Expandable parallel distributed integrated simulation integration method

Abstract

The invention discloses an extensible parallel distributed integrated simulation integration method, and relates to the technical field of combat simulation and deduction, and the method comprises the steps: designing an extensible parallel distributed integrated simulation integration framework, following the principles of modularization, standardization, configurability and extensibility, determining an integration strategy, determining key elements of an integration technology, and completing the construction of an integration environment; key integration steps including interface standardization, data synchronization and fault detection and recovery work are clarified, technologies used in integration work including a model integration technology, a data interaction technology and a time synchronization technology are clarified, and preparation is made for extensible parallel distribution integrated simulation integration application; and implementing an integration technology from analysis of integration requirements to preparation of the system, determination of pre-integration and final integration of the system, and recording and defining common integration problems and solutions. According to the invention, dynamic resource scheduling and high-precision space-time synchronization of multi-domain combat simulation can be realized.

Description

Technical Field

[0001] This invention relates to the field of combat simulation and deduction technology, specifically to a simulation integration method for military simulation, parallel distributed computing, joint operations modeling, and real-time fault tolerance. Background Technology

[0002] With the rapid development of information technology, naval combat simulation is playing an increasingly important role in strategic planning, equipment development, operational decision-making, and military training. Naval integrated combat simulation experiments, as a novel simulation method, integrate and coordinate multiple simulation systems to achieve overall simulation of complex systems. Scalable, parallel, distributed, and integrated simulation integration methods are key to improving the overall performance and reliability of complex system simulation systems. Summary of the Invention

[0003] This invention provides an scalable parallel distributed integrated simulation method to achieve dynamic resource scheduling and high-precision spatiotemporal synchronization in multi-domain combat simulation, solve the problem of cross-protocol collaboration and real-time interaction of heterogeneous equipment models, and improve the system's survivability and second-level fault tolerance under combat conditions.

[0004] This invention provides a scalable parallel distributed integrated simulation method, implemented based on a comprehensive simulation platform. This platform integrates multiple simulation tools, models, and data to form a distributed integrated simulation environment. The method includes: Design a scalable, parallel, distributed, and integrated simulation framework, adhering to the principles of modularity, standardization, configurability, and scalability, determine the integration strategy, identify key elements of the integration technology, and complete the construction of the integration environment; The key integration steps are clearly defined, including interface standardization, data synchronization, and fault detection and recovery. The technologies used in the integration work are also clearly defined, including model integration technology, data interaction technology, and time synchronization technology, in order to prepare for scalable, parallel, distributed, and integrated simulation integration applications. Implement integration technologies, from analyzing integration requirements to preparing the system, determining the pre-integration and final integration of the system, and recording and clarifying common integration problems and solutions.

[0005] In some instances, the distributed integrated simulation environment achieves integration through management software, that is, by using management software to integrate simulation software tools with different functions together, and achieving integration through data conversion interfaces; The distributed integrated simulation environment can also achieve integration with the database as the center, that is, to realize the sharing of data information of different stages of activities throughout the simulation process, support the integration of various activities, and realize an integrated simulation experimental environment by storing and managing simulation resources through the database system. The distributed integrated simulation environment can also achieve integrated operation and use of simulation software through the simulation operating system. That is, the simulation operating system can effectively manage simulation-related resources and support resource matching and operation, thus achieving a high degree of integration in the operation and use of the entire simulation software. The distributed integrated simulation environment can also achieve integrated optimization of the entire simulation lifecycle based on the plug-and-play integration method of the soft bus.

[0006] In some instances, the distributed integrated simulation environment includes: a model editing tool, which provides model design, compilation, and verification, supports users in building simulation models according to actual needs, and performs model verification and validation; A simulation programming environment is used to provide a platform for writing and verifying simulation programs, supporting users to write, debug, and verify simulation programs to ensure the correctness and reliability of the programs. Data preparation tools are used to provide prepared models and input data, supporting users in preparing the input data required for simulation. Data analysis tools are used to provide analysis models and output data, enabling users to perform statistical analysis and visualization of simulation output data in order to extract valuable information and conclusions. Experiment design tools are used to provide simulation experiments for designing and executing models, supporting users in designing simulation experiment schemes and executing experiments to obtain simulation results.

[0007] In some instances, the design of the scalable parallel distributed integrated simulation framework includes: components, design principles, implementation steps, and key technologies. The components include: system architecture, integration strategy, test environment, data preparation, and monitoring and logging. The design principles include: modularity, standardization, configurability, scalability, and observability. The implementation steps include: requirements analysis, system architecture design, interface definition and implementation, test environment setup, data preparation and import, integration execution, problem localization and resolution, performance evaluation and optimization, and documentation and training. The key technologies include: distributed system technology, interface testing technology, performance testing technology, automated testing technology, and monitoring and logging technology.

[0008] In some examples, the integration strategy includes: integration objectives, development of an integration strategy, precautions during integration, and optimization directions for the integration strategy. The integration objectives include functional completeness, performance compliance, and stability and reliability. The development of the integration strategy includes: developing an integration plan, building a stable integration environment, data preparation and verification, phased and modular integration, using professional testing tools, strengthening communication and collaboration, and recording and analyzing integration results. Precautions during integration include: security, stability, and backup and recovery. Optimization directions for the integration strategy include: introducing continuous integration / continuous deployment, strengthening monitoring and alerting, and improving team skills.

[0009] In some instances, the key elements of determining integration technology include: system architecture and module division, interface definition and protocol, test environment, test data, monitoring and logging, application interface simulation technology to simulate dependent services that are not yet fully developed or difficult to access, simulation of interface responses, use of service virtualization technology to create virtual services to simulate the behavior of real services, use of service simulation tools to simulate complex service environments, use of integration testing frameworks to write integration test cases, use of relevant tools for end-to-end integration testing, as well as continuous integration, version control and dependency management, and distributed tracing.

[0010] In some instances, the explicitly defined key integration steps include: interface standardization, data synchronization, and fault detection and recovery. The principles of interface standardization include universality, scalability, security, and stability. The practices of interface standardization include standard development, implementation, monitoring and evaluation, and continuous updates. Data synchronization includes real-time and periodic synchronization, and one-way and two-way synchronization. The implementation methods of data synchronization include cloud synchronization technology, data migration tools, and built-in backup and recovery functions of devices. The steps of data synchronization include requirements analysis, solution design, environment preparation, synchronization implementation, monitoring and maintenance, performance optimization, and data verification. Fault detection methods include monitoring, log analysis, parameter monitoring, signal analysis, health checks, threshold alarms, pattern recognition, and visual inspection. Detection indicators include timeliness, sensitivity, and accuracy. Fault recovery methods include retry mechanisms, rollback operations, fault switching, automatic restart, fault isolation, backup equipment switching, and self-repair. Recovery strategies include preventative maintenance, rapid response, and continuous improvement.

