Online simulation experiment system and method

Abstract

The present invention provides an online simulation experiment system and method. The system includes: an experiment design subsystem, including an experiment management module for managing simulation experiment projects created by simulation experimenters; an experiment design module for batch-assigning values ​​to each parameter variable in a simulation scenario selected by the simulation experimenter based on simulation experiment requirements, generating multiple experimental samples; and obtaining simulation parameters; an experiment operation control subsystem, including an experiment establishment module for allocating simulation nodes to each experimental sample; for each simulation node, deploying experimental resources according to the corresponding experimental sample; and an experiment operation module for reading simulation parameters after receiving an experiment operation command, running the simulation experiment according to the experimental resources deployed on each simulation node, and obtaining simulation experiment data. The present invention can realize online simulation real-time experiments.

Description

Technical Field

[0001] The present invention relates to the technical field of computer simulation, and in particular to an online simulation experiment system and method. Background Art

[0002] Whether verifying simulation models or optimizing combat tactics, both require simulation and deduction, and require a large number of simulation experiments for deduction and verification. Executing simulation experiments requires setting up the experimental environment, deploying resources such as experimental scripts, managing and controlling the experiments, collecting experimental data for analysis, and restoring the experimental environment. Therefore, how to efficiently and conveniently conduct simulation experiments to complete simulation model verification and combat tactic optimization has become a challenge that needs to be addressed. Summary of the Invention

[0003] The embodiment of the present invention proposes an online simulation experiment system for realizing online simulation real-time experiments to meet the needs of using online real-time experiments to perform model verification and strategy optimization. The system includes: an experiment design subsystem and an experiment operation control subsystem, wherein:

[0004] Experimental design subsystem, including:

[0005] The experiment management module is used to obtain simulation experiment projects created by simulation experiment personnel, wherein the simulation experiment projects are created by simulation experiment personnel based on simulation experiment requirements;

[0006] The experimental design module is used to batch assign values ​​to each parameter variable in the simulation scenario selected by the simulation experimenter based on the simulation experiment requirements, generate multiple experimental samples, and obtain the simulation parameters set by the simulation experimenter for multiple experimental samples;

[0007] Experimental operation control subsystem, including:

[0008] Experiment preparation module, used to obtain multiple experimental samples and simulation parameters of simulation experiment projects;

[0009] The experiment opening module is used to allocate simulation nodes to each experimental sample; for each simulation node, experimental resources are deployed according to the corresponding experimental sample;

[0010] The experiment running module is used to read the simulation parameters after receiving the experiment running command, run the simulation experiment according to the experimental resources deployed on each simulation node, and obtain simulation experiment data.

[0011] The embodiment of the present invention provides an online simulation experiment method for implementing online simulation real-time experiments to meet the needs of using online real-time experiments for model verification and strategy optimization, including:

[0012] Acquire a simulation experiment project created by a simulation experimenter, wherein the simulation experiment project is created by the simulation experimenter based on simulation experiment requirements;

[0013] Based on the simulation experiment requirements, batch assign values ​​to each parameter variable in the simulation scenario selected by the simulation experimenter to generate multiple experimental samples;

[0014] Obtain simulation parameters set by simulation experimenters for multiple experimental samples;

[0015] Assign simulation nodes to each experimental sample;

[0016] For each simulation node, deploy experimental resources according to the corresponding experimental samples;

[0017] After receiving the experiment running command, the simulation parameters are read, and the simulation experiment is run according to the experimental resources deployed on each simulation node to obtain simulation experiment data.

[0018] An embodiment of the present invention further provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned online simulation experiment method when executing the computer program.

[0019] An embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned online simulation experiment method is implemented.

[0020] An embodiment of the present invention further provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the online simulation experiment method is implemented.

[0021] In an embodiment of the present invention, an experiment design subsystem includes: an experiment management module for obtaining a simulation experiment project created by a simulation experimenter, wherein the simulation experiment project is created by the simulation experimenter based on the simulation experiment requirements; an experiment design module for batch-assigning values ​​to each parameter variable in the simulation scenario selected by the simulation experimenter based on the simulation experiment requirements to generate multiple experimental samples; obtaining simulation parameters set by the simulation experimenter for multiple experimental samples; an experiment operation control subsystem including: an experiment preparation module for obtaining multiple experimental samples and simulation parameters of the simulation experiment project; an experiment opening module for allocating simulation nodes to each experimental sample; for each simulation node, deploying experimental resources according to the corresponding experimental sample; and an experiment operation module for reading simulation parameters after receiving an experiment operation command, running the simulation experiment according to the experimental resources deployed on each simulation node, and obtaining simulation experiment data. Based on the simulation experiment requirements, batch-assigning values ​​to each parameter variable in the simulation scenario selected by the simulation experimenter to generate multiple experimental samples realizes batch generation of experimental samples, and then deploying and executing experiments based on the batch experimental samples, and finally obtaining simulation experiment data, thereby realizing online simulation real-time experiments, which can meet the needs of using online real-time experiments for model verification and strategy optimization. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for the embodiments or the description of the prior art. 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 work. In the drawings:

[0023] Figure 1 A schematic diagram of an online simulation experiment system according to an embodiment of the present invention;

[0024] Figure 2 Schematic diagram of an online simulation experiment scheme operating environment based on simulation scenarios in an embodiment of the present invention;

[0025] Figure 3 The architecture of the online simulation experiment system in the embodiment of the present invention;

[0026] Figure 4 A schematic diagram of the integrated management principle of a shared simulation platform according to an embodiment of the present invention;

[0027] Figure 5 Schematic diagram of a node registration state machine in an embodiment of the present invention;

[0028] Figure 6 This is a flow chart of simulation node registration based on a management and control operation agent in an embodiment of the present invention;

[0029] Figure 7 A schematic diagram of the experimental environment in accordance with an embodiment of the present invention;

[0030] Figure 8 A schematic diagram of an experimental resource deployment management state machine in an embodiment of the present invention;

[0031] Figure 9 This is a flow chart of experimental resource deployment based on the experiment management and control agent in an embodiment of the present invention;

