Heterogeneous system interconnection method and device for simulated joint training field

Abstract

The invention provides a heterogeneous system interconnection method and device oriented to the field of simulation combined training, and belongs to the technical field of simulation training, and the method comprises the steps: constructing a combined training data model according to a combined training task demand; generating a data interaction rule based on the joint training data model; establishing a data ordering relationship between the training nodes according to a data interaction rule; receiving the standardized data from each node adapter, and issuing the standardized data to the node adapter of the target training node; the standardized data is obtained by performing format conversion on the local service data of the corresponding training nodes by the node adapters according to the joint training data model based on the data ordering relationship. According to the method, the joint training data model is constructed, and the data interaction rule and the data ordering relation are generated under the constraint of the model, so that the interaction of standardized data among the multi-heterogeneous training nodes is realized, and the consistency and reliability of data interaction among the multi-heterogeneous nodes in the joint training process are realized.

Description

Technical Field

[0001] This invention relates to the field of simulation training technology, and in particular to a method and apparatus for interconnecting heterogeneous systems in the field of joint simulation training. Background Technology

[0002] With the development of simulation training technology, heterogeneous system joint simulation training has emerged as a new system training model, involving the collaborative cooperation between different heterogeneous independent training systems. Heterogeneous system joint simulation training is a complex, multi-dimensional training method that improves the collaborative capabilities between systems by simulating real-world environments to address complex challenges in practical applications.

[0003] In the current technological context, joint simulation training often employs each system's own data format and interface, exchanging data through temporary adaptations or point-to-point connections. However, this approach lacks a unified data interaction standard and centralized management mechanism. When data is converted between different interfaces, inconsistencies can easily arise due to the independent conversion logic of each system, leading to information distortion and synchronization errors. Furthermore, as the number of participating systems increases, the number of point-to-point interfaces will explode, resulting in poor consistency and reliability of data interaction between multiple heterogeneous nodes during joint simulation training. Summary of the Invention

[0004] This invention provides a heterogeneous system interconnection method and apparatus for the field of joint simulation training, which addresses the deficiencies in the prior art and achieves high consistency and high reliability of data interaction among multiple heterogeneous nodes during joint simulation training.

[0005] This invention provides a heterogeneous system interconnection method for the field of simulated joint training, applied to an interconnection management platform. The interconnection management platform communicates with multiple training nodes, and each training node is equipped with a corresponding node adapter. The method includes the following steps: A joint training data model is constructed based on the requirements of the joint training task. The joint training data model is used to define the attributes and data types of the data interacting between the training nodes. Data interaction rules are generated based on the joint training data model. These rules are used to define the processing methods and transmission strategies for data interaction between the training nodes. According to the data interaction rules, establish data ordering relationships between the training nodes; The system receives standardized data from each of the node adapters and distributes the standardized data to the node adapters of at least one target training node. The standardized data is obtained by each node adapter converting the local business data of the corresponding training node according to the joint training data model based on the data ordering relationship.

[0006] According to the present invention, a method for interconnecting heterogeneous systems in the field of simulated joint training is provided, wherein establishing a data subscription relationship between the training nodes includes: Based on the training business domain, the joint training data model is configured as different data themes; Receive data product publication requests from the node adapter for the data topic, and review the publication requests; After the published application is approved, order requests for the published data products will be received from other node adapters; The order request is reviewed according to the data interaction rules to establish the data order relationship.

[0007] The heterogeneous system interconnection method for the field of simulated joint training provided by the present invention further includes: During the training preparation phase, the key performance parameters of the training target system are fully or incrementally synchronized. During the training implementation phase, the synchronization of entity state data between training nodes is managed through a message queue mechanism. The received situation data is encapsulated into messages and sent to the message queue, and the messages are controlled to be distributed from the message queue to the corresponding target training nodes. During the training, evaluation, and withdrawal phase, the synchronous transmission of data files is controlled, and an appropriate transmission strategy is selected based on the characteristics of the data files. Consistency checks are performed on the transmitted data, and the data that passes the check is stored on the target training node.

[0008] The heterogeneous system interconnection method for the field of simulated joint training provided by the present invention further includes: During the training implementation phase, after receiving standardized data from the node adapter, the standardized data is unpacked to be broken down into single-frame data. The single frame data is verified according to the preset data verification rules, and the single frame data is discarded when the verification fails. According to the preset data parsing rules, the successfully verified single-frame data is parsed into structured data, and the structured data is recorded and stored.

[0009] The heterogeneous system interconnection method for the field of simulated joint training provided by the present invention further includes: The network status and access status of the multiple training nodes are monitored in real time; the real-time monitoring includes: Receive and process node discovery data periodically published by each of the node adapters; After completing node discovery with the node adapter, maintain node status heartbeat information with the node adapter; In addition, according to the preset warning strategy, when the training node is detected to be offline or in an abnormal state, real-time alarm information is generated.

[0010] The heterogeneous system interconnection method for the field of simulated joint training provided by the present invention further includes: Configure and distribute the collection and recording rules to each of the node adapters. The collection and recording rules define collection strategies including real-time recording, cached recording, or timeout recording. Receive the acquisition node information registered by each of the node adapters and the working status reported during the training implementation phase; Receive business data, task process data, training plan data, training entity data, and task environment data related to the training process collected by the node adapter according to the collection and recording rules; After training, the system provides the ability to retrieve received data based on acquisition time, data source, or data category, and performs data cleaning on the recorded data in the system according to data cleaning rules.

[0011] According to the present invention, a heterogeneous system interconnection method for the field of simulated joint training is provided, wherein the step of distributing the standardized data to the node adapter of at least one target training node includes: According to a preset push strategy for the data subscription relationship, the standardized data is pushed to the node adapter of the target training node. The push strategy includes at least one of real-time push, timed push, update-triggered push, or one-time push.

[0012] According to the present invention, a heterogeneous system interconnection method for the field of simulated joint training is provided, wherein the data interaction rules include data filtering rules, data compression rules, data cleaning rules, and data forwarding rules.