[0011] In some instances, the implementation integration technology includes: requirements analysis, system preparation, system pre-integration, system integration, problem localization and resolution, and performance evaluation and optimization. The requirements analysis includes clarifying the integration goals, scope, and requirements. The system preparation includes environment setup, data preparation, and interface testing. The system pre-integration is used for data path testing and simple functional interaction testing. The system integration is used to connect the various modules or components for overall testing and debugging.

[0012] In some instances, common integration problems include interface incompatibility, and solutions include redefining interfaces and protocols and ensuring interface consistency between individual modules or components. Solutions to data exchange errors include checking the data format, encoding, and transmission method, and making appropriate adjustments and optimizations. Solutions to system stability issues include optimizing system architecture, increasing system resources, or using load balancing to improve system stability and performance.

[0013] In summary, compared with the prior art, the above-described technical solutions conceived by this invention can achieve the following beneficial effects: (1) The integrated management software facilitates the management of simulation resources and builds an integrated simulation experimental environment.

[0014] (2) Develop a simulation operating system to realize the integrated operation and use of simulation software and meet the needs of complex simulation experiments.

[0015] (3) Based on the plug-and-play integration method of soft bus, the integration optimization of the entire simulation life cycle is realized. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a flowchart illustrating the implementation of the scalable parallel distributed integrated simulation method provided in this embodiment of the invention. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] In the following description, specific embodiments of the invention will be illustrated with reference to steps and symbols performed by one or more computers, unless otherwise stated. Therefore, these steps and operations will be referred to several times as being performed by a computer, and computer execution as referred to herein includes operations by a computer processing unit representing electronic signals of data in a structured format. This operation transforms the data or maintains it at a location in the computer's memory system, which can be reconfigured or otherwise alter the operation of the computer in a manner well known to those skilled in the art. The data structure maintained by the data is the physical location of the memory, which has specific characteristics defined by the data format. However, the principles of the invention described above are not intended to be limiting, and those skilled in the art will understand that many of the following steps and operations can also be implemented in hardware.

[0020] The terms "module" or "unit" as used herein can be considered as software objects executing on the computing system. Different components, modules, engines, and services described herein can be considered as implementations on the computing system. The apparatus and methods described herein are preferably implemented in software, but can also be implemented in hardware, both of which are within the scope of this invention.

[0021] Those skilled in the art will understand that, unless specifically stated otherwise, the singular forms “a,” “an,” and “the” used herein may also include the plural forms. It should be further understood that the term “comprising” as used in this specification means the presence of features, integers, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof. It should be understood that when we say an element is “connected” or “coupled” to another element, it can be directly connected or coupled to the other element, or there may be intermediate elements. Furthermore, “connected” or “coupled” as used herein can include wireless connections or wireless coupling. The term “and / or” as used herein includes all or any units and all combinations of one or more associated listed items.

[0022] The scalable parallel distributed integrated simulation integration method provided in this invention can realize battlefield situation-driven intelligent scheduling, dynamically adjust computing resources according to the red-blue confrontation situation, and reduce the response latency of priority tasks; it integrates simulation software tools with different functions together using management software, and achieves integration through data conversion interface, which facilitates the management of simulation resources and improves the efficiency and accuracy of simulation experiments; it adopts a multi-copy redundancy and cross-regional backup mechanism to realize a distributed redundant storage architecture, ensuring zero loss of critical battlefield data.

[0023] Scalable parallel distributed integrated simulation integration methods such as Figure 1 As shown, it can be divided into three parts: integrated research, integrated preparation, and integrated application.

[0024] The integration research phase involves designing a scalable, parallel, distributed, and integrated simulation framework, adhering to the principles of modularity, standardization, configurability, and scalability, conducting integration strategy research, identifying key elements of integration technology, and completing the construction of the integrated ecosystem.

[0025] The integration preparation phase primarily clarifies the key integration steps, including interface standardization, data synchronization, and fault detection and recovery. It also investigates the main technologies to be used in the integration process, including model integration, data interaction, and time synchronization technologies, in preparation for scalable, parallel, distributed, and integrated simulation applications.

[0026] The integration and application phase mainly involves the implementation of integration technologies, from analyzing integration requirements to preparing the system, carrying out system pre-integration and final integration work, and recording and clarifying common integration problems and solutions.

[0027] The scalable, parallel, distributed, and integrated simulation approach relies on a comprehensive simulation platform that integrates multiple simulation tools, models, and data. These tools constitute a distributed and integrated simulation environment, jointly supporting the entire simulation research process, including model description, experimental framework description, experimental execution, statistical analysis, output reports, and graphical displays. It is a highly integrated simulation system that tightly combines the three stages of simulation modeling, simulation experimentation, and simulation result analysis. It can support the entire simulation experiment process and provide unified management of simulation resources (such as models, parameter sets, experimental frameworks, algorithms, and experimental results), thereby improving the efficiency and accuracy of simulation experiments.

[0028] The concept of a distributed integrated simulation environment: A distributed integrated simulation environment is not limited to the simulation experiment phase, but covers the entire simulation lifecycle, including simulation modeling, simulation experiments, and results analysis. This environment integrates multiple software programs with different functions into a multifunctional software system to support the entire simulation research process.

[0029] (1) Implementation method of distributed integrated simulation environment There are several ways to implement a distributed integrated simulation environment, including but not limited to the following.

[0030] ① Achieve integration through management software.

[0031] By integrating simulation software tools with different functions using management software and achieving unification through data conversion interfaces, this approach facilitates the management of simulation resources and improves the efficiency and accuracy of simulation experiments.

[0032] ② Achieve integration centered on the database The simulation process enables data sharing across different stages and supports the integration of various activities. A database system stores and manages simulation resources, creating an integrated simulation environment. This approach ensures data integrity and consistency, improving the reliability of the simulation experiments.

[0033] ③ Develop a simulation operating system to achieve integrated operation and use of simulation software. A dedicated simulation operating system is developed to effectively manage simulation-related resources and support their matching and operation. This operating system achieves a high degree of integration in the operation and use of the entire simulation software. This approach provides a more flexible and scalable simulation environment, meeting the needs of complex simulation experiments.

