Data interaction method and system for power grid intelligent fusion terminal based on multi-protocol adaptation

Abstract

The application provides a power grid intelligent fusion terminal data interaction method and system based on multi-protocol adaptation, relates to the technical field of network protocols, and comprises the following steps: acquiring multi-source protocol communication data of a power grid intelligent fusion terminal, and constructing a multi-protocol data interaction task set; extracting interaction behavior features from the multi-protocol data interaction task set, identifying interaction types according to the interaction behavior features; analyzing the interaction behavior features to obtain an interaction coupling degree index; generating a protocol adaptation strategy corresponding to the interaction types and the interaction coupling degree index based on a protocol adaptation template, wherein the protocol adaptation template comprises protocol resource scheduling parameters, state parameters, cache parameters and protocol mapping levels; and performing protocol conversion of the multi-protocol data interaction task set by a protocol execution machine with the protocol adaptation strategy. The application can realize dynamic protocol adaptation of multi-protocol data interaction tasks, and improve the protocol conversion efficiency and communication stability.

Description

Technical Field

[0001] This application relates to the field of network protocol technology, and in particular to a data interaction method and system for a smart grid fusion terminal based on multi-protocol adaptation. Background Technology

[0002] With the continuous advancement of the construction of new power systems, power grid terminal equipment is gradually showing a development trend of multiple types, multiple manufacturers, and multiple communication protocols coexisting. Due to the significant differences in communication protocols, data structures, and interaction methods used by different devices, the smart converged terminal of the power grid is gradually becoming an important node for realizing the interconnection of heterogeneous devices, which puts forward higher requirements for the terminal's data interaction capabilities, protocol compatibility capabilities, and communication stability.

[0003] Currently, existing smart grid converged terminals employ fixed protocol conversion rules or static protocol mapping to achieve data conversion and interaction processing between different communication protocols during multi-protocol data interaction. Because different interaction tasks differ significantly in communication direction, session relationships, and communication behavior characteristics, fixed protocol processing mechanisms struggle to effectively distinguish the communication characteristics of different interaction tasks. In actual operation, when the communication behavior of an interaction task changes, the existing protocol conversion mechanism still executes data processing according to a uniform configuration, easily leading to unreasonable allocation of communication resources, decreased protocol conversion efficiency, and unstable communication status maintenance. Furthermore, in complex multi-protocol concurrent environments, the communication relationships and resource consumption between different interaction tasks exhibit dynamic changes. Static protocol adaptation methods cannot dynamically adjust protocol processing parameters according to the actual interaction status, resulting in a lack of flexibility and adaptability in the protocol conversion process, making it difficult to meet the data interaction needs of complex power grid business scenarios.

[0004] In summary, existing technologies suffer from the technical problem that the lack of a dynamic protocol adaptation mechanism based on interactive behavior characteristics makes it difficult for the protocol conversion method to adaptively adjust with changes in communication status during multi-protocol data interaction, further affecting the data interaction efficiency and communication stability of smart grid converged terminals in complex multi-protocol environments. Summary of the Invention

[0005] The purpose of this application is to provide a data interaction method and system for smart grid fusion terminals based on multi-protocol adaptation, in order to solve the technical problem in the prior art that the lack of a dynamic protocol adaptation mechanism based on interactive behavior characteristics makes it difficult for the protocol conversion method to adaptively adjust with changes in communication status during multi-protocol data interaction, which further affects the data interaction efficiency and communication stability of smart grid fusion terminals in complex multi-protocol environments.

[0006] In view of the above problems, this application provides a data interaction method and system for smart grid converged terminals based on multi-protocol adaptation.

[0007] Firstly, this application provides a data interaction method for a smart grid converged terminal based on multi-protocol adaptation, implemented through a data interaction system for a smart grid converged terminal based on multi-protocol adaptation. The method includes: acquiring multi-source protocol communication data from the smart grid converged terminal; constructing a multi-protocol data interaction task set; extracting interaction behavior features for each data interaction task in the multi-protocol data interaction task set; identifying the interaction type according to the interaction behavior features, wherein the interaction type includes bidirectional interaction type and unidirectional interaction type; analyzing the interaction behavior features to obtain an interaction coupling degree index; defining a protocol adaptation template; generating a protocol adaptation strategy corresponding to the interaction type and the interaction coupling degree index based on the protocol adaptation template, wherein the protocol adaptation template includes protocol resource scheduling parameters, state parameters, cache parameters, and protocol mapping levels; and executing protocol conversion of the multi-protocol data interaction task set through a protocol execution machine using the protocol adaptation strategy.