[0013] This invention also provides a heterogeneous system interconnection device for the field of simulated joint training, applied to an interconnection management platform. The interconnection management platform communicates with multiple training nodes, and each training node is equipped with a corresponding node adapter, including the following modules: The first processing module is used to construct a joint training data model according to the requirements of the joint training task. The joint training data model is used to define the attributes and data types of the data interacting between the training nodes. The second processing module is used to generate data interaction rules based on the joint training data model. The data interaction rules are used to limit the processing method and transmission strategy for data interaction between the training nodes. The second processing module is also used to establish a data ordering relationship between the training nodes according to the data interaction rules; The third processing module is used to receive standardized data from each of the node adapters and send the standardized data to the node adapter of at least one target training node; the standardized data is obtained by each of the node adapters converting the local business data of the corresponding training node according to the joint training data model based on the data ordering relationship.

[0014] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the heterogeneous system interconnection method for the field of simulated joint training as described above.

[0015] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the heterogeneous system interconnection method for the field of simulated joint training as described above.

[0016] The present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the heterogeneous system interconnection method for the field of simulated joint training as described above.

[0017] In summary, one or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages: By constructing a joint training data model based on the requirements of the joint training task, a unified specification and standard are established for data exchange between different training nodes. Data interaction rules are generated based on the joint training data model, thereby uniformly constraining the processing methods and transmission strategies for data interaction between training nodes. This ensures consistent execution logic during data distribution, filtering, compression, and forwarding, guaranteeing the security and efficiency of data transmission. By establishing data subscription relationships between training nodes according to the data interaction rules, the data supply and reception relationships between nodes are clarified, allowing the data transmission range and direction to be determined before training, avoiding communication redundancy and data conflicts. By receiving standardized data from each node adapter and distributing standardized data to at least one target training node, the interconnection management platform achieves centralized scheduling and distribution control of training node data. This ensures that the data received by each node is presented in a unified format, avoiding information distortion and parsing errors caused by differences in local data formats between different systems. Ultimately, this achieves high consistency and high reliability of data interaction between multiple heterogeneous nodes during joint training. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0019] Figure 1 This is one of the flowcharts illustrating the heterogeneous system interconnection method for the field of simulated joint training provided by the present invention.

[0020] Figure 2 This is the second flowchart of the heterogeneous system interconnection method for the field of simulated joint training provided by the present invention.

[0021] Figure 3 This is the third flowchart of the heterogeneous system interconnection method for the field of simulated joint training provided by the present invention.

[0022] Figure 4 This is the fourth flowchart of the heterogeneous system interconnection method for the field of simulated joint training provided by the present invention.

[0023] Figure 5 This is the fifth flowchart illustrating the heterogeneous system interconnection method for the field of simulated joint training provided by the present invention.

[0024] Figure 6 This is the sixth flowchart of the heterogeneous system interconnection method for the field of simulated joint training provided by the present invention.

[0025] Figure 7 This is a schematic diagram of the heterogeneous system interconnection device for the field of simulated joint training provided by the present invention.

[0026] Figure 8 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation

[0027] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0028] It should be noted that in the description of this invention, the terms "comprising," "including," or any other variations thereof are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element. The terms "upper," "lower," etc., indicating orientation or positional relationships according to the accompanying drawings, are only for the convenience of describing the invention and for simplifying the description, and do not indicate or imply that the system or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0029] The terms "first," "second," etc., used in this invention are used to distinguish similar objects, not to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the invention can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class, without limiting the number of objects; for example, a first object can be one or more. Furthermore, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0030] The following is combined with Figures 1-8 This invention describes the heterogeneous system interconnection method, apparatus, electronic device, storage medium, and computer program product provided by the present invention for the field of simulated joint training.

[0031] This invention is applied to an interconnection management platform that communicates with multiple training nodes, each of which has a corresponding node adapter. (See reference...) Figure 1 , Figure 1 This is one of the flowcharts illustrating the heterogeneous system interconnection method for the field of simulated joint training provided by the present invention, such as... Figure 1 As shown, steps 101 to 104 are included: Step 101: Construct a joint training data model based on the requirements of the joint training task. The joint training data model is used to define the attributes and data types of the data interacting between training nodes.

[0032] In step 101, the joint training task requirements refer to the task objectives of joint training, the division of training phases, the types of participating systems, the types of data that the participating systems need to interact with during the training process, and the way this data is used during the training process.

[0033] After analyzing the requirements of the joint training task, the interconnected management platform determines the range of data that each training node needs to interact with during the joint training process.

[0034] Training nodes refer to the various training target systems participating in joint training, and the corresponding node adapters are responsible for data interaction with the interconnection management platform.

[0035] The joint training data model is used to define the attributes and data types of the data that are interacted between training nodes.

[0036] Data attributes refer to the parameter information used to describe the interactive data itself. Data attributes include granularity, unit, resolution, and the meaning of the parameter during the training process. Data type refers to the structural representation of interactive data, which defines the structured expression and parsable range of the interactive data during transmission.

[0037] The joint training data model serves as a unified standard, enabling training nodes to adopt a consistent understanding of the meaning, structure, and value range of interactive data.

[0038] In the specific implementation process, the interconnection management platform establishes the joint training data model project according to the requirements of the joint training task. The interconnection management platform sorts out the business characteristics of the different systems to which each training node participating in the joint training belongs, and sorts out the data interfaces that need to be interacted between these systems.

[0039] Based on the analysis of the results, the content of these data interfaces is abstracted into object classes and interaction classes in the joint training data model. Object classes describe the entity information continuously represented by the training object system during training. Interaction classes describe the interactive behavior information between training nodes during training. The interconnection management platform sets corresponding attribute information for object classes and interaction classes, and specifies the data type, granularity, unit, resolution, and descriptive information for each attribute.

[0040] The interconnected management platform forms corresponding parent class models based on object classes and interaction classes, and generates sub-class models based on the needs of different training nodes in actual training. During the generation of sub-class models, the interconnected management platform supplements or trims the data items needed by different training nodes in actual training, so that the training node meets its own business needs while adhering to the unified parent class constraints.