[0034] ④ The plug-and-play integration method based on the soft bus enables integrated optimization throughout the entire simulation lifecycle.

[0035] The plug-and-play integration approach based on a soft bus can provide a large amount of real-time, environment-consistent, and spatially integrated environmental information from different locations within the same space. This integration approach also employs a secure information exchange mechanism, enabling simulated entities to efficiently perceive and manipulate each other. It is highly effective in resolving cross-domain issues in simulation modeling and addressing the problem that simulation processes and result analysis cannot be based on the same system.

[0036] (2) Core components of distributed integrated simulation environment Distributed integrated simulation environments typically include, but are not limited to, the following core components: ① Model editing tools It provides model design, compilation, and verification, supporting users to build simulation models according to actual needs and to verify and validate the models.

[0037] ② Simulation programming environment It provides simulation program writing and verification, supporting users to write, debug and verify simulation programs to ensure the correctness and reliability of the programs.

[0038] ③ Data preparation tools It provides a model preparation tool and input data, supporting users in preparing the input data required for simulation, including model parameters, initial conditions, etc.

[0039] ④ Data analysis tools It provides analytical models and output data, supporting users to perform statistical analysis and visualization of simulation output data to extract valuable information and conclusions.

[0040] ⑤ Experimental Design Tools It provides simulation experiments for designing and executing models, supporting users to design simulation experiment schemes, including experimental conditions, experimental steps, etc., and execute experiments to obtain simulation results.

[0041] In summary, the scalable parallel distributed integrated simulation method relies on a comprehensive distributed integrated simulation environment, which integrates multiple simulation tools, models, and data to support the entire simulation experiment process. Through high integration and optimization of each stage of the simulation process, it provides powerful support for the simulation of complex systems. The distributed integrated simulation environment can improve the efficiency and accuracy of simulation experiments, making significant contributions to the development of various fields.

[0042] 1. Design the integration framework The scalable, parallel, distributed, integrated simulation framework design refers to an integration and testing framework designed during software development to ensure that multiple system components or modules can work together correctly. It includes key components, design principles, implementation steps, and key technologies.

[0043] The design of a scalable, parallel, distributed, and integrated simulation framework typically includes the following main components.

[0044] ①System Architecture: Define the overall structure of the system, including the division of each module or component, interface definition, data flow, etc.

[0045] ② Integration Strategy: Develop specific integration strategies, including the order of integration, methods, and tool selection.

[0046] ③ Testing environment: Build a testing environment similar to the actual production environment to ensure the reliability of the integration results.

[0047] ④ Data preparation: Prepare test data for integration, including normal data, abnormal data, boundary data, etc.

[0048] ⑤ Monitoring and logging: Establish a monitoring mechanism and logging system to promptly identify and resolve problems.

[0049] The following principles should be followed when designing a scalable, parallel, distributed, and integrated simulation framework.

[0050] ① Modular principle. The framework should support modular design, dividing the system into multiple independent modules or components, minimizing direct dependencies between modules, improving module independence, and facilitating individual testing, integration, management, and maintenance.

[0051] ②Standardization principle. Interface design should follow unified standards, be clearly defined and standardized, and ensure accurate data exchange between different modules or components, facilitating interoperability between different modules.

[0052] ③ Configurability: Provides flexible configuration options to adapt to changes in different scenarios and needs.

[0053] ④ Scalability Principle. The framework should possess good scalability, considering future system expansion needs and ensuring that the scalable parallel distributed integrated simulation framework can support the addition of new modules or components to adapt to possible future changes in requirements.

[0054] ⑤ Observability: Through monitoring and logging systems, the system's operating status and performance can be observed in real time. Detailed log information is recorded to facilitate problem tracking and analysis.

[0055] The implementation steps for designing a scalable, parallel, distributed, integrated simulation framework typically include the following: ① Requirements Analysis. Determine the purpose of integration, such as verifying interfaces, data flows, and business processes between modules, clarify the functional and performance requirements of the system, and define the integration goals and scope.

[0056] ②System architecture design: Based on the requirements analysis results, design the overall system architecture and module division, and list all modules or systems that need to participate in the integration.

[0057] ③ Define interfaces and implementations: Analyze dependencies, understand the dependencies and calling relationships between modules, define the interface specifications between modules or components, and implement the corresponding interface functions.

[0058] ④ Test environment setup: Set up a test environment similar to the actual production environment, including hardware, software and network aspects.

[0059] ⑤ Data preparation and import: Prepare the test data for integration and import it into the test environment.

[0060] ⑥ Integration Execution: Execute integration tests according to the established integration strategy, and gradually integrate and test between modules or components. Verify the effectiveness of the framework.

[0061] ⑦ Problem identification and resolution: Collect feedback through the monitoring and logging system to promptly identify and resolve problems.

[0062] ⑧ Performance evaluation and optimization: Perform performance evaluation on the integrated system and make necessary optimizations based on the evaluation results.

[0063] 9. Documentation and Training: Provide detailed guidelines for the design, use, and maintenance of the framework. Provide training to integration personnel to ensure they can use the framework correctly.

[0064] By following the steps above, a high-efficiency, stable, and easy-to-maintain scalable parallel distributed integrated simulation framework can be designed, providing strong support for integration testing in the software development process.

[0065] The design of a scalable, parallel, distributed, and integrated simulation framework mainly involves the following key technologies: ① Distributed system technology. For distributed systems, key technologies such as distributed transaction management, load balancing, fault tolerance and recovery are required to ensure the reliability and performance of the system.

[0066] ② Interface testing technology: Using interface testing tools and methods, verify whether the interface functions between different modules or components are correct.

[0067] ③ Performance testing techniques: Using performance testing tools and methods to evaluate system performance metrics such as response time, throughput, and resource utilization.

[0068] ④ Automated testing technology: Improve testing efficiency and accuracy, and reduce testing costs through automated testing tools and methods.

[0069] ⑤ Monitoring and logging technology: Employ monitoring and logging systems to observe the system's operating status and performance in real time, and promptly identify and resolve problems.

[0070] In summary, designing a scalable, parallel, distributed, integrated simulation framework is a complex and critical process, requiring comprehensive consideration of multiple aspects such as system architecture, integration strategy, testing environment, data preparation, monitoring, and logging. By adhering to design principles and implementation steps, and employing key technical means, the effectiveness and reliability of the scalable, parallel, distributed, integrated simulation framework can be ensured, providing strong support for the smooth launch and stable operation of the system.

