IT health degree analysis and evaluation method and system based on digital twinning

Abstract

The invention relates to the field of digital twinning, and discloses an IT health degree analysis and evaluation method and system based on digital twinning, and the method comprises the steps: dividing standardized system data into system physical data and system driving data; identifying a data correlation coefficient of the system physical data, analyzing a functional structure of the IT system, and constructing a system physical model of the IT system; extracting system driving characteristics of the system driving data, analyzing a system driving rule of the IT system, and constructing a system driving model of the IT system; fusing the system physical model and the system driving model to obtain a system twinborn model, calculating a fusion coefficient of the system twinborn model, and adjusting model parameters of the system twinborn model to obtain an adjusted system twinborn model; and simulating operation of the IT system to obtain operation data, calculating a risk coefficient of the IT system, and constructing a health degree analysis report of the IT system. According to the invention, the analysis effect on the health degree of the IT system can be improved.

Description

Technical Field

[0001] The present invention relates to the field of digital twins, and in particular to an IT health analysis and evaluation method and system based on digital twins. Background Art

[0002] IT health analysis is a method for evaluating the stability, security, and reliability of an enterprise or organization's information technology system. By comprehensively inspecting and evaluating all aspects of the IT system, it is determined whether there are potential problems or risks in the system, and suggestions for improvement and optimization are provided to the enterprise and organization.

[0003] Currently, IT health analysis is mainly achieved by inspecting and evaluating system modules such as the system architecture, technology selection, and code quality of the IT system. This method mainly conducts health analysis on the functional system of the system and cannot identify the risks that may occur during system operation, resulting in poor IT system health analysis effects. Summary of the Invention

[0004] The present invention provides an IT health analysis and evaluation method and system based on digital twins, and its main purpose is to improve the analysis effect of the IT system health.

[0005] To achieve the above object, an IT health analysis and evaluation method based on digital twins provided by the present invention includes:

[0006] Collect the system data of the IT system, integrate the system data into the data lake, perform data standardization processing on the system data corresponding to the data lake to obtain standardized system data, and divide the standardized system data into system physical data and system drive data;

[0007] Identify the data correlation coefficient of the system physical data, analyze the functional structure of the IT system based on the data correlation coefficient, and construct the system physical model of the IT system through the functional structure;

[0008] Extract the system drive characteristics of the system drive data, analyze the system drive law of the IT system based on the system drive characteristics, and construct the system drive model of the IT system based on the system drive law and the system drive data;

[0009] Fuse the system physical model and the system drive model to obtain a system twin model, calculate the fusion coefficient of the system twin model, and adjust the model parameters of the system twin model based on the fusion coefficient to obtain an adjusted system twin model;

[0010] Simulate the operation of the IT system based on the adjusted system twin model to obtain operation data. Based on the operation data, calculate the risk coefficient of the IT system. Based on the risk coefficient, construct a health analysis report of the IT system.

[0011] Optionally, the data standardization process for the system data corresponding to the data lake to obtain standardized system data includes:

[0012] Identify the data structure of the system data corresponding to the data lake;

[0013] Based on the data structure, identify the data standard metrics of the system data;

[0014] Based on the data standard metrics, construct a data standardization instruction for the system data;

[0015] Through the data standardization instruction, perform data standardization processing on the system data to obtain the standardized system data.

[0016] Optionally, the identification of the data correlation coefficient of the system physical data includes:

[0017] Extract the data features of the system physical data;

[0018] Standardize the physical data features to obtain standardized features;

[0019] Based on the standardized features, calculate the feature covariance of the standardized features corresponding to the system physical data;

[0020] Based on the feature covariance, calculate the data correlation coefficient of the system physical data.

[0021] Optionally, the analysis of the functional structure of the IT system based on the data correlation coefficient includes:

[0022] Based on the data correlation coefficient, divide the system physical data corresponding to the IT system to obtain relevant data sets;

[0023] Analyze the system functional attributes of the relevant data sets;

[0024] Based on the system functional attributes, analyze the functional structure of the IT system.

[0025] Optionally, the construction of the system physical model of the IT system through the functional structure includes:

[0026] Based on the functional structure, construct a functional structure diagram of the IT system;

[0027] Convert the functional structure diagram into a mathematical description to obtain the mathematical description system structure;

[0028] Based on the mathematical description system structure, construct the system structure mathematical equation of the IT system;

[0029] Through the system structure mathematical equation, construct the system physical model of the IT system.

[0030] Optionally, the constructing the system structure mathematical equation of the IT system based on the mathematical description system structure includes:

[0031] Identify the structure variable values of the mathematical description system structure;

[0032] Based on the structure variable values, use the following formula to construct the system structure mathematical equation of the IT system:

[0033] dx / dt = f(t, x(t), x’(t), …, x^{(n)}(t))

[0034] where dx / dt represents the system structure mathematical equation of the IT system, x(t) represents the structure variable value of the x-th mathematical description system structure at time t, x’(t) represents the instantaneous change rate of the x-th mathematical description system structure at time t, and f(t, x(t), x’(t), …, x^{(n)}(t)) is a function related to the structure variable values of the x-th mathematical description system structure and the structure variable values of other mathematical description system structures at time t.

