Intelligent switch gateway control method and device for multi-protocol communication

Abstract

The present application provides a method and device for controlling a smart switch gateway with multi-protocol communication, the method comprising: constructing a knowledge graph according to a network topology diagram and protocol information of the smart switch to obtain a switch networking knowledge graph; determining an inference rule according to the switch networking knowledge graph to obtain an inference rule engine; obtaining historical data packets of the smart switch in a preset time period, and performing parsing and conversion to obtain a data conversion module; integrating the inference rule engine and the data conversion module to obtain a protocol conversion module of the smart gateway; dynamically designing the protocol conversion module according to a preset implementation framework to obtain a dynamic protocol adaptation mechanism; evaluating and optimizing the performance of the dynamic protocol adaptation mechanism to obtain an optimized protocol conversion system, the optimized protocol conversion system being used to assist the smart switch gateway in controlling the smart switch.

Description

Technical Field

[0001] The present application relates to the field of wireless communication technology, and in particular to a method and device for controlling a multi-protocol communication intelligent switch gateway. Background Art

[0002] Currently, in the field of Internet of Things (IoT), with the popularity of smart devices, the demand for data interoperability between different devices is increasing. However, different devices and systems usually use their own communication protocols and data formats, which leads to compatibility issues in data transmission. Especially in the smart home environment, common smart devices such as WiFi smart switches, ZigBee smart switches, Bluetooth smart switches, and Z-Wave smart switches usually use different communication protocols, which brings great challenges to the real-time transmission and application of data. Summary of the invention

[0003] The present application provides a multi-protocol communication intelligent switch gateway control method and device, which are used to process the communication data of intelligent switches with different transmission protocols to improve their transmission speed and accuracy.

[0004] In a first aspect, an embodiment of the present application provides a multi-protocol communication intelligent switch gateway control method, the method comprising:

[0005] Construct a knowledge graph based on the network topology and protocol information of the intelligent switch to obtain a switch networking knowledge graph;

[0006] Determine an inference rule according to the switch networking knowledge graph to obtain an inference rule engine;

[0007] Obtaining historical data packets of the intelligent switch in a preset time period, and performing parsing and conversion to obtain a data conversion module;

[0008] Integrate the inference rule engine and the data conversion module to obtain a protocol conversion module of the intelligent gateway;

[0009] Dynamically designing the protocol conversion module according to a preset implementation framework to obtain a dynamic protocol adaptation mechanism;

[0010] The dynamic protocol adaptation mechanism is evaluated and performance optimized to obtain an optimized protocol conversion system, and the optimized protocol conversion system is used to assist the intelligent switch gateway in controlling the intelligent switch.

[0011] In a second aspect, an embodiment of the present application provides a multi-protocol communication intelligent switch gateway control device, the device comprising:

[0012] A picture construction module is used to construct a knowledge graph based on the network topology and protocol information of the smart switch to obtain a switch networking knowledge graph;

[0013] A rule reasoning module, used to determine the reasoning rules according to the switch networking knowledge graph to obtain a reasoning rule engine;

[0014] A data analysis module, used to obtain historical data packets of the intelligent switch in a preset time period, and perform analysis and conversion to obtain a data conversion module;

[0015] An engine integration module, used to integrate the inference rule engine and the data conversion module to obtain a protocol conversion module of the intelligent gateway;

[0016] A dynamic adaptation module, used to dynamically design the protocol conversion module according to a preset implementation framework to obtain a dynamic protocol adaptation mechanism;

[0017] The system optimization module is used to evaluate and optimize the performance of the dynamic protocol adaptation mechanism to obtain an optimized protocol conversion system, and the optimized protocol conversion system is used to assist the intelligent switch gateway in controlling the intelligent switch.

[0018] In a third aspect, an embodiment of the present application provides an electronic device, the electronic device comprising a memory and a processor;

[0019] The memory is used to store computer programs;

[0020] The processor is used to execute the computer program and implement the multi-protocol communication intelligent switch gateway control method as described in any one of the embodiments of the present application when executing the computer program.

[0021] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the processor enables the processor to implement a multi-protocol communication intelligent switch gateway control method as described in any one of the embodiments of the present application.