[0071] 2. Research integration strategies Integration refers to the joint debugging of multiple systems or components. It is the overall debugging performed after multiple systems or components are integrated, and it is an indispensable and important step in many fields such as software development, hardware deployment, and system integration. Integration strategy research refers to the study of strategies and methods for joint debugging of software systems or products during the integration phase. Integration typically occurs after each module or subsystem has been developed individually, and it is necessary to integrate these modules or subsystems to ensure that they can work together to achieve the expected functional requirements.

[0072] The main contents and key points of the integrated strategy research are as follows: (1) Integration Objectives The primary purpose of integration is to identify and resolve potential problems within a system. During development, incompatibility or data exchange errors may occur between different systems or components. Integration allows for the comprehensive detection of these issues and the implementation of corresponding adjustments and optimizations. It aims to ensure that all systems or components function correctly and meet expected functional and performance requirements when working collaboratively. Integration objectives primarily include, but are not limited to, the following:

[0073] Functional completeness. Ensure that the system can perform all intended functions after all modules are integrated.

[0074] Performance compliance. Verify whether the integrated system's performance meets design requirements.

[0075] Stability and reliability. Ensure the system operates stably under various workloads without serious defects.

[0076] (2) Integration strategy formulation ① Develop a detailed integration plan Clearly define the integration goals, scope, timeline, and personnel responsibilities; develop integration steps and processes, including data preparation, environment setup, test execution, and result analysis. Use a simulated environment for integration when a real-world environment is unavailable or too costly. Start with the simplest scenario and gradually increase complexity until all scenarios are covered. If possible, integrate multiple teams or modules simultaneously to improve efficiency.

[0077] ②Build a stable integration environment Ensure that the integrated environment is as consistent as possible with the actual operating environment; build the necessary network, hardware and software environment to ensure that each system or component can communicate and interact normally.

[0078] ③ Data preparation and validation Prepare sufficient integration test data, including real or simulated datasets, encompassing both normal and abnormal data, as well as normal and abnormal boundary conditions. Validate the test data to ensure its accuracy and completeness. Design test cases to ensure all interfaces are tested. Design test cases capable of testing system performance bottlenecks.

[0079] ④ Integrate in stages and modules Integration can be divided into multiple phases, with the integration priority determined based on the importance and dependencies of the modules. For example, core modules can be integrated first, followed by peripheral modules. The entire system can also be divided into multiple configuration item modules, which can be integrated one by one. Only after each module or configuration item has been successfully integrated can the integration between modules or configuration items proceed. Alternatively, a risk-driven approach can be used to identify high-risk modules or interfaces and prioritize their integration to reduce overall risk.

[0080] ⑤ Use professional testing tools Utilize automated testing tools for integration to improve testing efficiency and accuracy. Write automated test scripts to enhance integration efficiency. Use performance testing tools to perform stress tests on the system, ensuring stable operation under high loads. Integrate integration testing into the continuous integration process to achieve automated deployment and testing.

[0081] ⑥ Strengthen communication and collaboration Establish an effective communication mechanism to ensure timely communication among teams during the integration process. Clearly define the roles and responsibilities of each team member. Maintain close communication and collaboration among teams throughout the integration process. Communicate promptly when problems arise and work together to find solutions.

[0082] ⑦ Record and analyze integrated results Document all issues and solutions during the integration process in detail. Ensure all modules have detailed logs for easy problem localization. Use debugging tools to analyze problems and performance bottlenecks. Use an issue tracking system to record, track, and resolve issues discovered during integration. Evaluate the integration results to determine if they meet expectations. Optimize the integration strategy based on the results. Compile and record the integration process, issues, and solutions to create a knowledge base. Regularly organize experience-sharing meetings to improve the team's overall integration capabilities. Analyze the integration results and process, summarize experiences and lessons learned, and provide references for subsequent development and testing.

[0083] By conducting in-depth research on integration strategies, we can improve the quality and efficiency of the software integration phase and reduce the risks and problems after the system goes live.

[0084] (3) Precautions during integration ① Security: Ensure the security of the integration process and avoid data leakage and system damage.

[0085] ② Stability: During the integration process, it is necessary to ensure the stability of the system and avoid system crashes or data loss due to integration.

[0086] ③ Backup and recovery: Data backup should be performed before integration so that it can be restored in time if problems occur.

[0087] (4) Optimization direction of integration strategy ① Introduce Continuous Integration / Continuous Deployment (CI / CD): Automate the integration process through CI / CD workflows to improve integration efficiency and accuracy.

[0088] ②Strengthen monitoring and alarms: Establish a sound monitoring and alarm mechanism to promptly identify and address problems during the integration process.

[0089] ③ Enhance team skills: Strengthen team members' learning and training on integration strategies and tools to improve the overall skill level of the team.

[0090] In conclusion, research on integration strategies is crucial for ensuring the overall performance and stability of the system. By developing detailed integration plans, building a stable integration environment, preparing and validating data, integrating modules separately, using professional testing tools, strengthening communication and collaboration, and recording and analyzing integration results, the efficiency and accuracy of integration can be effectively improved. Simultaneously, attention must be paid to security, stability, backup, and recovery during the integration process, and integration strategies should be continuously optimized to adapt to changing needs and environments.

[0091] 3. Identify key integration elements Integration refers to the technical approach in software development or system integration to integrate two or more software modules, hardware components, subsystems or services in their target environment, test and debug them to ensure that they can communicate, interact and work together correctly to meet the expected functional and performance requirements.

[0092] Key elements of integrated technology include, but are not limited to, the following.

[0093] ①System architecture and module division Before integration, it is necessary to clarify the overall architecture and module division of the system in order to determine the scope and order of integration.

[0094] ② Interface Definition and Protocol The interface definitions and communication protocols between various modules or components are the foundation of integration, and it is necessary to ensure the consistency of interfaces and the accuracy of protocols. Use a standardized interface definition language to define interfaces. Ensure that all interfaces have detailed documentation, including request / response formats, parameters, error codes, etc.

[0095] ③ Testing Environment Integration needs to be performed in a test environment similar to the target environment in order to more accurately simulate the actual operating scenario.

[0096] ④ Test data Prepare sufficient test data, including normal and abnormal data, to comprehensively test the system's functionality and performance.

[0097] ⑤ Monitoring and Logs Establish a monitoring mechanism and logging system to promptly identify and locate problems.