[0032] Figure 10 Schematic diagram of experimental environment status monitoring in an embodiment of the present invention;

[0033] Figure 11 This is a flow chart of monitoring the experimental environment status based on the experimental running agent in an embodiment of the present invention;

[0034] Figure 12 This is a flow chart of cleaning up the experimental environment based on the experiment management and control agent in an embodiment of the present invention;

[0035] Figure 13 This is a monitoring principle diagram of the experimental operation module in an embodiment of the present invention;

[0036] Figure 14 This is the process of performing time synchronization of experimental nodes based on the experiment management and control agent in an embodiment of the present invention;

[0037] Figure 15 Flowchart of the online simulation experiment method in an embodiment of the present invention. DETAILED DESCRIPTION

[0038] To make the purpose, technical solutions and advantages of the embodiments of the present invention more clear, the embodiments of the present invention are further described in detail below with reference to the accompanying drawings. Here, the exemplary embodiments of the present invention and their descriptions are used to explain the present invention, but are not intended to limit the present invention.

[0039] In the description of this specification, the terms "include", "including", "have", "contain", etc. are all open terms, which mean including but not limited to. The descriptions with reference to the terms "one embodiment", "a specific embodiment", "some embodiments", "for example", etc. mean that the specific features, structures or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures or characteristics described can be combined in a suitable manner in any one or more embodiments or examples. The order of steps involved in each embodiment is used to schematically illustrate the implementation of the present application, and the order of steps therein is not limited and can be appropriately adjusted as needed.

[0040] First, the terms involved in the embodiments of the present invention are explained.

[0041] Simulation scenario: It can be understood as a simulation running script, in which the simulated entities, deployment locations, behavioral actions, interaction relationships and execution tasks are defined, and the simulation deduction process is executed as the input of the simulation system.

[0042] Online experiments: Experimenters can complete experimental design, experimental environment construction, experimental resource deployment, experimental operation management and control, data collection and other tasks online through the web page, reducing experimental workload and improving simulation experiment efficiency.

[0043] Model verification: Test and verify the functions and performance of the simulation model to confirm whether the simulation model can truly and accurately reflect the characteristics of the actual system and ensure the correctness and usability of the simulation model.

[0044] Tactics optimization: mainly for simulation experiment personnel, through simulation experiments, to verify the advantages and disadvantages of different tactics.

[0045] The inventors believe that in order to solve the problems of simulation systems in applications such as model verification or tactical optimization, it is necessary to build a large number of simulation scenarios and execute and analyze experimental data, but it is impossible to meet the problems of rapid construction of scenarios and efficient conduct of simulation experiments.

[0046] The embodiment of the present invention solves the problem of difficulty in constructing a large number of scenarios by parameterizing simulation scenarios and generating executable experimental samples in batches; based on a virtual machine, it can solve the problem of simulation experiment environment; using middleware that integrates communication mechanisms such as remote procedure call, subscription publishing, and file transfer as a communication bus, it can solve problems such as remote deployment of simulation experiment resource files, collection and transmission of status data, and sending of process control command data.

[0047] Figure 1 This is a schematic diagram of an online simulation experiment system according to an embodiment of the present invention, comprising:

[0048] Experiment design subsystem 10 and experiment operation control subsystem 20, wherein,

[0049] The experimental design subsystem 10 includes:

[0050] The experiment management module 101 is used to obtain simulation experiment projects created by simulation experiment personnel, wherein the simulation experiment projects are created by simulation experiment personnel based on simulation experiment requirements;

[0051] The experiment design module 102 is used to batch assign values ​​to each parameter variable in the simulation scenario selected by the simulation experimenter based on the simulation experiment requirements, generate multiple experimental samples, and obtain the simulation parameters set by the simulation experimenter for the multiple experimental samples;

[0052] The experimental operation control subsystem 20 includes:

[0053] The experiment preparation module 201 is used to obtain multiple experimental samples and simulation parameters of the simulation experiment project;

[0054] The experiment setting module 202 is used to allocate simulation nodes to each experimental sample; for each simulation node, deploy experimental resources according to the corresponding experimental sample;

[0055] The experiment running module 203 is used to read simulation parameters after receiving the experiment running command, run the simulation experiment according to the experimental resources deployed on each simulation node, and obtain simulation experiment data.

[0056] Figure 2 Schematic diagram of the operating environment of an online simulation experiment scheme based on simulation assumptions in an embodiment of the present invention. Figure 2 The server is located in a cloud computing environment. The experiment design subsystem consists of a client and a server. The client provides an interface for simulation experimenters to create simulation experiment projects. This interface allows them to enter basic parameters, including the project name and requirement description, which includes the required number of experimental samples. The client also provides an interface for simulation experimenters to select simulation scenarios from a list of simulation scenarios, while the server batch generates multiple experimental samples. The client also retrieves simulation parameters set by the experimenter for multiple experimental samples. Simulation parameters can be set in batches, for example, the execution time can be set for all experimental samples, eliminating the need to set them one by one. The server stores the simulation parameters in a database. After the experiment design is completed, multiple experimental samples and simulation parameters are retrieved from the database, and the experiment operation control subsystem then executes the simulation. The experiment operation control subsystem can also be divided into a client and a server. The client and the client of the experiment operation control subsystem can be combined into a unified client, while the server and the server of the experiment operation control subsystem can be combined into a unified server.

[0057] based on Figure 2 The embodiment of the present invention provides an architecture of an online simulation experiment system. Figure 3The architecture of the online simulation experiment system in the embodiment of the present invention adopts the service-oriented concept, comprehensively utilizes the "cloud + terminal" architecture and "platform + plug-in" technology, and is guided by the unified simulation training model and computing center system architecture and standard specifications. With the support of computing resources, storage resources, network security resources, experimental cloud platform and other infrastructure, the client display is separated from the server logic, and the service or application plug-in form of the server is used to abstract the business logic and encapsulate the service. Through various client display methods such as web pages and executable program interfaces, a consistent, convenient and friendly operation interface is provided for simulation experiment personnel. The architecture of the online simulation experiment system is divided into three levels: infrastructure layer, service layer and application layer.

