 is an embodiment of the present invention, which provides a data center platform based on a multi-layer architecture for centralized management. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.

[0054] To verify the technical effectiveness of this invention, this embodiment selected a real-world business scenario from a provincial energy group for comparative testing. The test environment used the same hardware configuration: the server was configured with an Intel Xeon E5-2680v4 CPU, 256GB RAM, and an NVMe SSD array for storage. The test data included three months of energy production and consumption data, totaling approximately 500TB, encompassing both structured and unstructured data. The comparative test selected a traditional centralized data management platform (Comparison System A) and a data management platform based on a simple microservice architecture (Comparison System B) as references. The test content included multiple dimensions such as data processing performance, system availability, security protection effectiveness, and resource utilization. This embodiment adopted industry-standard testing methods, comprehensively evaluating system performance through stress testing, fault injection, and security penetration testing. The testing process simulated various real-world scenarios such as high-concurrency access, data anomalies, and network fluctuations to ensure the authenticity and reliability of the test results.

[0055] The testing lasted 30 days, collecting over 1 million test samples. Performance testing simulated concurrent user requests ranging from 100 to 10,000. Security testing included various attack tests such as SQL injection, cross-site scripting, and denial-of-service attacks. Reliability testing assessed the system's fault tolerance and recovery capabilities by randomly shutting down service nodes, simulating network latency, and triggering data anomalies. This embodiment also continuously monitored system resource consumption, including key indicators such as CPU utilization, memory usage, and storage I / O. To ensure objectivity, all test cases and data were verified by a third-party testing organization. After standardization, the test data was comprehensively analyzed and evaluated using an industry-recognized evaluation model.

[0056] Table 1 System Performance Comparison Data

[0057] Test metrics Traditional centralized platform Simple Microservice Platform This invention platform Performance improvement ratio Data processing speed (GB / s) 0.8 1.2 2.5 108.33％ System response time (ms) 850 650 320 50.77％ Concurrent processing capacity (requests per second) 2000 3500 8000 128.57％ Fault recovery time (minutes) 45 30 12 60.00％ Data loading latency (seconds) 25 18 8 55.56％ Resource utilization rate (%) 45 60 85 41.67％ System availability (%) 99.9 99.95 99.99 0.04％ Security protection success rate (%) 92 95 99.5 4.74％ Data processing accuracy (%) 95 97 99.8 2.89％ Storage space utilization rate (%) 65 75 90 20.00％

[0058] Analysis of the test data leads to the following conclusions: This invention significantly outperforms the comparative system in all key indicators. Specifically, in terms of data processing speed, this invention achieves 2.5GB / s, a 108.33% improvement compared to a simple microservice platform; system response time is reduced to 320ms, an average improvement of over 50% compared to the comparative system; concurrent processing capacity reaches 8000 requests / second, a 128.57% improvement compared to a simple microservice platform; fault recovery time is reduced to 12 minutes, an average reduction of over 60% compared to the comparative system; system resource utilization is increased to 85%, a 41.67% improvement compared to the traditional platform; in terms of security, the protection success rate reaches 99.5%, an improvement of approximately 4.74% compared to the comparative system; data processing accuracy reaches 99.8%, an improvement of approximately 2.89%; and storage space utilization is increased to 90%, a 20% improvement compared to the traditional platform. These data fully demonstrate the significant advantages of this invention in performance, reliability, security, and resource utilization efficiency. Of particular note is the system availability reaching a high level of 99.99%, a highly competitive metric in large-scale data processing systems, demonstrating the invention's exceptional stability and reliability. Furthermore, test data shows that the performance advantages of this invention become more pronounced with increasing concurrent users and data processing volume, indicating the platform's excellent scalability and stability.