[0098] In addition, it is necessary to apply interface simulation techniques to simulate dependent services that are not yet fully developed or are difficult to access, using tools such as Mockito and WireMock to simulate interface responses. Service virtualization technology is used to create virtual services that simulate the behavior of real services for testing and integration, employing service simulation tools (such as Service Virtualization tools) to simulate complex service environments. Integration testing frameworks are used to write integration test cases, and relevant tools are used for end-to-end integration testing. Furthermore, techniques and methods such as continuous integration, version control and dependency management, and distributed tracing are also required.

[0099] 4. Define key integration steps 4.1 Interface Standardization Interface standardization is a crucial concept in software development, system integration, and information technology. It refers to establishing a unified set of specifications to define the design and implementation of interfaces, ensuring efficient and accurate interaction between different systems, modules, or services. It defines the extent to which applications and platforms communicate, interoperate, and exchange data using predefined, clearly defined interfaces, protocols, and rules that cannot be altered.

[0100] (1) The significance of interface standardization ① Improve development efficiency. A unified interface standard can reduce communication costs during the development process. Standardized interfaces can also reduce additional development and maintenance costs caused by interface incompatibility.

[0101] ② Enhance system stability and interoperability. Standardized interfaces are easier to maintain and test, thereby improving system stability. Interface standardization makes it easier for devices from different manufacturers or different software modules to interoperate without the need for additional adaptation or conversion.

[0102] ③ Enhanced compatibility and improved system integration: Standardized interfaces help ensure that new applications or devices are compatible with existing platforms or systems, thereby protecting user investments. They also facilitate integration between different systems and reduce integration complexity.

[0103] ④ Enhance user experience and promote technological innovation: Interface standardization provides developers with a unified standard, allowing them to focus more on technological innovation rather than spending too much energy on interface compatibility. Consistent interface design can improve the user experience for external developers.

[0104] (2) Principles of Interface Standardization ① Universality: The interface design should be as universal as possible to meet a wide range of needs.

[0105] ② Scalability: The interface should be able to accommodate future functional expansions and changes to adapt to technological developments.

[0106] ③ Security: The interface design should ensure the security of data transmission and access to prevent data leakage or malicious attacks.

[0107] ④ Stability: The interface should be kept stable and frequent changes should be avoided to ensure the stability and reliability of the system.

[0108] (3) Practice of Interface Standardization ①Standardization: Based on business needs and technical specifications, develop detailed interface standards, including interface definitions, data formats, communication protocols, etc.

[0109] ② Implementation Standards: During the development process, strictly follow the interface standards for design, coding, and testing to ensure that the interface meets the standard requirements.

[0110] ③ Monitoring and evaluation: Monitor and evaluate the usage of the interface, promptly identify and resolve issues, and ensure the stability and reliability of the interface.

[0111] ④ Continuous updates: As technology advances and business needs change, the interface standards are regularly updated and improved to adapt to new challenges and opportunities.

[0112] (4) Challenges and countermeasures of interface standardization ① Technical Challenges: Standardizing interfaces between different systems, modules, or services may face technical challenges, such as protocol incompatibility and data format differences. The solution is to strengthen technical research and promote technological innovation to overcome these technical obstacles.

[0113] ② Management Challenges: Implementing interface standardization requires cross-departmental and cross-organizational collaboration and communication. The solution is to establish effective management and collaboration mechanisms to ensure that all parties can actively participate and jointly promote the interface standardization process.

[0114] ③ Security Challenges: With the widespread adoption of interface standardization, data security and privacy protection have become key concerns. The solution is to strengthen security technology research, develop stringent security standards and specifications, and ensure the security of interfaces.

[0115] In conclusion, interface standardization is a significant trend in information technology development, playing a crucial role in improving system interoperability, reducing costs, enhancing compatibility, and promoting technological innovation. In practice, it is necessary to adhere to principles such as universality, scalability, security, and stability when formulating and implementing interface standards. Simultaneously, it is essential to strengthen monitoring and evaluation, continuously update and improve interface standards to address evolving technological and business needs.

[0116] 4.2 Data Synchronization Data synchronization is the process of maintaining data consistency and real-time updates across multiple devices, systems, or applications. It can also refer to the process of copying and updating data between different systems, databases, or storage media to ensure data consistency and accuracy.

[0117] (1) The concept of data synchronization Data synchronization refers to ensuring data consistency and real-time updates across multiple devices, systems, or applications through specific technologies or methods. When data is modified, added, or deleted on one device or system, these changes can be quickly and accurately reflected on other related devices, systems, or applications.

[0118] The key concepts involved in data synchronization are as follows: ①Data source: The original location of the data that needs to be synchronized.

[0119] ② Target system: The system or storage location to which the data will be synchronized.

[0120] ③ Synchronization modes: including full synchronization, incremental synchronization, and real-time synchronization.

[0121] ④ Conflict resolution: Handling conflicts caused by asynchronous data update times.

[0122] ⑤ Full synchronization: Copy all data from the data source to the target system.

[0123] ⑥ Incremental synchronization: Only synchronize data that has changed since the last synchronization.

[0124] ⑦ Real-time synchronization: Data changes are immediately synchronized to the target system.

[0125] (2) Classification of data synchronization Data synchronization can be categorized according to different needs and application scenarios. Common categorization methods include: ① Real-time synchronization and periodic synchronization. Real-time synchronization updates data immediately on all connected devices or systems after modification, suitable for applications requiring immediate response, such as online collaboration tools and instant messaging software. Periodic synchronization updates data at preset time intervals, suitable for situations where real-time requirements are not high but periodic synchronization is necessary, such as backup systems or updates to non-critical business data.

[0126] ② One-way synchronization and two-way synchronization. One-way synchronization means that data can only be transferred from one device or system to another, and is usually used for data backup or distribution. Two-way synchronization means that data can be transferred bidirectionally between two devices or systems, ensuring that both parties can obtain the latest data status, and is suitable for application scenarios that require bidirectional communication.

[0127] (3) Implementation methods of data synchronization Data synchronization can be achieved in various ways, and the content described will differ depending on the perspective. From the perspective of media and tools used, it can be divided into the following types: ① Cloud synchronization technology Cloud synchronization technology uses the cloud as an intermediary to store and distribute data. When data changes on one device, these changes are immediately uploaded to the cloud and then quickly pushed to other related devices, enabling real-time data sharing.