[0058] The infrastructure layer consists of hardware devices and an experimental cloud platform. Hardware devices, including computing resources, storage resources, and network security resources, provide the foundational hardware facilities for conducting experimental tasks. The experimental cloud platform is provided by a cloud computing environment. Based on bare metal hardware devices, it uses virtualization technology to build a heterogeneous cloud environment that can allocate and elastically allocate basic resources for experimental tasks in complex scenarios on demand, providing an operating environment for cloud services.

[0059] The service layer consists of a service integration framework, basic services, and functional services. The service integration framework has the capabilities of service support and integrated development, providing unified cloud service access specifications and an integrated operating environment. Basic services include basic operating services, model management services, and data management services, providing basic support capabilities for the implementation of model online experiments, used to manage and control various simulation models and simulation engines, and providing unified data and product management functions for various applications. The online simulation experiment system can view and retrieve models by calling services. Functional services are oriented towards specific experimental applications and provide professional online experimental functions, including experimental design management services and experimental operation control services. Based on the visual modeling and display platform (client), the experimental design management service provides services such as simulation experiment project management, simulation scenario management, and experimental sample management. The experimental operation control service provides services such as experimental environment establishment, experimental process control, experimental resource recovery, experimental environment monitoring, experimental status monitoring, experimental result display, and experimental resource deployment, providing support for the implementation of full-process and full-factor simulation training experiments.

[0060] The application layer is directly oriented towards simulation experimenters and consists of an application integration framework and various applications. The application integration framework provides a unified integration environment for various applications in the form of a framework, including an application plug-in integration interface, a web page integration interface, a unified authentication and authority management interface, a data access interface, and an information interaction interface. Applications are divided into experimental design subsystem applications and experimental operation control subsystem applications according to their functional positioning. The experimental design subsystem application has functions such as simulation experiment project creation, simulation scenario editing, experimental sample management, simulation parameter configuration, and report generation. The experimental operation control subsystem application has functions such as node management, environment establishment, experiment management and control, experiment monitoring, indicator display, and environment withdrawal. Applications can have different forms and be displayed in the form of clients, including web pages, executable program interfaces, etc. Applications complete corresponding experimental business by calling relevant services of the service layer and present the results to simulation experimenters in different display methods, realizing human-computer interaction with simulation experimenters.

[0061] The following is an introduction to the experimental design subsystem and the experimental operation control subsystem.

[0062] The experimental design subsystem includes the experimental management module, the experimental design module and the experimental display module.

[0063] Experiment management module functions:

[0064] First, the experiment design subsystem can integrate multiple shared simulation platforms, providing registration, information editing, and retrieval capabilities for these platforms. The experiment management module can integrate and connect the various shared simulation platforms required for simulation experiments through configuration forms. The shared simulation platform primarily manages and integrates various simulation engines, providing a simulation engine registration interface. Each simulation engine registers its information with the experiment design subsystem by calling the registration interface. This information includes the name, version, and description. The experiment design subsystem provides information editing and retrieval capabilities for the simulation engines, providing unified management of these engines.

[0065] During the integrated management process of the shared simulation platform, first, the shared simulation platform opens the registration interface and waits for the registration of the simulation engine; each simulation engine registers its name, version, operating environment requirements and other information to the shared simulation platform through the registration interface of the shared simulation platform, and the shared simulation platform manages the registered information in a unified manner; simulation experimenters perform information retrieval, information editing and other operations on the registered simulation engines, and integrate and configure the simulation engines according to the simulation experiment requirements to provide support for conducting experiments.

[0066] The experiment management module can view and edit the registration information of the simulation engine, provide a visual configuration interface for the simulation engine, form the configuration of the simulation engine for different simulation experiments, and provide support for the environment establishment and experiment operation of the online experiment. Figure 4 Schematic diagram of the integrated management of a shared simulation platform in an embodiment of the present invention. Therefore, in one embodiment, the experiment management module is also used to:

[0067] An integrated shared simulation platform, wherein the shared simulation platform is used to provide a registration interface for the simulation engine and manage the registered simulation engines;

[0068] Call the shared simulation platform interface to view and edit the registration information of the simulation engine.

[0069] Second, simulation experimenters create simulation experiment projects in the experiment management module. These projects are centrally managed as a directory, providing functions such as editing basic information, browsing, and deleting data. The experiment management module supports collaborative management of simulation experiment projects by multiple simulation experimenters. In one embodiment, the experiment management module is further configured to collaboratively process operation instructions for simulation experiment projects received from multiple simulation experimenters.

[0070] Specifically, it supports multiple people to collaborate in simulation experiment project management through asynchronous login; it provides directory browsing and retrieval functions, and can monitor and manage various types of information such as the number of simulation experiment project management, the number of simulation experiment projects to be run, the progress of simulation experiment projects that have been run, and failures in running simulation experiment projects in a tabular and graphical manner, making it convenient for simulation experiment personnel to grasp the actual situation of running simulation experiment projects and make real-time adjustments according to different situations.

[0071] Specifically, the experiment management module creates simulation experiment projects in a wizard-like manner, including basic information such as name, purpose, and requirement description. At the same time, it can view the simulation models in the model resource library and set the required simulation models. In order to achieve the simulation experiment project, different simulation experiment personnel are sometimes required to design it. The experiment management module can support multiple people to collaborate online to improve efficiency. After the simulation experiment project is created, it can be browsed and viewed in the form of a directory, and specific simulation experiment projects can be searched and other operations can be performed. Incorrect simulation experiment projects can be deleted.

[0072] Third, the experiment management module manages experimental samples. It provides a directory-based structure for unified management of experimental samples, categorizes different types of experimental samples, and displays experimental samples in a table format for easy query and management. Basic information about experimental samples can be edited, and both single-query search and combined search capabilities for multiple query conditions enable rapid sample discovery. Individual and batch deletion of experimental samples ensures accuracy and effectiveness. The experiment management module provides comprehensive management of experimental samples through services, including data directory services, data access services, and data retrieval services.