[0035] Optionally, the analyzing the system driving law of the IT system based on the system driving characteristics includes:

[0036] Identify the system components of the IT system;

[0037] Based on the system driving characteristics, mark the driving interaction relationships between the system components;

[0038] Based on the driving interaction relationships, analyze the system driving law of the IT system.

[0039] Optionally, the constructing the system driving model of the IT system based on the system driving law and the system driving data includes:

[0040] Based on the system driving data, construct the initial component model of the IT system;

[0041] Based on the system driving law, construct the interaction instructions for the system components corresponding to the initial component model;

[0042] Based on the interaction instructions, construct the system driving model of the IT system.

[0043] Optionally, calculating the risk coefficient of the IT system based on the operation data includes:

[0044] Analyzing the operation characteristics of the IT system based on the operation data;

[0045] Identifying abnormal operation behaviors of the IT system based on the operation characteristics;

[0046] Calculating the risk coefficient of the IT system based on the abnormal operation behaviors by using the following formula:

[0047]

[0048] Wherein, represents the risk coefficient of the IT system, J 2 Lu represents the system health identification function, S i represents the i-th abnormal operation behavior, R i represents the abnormal weight corresponding to the i-th abnormal operation behavior, θ represents the influence coefficient of the i-th abnormal operation behavior on other abnormal operation behaviors, and n represents the number of abnormal operation behaviors.

[0049] To solve the above problems, the present invention also provides an IT health analysis and evaluation system based on digital twin, and the system includes:

[0050] A data processing module, configured to collect system data of the IT system, integrate the system data into a data lake, perform data standardization processing on the system data corresponding to the data lake to obtain standardized system data, and divide the standardized system data into system physical data and system drive data;

[0051] A system physical model construction module, configured to identify the data correlation coefficient of the system physical data, analyze the functional structure of the IT system based on the data correlation coefficient, and construct a system physical model of the IT system through the functional structure;

[0052] A system drive model construction module, configured to extract the system drive characteristics of the system drive data, analyze the system drive law of the IT system based on the system drive characteristics, and construct a system drive model of the IT system based on the system drive law and the system drive data;

[0053] A twin model fusion module, configured to fuse the system physical model and the system drive model to obtain a system twin model, calculate the fusion coefficient of the system twin model, and adjust the model parameters of the system twin model based on the fusion coefficient to obtain an adjusted system twin model;

[0054] A health analysis module is used to simulate the operation of the IT system based on the adjusted system twin model to obtain operation data, calculate the risk coefficient of the IT system based on the operation data, and construct a health analysis report of the IT system based on the risk coefficient.

[0055] In the embodiments of the present invention, by performing data standardization processing on the system data corresponding to the data lake, standardized system data is obtained to eliminate noise, missing values, and outliers, improving the reliability of the data. In the embodiments of the present invention, by identifying the data correlation coefficient of the system physical data, a data basis can be provided for later data function analysis; in the embodiments of the present invention, by analyzing the functional structure of the IT system based on the data correlation coefficient, the internal structure of the IT system can be better analyzed, thereby improving the reliability of model construction. In the embodiments of the present invention, by extracting the system drive characteristics of the system drive data to analyze the behavior characteristics of the IT system, a data basis can be provided for later system drive simulation. Optionally, in the embodiments of the present invention, based on the system drive law and the system drive data, constructing the system drive model of the IT system can accurately simulate the operation path of the system through the system drive model, thereby improving the reliability of system simulation data. Finally, in the embodiments of the present invention, by fusing the system physical model and the system drive model, a system twin model is obtained. In order to create a comprehensive system twin model that can reflect the behavior and characteristics of the actual physical system, thereby improving the accuracy of system health analysis. In the embodiments of the present invention, constructing the health analysis report of the IT system can achieve the health maintenance of the IT system. Therefore, the IT health analysis and evaluation method and system based on digital twin proposed by the present invention can improve the analysis effect of the health of the IT system. Brief Description of the Drawings

[0056] Figure 1 It is a schematic flowchart of the IT health analysis and evaluation method based on digital twin provided by an embodiment of the present invention;

[0057] Figure 2 It is a functional module diagram of the IT health analysis and evaluation system based on digital twin provided by an embodiment of the present invention;

[0058] Figure 3 It is a schematic structural diagram of an electronic device of the IT health analysis and evaluation system based on digital twin provided by an embodiment of the present invention;

[0059] The realization, functional features, and advantages of the object of the present invention will be further described in conjunction with the embodiments with reference to the drawings. Detailed Embodiments

[0060] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0061] An embodiment of the present application provides a method for analyzing and evaluating IT health based on digital twins. The execution subject of the method for analyzing and evaluating IT health based on digital twins includes, but is not limited to, at least one of electronic devices such as a server, a terminal, etc. that can be configured to execute the method provided by the embodiment of the present application. In other words, the method for analyzing and evaluating IT health based on digital twins can be executed by software or hardware installed on a terminal device or a server device, and the software can be a blockchain platform. The server includes, but is not limited to: a single server, a server cluster, a cloud server, or a cloud server cluster, etc. The server can be an independent server or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, Content Delivery Network (CDN), and big data and artificial intelligence platforms.