[0041] After completing the above modeling, the interconnect management platform saves the jointly trained data model in project form and generates a model description file. This model description file is used by the interconnect management platform and each node adapter in subsequent steps.

[0042] Step 102: Generate data interaction rules based on the joint training data model. The data interaction rules are used to limit the processing method and transmission strategy for data interaction between training nodes.

[0043] In step 102, data interaction rules are used to define the processing methods and transmission strategies for data interaction between training nodes. Data interaction rules include data filtering rules, data compression rules, data cleaning rules, and data forwarding rules.

[0044] Data filtering rules are used to limit the range of data content transmitted between training nodes. Data filtering rules filter data based on the spatial range, object range, or task range that the training business is concerned with. This filtering range can be understood as the space of interest.

[0045] Data compression rules are used to define the compression method and compression ratio of data transmitted between training nodes under bandwidth-constrained conditions, in order to reduce bandwidth and traffic consumption during transmission.

[0046] Data cleaning rules are used to define the preprocessing methods for interactive data, including removing or correcting invalid fields, redundant fields, or fields that do not meet the value requirements, thereby improving the reliability of transmitted data.

[0047] Data forwarding rules are used to define the transmission path and distribution relationship of interactive data between different training nodes. Data forwarding rules indicate the source training node, the target training node, and the forwarding conditions, thereby establishing a data flow that meets the training business requirements during joint training.

[0048] Processing methods refer to the filtering, compression, and cleaning actions performed on interactive data before, during, and after transmission. Transmission strategies refer to the distribution paths, conditions, and targets of the interactive data.

[0049] In the specific implementation process, the interconnection management platform obtains the joint training data model in step 101. The joint training data model defines the attributes and data types of the data exchanged between training nodes in a unified format. Based on this joint training data model, the interconnection management platform sets corresponding data interaction rules for each piece of interactive data.

[0050] The interconnected management platform first sets data filtering rules for each type of interactive data. The data filtering rules indicate whether the type of interactive data is within the scope of interest in joint training, and in which interest space it needs to be transmitted, thereby restricting irrelevant data from entering the transmission process.

[0051] The interconnection management platform then sets data compression rules for this type of interactive data. The data compression rules specify the compression method, compression level, and traffic limits to adapt to the link and bandwidth conditions of the training site.

[0052] The interconnected management platform further sets data cleaning rules for this type of interactive data. These rules constrain the cleaning process of this type of interactive data before transmission, including parameter value range checks, invalid field removal, and redundant field trimming.

[0053] The interconnection management platform also sets data forwarding rules for this type of interactive data. The data forwarding rules identify the target training node or the node adapter of the target training node for this type of interactive data, and identify the conditions that trigger forwarding, which are used to guide the transmission path of this type of interactive data between different training nodes.

[0054] After generating the aforementioned rules, the interconnected management platform binds the data interaction rules to the joint training data model, forming configuration content that can be distributed and audited, and provides a basis for establishing data ordering relationships between training nodes in subsequent steps.

[0055] Step 103: Establish data ordering relationships between training nodes according to data interaction rules.

[0056] In step 103, the data ordering relationship is the supply and receiving relationship set by the interconnection management platform for data interaction between training nodes. The data ordering relationship limits the range, transmission conditions, and transmission direction of data provided by the source training node to the target training node, and constrains the processing method and transmission strategy of the data during the interaction process. The data ordering relationship is used to indicate which training node acts as the data provider and which as the data receiver during joint training, and whether the data is exchanged according to the filtering, compression, cleaning, and forwarding requirements set in the data interaction rules.

[0057] In one specific implementation, refer to Figure 2 , Figure 2 This is the second flowchart of the heterogeneous system interconnection method for the field of simulated joint training provided by the present invention. Establishing the data ordering relationship between training nodes specifically includes steps 201 to 204: Step 201: Configure the joint training data model as different data themes according to the training business domain.

[0058] Step 202: Receive data product publication requests for data topics from node adapters and review the publication requests.

[0059] Step 203: After the published application is approved, receive order requests from other node adapters for the published data products.

[0060] Step 204: Review the order request according to the data interaction rules to establish a data order relationship.

[0061] In step 201, the interconnected management platform configures the joint training data model into different data themes according to the training business domain.

[0062] The training domain refers to the scope of operations formed in joint training according to mission objectives and organizational division of labor.

[0063] A data topic refers to an aggregation configuration unit based on a jointly trained data model. Data topics are used to collect data model entries and their attribute constraints that need to interact under the same training business domain.

[0064] After obtaining the joint training task requirements, the interconnected management platform classifies and maps the object classes and interaction classes involved, establishes a one-to-one or many-to-many correspondence between data topics and training business domains, and clarifies the topic name, topic description, business domain to which it belongs, and the data model configuration contained therein.

[0065] The interconnected management platform records the type, granularity, unit, and resolution of attribute fields for each data subject, as well as flags indicating whether external publication and subscription are permitted. This configuration forms a subject directory on the platform side and is persistently stored for reference in subsequent steps.

[0066] Through the above processing, the data models involved in the joint training are organized into themes oriented towards business domains, which facilitates subsequent publication and ordering based on themes.

[0067] In step 202, the interconnection management platform receives data product publication requests from node adapters for data topics and reviews the publication requests.

[0068] A node adapter is a boundary component corresponding to a training node. The node adapter is responsible for converting local business data into standardized data according to the joint training data model and interacting with the interconnection management platform.

[0069] A data product publication application refers to a request initiated by a node adapter to provide data to the outside world based on a certain data topic. The data product publication application carries the provider's training node identifier, the target data topic identifier, the instantiation information of the data model to be published, and the attribute boundary description consistent with the data topic.

[0070] The interconnected management platform performs consistency and compliance checks on publication requests. Consistency checks include verifying the existence of the data subject requested, whether the data model stated in the request matches the data model contained in the subject, and whether the field types and value ranges comply with the constraints of the jointly trained data model. Compliance checks include verifying whether the filtering scope, compression method, cleaning requirements, and forwarding requirements of this type of data meet preset boundaries according to data interaction rules, and verifying the visibility policy under this training business domain.