[0022] The embodiment of the present application provides a method for controlling a smart switch gateway with multi-protocol communication, the method comprising: constructing a knowledge graph according to a network topology diagram and protocol information of the smart switch to obtain a switch networking knowledge graph; determining an inference rule according to the switch networking knowledge graph to obtain an inference rule engine; obtaining historical data packets of the smart switch in a preset time period, and parsing and converting them to obtain a data conversion module; integrating the inference rule engine and the data conversion module to obtain a protocol conversion module of the smart gateway; dynamically designing the protocol conversion module according to a preset implementation framework to obtain a dynamic protocol adaptation mechanism; evaluating and optimizing the performance of the dynamic protocol adaptation mechanism to obtain an optimized protocol conversion system, the optimized protocol conversion system being used to assist the smart switch gateway in controlling the smart switch. In the above method, an inference rule engine in the form of a knowledge graph is determined according to the network topology and protocol information of the intelligent switch, and then the protocol information is processed in advance in combination with the parsing and conversion of historical data packets to form a complete protocol conversion module. The protocol conversion module is then dynamically designed to obtain a dynamic protocol adaptation mechanism, which can flexibly respond to changes in different protocols and network environments. After evaluation and performance optimization, the final protocol conversion system has higher efficiency and stability, reduces the complexity of system maintenance and upgrades, and significantly improves the control capability and efficiency of the intelligent switch gateway in a complex multi-protocol environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying any creative work.

[0024] Figure 1 A schematic flow chart of a multi-protocol communication intelligent switch gateway control method provided in an embodiment of the present application;

[0025] Figure 2 A schematic block diagram of a multi-protocol communication intelligent switch gateway control device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0026] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0027] The flowcharts shown in the accompanying drawings are only examples and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps may also be decomposed, combined or partially merged, so the actual execution order may change according to actual conditions.

[0028] It should also be understood that the terms used in this application specification are only for the purpose of describing specific embodiments and are not intended to limit the application. As used in this application specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0029] It should be further understood that the term “and / or” used in the specification and appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0030] See also Figure 1 , Figure 1 The embodiment of the present application also provides a schematic flow chart of a multi-protocol communication intelligent switch gateway control method. Figure 1 As shown, the specific steps of the multi-protocol communication intelligent switch gateway control method include: S101-S106.

[0031] S101. Construct a knowledge graph based on the network topology and protocol information of the intelligent switch to obtain a switch networking knowledge graph.

[0032] Exemplarily, the network structure and communication protocol information of the smart switch are integrated into a structured knowledge representation. The network topology provides the physical connection relationship between the smart switches, while the protocol information contains the communication standards and data formats used by each switch. By mapping this information into the knowledge graph, a comprehensive switch networking knowledge graph can be created. This switch networking knowledge graph not only contains nodes (representing switches) and edges (representing connections), but also includes the protocol attributes, communication capabilities and other related features of each node. This structured representation reduces the difficulty of understanding and analyzing complex network relationships, and provides a basis for subsequent reasoning and decision-making.

[0033] S102. Determine inference rules according to the switch networking knowledge graph to obtain an inference rule engine.

[0034] For example, after the switch networking knowledge graph has been constructed, reasoning rules that can run on the knowledge structure are formulated. These reasoning rules are designed based on domain expert knowledge and network communication principles to handle various possible network situations and communication scenarios. Reasoning rules may include how to handle conversions between different protocols, how to optimize data routing, how to handle communication conflicts, etc. By encoding these rules into the reasoning engine, the network status can be automatically analyzed and intelligent decisions can be made. The design of the reasoning rule engine needs to take into account efficiency, scalability, and robustness to ensure that it can quickly and accurately handle various complex network situations.

[0035] S103: Obtain historical data packets of the intelligent switch in a preset time period, and perform analysis and conversion to obtain a data conversion module.

[0036] Exemplarily, it involves collecting and processing historical communication data generated by intelligent switches within a specific time range. By capturing these data packets from the network, the interaction information, status updates, and control commands between intelligent switches are analyzed. Next, these raw data packets are parsed and converted to extract useful information and convert it into a standardized format. In this way, the protocol conversion situation in a specific time period is predicted, the required protocol files are loaded in advance, and the speed of protocol conversion is accelerated. This process may involve operations such as protocol parsing, data cleaning, and format conversion. The converted data is easier for the system to understand and process, providing a basis for subsequent analysis and decision-making. The design of the data conversion module needs to take into account the characteristics of different protocols to ensure that data packets in various formats can be accurately interpreted and converted into a unified internal representation.

[0037] S104: Integrate the inference rule engine and the data conversion module to obtain a protocol conversion module of the intelligent gateway.