[0062] Refer to Figure 1 As shown, it is a schematic flowchart of a method for analyzing and evaluating IT health based on digital twins provided by an embodiment of the present invention. In this embodiment, the method for analyzing and evaluating IT health based on digital twins includes:

[0063] S1. Collect system data of the IT system, integrate the system data into a data lake, perform data standardization processing on the system data corresponding to the data lake to obtain standardized system data, and divide the standardized system data into system physical data and system driver data.

[0064] In the embodiment of the present invention, the system data refers to the data involved in the IT system, such as system performance data, user behavior data, hardware status data, etc. The data lake refers to a storage space formed by uniformly storing the system data.

[0065] In the embodiment of the present invention, by performing data standardization processing on the system data corresponding to the data lake, standardized system data is obtained to eliminate noise, missing values, and outliers, and improve the reliability of the data. Among them, the standardized system data refers to a data set obtained by uniformly standardizing the system data.

[0066] Optionally, as an embodiment of the present invention, the performing data standardization processing on the system data corresponding to the data lake to obtain standardized system data includes: identifying the data structure of the system data corresponding to the data lake; based on the data structure, identifying the data standard indicators of the system data; based on the data standard indicators, constructing a data standardization instruction for the system data; and through the data standardization instruction, performing data standardization processing on the system data to obtain the standardized system data.

[0067] Among them, the data structure refers to the structure of the system data, such as attributes like data format and data form. The data standard index refers to the goal of standardizing the system data, and the data standardization instruction refers to the instruction for data standard corresponding to the system data, such as format conversion and duplicate value deletion.

[0068] In the embodiment of the present invention, by dividing the standardized system data into system physical data and system driver data, the data can be carefully differentiated, thereby mining deeper data information and improving the reliability of the data. Among them, the system physical data refers to the data describing the system function structure, such as database data, code data, etc., and the system driver data refers to the data describing the system operation rules, such as operation parameters, control instructions, logs, etc.

[0069] Optionally, as an embodiment of the present invention, the division of the standardized system data into system physical data and system driver data can be achieved through a clustering function.

[0070] S2. Identify the data correlation coefficient of the system physical data. Based on the data correlation coefficient, analyze the function structure of the IT system, and through the function structure, construct the system physical model of the IT system.

[0071] In the embodiment of the present invention, identifying the data correlation coefficient of the system physical data can provide a data basis for later data function analysis. Among them, the data correlation coefficient refers to the degree of correlation between the system physical data.

[0072] Optionally, as an embodiment of the present invention, the identification of the data correlation coefficient of the system physical data includes: extracting the data features of the system physical data; standardizing the physical data features to obtain standardized features; based on the standardized features, calculating the feature covariance of the system physical data corresponding to the standardized features; and based on the feature covariance, calculating the data correlation coefficient of the system physical data.

[0073] Among them, the data features refer to the characteristic attributes of the system physical data, such as data function features, data space features, etc. The standardized features refer to the set of features obtained by first standardizing all the initial data features so that PCA is not affected by the dimension, making them have unit variance and zero mean. The feature covariance refers to an index describing the data correlation between the system physical data.

[0074] Optionally, as an alternative embodiment of the present invention, the calculation of the data correlation coefficient of the system physical data based on the feature covariance can be achieved through the Pearson correlation coefficient formula.

[0075] In the embodiment of the present invention, by analyzing the functional structure of the IT system based on the data correlation coefficient, the internal structure of the IT system can be better analyzed, thereby improving the reliability of model construction. Among them, the functional structure refers to the internal structure of the IT system, such as structures like databases and code libraries.

[0076] As an embodiment of the present invention, the analysis of the functional structure of the IT system based on the data correlation coefficient includes: dividing the system physical data corresponding to the IT system based on the data correlation coefficient to obtain a relevant data set; analyzing the system functional attributes of the relevant data set; and analyzing the functional structure of the IT system based on the system functional attributes.

[0077] Among them, the relevant data set refers to the data set obtained by classifying the data with high data correlation degree in the system physical data, and the system functional attributes refer to the functional attributes of the system described by the relevant data set, such as attributes like code structure and database address.