[0008] Preferably, the data interaction method for the smart grid fusion terminal based on multi-protocol adaptation further includes: for each data interaction task, acquiring at least one message sample of the interaction sequence window within a sampling time window; parsing the message sample to obtain interaction behavior features, including communication mode features, timing features, and load features, wherein the communication mode features are used to characterize the message direction of the interaction task, the role of the session initiator, and whether there is a response pairing; the timing features are used to characterize the average message interval, interval jitter, and periodic window of the interaction task; and the load features are used to characterize the type code, data length distribution, and change frequency of key fields of the interaction task.

[0009] Preferably, the data interaction method for the smart grid fusion terminal based on multi-protocol adaptation further includes: performing response pairing detection according to the interaction behavior characteristics to obtain the pairing success rate; extracting the changes in the role of the session initiator for valid pairings that are greater than the preset success rate; extracting the message flow concentration degree that is less than the preset success rate, wherein the message flow concentration degree is the proportion of unidirectional flow in the total number of messages; and identifying the interaction type based on the pairing success rate, the changes in the role of the session initiator, and the message flow concentration degree.

[0010] Preferably, the data interaction method of the smart grid fusion terminal based on multi-protocol adaptation further includes: when the effective pairing ratio is greater than or equal to the first threshold and there is a change in the role of the session initiator, it is determined to be a two-way interaction type; when the effective pairing ratio is less than the first threshold and the concentration of the message flow is higher than the direction threshold, it is determined to be a one-way interaction type.

[0011] Preferably, the data interaction method for the smart grid fusion terminal based on multi-protocol adaptation further includes: calculating data dependency, temporal overlap, and resource contention based on the interaction behavior characteristics; the data dependency is obtained by performing read / write dependency calculation on the intersection data point set of the interaction data between the two parties; the temporal overlap is obtained by constructing an active intersection interval of the interaction data between the two parties and calculating the ratio of the length of the active intersection interval to the window length; the resource contention is the absolute value of the intersection and union of the resources required for interaction between the two parties; and the data dependency, temporal overlap, and resource contention are weighted and averaged to obtain an interaction coupling index.

[0012] Preferably, the data interaction method of the smart grid fusion terminal based on multi-protocol adaptation further includes: loading the baseline configuration set corresponding to the interaction type based on the protocol adaptation template, including a bidirectional interaction type baseline configuration set and a unidirectional interaction type baseline configuration set; dynamically adjusting the baseline configuration set according to the interaction coupling degree index, and outputting a protocol adaptation strategy, wherein the protocol adaptation template includes protocol resource scheduling parameters, status parameters, cache parameters, and protocol mapping level.

[0013] Preferably, the data interaction method of the smart grid fusion terminal based on multi-protocol adaptation further includes: configuring multiple adjustment step sizes corresponding to multiple preset coupling degree index intervals; identifying the matching coupling degree index interval in which the interaction coupling degree index is located, and adjusting the baseline configuration set according to the adjustment step size corresponding to the matching coupling degree index interval.

[0014] Preferably, the data interaction method for the smart grid fusion terminal based on multi-protocol adaptation further includes: the state parameters include session retention duration, transaction retention depth, and state timeout threshold; the cache parameters include cache capacity, cache refresh cycle, and cache retention duration; and the protocol mapping level includes complete semantic mapping level, partial semantic mapping level, and aggregated semantic mapping level.

[0015] Preferably, the data interaction method of the smart grid fusion terminal based on multi-protocol adaptation further includes: when the protocol executor detects a change in the interaction type, reloading the corresponding baseline configuration set, and updating the protocol adaptation strategy according to the reloaded baseline configuration set.