[0071] Once approved, the interconnected management platform generates a unique identifier for the data product, registers it as a publicly available data product that can be ordered externally, and synchronizes the entry and its metadata in the subject directory.

[0072] In step 203, after the application is approved, the interconnection management platform receives order requests from other node adapters for the published data products.

[0073] A subscription request refers to a request initiated by the subscriber node adapter based on the published data product. The subscription request carries the subscriber training node identifier, the target data product identifier, and subscription intent information consistent with the joint training task.

[0074] The interconnected management platform provides subscribers with a searchable list of published data products based on the subject directory. Subscribers then select the target item using their node adapter and submit a subscription request. The interconnected management platform receives and registers the subscription request and initiates the subsequent review process.

[0075] In step 204, the interconnected management platform reviews the order application according to the data interaction rules to establish a data order relationship.

[0076] Data ordering relationship refers to the binding relationship between the supplier and the receiver established for a certain type of interactive data during joint training. The data ordering relationship records the supplier training node and the receiver training node, the corresponding data product identifier, and the data filtering rules, data compression rules, data cleaning rules, and data forwarding rules applicable during transmission.

[0077] During the review process, the interconnection management platform verifies the orderer's access permissions, checks the consistency between the order scope and the supply scope, and binds the applicable data interaction rules during transmission. Upon approval, the interconnection management platform generates and persistently stores a data order relationship record. Simultaneously, it issues ordering guidelines to the node adapters of both the supplier and the orderer, enabling both parties to enforce transmission constraints in subsequent data interactions.

[0078] The above processing enables the supply and receiving relationships in joint training to form a traceable and auditable binding at the topic level, providing a prerequisite for the controlled distribution of subsequent standardized data.

[0079] Step 104: Receive standardized data from each node adapter and distribute standardized data to the node adapter of at least one target training node; the standardized data is obtained by each node adapter converting the local business data of the corresponding training node according to the joint training data model based on the data ordering relationship.

[0080] In step 104, the standardized data is the data obtained by each node adapter converting the local business data of the corresponding training node according to the joint training data model based on the data ordering relationship.

[0081] Local business data refers to the data generated and used by the training node during its own business operations. The format, field meanings, and representation of local business data are defined by the system to which the training node belongs.

[0082] When performing format conversion on local business data, the node adapter uses the jointly trained data model as a constraint to ensure that the converted data conforms to the unified expression method defined by the jointly trained data model in terms of field structure, field attributes, value units, and resolution.

[0083] Data ordering relationships define the data supply and reception relationships between source and target training nodes, and specify the applicable data interaction rules for the corresponding interactive data. The target training node refers to the training node designated as the data receiver under the data ordering relationship.

[0084] In the specific implementation process, the interconnection management platform first receives standardized data reported by each node adapter. Each node adapter extracts local business data according to the system to which its training node belongs, and performs field mapping, attribute constraint filling, unit unification, and structured encapsulation on the local business data according to the joint training data model, thereby forming standardized data.

[0085] When generating standardized data, the node adapter simultaneously performs scope trimming on local business data based on the corresponding data ordering relationship, removes data items that are not allowed to be distributed, and generates standardized expressions that conform to the jointly trained data model for data items belonging to the data ordering relationship.

[0086] Then, the node adapter sends the obtained standardized data to the interconnection management platform. After receiving the standardized data, the interconnection management platform registers the receipt of the standardized data and determines the target training node based on the data subscription relationship.

[0087] After identifying the target training node, the interconnect management platform distributes the standardized data to the node adapter of that target training node. During the distribution process, the interconnect management platform controls the distribution direction, recipients, and timing. Based on the supply and receiving relationships defined by the data ordering relationship, the interconnect management platform pushes the standardized data corresponding to at least one target training node to its node adapter, and does not distribute it to unauthorized training nodes.

[0088] Then, the node adapter of the target training node receives standardized data issued by the interconnection management platform and provides the target training node with data content for subsequent use accordingly. Regarding the timing of the issuance, in one implementation, the interconnection management platform pushes standardized data to the node adapter of the target training node according to a preset push strategy for the data subscription relationship. The push strategy includes at least one of real-time push, timed push, update-triggered push, or one-time push, thereby ensuring that the standardized data reaches the node adapter of the target training node at the appropriate time in different task scenarios.

[0089] Step 104 enables the Interconnect Management Platform to act as both the receiver and distributor of standardized data during the joint training process. The Interconnect Management Platform receives standardized data sent by the node adapter on the source training node's side and, based on data subscription relationships, distributes this standardized data to the node adapter of at least one target training node that matches that data subscription relationship. Thus, the production, transmission, and deployment of standardized data are all conducted under the constraints of the joint training data model, data interaction rules, and data subscription relationships. Data output from the source training node is not directly propagated in the network in its original local business data format. Instead, it is converted into standardized data by the node adapter based on the joint training data model and reported to the Interconnect Management Platform. The Interconnect Management Platform then distributes this standardized data to the node adapter of the target training node according to the data subscription relationship. In this way, data interaction between training nodes does not rely on temporary point-to-point negotiation but is uniformly scheduled by the Interconnect Management Platform. This also ensures that different training nodes receive standardized data that conforms to the joint training data model, thereby avoiding problems such as data meaning conflicts, inconsistent field interpretations, and inconsistent value scales caused by different local business data definition methods of each training node. Furthermore, it keeps the distribution scope, transmission direction, and transmission rhythm of data under control during the joint training process.

[0090] In one possible implementation, refer to Figure 3 , Figure 3 This is the third flowchart of the heterogeneous system interconnection method for the field of simulated joint training provided by the present invention. The method also includes steps 301 to 303: Step 301: During the training preparation phase, control the key performance parameters of the training target system to perform full or incremental synchronization.

[0091] Step 302: During the training implementation phase, the synchronization of entity state data between training nodes is managed through a message queue mechanism. The received situational data is encapsulated into messages and sent to the message queue, and the messages are controlled to be distributed from the message queue to the corresponding target training nodes.