[0078] Furthermore, in the embodiment of the present invention, by means of the functional structure, constructing the system physical model of the IT system can obtain the model of the stable state and dynamic characteristics of the system under different initial conditions. Among them, the system physical model refers to the model that can describe the dynamic relationship of the internal structure of the IT system.

[0079] Optionally, as an embodiment of the present invention, the construction of the system physical model of the IT system by means of the functional structure includes: constructing the functional structure diagram of the IT system based on the functional structure; converting the functional structure diagram into a mathematical description to obtain the mathematical description of the system structure; constructing the system structure mathematical equation of the IT system based on the mathematical description of the system structure; and constructing the system physical model of the IT system through the system structure mathematical equation.

[0080] Among them, the functional structure diagram refers to the structure association diagram of different functional modules of the IT system. The system structure diagram usually includes nodes and edges. Nodes represent each module in the system, and edges represent the interaction between modules. The mathematical description of the system structure refers to converting the functional structure diagram into a mathematical expression form, usually represented in the form of a matrix. The elements in the matrix represent the interaction intensity or dependence relationship between modules. The system structure mathematical equation refers to the equation that describes the dynamic relationship of the internal structure of the IT system.

[0081] Optionally, as an alternative embodiment of the present invention, constructing the system structure mathematical equation of the IT system based on the mathematical description system structure includes: identifying the structure variable values of the mathematical description system structure; and constructing the system structure mathematical equation of the IT system by using the following formula based on the structure variable values:

[0082] dx / dt = f(t, x(t), x'(t), …, x^{(n)}(t))

[0083] wherein, dx / dt represents the system structure mathematical equation of the IT system, x(t) represents the structure variable value of the x-th mathematical description system structure at time t, x'(t) represents the instantaneous change rate of the x-th mathematical description system structure at time t, and f(t, x(t), x'(t), …, x^{(n)}(t)) is a function related to the structure variable values of the x-th mathematical description system structure and the structure variable values of other mathematical description system structures at time t.

[0084] The structure variable values refer to the values of different structures in the mathematical description system structure at different times, such as system network speed, system cache, etc.

[0085] Optionally, as an alternative embodiment of the present invention, constructing the system physical model of the IT system through the system structure mathematical equation can be implemented by simulation tools (such as MATLAB and SIMULINK).

[0086] S3. Extract the system drive characteristics of the system drive data, analyze the system drive law of the IT system based on the system drive characteristics, and construct the system drive model of the IT system based on the system drive law and the system drive data.

[0087] In the embodiment of the present invention, the behavior characteristics of the IT system are analyzed by extracting the system drive characteristics of the system drive data, thereby providing a data basis for later system drive simulation. The system drive characteristics refer to the drive characteristic attributes of the system drive data, such as interface protocol, function call relationship, etc. The system drive characteristics can be extracted by statistically analyzing the system drive data.

[0088] Furthermore, in the embodiment of the present invention, by analyzing the system drive law of the IT system based on the system drive characteristics, the drive relationship between the components of the IT system can be identified, thereby improving the accuracy of model establishment. The system drive law refers to the law of drive interaction between the components of the IT system.

[0089] Optionally, as an embodiment of the present invention, analyzing the system driving law of the IT system based on the system driving characteristics includes: identifying the system components of the IT system; marking the driving interaction relationships between the system components based on the system driving characteristics; and analyzing the system driving law of the IT system based on the driving interaction relationships.

[0090] Among them, the system components refer to all components of the IT system, such as components like hardware, software, network, and data storage. The driving interaction relationship refers to the dependency relationship between the system components.

[0091] Optionally, the system driving model of the IT system can be constructed based on the system driving law and the system driving data in the embodiment of the present invention. The system driving model can accurately simulate the operation path of the system, thereby improving the reliability of the system simulation data. Among them, the system driving model refers to a constructed model that enables the components of the IT system to interact with each other.

[0092] As an embodiment of the present invention, constructing the system driving model of the IT system based on the system driving law and the system driving data includes: constructing an initial component model of the IT system based on the system driving data; constructing interaction instructions for the system components corresponding to the initial component model based on the system driving law; and constructing the system driving model of the IT system based on the interaction instructions.

[0093] Among them, the initial component model refers to a constructed model component framework to represent the structure and behavior of the system. This framework should be able to capture the main components of the system. The interaction instructions refer to quantifying the interaction relationships between the components, such as relationships like performance impact, resource consumption, and response time.

[0094] S4. Fuse the system physical model and the system driving model to obtain a system twin model, calculate the fusion coefficient of the system twin model, and adjust the model parameters of the system twin model based on the fusion coefficient to obtain an adjusted system twin model.

[0095] In the embodiment of the present invention, a system twin model is obtained by fusing the system physical model and the system driving model. In order to create a comprehensive system twin model that can reflect the behavior and characteristics of the actual physical system, the accuracy of system health analysis is thereby improved. Among them, the system twin model refers to a virtual and digital copy that can simulate the performance of the real system and is used for design, analysis, optimization, and prediction. The fusion of the system physical model and the system driving model can be achieved through simulation platforms such as MATLAB / Simulink and Ptolemy II.