[0073] Experimental design module functions:

[0074] First, the experimental design module integrates and loads a simulation scenario editing tool in the form of a plug-in, and can edit simulation scenarios based on the simulation scenario editing tool; therefore, in one embodiment, the experimental design module is further used to:

[0075] Integrate and load simulation scenario editing tools in the form of plug-ins;

[0076] The simulation scenario created by the simulation experimenter in the simulation scenario editing tool is received.

[0077] Then, based on the simulation experiment requirements, each parameter variable in the simulation scenario selected by the simulation experimenter is assigned a value in batches, generating multiple experimental samples. This allows the experimental sample design to be completed semi-automatically based on the wizard. The simulation scenario serves as a template, and after batch assignment of parameter variables, experimental samples are quickly generated.

[0078] Running simulation experiments requires obtaining experimental samples. For example, during model calibration, the model must be run on a large number of different experimental samples to verify its correctness. Simulation experiment design requires considerable time to construct experimental samples. If experimental samples could be generated in batches according to simulation experiment requirements, the efficiency of the simulation would be greatly improved. Therefore, in an embodiment of the present invention, information such as combat entities, behavioral actions, tasks, and routes in the simulation scenario is parameterized to generate a large number of experimental samples.

[0079] When generating a specific experimental sample, the parameter variables in the simulation scenario are replaced by the parameter variable values ​​of the specific model resource library. By combining the values ​​of different parameter variables, an experimental sample can be quickly generated to complete the design of the simulation experiment.

[0080] In one embodiment, the experimental design module is specifically used to:

[0081] Based on the model resource library, batch assignments are made to each parameter variable in the simulation scenario selected by the simulation experimenter. The model resource library includes a combat entity library, a behavior action library, a task library and a route library.

[0082] Simulation assumptions are a technology that structures and formalizes expressions in a way that can be understood and used by simulation experimenters and recognized and used by simulation systems. Its purpose is to enable simulation experimenters to obtain batch experimental samples efficiently and quickly based on simulation assumptions, and drive simulation nodes to perform automatic simulation according to the simulation.

[0083] There are multiple parameter variables in simulation scenarios. Table 1 gives an example of parameter variables for a combat simulation scenario.

[0084] Table 1

[0085]

[0086] When editing the experimental sample, you can select different parameter variables and then set the value range for the parameter variables. For example, set the entity as variable E, the combat mission as variable T, the action route as variable L, and the attack method as variable W; then, according to the simulation experiment requirements, set the value range of the parameter variables as follows:

[0087] E = {e1, e2, e3, ...}, supports single values ​​or subsets. The deployment position of entities can be set to random within the area or according to a certain formation;

[0088] L = {l1, l2, l3, ...}, selected from the route library, supports single value;

[0089] T = {t1, t2, t3, ...}, supports a value in the set;

[0090] W={w1,w2,w3,……}, supports setting.

[0091] Assuming that there are 5 possible values ​​for E, 3 for L, 2 for T, and 3 for W, then by combining the values ​​of the variables, 5×3×2×3=90 experimental samples can be generated.

[0092] After generating experimental samples based on simulation scenarios, the experimental design module provides executable scenario editing and management capabilities. This supports graphical scenario editing based on a GIS platform and military designations, allowing simulation experimenters to edit, view, and save simulation scenarios. Simulation scenario parameters and variables can be modified based on the specific experimental context, refining the scenario content to meet the current experimental needs. A wizard-based design approach based on the simulation scenario ensures the orderly conduct of the experiment. Furthermore, experimental samples can be obtained by importing them in a specified format. Table 2 provides examples of how to modify experimental samples after importing them. Different simulation samples can be generated through at least five simulation experiment design strategies, including changing entity type, number of entities, operational plan, entity or troop tactics, and operational environment parameters. This provides support for model verification during online experiments.

[0093] Table 2

[0094]

[0095] Second, the experimental design module can obtain the simulation parameters set by the simulation experimenter for multiple experimental samples. Specifically, the experimental design module assists the simulation experimenter in setting the simulation parameters in a visual manner. The simulation parameters include at least the simulation engine used in this simulation experiment project, the execution time and number of executions of the experimental sample in each experimental sample. The above simulation parameters can be stored in the database for reading and use by the experimental operation control subsystem. Among them, the experimental sample execution time refers to the time when each experimental sample starts execution, and the number of executions refers to the total number of executions. In addition, the operation configuration and startup sequence of the simulation model can be designed.

[0096] The aforementioned experiment management module integrates multiple shared simulation platforms. These platforms create a logical topology for the simulation engine. Furthermore, they can design simulation parameters for the simulation resources in the model resource library required for the experiment, allowing for subsequent modification and use during the experiment. During experiment design, a metamodel is used to describe the characteristics and relationships of node resources, software resources, and link resources in the experimental environment, thereby analyzing and determining the information that can be configured in the simulation resource configuration.

[0097] In one embodiment, the experiment design subsystem further includes an experiment display module.

[0098] Experimental demonstration module functions:

[0099] The Experimental Display Module primarily manages and displays model resources. It manages model resources in the model resource library in a directory format, supporting directory browsing, data viewing, and retrieval. It provides single-condition retrieval and multi-condition combined retrieval capabilities, making it easy for simulation experimenters to quickly and accurately find the appropriate model resources and providing a visual display of model resources.

[0100] There are a large number of model resources in the model resource library. How to quickly and accurately find the required model resources is a problem that needs to be solved by the unified management and display of model resources. By obtaining model resources from the model resource library and displaying them in tabular and visual forms, simulation experimenters can browse them conveniently. When simulation experimenters need a specific model resource, they can perform single-condition retrieval and multi-condition joint retrieval, and visualize the retrieval results, which makes it convenient for simulation experimenters to find and use model resources.

[0101] The experimental operation control subsystem includes the experimental preparation module, the experimental opening module, the experimental operation module, and the management and control support module.

[0102] Experiment preparation module functions:

[0103] First, simulation node information registration and maintenance. Simulation node information registration and maintenance provide functions such as simulation node information registration, node information viewing, and node information update, providing node information support for the conduct of experiments. During the experiment, node information can be obtained for resource deployment, status monitoring, etc.