[0059] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A data center platform based on centralized management of multi-tier architecture, characterized in that, It comprises a basic resource layer, a data resource layer, a data platform layer, an application platform layer, and a front-end business interaction layer. The basic resource layer is connected with the data resource layer, the data resource layer is connected with the data platform layer, the data platform layer is connected with the application platform layer, and the application platform layer is connected with the front-end business interaction layer. The data platform layer divides the application program into multiple independent service units through a micro-service architecture, and each independent service unit communicates through a RESTful API. A supporting system is provided, which comprises a system mechanism system, a standard specification system, an operation and maintenance guarantee system, and a security protection system, and is connected with the basic resource layer, the data resource layer, the data platform layer, the application platform layer, and the front-end business interaction layer. The standard specification system comprises a data resource display specification unit, a data classification storage specification unit, and a data application specification unit. If the data platform layer receives new data, the data classification storage specification unit classifies the data. If the data needs to be displayed, the data resource display specification unit selects a corresponding display template according to the display scenario. The standard specification system comprises a data resource display specification unit, a data classification storage specification unit, and a data application specification unit. The data classification storage specification unit establishes a three-level classification system for data, specifically: If the data belongs to the first level, it corresponds to the basic business data storage area. If the data belongs to the second level, it corresponds to the analysis and mining data storage area. If the data belongs to the third level, it corresponds to the derivative application data storage area. The data resource display specification unit assigns different data display templates according to the data level, and the data application specification unit establishes a data mapping table for cross-zone data access. The security protection system comprises a data encryption unit and an access control unit.

2. The centrally managed data center platform based on multi-tier architecture as claimed in claim 1, wherein: If the data is structured data, field-level encryption is used, and if the data is unstructured data, file-level encryption is used. The access control unit establishes a multi-dimensional access control matrix, which includes user dimension, data dimension, and time dimension, and determines data access permissions according to the calculation results of the access control matrix.

3. The centrally managed data center platform based on multi-tier architecture as claimed in claim 2, wherein: A data acquisition unit is provided between the basic resource layer and the data resource layer, which comprises a data extraction module and a data preprocessing module. When the data extraction module collects data, the data preprocessing module cleans the collected data, and the data preprocessing module transmits the cleaned data to the data resource layer. The data platform layer comprises a data storage module and a data analysis module. If a data storage request is received, the data storage module stores the data in a structured data area or an unstructured data area according to the data type. If a data analysis request is received, the data analysis module retrieves the data to be analyzed from the data storage module.

4. The centrally managed data center platform based on multi-tier architecture of claim 3, wherein: Each of the independent service units comprises a first API interface, and a communication connection is established between the first API interfaces of two adjacent independent service units through a RESTful API; If the first independent service unit sends a service call request to the second independent service unit, the second independent service unit returns service response data.

5. The centrally managed data center platform based on multi-tier architecture of claim 4, wherein: The security protection system further comprises a security monitoring unit; the security monitoring unit establishes a user access behavior model, and the user access behavior model comprises time characteristics, frequency characteristics and data correlation characteristics; If the deviation of the detected user access behavior from the user access behavior model exceeds a first preset threshold, the security monitoring unit generates an abnormal early warning signal; If the density of the abnormal early warning signal exceeds a second preset threshold, the access control unit automatically adjusts the permission level of the access control matrix.

6. The centrally managed data center platform based on multi-tier architecture of claim 5, wherein: The operation and maintenance guarantee system comprises a system monitoring unit and a fault processing unit; the system monitoring unit establishes a system health degree evaluation model, and the system health degree evaluation model comprises resource utilization rate indexes, performance indexes and stability indexes; If the evaluation result of the system health degree evaluation model is lower than a third preset threshold, a self-healing mechanism of the fault processing unit is triggered; the self-healing mechanism comprises resource dynamic adjustment and service degradation processing.

7. The centrally managed data center platform based on multi-tier architecture of claim 6, wherein: The front-end business interaction layer comprises a data display module and a user interaction module; the user interaction module establishes a user portrait model, and the user portrait model comprises user role characteristics, data access characteristics and business operation characteristics; The data display module automatically adjusts a data display strategy according to the user portrait model; if the user portrait model displays user preference data analysis, a data analysis result is preferentially displayed; if the user portrait model displays user preference original data, an original data set is preferentially displayed.

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