[0038] Exemplarily, a complete protocol conversion module is formed by integrating the previously developed inference rule engine and data conversion module. This integration process requires designing interfaces and data flows to ensure that the two components can work together seamlessly. The main function of the protocol conversion module is to receive data from different protocols, convert it into a standard format using the data conversion module, and then use the inference rule engine to analyze and process the data, and finally output data suitable for the target protocol. This module also needs to handle various abnormal situations.

[0039] S105. Dynamically design the protocol conversion module according to the preset implementation framework to obtain a dynamic protocol adaptation mechanism.

[0040] This step involves the flexible and dynamic design of the protocol conversion module according to the pre-set framework. During the design process, it is necessary to consider various possible protocol types and data formats, and build a mechanism that can adapt to different protocols. This dynamic protocol adaptation mechanism should be able to identify the incoming protocol type, automatically select the appropriate conversion algorithm, and convert the data into the target protocol format. At the same time, it should also be extensible to facilitate the addition of new protocol support in the future. Design patterns such as strategy pattern and adapter pattern may be used in the design to achieve high flexibility and maintainability. In addition, it is also necessary to consider how to deal with details such as protocol version differences and error handling mechanisms to ensure the stability and reliability of the entire adaptation process.

[0041] S106. Evaluate and optimize the performance of the dynamic protocol adaptation mechanism to obtain an optimized protocol conversion system, and the optimized protocol conversion system is used to assist the smart switch gateway in controlling the smart switch.

[0042] This step focuses on comprehensive evaluation and optimization of the designed dynamic protocol adaptation mechanism. During the evaluation process, key performance indicators such as the system's response time, throughput, and resource usage need to be considered, and a large number of tests need to be conducted to discover potential bottlenecks and problems. Optimization may involve multiple aspects, such as improving algorithm efficiency, optimizing memory usage, introducing caching mechanisms, etc. At the same time, it is also necessary to ensure the stability and reliability of the system under various extreme conditions. The optimized protocol conversion system should be able to efficiently handle various protocol conversion requirements and provide reliable protocol conversion support for the smart switch gateway. This optimization process may be an iterative process that requires multiple tests and adjustments to achieve the best results. Ultimately, the optimized system should be able to meet the real-time and reliability requirements of smart switch control and provide strong support for the stable operation of the smart home system.

[0043] The embodiment of the present application provides a multi-protocol communication intelligent switch gateway control method, the method comprising: constructing a knowledge graph according to the network topology diagram and protocol information of the intelligent switch to obtain a switch networking knowledge graph; determining the inference rule according to the switch networking knowledge graph to obtain an inference rule engine; obtaining the historical data packets of the intelligent switch in a preset time period, and parsing and converting them to obtain a data conversion module; integrating the inference rule engine and the data conversion module to obtain a protocol conversion module of the intelligent gateway; dynamically designing the protocol conversion module according to a preset implementation framework to obtain a dynamic protocol adaptation mechanism; evaluating and optimizing the performance of the dynamic protocol adaptation mechanism to obtain an optimized protocol conversion system, and the optimized protocol conversion system is used to assist the intelligent switch gateway in controlling the intelligent switch. In the above method, a complete protocol conversion module is formed by combining the parsing and conversion of historical data packets, and a dynamically designed adaptation mechanism is adopted to enable the system to flexibly respond to changes in different protocols and network environments. After evaluation and performance optimization, the protocol conversion system finally formed has higher efficiency and stability, greatly reducing the complexity of system maintenance and upgrades, and significantly improving the control capability and efficiency of the intelligent switch gateway in a complex multi-protocol environment.

[0044] This method not only improves the adaptability and interoperability of the smart switch gateway in a multi-protocol environment, but also enhances the scalability and flexibility of the system. Through the application of knowledge graphs and inference rules, it can more intelligently understand and process complex network topologies and protocol relationships, thereby improving control accuracy and response speed. The introduction of a dynamic protocol adaptation mechanism enables the system to adaptively handle different types of smart switches and communication protocols.

[0045] In order to more clearly introduce the technical solution of the present application, the technical solution of the present application will be introduced through specific embodiments below. It should be noted that the specific embodiments are used to expand the technical solution of the present application, but are not intended to limit the present application.

[0046] In some embodiments, a knowledge graph is constructed based on the network topology diagram and protocol information of the intelligent switch to obtain a switch networking knowledge graph, and the specific steps include: S1011-S1015.

[0047] S1011, traversing the network topology diagram of the intelligent switch to obtain a topology relationship matrix, and determining a switch adjacency matrix according to the topology relationship matrix.