[0096] Furthermore, in the embodiments of the present invention, by calculating the fusion coefficient of the system twin model, it is possible to analyze whether the system twin model has the ability to simulate the operation of the system, thereby improving the accuracy of the operation data of the twin model. Among them, the fusion coefficient refers to the degree of fusion between the system physical model and the system drive model. The fusion coefficient can be achieved by identifying data conflicts in the system twin model. The more data conflicts, the lower the fusion coefficient.

[0097] Optionally, adjusting the model parameters of the system twin model based on the fusion coefficient to obtain an adjusted system twin model can improve the model performance of the system twin model, thereby improving the effect of system health analysis. Among them, the adjusted system twin model refers to the twin model whose model parameters are adjusted through the data conflicts.

[0098] S5. Simulate the operation of the IT system based on the adjusted system twin model to obtain operation data. Based on the operation data, calculate the risk coefficient of the IT system. Based on the risk coefficient, construct a health analysis report of the IT system.

[0099] In the embodiments of the present invention, the operation data refers to the data generated by simulating the operation of the IT system through the adjusted system twin model. For example, data such as log files, user activities, system performance indicators, transaction records, and network traffic information.

[0100] Furthermore, in the embodiments of the present invention, calculating the risk coefficient of the IT system based on the operation data can identify system anomalies by simulating system operation, thereby improving the accuracy of IT system health analysis. Among them, the risk coefficient refers to the degree of risk generated during the process of the model simulating the operation of the IT system.

[0101] Optionally, as an embodiment of the present invention, calculating the risk coefficient of the IT system based on the operation data includes: analyzing the operation characteristics of the IT system based on the operation data; identifying the abnormal operation behavior of the IT system based on the operation characteristics; and calculating the risk coefficient of the IT system by using the following formula based on the abnormal operation behavior:

[0102]

[0103] Among them, represents the risk coefficient of the IT system, J 2 Lu represents the system health identification function, S i represents the i-th abnormal operation behavior, R iIt represents the abnormal weight corresponding to the i-th abnormal operation behavior, θ represents the influence coefficient of the i-th abnormal operation behavior on other abnormal operation behaviors, and n represents the number of abnormal operation behaviors.

[0104] Among them, the operation characteristics refer to the behaviors, performances, and attributes of a system, device, or application program during actual operation, such as performance indicators, stability, availability, scalability, and other attributes. The abnormal operation behaviors refer to the abnormal operation behaviors during the operation of the IT system, such as slow response time, sluggish processing speed, and other behaviors.

[0105] Based on the risk coefficient, the embodiment of the present invention constructs a health analysis report of the IT system to achieve the health maintenance of the IT system. The health analysis report refers to an evaluation report on the health of the IT system, and the health analysis report includes the health values of each module of the IT system, the reasons for module operation abnormalities, abnormal maintenance plans, and other contents.

[0106] In the embodiment of the present invention, through data standardization processing of the system data corresponding to the data lake, standardized system data is obtained to eliminate noise, missing values, and outliers, improving the reliability of the data. By identifying the data correlation coefficient of the system physical data, the embodiment of the present invention can provide a data basis for subsequent data function analysis. By analyzing the functional structure of the IT system based on the data correlation coefficient, the embodiment of the present invention can better analyze the internal structure of the IT system, thereby improving the reliability of model construction. By extracting the system drive characteristics of the system drive data and analyzing the behavior characteristics of the IT system, the embodiment of the present invention provides a data basis for subsequent system drive simulation. Optionally, based on the system drive law and the system drive data, the embodiment of the present invention constructs a system drive model of the IT system, which can accurately simulate the operation path of the system through the system drive model, thereby improving the reliability of system simulation data. Finally, by fusing the system physical model and the system drive model, the embodiment of the present invention obtains a system twin model to create a comprehensive system twin model that can reflect the behaviors and characteristics of the actual physical system, thereby improving the accuracy of system health analysis. The embodiment of the present invention constructs a health analysis report of the IT system to achieve the health maintenance of the IT system. Therefore, the IT health analysis and evaluation method based on digital twin proposed by the present invention can improve the analysis effect of the health of the IT system.

[0107] As Figure 2 shown, it is a functional module diagram of an IT health analysis and evaluation system based on digital twin provided by an embodiment of the present invention.

[0108] The IT health analysis and evaluation system 200 based on digital twin according to the present invention can be installed in an electronic device. According to the functions achieved, the IT health analysis and evaluation system 200 based on digital twin can include a data processing module 201, a system physical model construction module 202, a system drive model construction module 203, a twin model fusion module 204, and a health analysis module 205. The modules in the present invention can also be referred to as units, which refer to a series of computer program segments that can be executed by the processor of an electronic device and can complete fixed functions, and are stored in the memory of the electronic device.