[0092] Step 303: During the training, evaluation and withdrawal phase, control the synchronous transmission of data files, select the appropriate transmission strategy according to the characteristics of the data files, perform consistency verification on the transmitted data, and control the data that passes the verification to be stored on the target training node.

[0093] In step 301, the training preparation phase refers to the preparatory process before the joint training begins. The training target system is the actual system to which the training nodes participating in the joint training belong. Key performance parameters refer to the parameters used by the training target system to characterize the system's operational characteristics and capability boundaries during joint training; these parameters are used as fundamental constraints in the joint training. Full synchronization refers to performing a one-time alignment of all key performance parameters across multiple training nodes, ensuring that each training node holds consistent initial parameters. Incremental synchronization refers to performing alignment only on the key performance parameters that have changed when parameter updates occur.

[0094] During the training preparation phase, the interconnection management platform performs full or incremental synchronization of the key performance parameters of the participating systems to ensure that all training nodes maintain consistency in the definition of key performance parameters before joint training begins. The platform controls the synchronization scope, target training nodes, and timing during synchronization to guarantee that key performance parameters are consistent across all training nodes at the start of training, thereby establishing unified initial foundational data for the subsequent joint training process.

[0095] In step 302, the training implementation phase refers to the actual period during joint training. Entity status data refers to the description of the status information of participating entities by training nodes during the training implementation phase. Participating entities include objects that participate in the execution of tasks in the training plan. Situation data refers to the information used to describe the training situation during the training process. Situation data reflects the progress of the task flow, the status of participating entities, and changes in the training environment during the training process.

[0096] During the training and implementation phase, the interconnection management platform receives and encapsulates situational data, forming messages. The platform then sends these messages to a message queue for centralized management. The message queue mechanism refers to the process by which the interconnection management platform receives, buffers, and distributes the encapsulated messages.

[0097] The interconnection management platform controls the message distribution direction from the message queue based on the synchronization requirements between training nodes, and distributes messages from the message queue to the corresponding target training nodes. The target training node is determined based on the established data subscription relationship between the training task and the training nodes to be the training node that should receive the entity's state data.

[0098] Through the above process, the interconnected management platform uniformly schedules the synchronization of entity state data during the training implementation phase. Training nodes receive entity state data related to themselves according to the distribution results of the interconnected management platform, thereby maintaining the consistency of the situation among training nodes during the training implementation phase.

[0099] In step 303, the training evaluation and withdrawal phase refers to the phase following the completion of joint training. This phase involves summarizing training process data, organizing training results, and withdrawing the training from the training site. Data files refer to the recorded document content generated during the training process, including training analysis and evaluation data, audio and video recording data, and summary report data.

[0100] The interconnected management platform selects appropriate transmission strategies based on the characteristics of the data files and controls the synchronous transmission of these data files between different training nodes during the training, evaluation, and withdrawal phases. The transmission strategy refers to the transmission method and arrangement adopted for different types of data files. Different types of data files differ in size, timeliness, and purpose, and the transmission strategy matches these differences.

[0101] While controlling the synchronous transmission of data files, the interconnection management platform performs consistency checks on the transmitted data. Consistency checks refer to the interconnection management platform comparing the data files obtained by the receiving training nodes with the data files provided by the sending training nodes to confirm the integrity and correctness of the data files during transmission.

[0102] Once the consistency check passes, the interconnection management platform controls the storage of the data file on the target training node. Here, the target training node refers to the training node responsible for retention during the training evaluation and withdrawal phase.

[0103] Through the above process, the training analysis and evaluation results, audio and video records, and summary data generated during the training evaluation and withdrawal phase are stored in a consistent state across multiple training nodes, and are in a searchable and reusable state after training is completed.

[0104] In one possible implementation, refer to Figure 4 , Figure 4 This is the fourth flowchart of the heterogeneous system interconnection method for the field of simulated joint training provided by the present invention. The method also includes steps 401 to 403: Step 401: During the training implementation phase, after receiving the standardized data from the node adapter, the standardized data is unpacked to be broken down into single-frame data.

[0105] Step 402: Verify the single frame data according to the preset data verification rules, and discard the single frame data if the verification fails.

[0106] Step 403: Parse the successfully verified single-frame data into structured data according to the preset data parsing rules, and record and store the structured data.

[0107] In step 401, the standardized data is generated by the node adapter in step 104 based on the joint training data model. The standardized data is data content with a unified format and field definitions. A single frame of data refers to the smallest resolvable unit obtained by dividing the standardized data according to a preset frame structure. Each frame contains a complete set of data fields used to represent the state of a certain point in time or a certain event during the training process.

[0108] During the unpacking process, the interconnect management platform identifies the boundaries of data frames based on the structure description file of the jointly trained data model. It segments the received standardized data according to field order and data type, breaking down the continuous data stream into independent single frames. During unpacking, the platform identifies the frame header, frame length, and frame tail identifiers and records the frame sequence number to ensure the temporal integrity of the data during subsequent parsing and verification.

[0109] After unpacking, the standardized data is restored to a data set consisting of multiple single-frame data. Each frame corresponds to an independent interaction record, providing the input basis for data verification and parsing in subsequent steps.

[0110] In step 402, the data verification rules are a set of rules set by the interconnection management platform before the joint training system is deployed, which are used to verify the correctness and integrity of single frame data.

[0111] Data validation rules include format validation, field value range validation, timestamp continuity validation, and frame sequence number consistency validation. Format validation confirms whether a single frame of data conforms to the field type and length requirements defined in the joint training data model. Field value range validation determines whether field values ​​are within a reasonable range, such as whether they exceed defined upper and lower limits. Timestamp continuity validation checks whether the timestamps of the data frames conform to the logical order of the training process. Frame sequence number consistency validation confirms that no frames were lost or duplicated during reception.

[0112] The interconnected management platform performs the above verification operations on each frame of data. When a frame fails any verification item, that frame of data is marked as invalid and removed from the data set. Frames of data that pass verification are retained for the next stage of data parsing.