[0048] Exemplarily, when traversing the network topology of the smart switch, a depth-first search algorithm is used. The smart switch network is represented as a graph structure, in which nodes represent smart switches and edges represent connections between switches. An adjacency matrix or an adjacency list can be used to store the graph structure.

[0049] Select a starting node, mark it as visited, recursively visit the unvisited neighbor nodes of the node, and when there are no unvisited neighbors, backtrack to the previous node and repeat this process until all nodes are visited. In the above process, a stack is used instead of recursion to avoid stack overflow problems in large networks. Collect additional information during the traversal process, such as the depth of each node, parent node, etc.

[0050] S1012: Classify and cluster the protocol information of the intelligent switch according to the topological relationship matrix to obtain a protocol category vector.

[0051] Exemplarily, the classification clustering process includes clustering the protocol information using a K-means algorithm, and determining the optimal number of clusters by calculating a silhouette coefficient.

[0052] S1013. Perform semantic embedding on the protocol category vector to obtain a protocol semantic vector.

[0053] Exemplarily, the semantic embedding process includes using a preset Word2Vec model to embed the protocol category into words, and predicting the probability distribution of context words through the Skip-gram algorithm to obtain the protocol semantic vector.

[0054] S1014. Through multi-layer convolution operations, the topological relationship matrix and the protocol semantic vector are graph-embedded to obtain a node representation vector.

[0055] Exemplarily, the graph embedding process includes using a Graph Convolutional Network (GCN) model to aggregate neighbor node information through multi-layer convolution operations.

[0056] S1015. Perform knowledge graph construction processing on the node representation vector to obtain a switch networking knowledge graph.

[0057] Exemplarily, the knowledge graph construction process includes using the TransE algorithm to learn low-dimensional vector representations of entities and relations, and optimizing the semantic relationships between entities by minimizing an energy function.

[0058] In some embodiments, a knowledge graph is constructed and processed on the node representation vector to obtain a switch networking knowledge graph, including: performing sequence labeling on the node representation vector to obtain a node labeling vector, solving the optimal labeling path of the node labeling vector by a preset Viterbi algorithm to obtain an entity set; performing relationship classification on the entity set by using a convolutional neural network model of an attention mechanism to obtain a relationship triple set; calculating the semantic similarity of the relationship triple set to obtain a similarity matrix, processing the similarity matrix by using a hierarchical clustering algorithm to obtain an ontology concept hierarchy; performing frequent item set calculations on the ontology concept hierarchy and the relationship triple set to obtain a candidate rule set, screening the candidate rule set according to preset minimum support and confidence thresholds to obtain an inference rule set; calculating the entity similarity in the inference rule set according to a preset graph matching algorithm to obtain an entity similarity matrix, performing probabilistic inference on the entity similarity matrix by using a Markov logic network to obtain a fused knowledge graph; performing low-dimensional vector representation learning on the entities and relationships in the fused knowledge graph to obtain an initial vector representation, optimizing the initial vector representation to obtain a switch networking knowledge graph.

[0059] The solution achieves accurate entity recognition through conditional random fields and Viterbi algorithm, and the convolutional neural network with remote supervision and attention mechanism improves the accuracy of relationship extraction. WordNet and hierarchical clustering algorithm construct semantically rich ontology structure, and the preset graph matching algorithm (APRIORI algorithm) and rule screening mechanism ensure the quality of inference rules. The graph matching algorithm and Markov logic network realize knowledge fusion and improve the integrity of the graph. The negative sampling optimization method effectively learns the low-dimensional representation of entities and relationships. The overall solution combines a variety of advanced algorithms to realize full-process intelligent processing from entity recognition to knowledge representation, significantly improves the construction efficiency and quality of switch networking knowledge graph, and provides a solid knowledge foundation for intelligent switch gateway control.

[0060] In some embodiments, an inference rule is determined based on a switch networking knowledge graph to obtain an inference rule engine, including: performing subgraph pattern matching on the switch networking knowledge graph to obtain a candidate rule set; determining a rule scoring matrix based on the candidate rule set and the switch networking knowledge graph, performing non-dominated sorting on the rule scoring matrix to obtain a Pareto optimal rule set; performing rule conflict detection on the switch networking knowledge graph based on the Pareto optimal rule set to obtain a conflict-free rule set; converting the conflict-free rule set into a Rete network structure, the Rete network structure includes α nodes and β nodes, optimizing the combination of α nodes and β nodes to obtain an inference rule engine.