[0016] Secondly, this application also provides a data interaction system for a smart grid converged terminal based on multi-protocol adaptation, used to execute the data interaction method for a smart grid converged terminal based on multi-protocol adaptation as described in the first aspect, comprising: a multi-protocol data interaction task set construction module, used to acquire multi-source protocol communication data of the smart grid converged terminal and construct a multi-protocol data interaction task set; an interaction type identification module, used to extract interaction behavior features for each data interaction task in the multi-protocol data interaction task set, and identify the interaction type according to the interaction behavior features, wherein the interaction type includes bidirectional interaction type and unidirectional interaction type; an interaction coupling degree index acquisition module, used to analyze the interaction behavior features and obtain an interaction coupling degree index; a protocol adaptation strategy generation module, used to define a protocol adaptation template, and generate a protocol adaptation strategy corresponding to the interaction type and the interaction coupling degree index based on the protocol adaptation template, wherein the protocol adaptation template includes protocol resource scheduling parameters, status parameters, cache parameters, and protocol mapping levels; and a protocol conversion execution module, used to execute the protocol conversion of the multi-protocol data interaction task set through a protocol execution machine using the protocol adaptation strategy.

[0017] The technical solution provided in this application has at least the following technical effects or advantages: by achieving the technical goals of identifying the interaction type of multi-protocol data interaction tasks, analyzing the interaction coupling relationship, and dynamically adjusting the protocol adaptation strategy, it achieves the technical effects of improving the flexibility of protocol conversion, the efficiency of data interaction, and the stability of communication operation in a multi-protocol communication environment.

[0018] The above description is merely an overview of the technical solution of this application. To enable a clearer understanding of the technical means of this application and to facilitate its implementation according to the description, and to make the above and other objects, features, and advantages of this application more apparent, specific embodiments of this application are described below. It should be understood that the content described in this section is not intended to identify key or important features of the embodiments of this application, nor is it intended to limit the scope of this application. Other features of this application will become readily apparent through the following description. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in this application 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 merely exemplary. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0020] Figure 1 This is a flowchart illustrating the data interaction method for the smart grid fusion terminal based on multi-protocol adaptation proposed in this application.

[0021] Figure 2This is a schematic diagram of the data interaction system of the smart grid fusion terminal based on multi-protocol adaptation in this application.

[0022] Figure labeling: Module 1 for constructing a multi-protocol data interaction task set, Module 2 for identifying interaction type, Module 3 for obtaining interaction coupling index, Module 4 for generating protocol adaptation strategy, and Module 5 for executing protocol conversion. Detailed Implementation

[0023] This application provides a data interaction method and system for smart grid converged terminals based on multi-protocol adaptation. It addresses the technical problem in existing technologies where the lack of a dynamic protocol adaptation mechanism based on interactive behavior characteristics makes it difficult to adaptively adjust protocol conversion methods during multi-protocol data interaction, further impacting the data interaction efficiency and communication stability of smart grid converged terminals in complex multi-protocol environments. The application achieves the technical objectives of identifying interaction types, analyzing interaction coupling relationships, and dynamically adjusting protocol adaptation strategies for multi-protocol data interaction tasks, thereby improving protocol conversion flexibility, data interaction efficiency, and communication stability in multi-protocol communication environments.

[0024] The technical solutions of this application will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. It should be understood that this application is not limited to the exemplary embodiments described herein. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application. It should also be noted that, for ease of description, only the parts related to this application are shown in the accompanying drawings, not all of them.

[0025] Example 1, please refer to the appendix. Figure 1 This application provides a data interaction method for a smart grid converged terminal based on multi-protocol adaptation, which is applied to a data interaction system for a smart grid converged terminal based on multi-protocol adaptation, and specifically includes the following steps: Acquire multi-source protocol communication data from the smart grid fusion terminal and construct a set of multi-protocol data interaction tasks.

[0026] Specifically, acquiring multi-source protocol communication data from the smart grid converged terminal refers to the process of uniformly collecting raw communication message data from various communication protocols, communication links, and data formats during the operation of the smart grid converged terminal. This forms a basic data input set covering a multi-protocol environment. Multi-source protocol communication data is used to characterize the actual communication interaction status of the smart grid converged terminal under conditions of multiple protocols coexisting, providing a data foundation for subsequent data analysis and task allocation.

[0027] After acquiring multi-source protocol communication data, constructing a multi-protocol data interaction task set refers to structurally dividing the data interaction process with different protocol characteristics based on the protocol type identification results and communication session division results of the communication messages, and organizing it at the task level according to the communication session dimension, protocol type dimension, and interaction behavior dimension, forming a set of multiple independent data processing units with clear interaction boundaries, thereby realizing the task-based decomposition and unified management of complex communication flows.