[0113] In step 403, the data parsing rules define the logical meaning of each field in a single frame of data, the parsing order, and the corresponding storage field mapping relationship.

[0114] During the parsing process, the interconnected management platform reads fields from single-frame data and converts the field content into structured data objects according to data parsing rules. These structured data objects are stored in the database in an indexable format. When storing, the platform adds a timestamp, source node identifier, and data type identifier to each structured data record to support subsequent retrieval and statistical analysis. The structured data records are stored using both real-time and batch writing methods, with the platform selecting the appropriate method based on the timeliness requirements of the training task. After parsing and storage, the platform creates a corresponding record set for real-time monitoring, result evaluation, and post-training review.

[0115] By executing steps 401 to 403, the interconnected management platform automatically receives, verifies, parses, and stores standardized data. This ensures that all types of interactive data generated during the training phase undergo a complete verification process upon entering the system, guaranteeing that the data entering the database is correctly formatted, has complete fields, and is logically coherent. This process avoids inconsistencies in data structure or missing fields in data uploaded from different nodes, ensuring the reliability and consistency of the joint training data and providing accurate data support for real-time monitoring of the training process and evaluation and analysis of training results.

[0116] In one possible implementation, refer to Figure 5 , Figure 5 This is the fifth flowchart of the heterogeneous system interconnection method for the field of simulated joint training provided by the present invention. The method further includes step 501: Step 501: Real-time monitoring of the network status and access status of multiple training nodes; real-time monitoring includes: receiving and processing node discovery data periodically published by each node adapter; maintaining node status heartbeat information with the node adapter after node discovery is completed; and generating real-time alarm information when a training node is detected to be offline or in an abnormal state, according to a preset warning policy.

[0117] In step 501, "network status" refers to the network connection status between the training node and the interconnection management platform, including whether the connection is established, whether the link is stable, and the communication latency. "Access status" refers to the registration and maintenance status of the training node in the interconnection management platform, including whether the node has successfully joined the joint training network and whether the node's current operating status is normal. The node adapter is the communication component between the training node and the interconnection management platform, responsible for periodically sending node discovery data to the interconnection management platform and maintaining status heartbeat information. Node discovery data refers to the data content used by the node adapter to identify its own information and communication capabilities during the communication initialization phase. Node status heartbeat information refers to the status information periodically reported by the node adapter after communication is established, used to maintain the node's online status. "Alarm policy" refers to the alarm triggering conditions and alarm output methods preset in the interconnection management platform for node disconnection or abnormal status.

[0118] In practice, during the joint training initialization phase, the interconnection management platform assigns unique identification information to the node adapter of each training node. Each node adapter sends node discovery data to the interconnection management platform upon joining the joint training network. This data includes the node identifier, the training system to which the node belongs, supported data topics, and communication configuration parameters. Upon receiving the node discovery data, the interconnection management platform establishes a corresponding connection instance for the node and performs identity verification and resource registration based on the information contained in the node discovery data. After completing node discovery, the interconnection management platform establishes a communication link with the node adapter, forming the foundation for node monitoring. Subsequently, the interconnection management platform controls the node adapter to periodically publish node discovery data to confirm that the node remains active and to check the reachability of the network link. Upon receiving the periodically published node discovery data, the interconnection management platform updates the node's real-time connection status based on the node identifier.

[0119] Once the node discovery process is complete, the interconnect management platform and the node adapter enter the node status maintenance phase. The node adapter and the interconnect management platform maintain node status heartbeat information. This heartbeat information includes the node's operating load, data exchange rate, network latency, packet loss rate, and device health status. The interconnect management platform continuously assesses the node's operational status by receiving and processing this heartbeat information. Internally, the interconnect management platform records the heartbeat time intervals and forms a time series model based on continuous heartbeat data. If the interconnect management platform does not receive a heartbeat from a node within a predetermined time window, it determines that the node may be offline or experiencing a network anomaly.

[0120] The interconnection management platform generates real-time alarms when it detects a training node going offline or exhibiting abnormal status, based on a preset warning policy. The warning policy defines the alarm triggering conditions, alarm levels, and alarm output methods. Alarm triggering conditions include heartbeat timeouts, communication interruptions, abnormal data reporting, or incorrect status data. Alarm levels are categorized according to the node's importance in the joint training process. Alarm output methods include marking abnormal nodes on the interconnection management platform's visual monitoring interface, generating alarm logs, and sending alarm messages to the system administrator. After generating the alarm information, the interconnection management platform binds the alarm information to the node identifier and writes it to the alarm log module for subsequent status analysis and system maintenance.

[0121] In one possible implementation, refer to Figure 6 , Figure 6 This is the sixth flowchart of the heterogeneous system interconnection method for the field of simulated joint training provided by the present invention. The method further includes steps 601 to 604: Step 601: Configure and distribute the collection and recording rules to each node adapter. The collection and recording rules define collection strategies including real-time recording, cached recording, or timeout recording.

[0122] Step 602: Receive the data collection node information registered by each node adapter and the working status reported during the training implementation phase.

[0123] Step 603: Receive business data, task process data, training plan data, training entity data, and task environment data related to the training process collected by the node adapter according to the collection and recording rules.

[0124] Step 604: After training, provide the function of retrieving the received data based on the acquisition time, data source or data classification, and perform data cleaning on the data recorded in the system according to the data cleaning rules.

[0125] In step 601, the interconnection management platform configures and distributes data collection and recording rules to each node adapter. Data collection and recording rules refer to the set of control parameters defined by the interconnection management platform for data collection and recording during joint training. These rules define collection strategies including real-time recording, cached recording, and timeout recording. Real-time recording means that the node adapter continuously and immediately sends the collected data to the interconnection management platform for storage during training. Cached recording means that the node adapter caches a certain amount of data or a period of time locally before batch reporting it. Timeout recording means that the node adapter archives and reports the collected data for a set time interval. The interconnection management platform determines the type and parameter settings of the collection strategy based on the training task scale, network load, and training node performance. The interconnection management platform distributes the data collection and recording rules to each node adapter in the form of configuration instructions, enabling each node adapter to perform data collection and reporting according to these rules during the training implementation phase.