[0061] Exemplarily, candidate rules are extracted by subgraph pattern matching, and Pareto optimal rules are screened out using non-dominated sorting, which effectively reduces the number of rules. Rule conflict detection ensures the consistency of the rule set. The rules are converted into Rete network structures and optimized to improve the efficiency of rule execution. Overall, this method can automatically extract high-quality inference rules from complex switch networking knowledge graphs and build an efficient rule engine. This method avoids the tediousness and subjectivity of manual rule formulation and can better utilize the rule information implicit in the knowledge graph. At the same time, through multi-step screening and optimization, the quality and execution efficiency of the final rule set are guaranteed, providing strong support for intelligent decision-making and fault diagnosis related to switch networking.

[0062] In some embodiments, historical data packets of the intelligent switch in a preset time period are obtained, and parsed and converted to obtain a data conversion module, including: performing time series segmentation on the historical data packets of the intelligent switch to obtain a data segment set; performing protocol identification on the data packets according to the data segment set to obtain a protocol type matrix; performing feature extraction and dimensionality reduction processing on the protocol type matrix to obtain a feature vector set; constructing a deep neural network model according to the feature vector set, performing semantic parsing on the data packets to obtain a semantic parsing result; and normalizing and formatting the semantic parsing result to obtain a data conversion module.

[0063] For example, raw data is converted into standardized data modules through steps such as time series segmentation, protocol identification, feature extraction and dimensionality reduction, and deep neural network semantic parsing. This method can effectively process a large amount of heterogeneous data, improve data analysis efficiency, and provide high-quality input for subsequent intelligent decision-making. Overall, it realizes the automated conversion from raw data to structured information.

[0064] In some embodiments, a protocol conversion module is dynamically designed according to a preset implementation framework to obtain a dynamic protocol adaptation mechanism, including: modularly decomposing the protocol conversion module to obtain a set of functional sub-modules; constructing a dependency graph based on the set of functional sub-modules to obtain a module dependency matrix; topologically sorting the module dependency matrix to obtain a module loading order; dynamically loading the functional sub-modules according to the module loading order to obtain a reconfigurable protocol stack; performing parallel scheduling optimization on the reconfigurable protocol stack to obtain a parallel execution plan; and determining the dynamic protocol adaptation mechanism based on the parallel execution plan and the reconfigurable protocol stack.

[0065] For example, a reconfigurable protocol stack was constructed and optimized in parallel through modular decomposition, dependency analysis, topological sorting and other steps. This method improves the flexibility and efficiency of protocol conversion and enables the system to quickly adapt to different protocol requirements. The dynamic protocol adaptation mechanism can automatically adjust the protocol stack configuration according to actual needs, improve the adaptability and scalability of the system, and provide technical support for cross-protocol interoperability of smart switches.

[0066] In some embodiments, a dynamic protocol adaptation mechanism is determined based on a parallel execution scheme and a reconfigurable protocol stack, including: performing task decomposition on the parallel execution scheme to obtain a task dependency graph; performing resource allocation on the reconfigurable protocol stack based on the task dependency graph to obtain an initial resource allocation scheme; performing load balancing calculation on the initial resource allocation scheme to obtain a load balancing matrix; dynamically adjusting the initial resource allocation scheme based on the load balancing matrix to obtain an optimized resource allocation scheme; performing concurrent conflict detection on the optimized resource allocation scheme to obtain a conflict detection result; performing conflict resolution on the optimized resource allocation scheme based on the conflict detection result to obtain a dynamic protocol adaptation mechanism.

[0067] For example, through the steps of task decomposition, resource allocation, load balancing, conflict detection and resolution, the dynamic optimization of the protocol stack is realized. This method can make full use of system resources, improve the parallel efficiency of protocol conversion, and ensure the correctness of the conversion process. The dynamic protocol adaptation mechanism can automatically adjust resource allocation according to the real-time load situation, effectively avoiding resource conflicts and performance bottlenecks, and providing a guarantee for the stable operation of the smart switch in a complex network environment.

[0068] See also Figure 2 , Figure 2 The embodiment of the present application also provides a schematic block diagram of a multi-protocol communication intelligent switch gateway control device, and the multi-protocol communication intelligent switch gateway control device 200 is used to execute the multi-protocol communication intelligent switch gateway control method described above. The multi-protocol communication intelligent switch gateway control device 200 can be configured in a server.