[0028] Furthermore, the multi-protocol data interaction task set is used to classify and model the communication behavior between different protocols in the smart grid fusion terminal, so that subsequent interaction feature extraction and protocol adaptation processing can be performed separately for each interaction task, and a standardized input structure can be provided for interaction type identification and coupling degree analysis.

[0029] Interaction behavior features are extracted for each data interaction task in the multi-protocol data interaction task set, and the interaction type is identified according to the interaction behavior features. The interaction type includes bidirectional interaction type and unidirectional interaction type.

[0030] Furthermore, this application also includes: for each data interaction task, acquiring at least one message sample of an interaction sequence window within a sampling time window; parsing the message sample to obtain interaction behavior features, including communication mode features, timing features, and payload features, wherein the communication mode features are used to characterize the message direction of the interaction task, the role of the session initiator, and whether there is a response pairing; the timing features are used to characterize the average message interval, interval jitter, and periodic window of the interaction task; and the payload features are used to characterize the type code, data length distribution, and change frequency of key fields of the interaction task.

[0031] Furthermore, this application also includes: performing response pairing detection according to the interaction behavior characteristics to obtain the pairing success rate; extracting the changes in the session initiator role of valid pairings that are greater than the preset success rate; extracting the message flow concentration degree that is less than the preset success rate, wherein the message flow concentration degree is the proportion of unidirectional flow in the total number of messages; and identifying the interaction type based on the pairing success rate, the changes in the session initiator role, and the message flow concentration degree.

[0032] Furthermore, this application also includes: when the effective pairing ratio is greater than or equal to the first threshold and there is a change in the role of the session initiator, it is determined to be a two-way interaction type; when the effective pairing ratio is less than the first threshold and the concentration of the message flow is higher than the direction threshold, it is determined to be a one-way interaction type.

[0033] Specifically, for each data interaction task, obtaining message samples of at least one interaction sequence window within the sampling time window means continuously sampling communication messages according to a preset time window within the execution cycle of each divided data interaction task to obtain a representative message sequence. The interaction sequence window contains the set of communication messages that occur within the time window, which is used to characterize the communication behavior characteristics of the interaction task within a specific time period, thereby providing a reliable data foundation for subsequent feature extraction.

[0034] Parsing message samples to obtain interaction behavior features refers to performing protocol parsing and information extraction on the collected message samples to obtain a multi-dimensional feature set that can characterize the data interaction task behavior. Interaction behavior features are used to describe the communication patterns, time relationships, and data payload characteristics during the interaction process, providing a basis for interaction type identification and coupling degree analysis.

[0035] Communication pattern features are used to characterize the message direction, session initiator role, and whether a response pairing exists in an interactive task. This means that by analyzing the message sending direction, the role of the party initiating the communication request, and whether the message forms a request-response pairing in the session, the communication method and structural characteristics of the interactive task can be determined, thereby judging the information flow pattern of the task in the interaction.

[0036] Temporal features are used to characterize the average message interval, interval jitter, and periodic window of an interactive task. They refer to the statistical analysis of message timestamps in the interactive sequence to obtain the average time interval, interval fluctuation range, and possible periodic patterns of message transmission. This is used to characterize the time dynamic behavior of the interactive task and provide a time reference for determining the interaction type.

[0037] Payload characteristics are used to characterize the type code, data length distribution, and frequency of change of key fields of interactive tasks. They refer to the process of analyzing the message payload content to extract message type identifiers, data length changes of each message, and changes of key fields in different messages, thereby reflecting the data characteristics and content dynamics of interactive tasks and providing information support for the generation of protocol adaptation strategies.

[0038] Performing response pairing detection based on interaction behavior characteristics and obtaining the pairing success rate refers to judging whether each communication message forms a request-response pairing in the session based on the aforementioned communication mode characteristics and message timing characteristics. By statistically analyzing the ratio of the number of valid response pairings to the total number of interaction messages, the pairing success rate index is obtained. This index is used to quantify the response integrity and interaction reliability of the interaction task in the communication process, thereby providing basic data support for interaction type determination.

[0039] Extracting changes in the role of the session initiator in valid pairings with a success rate greater than a preset threshold refers to analyzing the role changes of the session initiator in continuous interactions among valid pairings with a success rate higher than a preset threshold. This identifies the alternation pattern of information sending and receiving roles, reflecting the two-way communication characteristics of the interaction task and providing a basis for distinguishing between two-way and one-way interactions.