[0126] In step 602, the interconnect management platform receives the data collection node information registered by each node adapter and the working status reported during the training and implementation phase. Data collection node information refers to the identity data registered by the node adapter with the interconnect management platform when it starts the data collection function, including node identifier, data collection module configuration, data collection scope, data subject, and storage path. Working status refers to the operational status information periodically reported by the node adapter during the training and implementation phase, including data collection progress, data cache capacity, reporting rate, and abnormal status flags. After receiving the data collection node information, the interconnect management platform establishes a data collection node directory and records the data collection capabilities and status of each node. During the training and implementation phase, the interconnect management platform continuously monitors the working status of the node adapters and checks whether the data collection progress of each node meets the requirements of the data collection recording rules. When a node reports an abnormal status flag or a data collection interruption occurs, the interconnect management platform triggers an alarm or reissues the data collection rule instructions based on its internal monitoring logic to ensure the continuity and integrity of the data collection process.

[0127] In step 603, the interconnection management platform receives business data, task flow data, training plan data, participating entity data, and task environment data related to the training process, collected by the node adapters according to the collection and recording rules. Business data consists of operational information generated by the training nodes during training; task flow data comprises operational steps and execution status information generated during training activities; training plan data includes the pre-established plan and execution progress information; participating entity data represents the operational status data of each participating system; and task environment data consists of parameter data of the external environment during training. The node adapters determine the collection frequency and scope according to the collection and recording rules, standardize the collected data, and send it to the interconnection management platform. The interconnection management platform classifies and registers the received data, and stores it hierarchically based on data source, data type, and collection time. During data reception, the interconnection management platform performs data integrity checks and timestamp alignment to ensure consistency in both time and content dimensions for data collected by multiple nodes.

[0128] In step 604, after training, the interconnected management platform provides the function of retrieving received data based on collection time, data source, or data category, and performs data cleaning on the recorded data in the system according to data cleaning rules. Data cleaning rules refer to the management specifications formulated by the interconnected management platform for the retention and deletion of historical data, including retention period, cleaning conditions, and cleaning methods. During the training evaluation phase, the interconnected management platform queries the collected data according to the retrieval conditions. It can filter training records within a certain time period by collection time, distinguish the collection content of different training nodes by data source, or select specific types of training data for analysis by data category. After completing data retrieval and analysis, the interconnected management platform cleans up expired, redundant, and invalid data according to the data cleaning rules to free up storage space and maintain the manageability of data resources. The interconnected management platform selects the specific cleanup operation execution method according to the system configuration.

[0129] It should be noted that after the interconnection management platform is deployed, the system administrator can view the real-time acquisition status information of each node through the acquisition management interface, including acquisition rate, cache utilization, reporting latency, and data classification statistics. The interconnection management platform dynamically adjusts the acquisition strategy parameters in the acquisition recording rules based on the current network load and the operating status of the training nodes. When network bandwidth is strained, the system automatically switches to cache recording mode to reduce real-time transmission pressure; when the task enters a critical stage, the interconnection management platform reverts to the real-time recording strategy to ensure data timeliness.

[0130] Meanwhile, the real-time monitoring interface displays the acquisition progress and data distribution through data visualization. Administrators can manually intervene based on the visualization results, such as pausing, restarting, or reconfiguring the acquisition task. This feature ensures that the acquisition and recording process remains flexible and highly controllable even in complex training environments.

[0131] Furthermore, the interconnected management platform performs data file transfer functions within the distributed training interaction service. Data file transfer includes file transfer proxy, file transfer control, file transfer configuration management, file transfer monitoring management, and data file transfer rules. The file transfer proxy is used to establish file transfer channels between different nodes, and the file transfer control is used to schedule file transfer tasks according to the training task phase. During the training preparation phase, the interconnected management platform configures transfer parameters based on task requirements, determining the target node, file path, bandwidth limits, and security verification methods.

[0132] During the training implementation phase, the interconnected management platform establishes multi-channel transmission connections through a file transfer agent, employing a chunked transmission mechanism for large training files to improve transmission efficiency. During transmission, the platform monitors the file transmission status in real time, recording the transmission rate, progress, and number of errors. When a transmission interruption is detected, it automatically triggers a resume operation based on file transmission rules. During the training evaluation and withdrawal phase, the platform archives the file transmission logs, performs data integrity verification, and updates the training evaluation records based on the verification results. This process ensures the secure, efficient, and reliable transmission of large-scale training data files between geographically dispersed nodes.

[0133] Reference Figure 7 , Figure 7 This is a schematic diagram of the heterogeneous system interconnection device for the field of simulated joint training provided by the present invention. The device includes: The first processing module is used to construct a joint training data model according to the requirements of the joint training task. The joint training data model is used to define the attributes and data types of the data interacting between training nodes. The second processing module is used to generate data interaction rules based on the joint training data model. The data interaction rules are used to limit the processing method and transmission strategy for data interaction between training nodes. The second processing module is also used to establish data ordering relationships between training nodes according to data interaction rules; The third processing module is used to receive standardized data from each node adapter and send standardized data to the node adapter of at least one target training node. The standardized data is obtained by each node adapter converting the local business data of the corresponding training node according to the joint training data model based on the data ordering relationship.

[0134] It should be noted that the heterogeneous system interconnection device for the field of simulated joint training provided by the present invention can execute the heterogeneous system interconnection method for the field of simulated joint training of any of the above embodiments during specific operation, which will not be described in detail in this embodiment.