[0109] In this embodiment, the functions of each module / unit are as follows:

[0110] The data processing module 201 is used to collect the system data of the IT system, integrate the system data into the data lake, perform data standardization processing on the system data corresponding to the data lake to obtain standardized system data, and divide the standardized system data into system physical data and system drive data;

[0111] The system physical model construction module is used to identify the data correlation coefficient of the system physical data, analyze the functional structure of the IT system based on the data correlation coefficient 202, and construct the system physical model of the IT system through the functional structure;

[0112] The system drive model construction module 203 is used to extract the system drive characteristics of the system drive data, analyze the system drive law of the IT system based on the system drive characteristics, and construct the system drive model of the IT system based on the system drive law and the system drive data;

[0113] The twin model fusion module 204 is used to fuse the system physical model and the system drive model to obtain a system twin model, calculate the fusion coefficient of the system twin model, and adjust the model parameters of the system twin model based on the fusion coefficient to obtain an adjusted system twin model;

[0114] The health analysis module 205 is used to simulate the operation of the IT system based on the adjusted system twin model to obtain operation data, calculate the risk coefficient of the IT system based on the operation data, and construct a health analysis report of the IT system based on the risk coefficient.

[0115] Specifically, each module in the IT health analysis and evaluation system 200 based on digital twin in the embodiment of the present invention uses the same technical means as the IT health analysis and evaluation method based on digital twin described in the accompanying drawings when in use, and can produce the same technical effects, which will not be elaborated here.

[0116] An embodiment of the present invention provides an electronic device for implementing an IT health analysis and evaluation method based on digital twin.

[0117] See Figure 3 As shown, the electronic device may include a processor 30, a memory 31, a communication bus 32, and a communication interface 33. It may also include a computer program stored in the memory 31 and executable on the processor 30, such as an IT health analysis and evaluation method program based on digital twin.

[0118] Among them, in some embodiments, the processor may be composed of integrated circuits. For example, it may be composed of a single packaged integrated circuit, or may be composed of multiple integrated circuits with the same or different functions, including a combination of one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and various control chips. The processor is the control core (Control Unit) of the electronic device, connecting various components of the entire electronic device through various interfaces and lines, and by running or executing programs or modules stored in the memory (such as executing an IT health analysis and evaluation program based on digital twin, etc.), and calling data stored in the memory, to perform various functions of the electronic device and process data.

[0119] The memory includes at least one type of readable storage medium, which includes flash memory, mobile hard disks, multimedia cards, card-type memories (such as SD or DX memories, etc.), magnetic memories, magnetic disks, optical disks, etc. In some embodiments, the memory may be an internal storage unit of the electronic device, such as the mobile hard disk of the electronic device. In other embodiments, the memory may also be an external storage device of the electronic device, such as a plug-in mobile hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the electronic device. Further, the memory may also include both the internal storage unit and the external storage device of the electronic device. The memory can not only be used to store application software installed on the electronic device and various types of data, such as the code of an IT health analysis and evaluation program based on digital twin, etc., but also be used to temporarily store data that has been output or will be output.

[0120] The communication bus may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The bus can be divided into an address bus, a data bus, a control bus, etc. The bus is configured to enable connection communication between the memory, at least one processor, and the like.

[0121] The communication interface is used for communication between the above-mentioned electronic device and other devices, including a network interface and a user interface. Optionally, the network interface may include a wired interface and / or a wireless interface (such as a WI-FI interface, a Bluetooth interface, etc.), and is generally used to establish a communication connection between the electronic device and other electronic devices. The user interface may be a display, an input unit (such as a keyboard), and optionally, the user interface may also be a standard wired interface or a wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch liquid crystal display, and an OLED (Organic Light-Emitting Diode) toucher, etc. Among them, the display may also be appropriately referred to as a display screen or a display unit, and is used to display the information processed in the electronic device and to display a visual user interface.

[0122] For example, although not shown, the electronic device may further include a power source (such as a battery) for powering each component. Preferably, the power source can be logically connected to the at least one processor through a power management system, so as to implement functions such as charge management, discharge management, and power consumption management through the power management system. The power source may further include any components such as one or more DC or AC power sources, a recharge system, a power failure detection circuit, a power converter or an inverter, and a power status indicator. The electronic device may further include various sensors, a Bluetooth module, a Wi-Fi module, etc., which will not be elaborated here.

[0123] It should be understood that the above embodiments are only for illustration purposes and are not limited by this structure in the scope of the patent application.