[0128] Cloud synchronization technology is not limited to files and media content, but also includes application status, settings, and various data streams. It relies on powerful background processing capabilities and efficient data transmission protocols to ensure that data flows quickly and accurately between different devices.

[0129] ② Data migration tools Data migration tools refer to software or applications specifically designed for data synchronization. They can transfer data from one device or system to another via various methods (such as Wi-Fi, data cable, Bluetooth, etc.). Common data migration tools include mobile phone data migration tools (such as Huawei phone cloning) and tools for enterprise data migration (such as Rayspeed).

[0130] ③ Built-in backup and restore functions of the device Some devices or systems offer backup and restore functionality in their settings, allowing users to back up data to local storage or external storage (such as an SD card) and then restore it on a new device or system. This method is typically suitable for data synchronization between devices of the same brand or model.

[0131] (4) Steps for data synchronization ① Needs analysis: Determine the data range, synchronization frequency, and synchronization direction (one-way or two-way) for synchronization.

[0132] ② Solution design: Select appropriate synchronization tools and technologies, such as ETL tools, database replication, message queues, etc. Design the synchronization process, including triggering conditions, execution plan, conflict resolution strategies, etc.

[0133] ③ Environment preparation: Configure the network environment to ensure that the data source and target system can access each other. Set necessary authentication and permissions to ensure data security.

[0134] ④ Implement synchronously, developing or configuring synchronization scripts / tasks. Perform full synchronization to initialize target system data. Initiate incremental or real-time synchronization mechanisms.

[0135] ⑤ Monitoring and maintenance: Monitor the operational status of the synchronization operation to ensure the timeliness and accuracy of data synchronization. Regularly check the synchronization logs to identify and resolve problems that arise during the synchronization process.

[0136] ⑥ Performance optimization: Based on the operation status of the synchronous task, optimize the synchronization performance and reduce synchronization latency. Adjust the synchronization strategy, such as batch synchronization, off-peak synchronization, etc.

[0137] ⑦ Data verification: Regularly compare data to ensure consistency between the data source and the target system. Repair any abnormal data that occurs during the synchronization process.

[0138] Data synchronization is an indispensable part of modern information systems, and it is of great significance for ensuring data consistency and supporting business continuity.

[0139] (5) Application scenarios of data synchronization Data synchronization has wide applications in many fields and scenarios, including but not limited to: ① Individual users: Individual users can use cloud synchronization technology or data migration tools to synchronize data on devices such as mobile phones and computers, such as contacts, photos, and documents.

[0140] ② Enterprise users: Enterprise users can use data synchronization technology to ensure data consistency and real-time updates between different departments or branches, such as Customer Relationship Management (CRM) systems and Enterprise Resource Planning (ERP) systems.

[0141] ③ Cross-platform applications: Cross-platform applications require the use of data synchronization technology to ensure data consistency and user experience across different operating systems or devices.

[0142] (6) Challenges and solutions for data synchronization During data synchronization, challenges and problems may arise, such as data conflicts, network latency, and data loss. To address these issues, the following measures can be taken: ① Data conflict resolution mechanism: During data synchronization, data conflicts may occur, such as two devices modifying the same data simultaneously. To solve this problem, a data conflict resolution mechanism can be established, such as using version numbers or timestamps to determine data priority, or allowing users to manually choose which version of the data to retain.

[0143] ② Optimize network performance: Network performance has a significant impact on data synchronization efficiency. To optimize network performance, various measures can be taken, such as using high-speed networks, reducing network latency, and rationally planning network bandwidth.

[0144] ③ Data Backup and Recovery: To prevent data loss or corruption, back up your data regularly and test the recovery process. In the event of data loss or corruption, you can use the backup data for recovery.

[0145] In summary, data synchronization is a crucial process for maintaining data consistency and real-time updates across multiple devices, systems, or applications. By selecting appropriate synchronization methods, optimizing network performance, and establishing effective data conflict resolution mechanisms, the accuracy and reliability of data synchronization can be ensured.

[0146] 4.3 Fault Detection and Recovery Fault detection and recovery are critical components for ensuring stable system operation and business continuity. They are responsible for identifying faults, locating problems, and restoring the system to normal operation, respectively.

[0147] (1) Fault detection Fault detection involves monitoring and analyzing system status to identify potential problems. It typically employs specific methods and techniques to determine if a system fault exists and to preliminarily identify the type and location of the fault. Its importance lies in the timely detection of potential problems, preventing further escalation of the fault and thus ensuring the stable operation of the system.

[0148] ①Detection method i. Monitoring: Monitoring system, application, and business operations to determine system status and identify potential faults. System monitoring: CPU, memory, disk I / O, network traffic, etc. Application monitoring: Response time, transaction success rate, error logs, etc. Business monitoring: Key performance indicators (KPIs).

[0149] ii. Log Analysis: Collect logs from systems, applications, and services. Use log analysis tools (such as ELKStack and Splunk) for pattern recognition and anomaly detection.

[0150] iii. Parameter monitoring: By monitoring key parameters in the system (such as current, voltage, power, etc.), it is possible to determine whether there are abnormal changes, thereby identifying faults.

[0151] iv. Signal Analysis: Using signal processing and analysis techniques, analyze the signals in the system to discover potential fault characteristics.

[0152] v. Health Checks: Regularly execute scripts or tools to check the system's health. Utilize service checks (such as HTTP probes and TCP probes) to verify service availability, thereby identifying and detecting anomalies.

[0153] vi. Threshold Alarm: Set a threshold for a performance metric, and trigger an alarm when the threshold is exceeded.

[0154] vii. Pattern recognition: Identifying normal behavioral patterns through machine learning algorithms and detecting abnormal behaviors that deviate from these patterns.

[0155] viii. Visual inspection: When instruments are not available, the appearance of the equipment is inspected by the eyes or other sensory organs and by applying necessary tools in order to discover obvious signs of malfunction.

[0156] ②Detection indicators • Timeliness: The ability of the system to detect a fault in the shortest possible time after it occurs.

[0157] • Sensitivity: The system's ability to detect minute fault signals. The higher the sensitivity, the more timely the detection of potential problems.

[0158] • Accuracy: The accuracy of fault detection results, i.e. the ability to correctly identify the type and location of the fault.

[0159] (2) Fault recovery Fault recovery refers to taking necessary measures, based on fault detection, to restore the system from a faulty state to normal operation. Its goal is to eliminate the impact of the fault as quickly as possible and ensure the system can continue to provide stable service.