[0104] First, the experiment management and control agent involved in the deployment of the simulation node automatically detects the configuration of the simulation node (including IP address, node configuration, deployed executable assumptions, etc.) after the simulation node is started, and registers the above information to the experiment preparation module of the experiment operation control subsystem based on the provided node registration service. After successful registration, the registration information in the node can be queried to provide support for the automated deployment of experimental resources. At the same time, the scheduled update setting is started to ensure the timeliness and reliability of the registration information.

[0105] The registration information of the node mainly includes the node identification, node type, basic configuration information of the node, IP address of the node, experimental resource information deployed by the node, experimental samples installed by the node, etc. The detailed information is shown in Table 3.

[0106] Table 3

[0107]

[0108]

[0109] In one embodiment, the simulation node is deployed with an experiment control agent, which runs when the simulation node is started, collects basic parameters of the simulation node, registers it with the experiment operation control subsystem, and stores the registration information in the experiment preparation module; the registration information of each node has a validity period; the simulation node sends updated registration information to the experiment preparation module according to preset conditions;

[0110] The experiment preparation module is specifically used to:

[0111] For each registered simulation node, deploy experimental resources according to the corresponding experimental samples;

[0112] After receiving the updated registration information, the validity period of the registration information is recalculated.

[0113] The validity period is designed to ensure the availability of the simulation node. A simulation node is only available if its registration information is valid within the validity period. Pre-set conditions include periodic updates or changes. The simulation node sends updated registration information to the experiment preparation module based on the preset conditions to ensure timely updates and maintain the validity of the simulation node's registration information. Figure 5 Schematic diagram of a node registration state machine in an embodiment of the present invention. Figure 6 This is a flowchart of simulation node registration based on the management and control operation agent in an embodiment of the present invention, and Figure 5 correspond. Figure 5 The status of the simulation node is mainly divided into three states: registering, registration completed, and registration failed. First, the simulation node obtains its registration information and registers with the central node. If the registration fails three times in a row, the node is considered unreachable and the registration fails. If the registration is successful, a timer is started and triggered at fixed intervals to send or update the registration information.

[0114] Second, multiple experimental samples and simulation parameters of the simulation experiment project are obtained, wherein the simulation parameters can be obtained by reading the database.

[0115] Experimental module functions:

[0116] First, the experimental environment is set up and a simulation node is allocated to each experimental sample. In one embodiment, the simulation node includes a physical machine, a virtual machine, and a container.

[0117] The experimental module is specifically used for:

[0118] When the simulation node is a virtual machine, obtain the current number of virtual machines;

[0119] When the number of experimental samples is greater than the current number of virtual machines and less than the currently set maximum number of parallel operations, a new virtual machine is opened.

[0120] In practice, when a new virtual machine is created, a cloud computing creation interface is called. A new virtual machine is created based on a virtual machine template. An experiment control agent is deployed within the virtual machine, running as the virtual machine starts up. It collects basic virtual machine parameters and registers them with the experiment operation control subsystem. Based on this registration information, the experiment operation control subsystem maintains the currently available virtual machine resources and, through the experiment control agent, manages and deploys these resources. Figure 7 This is a schematic diagram of the experimental environment in an embodiment of the present invention. The process includes:

[0121] ① The experiment operation control subsystem loads the experimental samples;

[0122] ② Virtual machine nodes are opened on demand or automatically, and physical nodes are started manually;

[0123] ③ Node information acquisition and registration, including virtual machine nodes and physical nodes;

[0124] ④The experimental operation control subsystem sends deployment instructions to the virtual machine node;

[0125] ⑤The virtual machine node downloads experimental resources from the model resource library;

[0126] ⑥Install experimental resources on virtual machine nodes, including simulation engines, various simulation models, and experimental sample analysis;

[0127] ⑦The virtual machine node reports the node opening status;

[0128] ⑧The experimental operation control subsystem monitors the operation status.

[0129] Second, remote automated deployment of experimental resources mainly provides functions such as experimental resource distribution and installation, script deployment, and status monitoring, providing support for the automated deployment of experiments. Simulation experiment personnel can uniformly manage the experimental environment through visual operations, thereby improving the efficiency of experimental environment setup.

[0130] After the node registration is completed, the experiment opening module of the experiment operation control subsystem automatically searches for the experimental resources corresponding to the simulation node, automatically disassembles the experimental samples, and completes the resource preparation; on this basis, the experimental resources are deployed to each simulation node, and then the experiment opening module sends deployment instructions to the listening service deployed on each simulation node. At the same time, an exclusive experimental space is divided for the simulation experiment project to ensure that the experimental process, status, data, etc. are relatively independent and do not affect each other.

[0131] In one embodiment, the experiment start module is specifically used to: for each simulation node, based on the corresponding experimental sample, download the corresponding experimental resources from the experimental resource library, the experimental resources including the simulation engine and the simulation model; and deploy the experimental resources through the experiment management agent.

[0132] That is, the deployment of experimental resources relies on the experimental control agent, which cooperates with the implementation of experimental resources, including the download of software, models, and simulation parameters. Figure 8 This is a schematic diagram of the experimental resource deployment management state machine in an embodiment of the present invention, which mainly includes four states: experimental resource download and installation, experimental sample deployment, deployment success, and deployment failure. First, after each simulation node receives the deployment instruction, it starts the experimental resource deployment management state machine to determine whether the node needs to install experimental resources, mainly referring to simulation models, or becoming simulation software. If installation is required, the corresponding experimental resources are downloaded and installed. After successful installation, the next step is entered. If the installation fails, a deployment failure (installation failure) message is sent; when the required experimental resources have been installed at the node, it is determined whether the experimental sample needs to be deployed. If so, the experimental sample deployment state management is entered, otherwise the deployment success state is directly entered; after the experimental sample is successfully deployed, a resource deployment success message is sent, otherwise a deployment failure (experimental sample failure) message is sent. If the simulation node does not need to deploy experimental resources and experimental samples, the experimental resource deployment success message is directly sent.