[0124] The IT health analysis and evaluation program based on digital twin stored in the memory of the electronic device is a combination of multiple instructions, and when running in the processor, it can implement:

[0125] Collect the system data of the IT system, integrate the system data into the data lake, perform data standardization processing on the system data corresponding to the data lake to obtain standardized system data, and divide the standardized system data into system physical data and system drive data;

[0126] Identify the data correlation coefficient of the system physical data of the system. Based on the data correlation coefficient, analyze the functional structure of the IT system, and through the functional structure, construct the system physical model of the IT system;

[0127] Extract the system driving characteristics of the system driving data of the system. Based on the system driving characteristics, analyze the system driving law of the IT system. Based on the system driving law and the system driving data, construct the system driving model of the IT system;

[0128] Fuse the system physical model and the system driving model to obtain a system twin model. Calculate the fusion coefficient of the system twin model, and based on the fusion coefficient, adjust the model parameters of the system twin model to obtain an adjusted system twin model;

[0129] Based on the adjusted system twin model, simulate the operation of the IT system to obtain operation data. Based on the operation data, calculate the risk coefficient of the IT system. Based on the risk coefficient, construct the health analysis report of the IT system.

[0130] Specifically, the specific implementation method of the above instructions by the processor can refer to the description of the relevant steps in the corresponding embodiments of the attached drawings, which will not be elaborated here.

[0131] Further, if the modules / units integrated in the electronic device are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. The computer-readable storage medium can be volatile or non-volatile. For example, the computer-readable medium can include: any entity or system that can carry the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disc, computer memory, read-only memory (ROM, Read-Only Memory).

[0132] The present invention also provides a computer-readable storage medium. The readable storage medium stores a computer program, and when the computer program is executed by a processor of an electronic device, it can implement:

[0133] Collect the system data of the IT system, integrate the system data into a data lake, perform data standardization processing on the system data corresponding to the data lake to obtain standardized system data, and divide the standardized system data into system physical data and system driving data;

[0134] Identify the data correlation coefficient of the system physical data, based on the data correlation coefficient, analyze the functional structure of the IT system, and through the functional structure, construct the system physical model of the IT system;

[0135] Extract the system driver features of the system driver data, analyze the system driver rules of the IT system based on the system driver features, and construct the system driver model of the IT system based on the system driver rules and the system driver data;

[0136] Fuse the system physical model and the system driver model to obtain a system twin model, calculate the fusion coefficient of the system twin model, and adjust the model parameters of the system twin model based on the fusion coefficient to obtain an adjusted system twin model;

[0137] Simulate the operation of the IT system based on the adjusted system twin model to obtain operation data, calculate the risk coefficient of the IT system based on the operation data, and construct a health analysis report of the IT system based on the risk coefficient.

[0138] In several embodiments provided by the present invention, it should be understood that the disclosed devices, systems, and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative. For example, the division of the modules is only a logical function division, and there may be other division methods in actual implementation.

[0139] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0140] In addition, in each embodiment of the present invention, the functional modules can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above integrated units can be implemented in the form of hardware or in the form of a combination of hardware and software functional modules.

[0141] For those skilled in the art, it is obvious that the present invention is not limited to the details of the above exemplary embodiments, and can be implemented in other specific forms without departing from the spirit or basic characteristics of the present invention.

[0142] Therefore, from any point of view, the embodiments should be regarded as exemplary and non-limiting. The scope of the present invention is defined by the appended claims rather than the above description. Therefore, all changes falling within the meaning and scope of the equivalent elements of the claims are intended to be included in the present invention. Any associated drawing marks in the claims should not be regarded as limiting the claimed rights.

[0143] The embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Among them, artificial intelligence (AI) is a theory, method, technology, and application system that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use the knowledge to obtain the best results.

[0144] In addition, it is obvious that the word "including" does not exclude other units or steps, and the singular does not exclude the plural. The multiple units or systems stated in the system claims can also be implemented by one unit or system through software or hardware. The terms such as first and second are used to denote names and do not represent any particular order.

[0145] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. An IT health analysis and evaluation method based on digital twin, characterized in that, The method includes: Collecting system data of the IT system, integrating the system data into a data lake, performing data standardization processing on the system data corresponding to the data lake to obtain standardized system data, and dividing the standardized system data into system physical data and system driver data; Identifying the data correlation coefficient of the system physical data, analyzing the functional structure of the IT system based on the data correlation coefficient, and constructing the system physical model of the IT system through the functional structure; Extracting the system driver features of the system driver data, analyzing the system driver rules of the IT system based on the system driver features, and constructing the system driver model of the IT system based on the system driver rules and the system driver data; Fusing the system physical model and the system driver model to obtain a system twin model, calculating the fusion coefficient of the system twin model, and adjusting the model parameters of the system twin model based on the fusion coefficient to obtain an adjusted system twin model; Simulating the operation of the IT system based on the adjusted system twin model to obtain operation data, calculating the risk coefficient of the IT system based on the operation data, and constructing a health analysis report of the IT system based on the risk coefficient.