[0069] Among them, the server can be an independent server or a server cluster, or it can be a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (Content Delivery Network, CDN) and big data and artificial intelligence platforms.

[0070] like Figure 2As shown, the intelligent switch gateway control device 200 for multi-protocol communication includes: an image construction module 201, a rule reasoning module 202, a data analysis module 203, an engine integration module 204, a dynamic adaptation module 205 and a system optimization module 206.

[0071] The image construction module 201 is used to construct a knowledge graph according to the network topology diagram and protocol information of the intelligent switch to obtain a switch networking knowledge graph.

[0072] The rule reasoning module 202 is used to determine the reasoning rules according to the switch networking knowledge graph and obtain the reasoning rule engine.

[0073] When the rule reasoning module 202 is used to construct a knowledge graph based on the network topology diagram and protocol information of the intelligent switch to obtain the switch networking knowledge graph, it is specifically used to implement: traversing the network topology diagram of the intelligent switch to obtain a topology relationship matrix, and determining the switch adjacency matrix based on the topology relationship matrix; classifying and clustering the protocol information of the intelligent switch based on the switch adjacency matrix to obtain a protocol category vector; semantically embedding the protocol category vector to obtain a protocol semantic vector; through multi-layer convolution operations, graph embedding the topology relationship matrix and the protocol semantic vector to obtain a node representation vector; performing knowledge graph construction processing on the node representation vector to obtain a switch networking knowledge graph.

[0074] When the rule reasoning module 202 is used to implement knowledge graph construction processing of the node representation vector to obtain the switch networking knowledge graph, it is specifically used to implement: sequence labeling of the node representation vector to obtain the node labeling vector, solving the optimal labeling path of the node labeling vector to obtain the entity set; performing relationship classification on the entity set to obtain the relationship triple set; calculating the semantic similarity of the relationship triple set to obtain the similarity matrix, performing hierarchical clustering on the similarity matrix to obtain the ontology concept hierarchy; performing frequent item set calculation on the ontology concept hierarchy and the relationship triple set to obtain the candidate rule set, screening the candidate rule set according to the preset minimum support and confidence thresholds to obtain the inference rule set; calculating the entity similarity in the inference rule set to obtain the entity similarity matrix, performing probabilistic reasoning on the entity similarity matrix to obtain the fused knowledge graph; performing low-dimensional vector representation learning based on the entities and relationships in the fused knowledge graph to obtain the initial vector representation, optimizing the initial vector representation, and obtaining the switch networking knowledge graph.

[0075] The data analysis module 203 is used to obtain historical data packets of the intelligent switch in a preset time period, and perform analysis and conversion to obtain a data conversion module.

[0076] The data analysis module 203 is used to obtain the historical data packets of the intelligent switch in a preset time period, and perform analysis and conversion to obtain the data conversion module. Specifically, it is used to implement: time series segmentation of the historical data packets of the intelligent switch to obtain a data segment set; protocol identification of the data packets according to the data segment set to obtain a protocol type matrix; feature extraction and dimensionality reduction processing of the protocol type matrix to obtain a feature vector set; analysis and conversion of the feature vector set through a preset natural language model to determine the semantic analysis result; normalization and format conversion of the semantic analysis result to obtain the data conversion module.

[0077] The engine integration module 204 is used to integrate the inference rule engine and the data conversion module to obtain the protocol conversion module of the intelligent gateway.

[0078] When the engine integration module 204 is used to determine the inference rules according to the switch networking knowledge graph and obtain the inference rule engine, it is specifically used to implement: performing subgraph pattern matching on the switch networking knowledge graph to obtain a candidate rule set; determining a rule scoring matrix according to the candidate rule set and the switch networking knowledge graph; performing non-dominated sorting on the rule scoring matrix to obtain a Pareto optimal rule set; performing rule conflict detection on the switch networking knowledge graph according to the Pareto optimal rule set to obtain a conflict-free rule set; converting the conflict-free rule set into a Rete network structure, the Rete network structure includes α nodes and β nodes, optimizing the combination of α nodes and β nodes to obtain an inference rule engine.

[0079] The dynamic adaptation module 205 is used to dynamically design the protocol conversion module according to a preset implementation framework to obtain a dynamic protocol adaptation mechanism.