[0133] Figure 9 This is a flowchart of experimental resource deployment based on the experimental management and control agent in an embodiment of the present invention. Figure 8 Correspondingly, in the step of downloading and installing experimental resources, the experimental management and control agent is required to perform it. Specifically, the experiment opening module queries the node IP address from the registration server according to the bound simulation node information, and issues a resource download command to the experiment management and control agent of this node according to the IP address. After receiving the download command, the experiment management and control agent determines the installation directory of the experimental resources (mainly software) and downloads the experimental resources from the experimental resource library. During the download process, the download progress is reported to the experiment opening module. If the download fails, the download failure is reported to the experiment opening module; if the download is successful, the downloaded file is decompressed and the installation is reported to be complete, and the experimental resource deployment of this simulation node is completed.

[0134] After the experimental resources are deployed successfully and the participating simulation models complete the initialization work, the ready status is reported to the experiment opening module; the experiment opening module provides opening status management function. After receiving the ready status reported by all simulation nodes, it means that the experimental environment is opened successfully, and the experiment execution phase can be entered.

[0135] Third, environmental status monitoring and management. Simulation experimenters can monitor and manage the experimental environment status. The environmental status monitoring and management function provides auxiliary functions such as monitoring of simulation node registration information, experimental environment connectivity detection, and simulation node clock verification. At the same time, it can diagnose and locate a variety of basic faults, helping simulation experimenters to monitor the status of experimental resources during the experiment and realize health diagnosis of the experiment.

[0136] The environmental status monitoring and management function mainly helps simulation experiment personnel to timely grasp the experimental environment conditions and troubleshoot faults, monitor node registration information in a visual form, and provide alarm configuration for abnormal node information. It can automatically monitor node information. When there is abnormal node information, it can issue an alarm according to the alarm rules. Simulation experiment personnel diagnose the erroneous node based on the alarm information, use diagnostic tools to diagnose possible fault locations, and troubleshoot according to the fault information located by the diagnostic tools.

[0137] The monitoring and management of the experimental environment status depends on the experimental control agent. After the experimental control agent is started, it automatically updates the status information of the simulation node through subscription and publication in each diagnostic cycle. The monitoring service of the experimental operation control subsystem subscribes to this status information, summarizes and statistically analyzes all status information within a diagnostic cycle, and notifies and displays status information according to the set alarms and error conditions, assisting simulation experiment personnel in diagnosing the experimental status and locating experimental faults. Figure 10 This is a schematic diagram of the experimental environment status monitoring in an embodiment of the present invention. Figure 11 This is a flow chart of monitoring the experimental environment status based on the experimental running agent in an embodiment of the present invention.

[0138] Fourth, resource cleanup and environment recovery. In one embodiment, the experiment opening module is also used to: divide an experimental space for each simulation experiment project; allocate a simulation node to each experimental sample in the experimental space; and clear the experimental space through the experiment management agent after the simulation is completed.

[0139] Resource cleanup and environment recovery refer to resource cleanup and environment recovery after the experiment is completed. They can assist simulation experimenters in quickly deleting deployed useless resources and restoring nodes to their pre-experimental state to support subsequent experiments.

[0140] The cleanup of experimental resources and the recovery of the environment rely on experimental space technology. Different simulation experiment projects are assigned to different experimental spaces. On the one hand, it can achieve isolation between simulation experiment projects and avoid interference between multiple groups of parallel simulation experiment projects. On the other hand, it can achieve efficient management of experimental resources. After the experiment is over, you only need to clear the experimental space to complete the cleanup of experimental resources and the recovery of the environment. The experimental space is a physically independent storage unit, organized in the form of multi-level folders. Each simulation experiment project generates an experimental ID with a unique identifier. The experimental ID is used as the top-level directory of the experimental space. Then, according to the experimental resources, experimental samples, simulation parameter configuration and logs, the various resources of this simulation experiment project are organized and managed. This ensures that the experimental resources of different simulation experiment projects are isolated and independent from each other, and will not affect each other during execution, thereby producing erroneous results on the execution results. When the environment is cleaned up and withdrawn after the experiment, the entire experimental space directory is directly deleted to achieve the cleanup of experimental resources and the recovery of the environment.

[0141] Figure 12 This is a flowchart of the experimental environment cleanup based on the experimental management and control agent in an embodiment of the present invention. After the experiment is completed, the experiment opening module of the experimental operation control subsystem queries the address information of the node according to the node binding situation, and sends a data recovery instruction to the experimental management and control agent of the corresponding node. After receiving the instruction, the experimental management and control agent searches for the experimental data file in the corresponding data file directory and uploads it to the file server. After the upload is complete, the files in the current node experimental space are cleaned up and the results are reported to the experimental operation control subsystem. The experimental operation control subsystem downloads the experimental data files of each experimental node from the file server and summarizes the data.

[0142] Experiment running module functions:

[0143] First, experiment operation monitoring. The experiment operation module of the experiment operation control subsystem provides the experiment operation monitoring function. It performs statistical analysis on the status information reported by each simulation node and experimental resource. It can monitor the status of experimental resources, the process of simulation experiments, the progress of experiments and key events, and supports simulation experiment personnel to view the progress of experiment execution in the experiment visualization module.

[0144] Experimental operation monitoring is based on various status information reported by each simulation node and experimental resource. First, the status is classified, the status data of multiple cycles are counted and analyzed, and alarm judgments are made according to the alarm rules. The status statistics and alarm information are displayed in a visual manner.

[0145] The experimental operation status monitoring function mainly includes monitoring parameter setting, status monitoring, process monitoring, progress monitoring and event monitoring. Figure 13This is a monitoring principle diagram of the experimental operation module in the embodiment of the present invention. The monitoring parameter setting mainly configures the relevant parameter information of the monitoring object and the monitoring information; the process monitoring obtains the current entity information from the distributed simulation middleware to build a data flow view; the progress monitoring obtains the assumptions and entity operation status from the distributed simulation middleware to evaluate the current progress; the event monitoring mainly obtains event record information from the distributed simulation middleware. Among them, Figure 13 The entity in is a kind of simulation model.