2. The IT health analysis and evaluation method based on digital twin according to claim 1, wherein The performing data standardization processing on the system data corresponding to the data lake to obtain standardized system data includes: Identifying the data structure of the system data corresponding to the data lake; Identifying the data standard metrics of the system data based on the data structure; Constructing a data standardization instruction for the system data based on the data standard metrics; Performing data standardization processing on the system data through the data standardization instruction to obtain the standardized system data.

3. The IT health analysis and evaluation method based on digital twin according to claim 1, characterized in that, The identifying the data correlation coefficient of the system physical data includes: Extracting the data features of the system physical data; Standardizing the physical data features to obtain standardized features; Calculating the feature covariance of the standardized features corresponding to the system physical data based on the standardized features; Calculating the data correlation coefficient of the system physical data based on the feature covariance.

4. The IT health analysis and evaluation method based on digital twin according to claim 1, wherein The analyzing the functional structure of the IT system based on the data correlation coefficient includes: Dividing the system physical data corresponding to the IT system based on the data correlation coefficient to obtain relevant data sets; Analyzing the system function attributes of the relevant data sets; Analyzing the functional structure of the IT system based on the system function attributes.

5. The IT health analysis and evaluation method based on digital twin according to claim 1, characterized in that The constructing the system physical model of the IT system through the functional structure includes: Constructing a functional structure diagram of the IT system based on the functional structure; Converting the functional structure diagram into a mathematical description to obtain a mathematical description system structure; Constructing a system structure mathematical equation of the IT system based on the mathematical description system structure; Constructing the system physical model of the IT system through the system structure mathematical equation.

6. The IT health analysis and evaluation method based on digital twin according to claim 5, wherein The constructing the system structure mathematical equation of the IT system based on the mathematical description system structure includes: Identifying the structure variable values of the mathematical description system structure; Based on the structural variable values, construct the system structure mathematical equation of the IT system using the following formula: dx / dt = f(t, x(t), x'(t), …, x^{(n)}(t)) where dx / dt represents the system structure mathematical equation of the IT system, x(t) represents the structural variable value of the x-th mathematical description of the system structure at time t, x'(t) represents the instantaneous change rate of the x-th mathematical description of the system structure at time t, and f(t, x(t), x'(t), …, x^{(n)}(t)) is a function related to the structural variable values of the x-th mathematical description of the system structure and the corresponding structural variable values of other mathematical descriptions of the system structure at time t.

7. The IT health analysis and evaluation method based on digital twin according to claim 1, wherein, Based on the system driving characteristics, analyze the system driving law of the IT system, including: Identify the system components of the IT system; Based on the system driving characteristics, mark the driving interaction relationships between the system components; Based on the driving interaction relationships, analyze the system driving law of the IT system.

8. The IT health analysis and evaluation method based on digital twin according to claim 1, wherein Based on the system driving law and the system driving data, construct the system driving model of the IT system, including: Based on the system driving data, construct the initial component model of the IT system; Based on the system driving law, construct the interaction instructions for the system components corresponding to the initial component model; Based on the interaction instructions, construct the system driving model of the IT system.

9. The IT health analysis and evaluation method based on digital twin according to claim 1, wherein Based on the operation data, calculate the risk coefficient of the IT system, including: Based on the operation data, analyze the operation characteristics of the IT system; Based on the operation characteristics, identify the abnormal operation behaviors of the IT system; Based on the abnormal operation behaviors, calculate the risk coefficient of the IT system using the following formula: Among them, represents the risk coefficient of the IT system, H 2 Lu represents the system health identification function, S i represents the i-th abnormal operation behavior, R i represents the abnormal weight corresponding to the i-th abnormal operation behavior, θ represents the influence coefficient of the i-th abnormal operation behavior on other abnormal operation behaviors, and n represents the number of abnormal operation behaviors.

10. An IT health analysis and evaluation system based on digital twin, characterized in that, A system for performing the digital twin-based IT health analysis and evaluation method according to any one of claims 1-9, the system comprising: A data processing module for collecting the system data of the IT system, integrating the system data into a data lake, performing data standardization processing on the system data corresponding to the data lake to obtain standardized system data, and dividing the standardized system data into system physical data and system driving data; A system physical model construction module for identifying the data correlation coefficient of the system physical data, analyzing the functional structure of the IT system based on the data correlation coefficient, and constructing the system physical model of the IT system through the functional structure; A system driving model construction module for extracting the system driving characteristics of the system driving data, analyzing the system driving law of the IT system based on the system driving characteristics, and constructing the system driving model of the IT system based on the system driving law and the system driving data; A twin model fusion module for fusing the system physical model and the system driving model to obtain a system twin model, calculating the fusion coefficient of the system twin model, and adjusting the model parameters of the system twin model based on the fusion coefficient to obtain an adjusted system twin model; A health analysis module, which is used to simulate the operation of the IT system based on the adjusted system twin model to obtain operation data, calculate the risk coefficient of the IT system based on the operation data, and construct a health analysis report of the IT system based on the risk coefficient.

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