[0080] The dynamic adaptation module 205, when used to implement dynamic design of the protocol conversion module according to a preset implementation framework to obtain a dynamic protocol adaptation mechanism, is specifically used to implement: modular decomposition of the protocol conversion module to obtain a set of functional sub-modules; constructing a dependency graph based on the set of functional sub-modules to obtain a module dependency matrix; topologically sorting the module dependency matrix to obtain a module loading order; dynamically loading the functional sub-modules according to the module loading order to obtain a reconfigurable protocol stack; performing parallel scheduling optimization on the reconfigurable protocol stack to obtain a parallel execution plan; determining the dynamic protocol adaptation mechanism based on the parallel execution plan and the reconfigurable protocol stack.

[0081] When the dynamic adaptation module 205 is used to implement the dynamic protocol adaptation mechanism according to the parallel execution scheme and the reconfigurable protocol stack, it is specifically used to implement: performing task decomposition on the parallel execution scheme to obtain a task dependency graph; performing resource allocation on the reconfigurable protocol stack according to the task dependency graph to obtain an initial resource allocation scheme; performing load balancing calculation on the initial resource allocation scheme to obtain a load balancing matrix; dynamically adjusting the initial resource allocation scheme according to the load balancing matrix to obtain an optimized resource allocation scheme; performing concurrent conflict detection on the optimized resource allocation scheme to obtain a conflict detection result; performing conflict resolution on the optimized resource allocation scheme according to the conflict detection result to obtain a dynamic protocol adaptation mechanism.

[0082] The system optimization module 206 is used to evaluate and optimize the performance of the dynamic protocol adaptation mechanism to obtain an optimized protocol conversion system. The optimized protocol conversion system is used to assist the smart switch gateway in controlling the smart switch.

[0083] An embodiment of the present application provides an electronic device, which includes a memory and a processor; the memory is used to store a computer program; the processor is used to execute the computer program and implement a multi-protocol communication intelligent switch gateway control method such as any one of the embodiments of the present application when executing the computer program.

[0084] An embodiment of the present application provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the processor implements a multi-protocol communication intelligent switch gateway control method as described in any one of the embodiments of the present application.

[0085] The above are only specific implementations of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed in the present application, and these modifications or replacements should be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be based on the protection scope of the claims.

Claims

1. A multi-protocol communication intelligent switch gateway control method, characterized in that: The method comprises: Traversing the network topology diagram of the intelligent switch to obtain a topology relationship matrix, and determining the switch adjacency matrix according to the topology relationship matrix; classifying and clustering the protocol information of the intelligent switch according to the switch adjacency matrix to obtain a protocol category vector; semantically embedding the protocol category vector to obtain a protocol semantic vector; embedding the topology relationship matrix and the protocol semantic vector into a graph through multi-layer convolution operations to obtain a node representation vector; performing knowledge graph construction processing on the node representation vector to obtain a switch networking knowledge graph; Determine an inference rule according to the switch networking knowledge graph to obtain an inference rule engine; Obtaining historical data packets of the intelligent switch in a preset time period, and performing parsing and conversion to obtain a data conversion module; Integrate the inference rule engine and the data conversion module to obtain a protocol conversion module of the intelligent gateway; Dynamically designing the protocol conversion module according to a preset implementation framework to obtain a dynamic protocol adaptation mechanism; The dynamic protocol adaptation mechanism is evaluated and performance optimized to obtain an optimized protocol conversion system, and the optimized protocol conversion system is used to assist the intelligent switch gateway in controlling the intelligent switch.

2. The multi-protocol communication intelligent switch gateway control method according to claim 1, characterized in that: The step of performing knowledge graph construction processing on the node representation vector to obtain a switch networking knowledge graph includes: Performing sequence labeling on the node representation vector to obtain a node labeling vector, solving an optimal labeling path of the node labeling vector, and obtaining an entity set; Performing relationship classification on the entity set to obtain a relationship triple set; Calculating the semantic similarity of the relationship triple set to obtain a similarity matrix, and performing hierarchical clustering on the similarity matrix to obtain an ontology concept hierarchy; Performing frequent item set calculation on the ontology concept hierarchy and the relationship triple set to obtain a candidate rule set, and screening the candidate rule set according to preset minimum support and confidence thresholds to obtain an inference rule set; Calculating the entity similarity in the inference rule set to obtain an entity similarity matrix, performing probabilistic reasoning on the entity similarity matrix to obtain a fused knowledge graph; Low-dimensional vector representation learning is performed based on the entities and relationships in the fused knowledge graph to obtain an initial vector representation, and the initial vector representation is optimized to obtain a switch networking knowledge graph.