[0040] Extract the message flow concentration degree for messages with a success rate lower than the preset threshold. The message flow concentration degree is the proportion of unidirectional flow in the total number of messages. It refers to the proportion of unidirectional transmission of messages in the interaction sequence with a pairing success rate lower than the preset threshold. The proportion is used to characterize the degree of concentration of information flow direction in the interaction task, so as to help determine the strength of unidirectional communication characteristics in the interaction type.

[0041] When the effective pairing ratio is greater than or equal to the first threshold and there is a role alternation between the session initiator, it is determined to be a two-way interaction type. This means that in the interaction task, by statistically analyzing the response pairing success rate, when the proportion of successful pairings to the total interaction messages reaches or exceeds the preset first threshold, and there is a role alternation phenomenon between the session initiator in continuous messages, the interaction task is identified as a two-way interaction type. The two-way interaction type represents the interactive characteristics of continuous information sending and receiving between the two parties in the communication process, and can reflect the two-way communication capability of the interaction task.

[0042] When the effective pairing ratio is less than the first threshold and the message flow concentration is higher than the direction threshold, it is determined to be a one-way interaction type. This means that in the interaction task, by jointly analyzing the pairing success rate and the message flow concentration, when the successful pairing ratio is lower than the first threshold and the proportion of one-way message transmission exceeds the preset direction threshold, the interaction task is identified as a one-way interaction type. The one-way interaction type represents that information is mainly transmitted in a single direction during the communication process, reflecting the one-way characteristics of the interaction task in the interaction structure.

[0043] The interaction behavior characteristics are analyzed to obtain the interaction coupling degree index.

[0044] Furthermore, this application also includes: calculating data dependency, temporal overlap, and resource contention based on the interaction behavior characteristics; the data dependency is obtained by calculating read / write dependency on the intersection data point set of the interaction data of both parties; the temporal overlap is obtained by constructing an active intersection interval of the interaction data of both parties and calculating the ratio of the length of the active intersection interval to the window length; the resource contention is the absolute value of the intersection and union of the resources required for interaction between the two parties; and performing a weighted average fusion of the data dependency, temporal overlap, and resource contention to obtain an interaction coupling index.

[0045] Specifically, calculating data dependency, temporal overlap, and resource contention based on interaction behavior characteristics refers to the quantitative analysis of the multidimensional dependencies in the interaction process between the two parties in each data interaction task, based on the aforementioned communication mode characteristics, temporal characteristics, and load characteristics. Data dependency is obtained by calculating read-write dependencies on the intersection data point set of the interaction data between the two parties. Read-write dependencies reflect whether the generation or modification of data by one party directly affects the use of data by the other party during the interaction process, and are used to characterize the strength of data dependencies in the interaction task.

[0046] Temporal overlap is obtained by constructing the intersection active interval of the interactive data between the two parties and calculating the ratio of the length of the intersection active interval to the window length. The intersection active interval refers to the time period in which both parties are simultaneously in an active communication state within the same sampling time window. By calculating the proportion of this time period in the total time window, the degree of synchronization of interactive tasks in the time dimension can be quantified, providing a basis for evaluating task parallelism and temporal coupling.

[0047] Resource contention is the absolute value of the intersection and union of the resources required for interaction between two parties. It refers to the relationship between the number of shared resources and the total number of resources in the set of communication resources, cache resources and processing resources accessed or occupied by both parties during the interaction process. By calculating the ratio of intersection to union, it reflects the degree of competition between the two parties in resource use, and provides a reference for analyzing the execution conflict and collaborative efficiency of interactive tasks.

[0048] The interaction coupling index is obtained by weighted averaging and fusion of data dependency, time overlap and resource competition. This means that the three quantitative indicators mentioned above are comprehensively calculated according to preset weights to form a single coupling index, which is used to comprehensively describe the comprehensive coupling characteristics of interactive tasks in terms of data dependency, time synchronization and resource sharing, and provides a quantitative basis for the dynamic adjustment and optimization of protocol adaptation strategies.