[0160] ①Recovery Method i. Retry mechanism: For temporary errors, the operation can be retried.

[0161] ii. Rollback operation: Undo the operations that have been executed when the transaction fails.

[0162] iii. Failover: Transfer traffic from the failed node to the healthy standby node.

[0163] iv. Automatic restart: For some types of failures, the system can recover to normal operation through an automatic restart. This method is simple and quick, but it may not be able to solve all types of failures.

[0164] v. Fault isolation: Isolating the faulty area from the normal operating area to prevent the fault from spreading and protect other parts of the system from being affected.

[0165] vi. Backup equipment switching: In the event of a failure, the faulty equipment shall be switched to the backup equipment in a timely manner to ensure continuous power supply and stable operation of the system.

[0166] vii. Self-repair: The system has the ability to automatically detect and repair certain types of faults.

[0167] ②Recovery Strategy • Preventive maintenance: By conducting regular inspections and maintenance, potential problems can be identified and addressed in a timely manner, reducing the probability of malfunctions.

[0168] • Rapid Response: After a failure occurs, the recovery process is initiated quickly, and necessary measures are taken to eliminate the impact of the failure.

[0169] • Continuous improvement: Based on lessons learned from fault detection and recovery, continuously optimize system design and maintenance strategies to improve system reliability and stability.

[0170] (3) Practical application Fault detection and recovery technologies have wide applications in various fields, such as power systems, automobile manufacturing, and industrial automation. Taking power systems as an example, fault detection and recovery technologies can promptly detect and handle power faults, ensuring the stable operation of the power system and the quality of power supply. In the automobile manufacturing field, fault detection and recovery technologies help maintenance personnel quickly locate and resolve vehicle faults, improving maintenance efficiency and service quality.

[0171] In conclusion, fault detection and recovery are crucial for ensuring stable system operation. By employing effective fault detection technologies and recovery strategies, we can promptly identify and address potential problems, reduce the impact of faults on the system, and improve its reliability and stability.

[0172] Effective fault detection and recovery mechanisms can significantly improve system reliability and user experience.

[0173] 5. Key technologies integrated ① Model ensemble technology Naval combat simulation involves various models, including ship motion models, weapon system launch models, and target detection models. Model integration technology needs to address the interface consistency issues between different models. For example, the data format output by the ship's speed and heading models must be compatible with the input data format of the weapon system's target calculation model. Unified data standards and interface specifications are typically used to achieve seamless integration between models, such as using XML (Extensible Markup Language) to define data exchange formats, enabling different models to accurately transmit information.

[0174] ② Data Interaction Technology During integration, a large amount of data needs to be exchanged between various subsystems. This data includes battlefield situational data (such as enemy ship positions and speeds), command and control data (combat orders), and equipment status data (remaining weapon and ammunition). To ensure the real-time performance and accuracy of data exchange, high-speed data bus technologies, such as Fibre Channel (FC), are employed. Simultaneously, Data Distribution Management (DDM) technology is required to classify, filter, and distribute data, avoiding redundancy and confusion. For example, in a joint simulation experiment involving ships, aircraft, and submarines, the DDM system will send relevant battlefield situational data only to the platforms that need it, such as sending underwater target information only to anti-submarine aircraft and submarines.

[0175] ③ Time synchronization technology Because different combat simulation subsystems may run on different computer nodes and their internal time progression mechanisms may differ, precise time synchronization technology is required. Common methods include time synchronization based on Network Time Protocol (NTP) and high-precision time synchronization protocols (such as the IEEE 1588 precise time synchronization protocol). For example, in simulating a joint naval and air strike mission, the air defense systems on ships and the attack actions of fighter jets must be carried out on the same time scale. Time synchronization technology ensures that the radar detection time of ships and the attack time of fighter jets can be accurately matched; otherwise, uncoordinated combat operations will occur.

[0176] The aforementioned technologies and methods enable more effective integration, ensuring seamless integration of all parts of the software system, thereby improving software quality and development efficiency.

[0177] 6. Implementation steps of the integration method ① Requirements Analysis Define the goals, scope, and requirements of the integration in order to develop a detailed integration plan.

[0178] ②System Preparation First, a simulation environment needs to be built, including hardware (such as high-performance server clusters and network equipment) and software (operating system, simulation software platform, etc.). Initialization settings must be performed on each subsystem involved in the integration, such as setting the initial position of the ship and the initial state of weaponry. Simultaneously, the models and data interfaces of each subsystem must be checked to ensure they meet the integration requirements. The main tasks are as follows.

[0179] i. Environment setup: Based on the requirements analysis results, set up a test environment similar to the target environment.

[0180] ii. Data preparation: Prepare test data and ensure its accuracy and completeness.

[0181] iii. Interface testing: Test the interfaces between each module or component individually to ensure the correctness of the interface functions.

[0182] ③System pre-integration The main tasks include data path testing and simple functional interaction testing. For example, testing the communication link between the ship and its carrier-based aircraft to ensure its smooth operation, and whether the aircraft can receive and correctly interpret command instructions sent by the ship. A small amount of test data is used to check for obvious problems in the collaborative operation between various subsystems, such as data loss or incorrect instructions.

[0183] ④ System Integration Connect the various modules or components for overall testing and debugging. Conduct comprehensive combat simulation experiments according to the predetermined operational scenarios. During this process, closely monitor the interactions between the various subsystems, including data transmission and model operation status. Collect a large amount of experimental data, such as combat effectiveness data (damage assessment results, etc.) and coordination data (coordination time between platforms, etc.). For example, in simulating a formation air defense operation, record data such as the success rate of air defense missile launches and the delay time of target designation information transmission between ships and early warning aircraft.

[0184] ⑤ Problem Identification and Solution By using a monitoring and logging system, problems can be identified and located in a timely manner, and corresponding repairs and optimizations can be carried out.

[0185] ⑥ Performance evaluation and optimization The collected experimental data are analyzed and evaluated. Data analysis methods, such as statistical analysis and data mining, are used to assess the feasibility of the combat plan, the effectiveness of tactics and methods, and the performance of equipment. Based on the evaluation results, the combat simulation system is optimized and improved, such as adjusting model parameters and refining data interaction mechanisms.

[0186] 7. Integrates common problems and solutions ① Interface incompatibility Integration failures occur due to inconsistent interface definitions or mismatched communication protocols between modules or components. The solution is to redefine the interfaces and protocols and ensure interface consistency between modules or components.