3. The multi-protocol communication intelligent switch gateway control method according to claim 1, characterized in that: The determining of the inference rules according to the switch networking knowledge graph to obtain the inference rule engine includes: Performing subgraph pattern matching on the switch networking knowledge graph to obtain a candidate rule set; Determining a rule scoring matrix according to the candidate rule set and the switch networking knowledge graph; Performing non-dominated sorting on the rule scoring matrix to obtain a Pareto optimal rule set; Performing rule conflict detection on the switch networking knowledge graph according to the Pareto optimal rule set to obtain a conflict-free rule set; The conflict-free rule set is converted into a Rete network structure, wherein the Rete network structure includes an α node and a β node, and the α node and the β node are optimized and combined to obtain the inference rule engine.

4. The multi-protocol communication intelligent switch gateway control method according to claim 1, characterized in that: The step of obtaining the historical data packets of the intelligent switch in a preset time period and performing parsing and conversion to obtain a data conversion module includes: Performing time series segmentation on the historical data packets of the intelligent switch to obtain a data segment set; Perform protocol identification on the data packet according to the data segment set to obtain a protocol type matrix; Performing feature extraction and dimensionality reduction processing on the protocol type matrix to obtain a feature vector set; Parsing and converting the feature vector set through a preset natural language model to determine a semantic parsing result; The semantic analysis result is normalized and formatted to obtain the data conversion module.

5. The multi-protocol communication intelligent switch gateway control method according to claim 1, characterized in that: The protocol conversion module is dynamically designed according to a preset implementation framework to obtain a dynamic protocol adaptation mechanism, including: Decomposing the protocol conversion module into modules to obtain a set of functional sub-modules; Construct a dependency graph according to the functional sub-module set to obtain a module dependency matrix; Topologically sorting the module dependency matrix to obtain a module loading order; Dynamically load the functional submodules according to the module loading order to obtain a reconfigurable protocol stack; Performing parallel scheduling optimization on the reconfigurable protocol stack to obtain a parallel execution plan; A dynamic protocol adaptation mechanism is determined according to the parallel execution scheme and the reconfigurable protocol stack.

6. The multi-protocol communication intelligent switch gateway control method according to claim 5, characterized in that: Determining a dynamic protocol adaptation mechanism according to the parallel execution scheme and the reconfigurable protocol stack includes: Decomposing the parallel execution scheme into tasks to obtain a task dependency graph; Allocate resources for the reconfigurable protocol stack according to the task dependency graph to obtain an initial resource allocation plan; Performing load balancing calculation on the initial resource allocation scheme to obtain a load balancing matrix; Dynamically adjusting the initial resource allocation scheme according to the load balancing matrix to obtain an optimized resource allocation scheme; Performing concurrent conflict detection on the optimized resource allocation scheme to obtain a conflict detection result; The optimized resource allocation scheme is conflict-resolved according to the conflict detection result to obtain a dynamic protocol adaptation mechanism.

7. A multi-protocol communication intelligent switch gateway control device, characterized in that: The multi-protocol communication intelligent switch gateway control device is used to execute the multi-protocol communication intelligent switch gateway control method according to any one of claims 1 to 6, and the multi-protocol communication intelligent switch gateway control device includes: The image construction module is used to traverse the network topology diagram of the intelligent switch to obtain a topology relationship matrix, determine the switch adjacency matrix according to the topology relationship matrix; classify and cluster the protocol information of the intelligent switch according to the switch adjacency matrix to obtain a protocol category vector; perform semantic embedding on the protocol category vector to obtain a protocol semantic vector; perform graph embedding on the topology relationship matrix and the protocol semantic vector through multi-layer convolution operations to obtain a node representation vector; perform knowledge graph construction processing on the node representation vector to obtain a switch networking knowledge graph; A rule reasoning module, used to determine the reasoning rules according to the switch networking knowledge graph to obtain a reasoning rule engine; A data analysis module, used to obtain historical data packets of the intelligent switch in a preset time period, and perform analysis and conversion to obtain a data conversion module; An engine integration module, used to integrate the inference rule engine and the data conversion module to obtain a protocol conversion module of the intelligent gateway; A dynamic adaptation module, used to dynamically design the protocol conversion module according to a preset implementation framework to obtain a dynamic protocol adaptation mechanism; The system optimization module is used to evaluate and optimize the performance of the dynamic protocol adaptation mechanism to obtain an optimized protocol conversion system, and the optimized protocol conversion system is used to assist the intelligent switch gateway in controlling the intelligent switch.

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