[0049] Define a protocol adaptation template, and generate a protocol adaptation strategy corresponding to the interaction type and the interaction coupling index based on the protocol adaptation template. The protocol adaptation template includes protocol resource scheduling parameters, status parameters, cache parameters, and protocol mapping level.

[0050] Furthermore, this application also includes: loading a baseline configuration set corresponding to the interaction type based on the protocol adaptation template, including a bidirectional interaction type baseline configuration set and a unidirectional interaction type baseline configuration set; dynamically adjusting the baseline configuration set according to the interaction coupling index, and outputting a protocol adaptation strategy, wherein the protocol adaptation template includes protocol resource scheduling parameters, status parameters, cache parameters, and protocol mapping level.

[0051] Furthermore, this application also includes: configuring multiple adjustment step sizes corresponding to multiple preset coupling index intervals; identifying the matching coupling index interval in which the interaction coupling index is located, and adjusting the baseline configuration set according to the adjustment step size corresponding to the matching coupling index interval.

[0052] Furthermore, this application also includes: the state parameters include session retention duration, transaction retention depth, and state timeout threshold; the cache parameters include cache capacity, cache refresh cycle, and cache retention duration; and the protocol mapping level includes full semantic mapping level, partial semantic mapping level, and aggregate semantic mapping level.

[0053] Specifically, defining a protocol adaptation template and loading the baseline configuration set corresponding to the interaction type based on the protocol adaptation template refers to determining the initial framework of protocol resource scheduling parameters, status parameters, caching parameters, and protocol mapping levels in a multi-protocol data interaction environment by using a preset protocol adaptation template, and loading the corresponding baseline configuration set according to different interaction types. The baseline configuration set for bidirectional interaction types includes high priority, short communication maintenance cycle, and deep protocol mapping configurations, while the baseline configuration set for unidirectional interaction types includes low priority, long communication maintenance cycle, and lightweight protocol mapping configurations, thereby providing initial parameter basis for protocol adaptation strategy generation.

[0054] Configuring multiple adjustment steps corresponding to multiple preset coupling index ranges refers to setting corresponding dynamic adjustment steps for different ranges of interaction coupling indexes in the protocol adaptation template. The adjustment steps are used to add, subtract, or optimize protocol resource scheduling, status parameters, and cache parameters based on the baseline configuration, thereby realizing adaptive strategy generation for multi-protocol interaction tasks under different coupling strength conditions.

[0055] Identifying the matching coupling index range where the interaction coupling index falls, adjusting the baseline configuration set according to the adjustment step size corresponding to the matching coupling index range, and outputting the protocol adaptation strategy means that during operation, the calculated interaction coupling index is compared with the preset coupling range to determine the matching range. After that, the loaded baseline configuration set is dynamically modified according to the corresponding adjustment step size, and the modified configuration is output as the protocol adaptation strategy. The protocol adaptation strategy is used to guide the protocol executor to perform data interaction tasks and realize communication optimization control under different interaction types and different coupling conditions.

[0056] State parameters include session hold duration, transaction hold depth, and state timeout threshold. These are parameter configurations used in protocol adaptation strategies to maintain session continuity, transaction integrity, and prevent state information from expiring. Session hold duration controls the duration of the session, transaction hold depth limits the number of concurrent transactions, and state timeout threshold determines the validity of state information.

[0057] Cache parameters include cache capacity, cache refresh cycle, and cache retention time. These are parameter configurations used to control data cache management during protocol execution. Cache capacity limits the amount of data that can be stored in the cache, cache refresh cycle defines the frequency of cache data updates, and cache retention time determines the effective retention time of data in the cache.

[0058] Protocol mapping levels include full semantic mapping level, partial semantic mapping level, and aggregate semantic mapping level. These levels are used in protocol adaptation strategies to define the depth and precision of data mapping for different interaction types. Full semantic mapping level is used to implement deep protocol mapping for bidirectional interaction tasks, partial semantic mapping level is used to implement partial information mapping, and aggregate semantic mapping level is used to implement lightweight mapping for unidirectional or low-priority interaction tasks.

[0059] The protocol execution machine performs protocol conversion of the multi-protocol data interaction task set using the protocol adaptation strategy.

[0060] Furthermore, this application also includes: when the protocol executor detects a change in the interaction type, it reloads the corresponding baseline configuration set and updates the protocol adaptation strategy according to the reloaded baseline configuration set.