[0187] ② Data interaction error During integration, data exchange errors may occur due to issues with data format, encoding, or transmission methods. The solution is to check the data format, encoding, and transmission methods, and make corresponding adjustments and optimizations.

[0188] ③ System stability issues During integration, system crashes or instability may occur due to limitations in system resources or excessive concurrent requests. Solutions include optimizing the system architecture, increasing system resources, or employing load balancing techniques to improve system stability and performance.

[0189] The above provides a detailed description of a scalable parallel distributed integrated simulation method provided by the embodiments of the present invention. Specific examples have been used to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only for the purpose of helping to understand the method and core ideas of the present invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A scalable parallel distributed integrated simulation method, characterized in that, Based on a comprehensive simulation platform, which integrates multiple simulation tools, models, and data to form a distributed, integrated simulation environment, the method includes: Design a scalable, parallel, distributed, and integrated simulation framework, following the principles of modularity, standardization, configurability, and scalability, determine the integration strategy, identify key elements of the integration technology, and complete the construction of the integration environment; The key integration steps are clearly defined, including interface standardization, data synchronization, and fault detection and recovery. The technologies used in the integration work are also clearly defined, including model integration technology, data interaction technology, and time synchronization technology, in order to prepare for scalable, parallel, distributed, and integrated simulation integration applications. Implement integration technologies, from analyzing integration requirements to preparing the system, determining the pre-integration and final integration of the system, and recording and clarifying common integration problems and solutions.

2. The method according to claim 1, characterized in that, The distributed integrated simulation environment achieves integration through management software, that is, it integrates simulation software tools with different functions together through data conversion interface. The distributed integrated simulation environment can also achieve integration with the database as the center, that is, to realize the sharing of data information of different stages of activities throughout the simulation process, support the integration of various activities, and realize an integrated simulation experimental environment by storing and managing simulation resources through the database system. The distributed integrated simulation environment can also achieve integrated operation and use of simulation software through the simulation operating system. That is, the simulation operating system can effectively manage simulation-related resources and support resource matching and operation, thus achieving a high degree of integration in the operation and use of the entire simulation software. The distributed integrated simulation environment can also achieve integrated optimization of the entire simulation lifecycle based on the plug-and-play integration method of soft bus.

3. The method according to claim 2, characterized in that, The distributed integrated simulation environment includes: a model editing tool, which provides model design, compilation and verification, supports users to build simulation models according to actual needs, and performs model verification and validation; A simulation programming environment is used to provide a platform for writing and verifying simulation programs, supporting users to write, debug, and verify simulation programs to ensure the correctness and reliability of the programs. Data preparation tools are used to provide prepared models and input data, supporting users in preparing the input data required for simulation. Data analysis tools are used to provide analysis models and output data, enabling users to perform statistical analysis and visualization of simulation output data in order to extract valuable information and conclusions; Experiment design tools are used to provide simulation experiments for designing and executing models, supporting users in designing simulation experiment schemes and executing experiments to obtain simulation results.

4. The method according to claim 3, characterized in that, The proposed scalable, parallel, distributed, and integrated simulation framework includes: components, design principles, implementation steps, and key technologies. The components include: system architecture, integration strategy, testing environment, data preparation, and monitoring and logging. The design principles include: modularity, standardization, configurability, scalability, and observability. The implementation steps include: requirements analysis, system architecture design, interface definition and implementation, testing environment setup, data preparation and import, integration execution, problem identification and resolution, performance evaluation and optimization, and documentation and training. The key technologies include: distributed system technology, interface testing technology, performance testing technology, automated testing technology, and monitoring and logging technology.

5. The method according to claim 4, characterized in that, The integration strategy includes: integration objectives, development of an integration strategy, precautions during integration, and optimization directions for the integration strategy. The integration objectives include functional completeness, performance compliance, and stability and reliability. The development of the integration strategy includes: developing an integration plan, building a stable integration environment, data preparation and verification, phased and modular integration, using professional testing tools, strengthening communication and collaboration, and recording and analyzing integration results. The precautions during integration include: security, stability, and backup and recovery. The optimization directions for the integration strategy include: introducing continuous integration / continuous deployment, strengthening monitoring and alerting, and improving team skills.

6. The method according to claim 5, characterized in that, The key elements of the integration technology include: system architecture and module division, interface definition and protocol, test environment, test data, monitoring and logging, application interface simulation technology to simulate dependent services that are not yet developed or are difficult to access, simulation of interface responses, use of service virtualization technology to create virtual services to simulate the behavior of real services, use of service simulation tools to simulate complex service environments, use of integration testing frameworks to write integration test cases, use of relevant tools for end-to-end integration testing, as well as continuous integration, version control and dependency management, and distributed tracing.

7. The method according to claim 6, characterized in that, The clearly defined key integration steps include: interface standardization, data synchronization, and fault detection and recovery. The principles of interface standardization include universality, scalability, security, and stability. The practices of interface standardization include standard development, implementation, monitoring and evaluation, and continuous updates. Data synchronization includes real-time and periodic synchronization, and one-way and two-way synchronization. The implementation methods of data synchronization include cloud synchronization technology, data migration tools, and built-in backup and recovery functions of devices. The steps of data synchronization include requirements analysis, solution design, environment preparation, synchronization implementation, monitoring and maintenance, performance optimization, and data verification. Fault detection methods include monitoring, log analysis, parameter monitoring, signal analysis, health checks, threshold alarms, pattern recognition, and visual inspection. Detection indicators include timeliness, sensitivity, and accuracy. Fault recovery methods include retry mechanisms, rollback operations, fault switching, automatic restart, fault isolation, backup equipment switching, and self-repair. Recovery strategies include preventative maintenance, rapid response, and continuous improvement.

8. The method according to claim 7, characterized in that, The implementation integration technology includes: requirements analysis, system preparation, system pre-integration, system integration, problem localization and resolution, and performance evaluation and optimization. The requirements analysis includes clarifying the integration goals, scope, and requirements. The system preparation includes environment setup, data preparation, and interface testing. The system pre-integration is used for data path testing and simple functional interaction testing. The system integration is used to connect the various modules or components for overall testing and debugging.

9. The method according to claim 8, characterized in that, Common integration problems include interface incompatibility, and solutions include redefining interfaces and protocols and ensuring interface consistency between modules or components. Solutions to data exchange errors include checking the data format, encoding, and transmission method, and making appropriate adjustments and optimizations. Solutions to system stability issues include optimizing system architecture, increasing system resources, or using load balancing to improve system stability and performance.

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