[0135] Figure 8 This is a schematic diagram of the structure of the electronic device provided by the present invention, such as... Figure 8 As shown, the electronic device may include: a processor 810, a communication interface 820, a memory 830, and a communication bus 840, wherein the processor 810, the communication interface 820, and the memory 830 communicate with each other through the communication bus 840. The processor 810 can call logical instructions in the memory 830 to execute a heterogeneous system interconnection method for the field of simulated joint training. This method includes: constructing a joint training data model according to the requirements of the joint training task, the joint training data model being used to define the attributes and data types of data interacting between training nodes; generating data interaction rules based on the joint training data model, the data interaction rules being used to limit the processing methods and transmission strategies for data interaction between training nodes; establishing data subscription relationships between training nodes according to the data interaction rules; receiving standardized data from each node adapter and sending standardized data to the node adapter of at least one target training node; the standardized data is obtained by each node adapter converting the local business data of the corresponding training node according to the joint training data model based on the data subscription relationship.

[0136] Furthermore, the logical instructions in the aforementioned memory 830 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0137] On the other hand, the present invention also provides a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium. The computer program includes program instructions, and when the program instructions are executed by a computer, the computer is able to execute the heterogeneous system interconnection method for the field of simulated joint training provided in the above embodiments.

[0138] In another aspect, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to perform the heterogeneous system interconnection method for the field of simulated joint training provided in the above embodiments.

[0139] The system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0140] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., including several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods of various embodiments or some parts of embodiments.

[0141] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for interconnecting heterogeneous systems in the field of simulated joint training, characterized in that, The method, applied to an interconnection management platform that communicates with multiple training nodes, wherein each training node is equipped with a corresponding node adapter, includes: A joint training data model is constructed based on the requirements of the joint training task. The joint training data model is used to define the attributes and data types of the data interacting between the training nodes. Data interaction rules are generated based on the joint training data model. These rules are used to define the processing methods and transmission strategies for data interaction between the training nodes. According to the data interaction rules, establish data ordering relationships between the training nodes; The system receives standardized data from each of the node adapters and distributes the standardized data to the node adapters of at least one target training node. The standardized data is obtained by each node adapter converting the local business data of the corresponding training node according to the joint training data model based on the data ordering relationship.

2. The heterogeneous system interconnection method for the field of simulated joint training according to claim 1, characterized in that, Establishing the data ordering relationship between the training nodes includes: Based on the training business domain, the joint training data model is configured as different data themes; Receive data product publication requests from the node adapter for the data topic, and review the publication requests; After the published application is approved, order requests for the published data products will be received from other node adapters; The order request is reviewed according to the data interaction rules to establish the data order relationship.

3. The heterogeneous system interconnection method for the field of simulated joint training according to claim 1, characterized in that, Also includes: During the training preparation phase, the key performance parameters of the training target system are synchronized fully or incrementally. During the training implementation phase, the synchronization of entity state data between training nodes is managed through a message queue mechanism. The received situation data is encapsulated into messages and sent to the message queue, and the messages are controlled to be distributed from the message queue to the corresponding target training nodes. During the training, evaluation, and withdrawal phase, the synchronous transmission of data files is controlled, and an appropriate transmission strategy is selected based on the characteristics of the data files. Consistency checks are performed on the transmitted data, and the data that passes the check is stored on the target training node.

4. The heterogeneous system interconnection method for the field of simulated joint training according to claim 1, characterized in that, Also includes: During the training implementation phase, after receiving standardized data from the node adapter, the standardized data is unpacked to be broken down into single-frame data. The single frame data is verified according to the preset data verification rules, and the single frame data is discarded when the verification fails. According to the preset data parsing rules, the successfully verified single-frame data is parsed into structured data, and the structured data is recorded and stored.

5. The heterogeneous system interconnection method for the field of simulated joint training according to claim 1, characterized in that, Also includes: The network status and access status of the multiple training nodes are monitored in real time. The real-time monitoring includes: Receive and process node discovery data periodically published by each of the node adapters; After completing node discovery with the node adapter, maintain node status heartbeat information with the node adapter; In addition, according to the preset warning strategy, when the training node is detected to be offline or in an abnormal state, real-time alarm information is generated.

6. The heterogeneous system interconnection method for the field of simulated joint training according to claim 1, characterized in that, Also includes: Configure and distribute the collection and recording rules to each of the node adapters. The collection and recording rules define collection strategies including real-time recording, cached recording, or timeout recording. Receive the acquisition node information registered by each of the node adapters and the working status reported during the training implementation phase; Receive business data, task process data, training plan data, training entity data, and task environment data related to the training process collected by the node adapter according to the collection and recording rules; After training, the system provides the ability to retrieve received data based on acquisition time, data source, or data category, and performs data cleaning on the recorded data in the system according to data cleaning rules.

7. The heterogeneous system interconnection method for the field of simulated joint training according to claim 1, characterized in that, The step of sending the standardized data to the node adapter of at least one target training node includes: According to a preset push strategy for the data subscription relationship, the standardized data is pushed to the node adapter of the target training node. The push strategy includes at least one of real-time push, timed push, update-triggered push, or one-time push.

8. The heterogeneous system interconnection method for the field of simulated joint training according to claim 1, characterized in that, The data interaction rules include data filtering rules, data compression rules, data cleaning rules, and data forwarding rules.

9. A heterogeneous system interconnection device for the field of simulated joint training, characterized in that, The device is applied to an interconnection management platform that communicates with multiple training nodes, each of which is equipped with a corresponding node adapter. The device includes: The first processing module is used to construct a joint training data model according to the requirements of the joint training task. The joint training data model is used to define the attributes and data types of the data interacting between the training nodes. The second processing module is used to generate data interaction rules based on the joint training data model. The data interaction rules are used to limit the processing method and transmission strategy for data interaction between the training nodes. The second processing module is also used to establish a data ordering relationship between the training nodes according to the data interaction rules; The third processing module is used to receive standardized data from each of the node adapters and send the standardized data to the node adapter of at least one target training node; the standardized data is obtained by each of the node adapters converting the local business data of the corresponding training node according to the joint training data model based on the data ordering relationship.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the heterogeneous system interconnection method for the field of simulated joint training as described in any one of claims 1 to 8.

11. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the heterogeneous system interconnection method for the field of simulated joint training as described in any one of claims 1 to 8.

12. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the heterogeneous system interconnection method for the field of simulated joint training as described in any one of claims 1 to 8.

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