[0146] The experiment run status monitoring function monitors the status of various experimental resources during the experiment, providing a means for experimental execution and analysis. The core view of the run status monitoring function uses JSON to encode inter-module call instructions. The experimental process uses a multi-view mode to categorize and display monitoring information. A data caching mechanism and a strategy of updating only changed data are used to handle large-scale real-time data updates. Monitoring results are presented using various methods, such as progress bars, tables, pie charts, and text, enabling diversified monitoring of experimental processes, progress, and events.

[0147] Second, the experimental result viewing and report generation function can support simulation experiment personnel to display and view experimental results in visual ways such as line charts, bar charts, pie charts, radar charts, scatter plots, tables, etc. by configuring the experimental result display scheme based on the experimental database. It provides an experimental report template, can associate the experimental results with the experimental report, and generate an experimental report for summary and review.

[0148] Experimental result report generation includes functions such as experimental report template management, experimental report editing, experimental report export and experimental report management. It supports simulation experimenters to select experimental results on demand and automatically generate the selected content into an experimental result report that meets the format requirements according to the specified experimental result report template.

[0149] Supports local file export of experimental reports, and the export format supports file formats such as Word, HTML, PDF and Excel.

[0150] Functions of the management and control support module:

[0151] First, control basic transmission services. These services provide support for access and operational control of experimental resources through service interfaces. These services provide a unified, standardized set of APIs. These encapsulated basic services primarily include node registration, resource deployment, activity coordination, data interaction, status query, and clock management. Through interface encapsulation, the underlying technical details are abstracted, forming a standard service interface development kit (DEP) that facilitates agile user access and rapid integration and control of experimental resources.

[0152] Second, experimental control agent

[0153] The experiment control agent is a system backend service running on every physical or virtual machine node, providing a range of basic services, such as file transfer, process management, compression and decompression, and connectivity. The experiment control agent itself calls these basic services in combination to complete functions such as experimental resource registration and deployment, simulation node time synchronization, and experimental status monitoring. The experiment control system also remotely calls these basic services to automatically set up the experimental environment, physically isolate experimental resources, and clean up the experimental environment.

[0154] The experiment control agent collaborates with other modules in the experiment operation control subsystem to manage experiments. The experiment operation control subsystem adopts a server-client architecture. On the client side, the experiment control agent can quickly respond to commands from the experiment operation control subsystem, such as environment setup, experiment control, status monitoring, and environment teardown. On the server side, a separate thread manages each simulation node, supporting operation control of at least 100 simulation nodes. The basic services provided by the experiment control agent are shown in Table 4.

[0155] Table 4

[0156]

[0157]

[0158] Based on the services provided by the experiment management and control agent, in conjunction with the experiment environment creation, experiment status monitoring and other modules in the experiment operation control subsystem, it is possible to realize the rapid and on-demand automatic construction of the experiment environment, realize the visual monitoring of the experiment environment and experiment progress, and realize the recovery of experiment data and the withdrawal of the experiment environment.

[0159] The experiment control agent primarily coordinates with the experiment operation control subsystem to manage experimental resources. The process by which the experiment control agent implements simulation node registration, experimental resource deployment, experimental environment status monitoring, and experimental environment cleanup has been previously described and will not be repeated here. The following describes the workings and functions of the experiment control agent, starting with simulation node time synchronization.

[0160] Figure 14 This is the process of performing time synchronization of experimental nodes based on the experimental control agent in an embodiment of the present invention. During operation, the experimental control agent periodically sends a time synchronization request to the clock source. After the request is passed, it obtains the current time from the clock source, and then parses and sets the time information of the simulation node to complete the time synchronization of the simulation node.

[0161] To sum up, in the system proposed in the embodiment of the present invention, based on the simulation experiment requirements, batch assignments can be made to each parameter variable in the simulation scenario selected by the simulation experiment personnel to generate multiple experimental samples, thereby realizing batch generation of experimental samples, and then deploying and executing experiments based on batch experimental samples, and finally obtaining simulation experiment data, thereby realizing online simulation real-time experiments, which can meet the needs of using online real-time experiments for model verification and strategy optimization.

[0162] The embodiment of the present invention further provides an online simulation experiment method, the principle of which is similar to that of the online simulation experiment system and will not be described in detail here.

[0163] Figure 15 This is a flow chart of an online simulation experiment method according to an embodiment of the present invention, including:

[0164] Step 1501: Acquire a simulation experiment project created by a simulation experimenter, wherein the simulation experiment project is created by the simulation experimenter based on simulation experiment requirements;

[0165] Step 1502: Based on the simulation experiment requirements, batch assign values ​​to each parameter variable in the simulation scenario selected by the simulation experimenter to generate multiple experimental samples;

[0166] Step 1503: obtaining simulation parameters set by simulation experimenters for multiple experimental samples;

[0167] Step 1504, assigning a simulation node to each experimental sample;

[0168] Step 1505: deploy experimental resources for each simulation node according to the corresponding experimental sample;

[0169] Step 1506: After receiving the experiment running command, read the simulation parameters, run the simulation experiment according to the experimental resources deployed on each simulation node, and obtain simulation experiment data.

[0170] In one embodiment, batch assignment of values ​​to each parameter variable in a simulation scenario selected by a simulation experimenter includes:

[0171] Based on the model resource library, batch assignments are made to each parameter variable in the simulation scenario selected by the simulation experimenter. The model resource library includes a combat entity library, a behavior action library, a task library and a route library.

[0172] In one embodiment, the simulation node is deployed with an experiment control agent, which runs when the simulation node is started, collects basic parameters of the simulation node, registers it with the experiment operation control subsystem, and stores the registration information in the experiment preparation module; the registration information of each node has a validity period; the simulation node sends updated registration information to the experiment preparation module according to preset conditions;

[0173] The method further comprises:

[0174] For each registered simulation node, deploy experimental resources according to the corresponding experimental samples;

[0175] After receiving the updated registration information, the validity period of the registration information is recalculated.

[0176] In one embodiment, the simulation node includes a physical machine, a virtual machine, and a container;

[0177] The method further comprises:

[0178] When the simulation node is a virtual machine, obtain the current number of virtual machines;

[0179] When the number of experimental samples is greater than the current number of virtual machines and less than the currently set maximum number of parallel operations, a new virtual machine is opened.

[0180] In one embodiment, for each simulation node, experimental resources are deployed according to the corresponding experimental sample, including:

[0181] For each simulation node, based on the corresponding experimental sample, the corresponding experimental resources are downloaded from the experimental resource library, wherein the experimental resources include a simulation engine and a simulation model;

[0182] The experimental resources are deployed through the experiment management and control agent.

[0183] In one embodiment, the method further comprises:

[0184] Divide an experimental space for each simulation experiment project;

[0185] Allocating a simulation node to each experimental sample in the experimental space;

[0186] After the simulation is completed, the experiment space is cleared through the experiment control agent.

[0187] To sum up, in the method proposed in the embodiment of the present invention, based on the needs of the simulation experiment, batch assignment can be made to each parameter variable in the simulation scenario selected by the simulation experiment personnel to generate multiple experimental samples, thereby realizing batch generation of experimental samples, and then deploying and executing experiments based on batch experimental samples, and finally obtaining simulation experiment data, realizing online simulation real-time experiments, which can meet the needs of using online real-time experiments for model verification and strategy optimization.

[0188] An embodiment of the present invention further provides a computer device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the above-mentioned online simulation experiment method is implemented.

[0189] An embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned online simulation experiment method is implemented.

[0190] An embodiment of the present invention further provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the online simulation experiment method is implemented.

[0191] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program service systems. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program service system implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0192] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program business systems according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as combinations of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0193] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0194] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0195] The specific embodiments described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. An online simulation experiment system, characterized in that: include: Experimental design subsystem and experimental operation control subsystem, among which, Experimental design subsystem, including: The experiment management module is used to obtain simulation experiment projects created by simulation experiment personnel, wherein the simulation experiment projects are created by simulation experiment personnel based on simulation experiment requirements; The experimental design module is used to batch assign values ​​to each parameter variable in the simulation scenario selected by the simulation experimenter based on the simulation experiment requirements, generate multiple experimental samples, and obtain the simulation parameters set by the simulation experimenter for multiple experimental samples; The experimental design module is further configured to: integrate and load a simulation scenario editing tool in the form of a plug-in; receive simulation scenarios created by simulation experimenters in the simulation scenario editing tool; replace parameter variables in the simulation scenario with parameter variable values ​​from a model resource library, and generate an experimental sample by combining values ​​of different parameter variables; Experimental operation control subsystem, including: Experiment preparation module, used to obtain multiple experimental samples and simulation parameters of simulation experiment projects; The experiment opening module is used to allocate simulation nodes to each experimental sample; for each simulation node, experimental resources are deployed according to the corresponding experimental sample; The experiment running module is used to read the simulation parameters after receiving the experiment running command, run the simulation experiment according to the experimental resources deployed on each simulation node, and obtain the simulation experiment data; The simulation node is deployed with an experiment control agent, which runs when the simulation node is started, collects basic parameters of the simulation node, registers it with the experiment operation control subsystem, and stores the registration information in the experiment preparation module; the registration information of each node has an expiration date; the simulation node sends the updated registration information to the experiment preparation module according to preset conditions; The experiment preparation module is specifically used to: For each registered simulation node, deploy experimental resources according to the corresponding experimental samples; After receiving the updated registration information, recalculate the validity period of the registration information; The simulation node obtains the registration information of the simulation node and registers with the central node; if the registration fails for a preset number of consecutive times, it is determined that the node is unreachable and the registration fails; if the registration is successful, the timer is started and triggered at fixed intervals to send or update the registration information; The experiment control agent completes the registration and deployment of experimental resources, the time synchronization of simulation nodes, and the monitoring of experimental status by combining and calling basic services; The experiment control agent cooperates with other modules in the experiment operation control subsystem to complete the control of the experiment. The experiment control agent responds to the environment establishment, experiment control, status monitoring, and environment withdrawal instructions from the experiment operation control subsystem.

2. The system according to claim 1, wherein The Experimental Design module is specifically used to: Based on the model resource library, batch assignments are made to each parameter variable in the simulation scenario selected by the simulation experimenter. The model resource library includes a combat entity library, a behavior action library, a task library and a route library.

3. The system according to claim 1, wherein The simulation nodes include physical machines, virtual machines and containers; The experimental module is specifically used for: When the simulation node is a virtual machine, obtain the current number of virtual machines; When the number of experimental samples is greater than the current number of virtual machines and less than the currently set maximum number of parallel operations, a new virtual machine is opened.

4. The system according to claim 1, wherein: The experimental module is specifically used for: For each simulation node, based on the corresponding experimental sample, the corresponding experimental resources are downloaded from the experimental resource library, wherein the experimental resources include a simulation engine and a simulation model; The experimental resources are deployed through the experiment management and control agent.

5. The system according to claim 1, wherein: The experimental setup module is also used to: Divide an experimental space for each simulation experiment project; Allocating a simulation node to each experimental sample in the experimental space; After the simulation is completed, the experiment space is cleared through the experiment control agent.

6. An online simulation experiment method, characterized in that: The system according to any one of claims 1 to 5, comprising: Acquire a simulation experiment project created by a simulation experimenter, wherein the simulation experiment project is created by the simulation experimenter based on simulation experiment requirements; Based on the simulation experiment requirements, batch assign values ​​to each parameter variable in the simulation scenario selected by the simulation experimenter to generate multiple experimental samples; Obtain simulation parameters set by simulation experimenters for multiple experimental samples; Assign simulation nodes to each experimental sample; For each simulation node, deploy experimental resources according to the corresponding experimental samples; After receiving the experiment running command, the simulation parameters are read, and the simulation experiment is run according to the experimental resources deployed on each simulation node to obtain simulation experiment data.

7. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the method according to claim 6 is implemented.

8. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to claim 6 is implemented.

9. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the method according to claim 6 is implemented.

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