[0061] Specifically, the protocol conversion of a set of multi-protocol data interaction tasks by the protocol executor with a protocol adaptation strategy refers to the protocol executor acting as the core control unit in a multi-protocol data interaction environment. According to the generated protocol adaptation strategy, the protocol executor performs protocol format conversion, message mapping, status management and resource scheduling for each data interaction task. Protocol conversion includes converting source protocol data messages into target protocol formats, adjusting message content and time sequence, updating communication status information and allocating necessary resources, thereby ensuring effective communication and interoperability of multi-source protocol data under a unified interaction framework.

[0062] When the protocol executor detects a change in the interaction type and reloads the corresponding baseline configuration set, it means that during the multi-protocol data interaction process, the protocol executor continuously monitors the behavioral characteristics and interaction type of the interaction task. When the interaction task changes from a bidirectional type to a unidirectional type or from a unidirectional type to a bidirectional type, the baseline configuration set is reloaded according to the change in interaction type. The baseline configuration set is an initial parameter set of the preset interaction type, which is used to guide the generation of subsequent protocol adaptation strategies.

[0063] The protocol adaptation strategy is updated based on the reloaded baseline configuration set. This means that after the baseline configuration set is reloaded, the protocol executor dynamically adjusts the protocol resource scheduling parameters, status parameters, cache parameters, and protocol mapping level in combination with the current interaction coupling degree index and the preset adjustment step size. This generates an updated protocol adaptation strategy, which is then used for the execution and control of subsequent multi-protocol data interaction tasks, ensuring the continuity and adaptation effect of communication tasks under changing interaction types.

[0064] In summary, the data interaction method for smart grid fusion terminals based on multi-protocol adaptation provided in this application has the following technical effects: by realizing the technical objectives of interaction type identification, interaction coupling relationship analysis, and dynamic adjustment of protocol adaptation strategies for multi-protocol data interaction tasks, it achieves the technical effects of improving the flexibility of protocol conversion, data interaction efficiency, and communication operation stability in a multi-protocol communication environment.

[0065] Example 2: Based on the same inventive concept as the data interaction method for smart grid converged terminals based on multi-protocol adaptation in the foregoing examples, this application also provides a data interaction system for smart grid converged terminals based on multi-protocol adaptation. Please refer to the appendix. Figure 2 The system includes: a multi-protocol data interaction task set construction module 1, used to acquire multi-source protocol communication data from the smart grid fusion terminal and construct a multi-protocol data interaction task set; an interaction type identification module 2, used to extract interaction behavior features from each data interaction task in the multi-protocol data interaction task set and identify the interaction type according to the interaction behavior features, wherein the interaction type includes bidirectional interaction type and unidirectional interaction type; an interaction coupling degree index acquisition module 3, used to analyze the interaction behavior features and obtain the interaction coupling degree index; a protocol adaptation strategy generation module 4, used to define a protocol adaptation template and generate a protocol adaptation strategy corresponding to the interaction type and the interaction coupling degree index based on the protocol adaptation template, wherein the protocol adaptation template includes protocol resource scheduling parameters, status parameters, cache parameters, and protocol mapping level; and a protocol conversion execution module 5, used to execute the protocol conversion of the multi-protocol data interaction task set through a protocol execution machine using the protocol adaptation strategy.

[0066] Furthermore, the data interaction system of the smart grid fusion terminal based on multi-protocol adaptation is also used for: acquiring message samples of at least one interaction sequence window within a sampling time window for each data interaction task; parsing the message samples to obtain interaction behavior characteristics, including communication mode characteristics, timing characteristics, and load characteristics, wherein the communication mode characteristics are used to characterize the message direction of the interaction task, the role of the session initiator, and whether there is a response pairing; the timing characteristics are used to characterize the average message interval, interval jitter, and periodic window of the interaction task; and the load characteristics are used to characterize the type code, data length distribution, and change frequency of key fields of the interaction task.

[0067] Furthermore, the data interaction system of the smart grid fusion terminal based on multi-protocol adaptation is also used for: performing response pairing detection according to the interaction behavior characteristics to obtain the pairing success rate; extracting the changes in the role of the session initiator for valid pairings that are greater than the preset success rate; extracting the message flow concentration degree that is less than the preset success rate, wherein the message flow concentration degree is the proportion of unidirectional flow in the total number of messages; and identifying the interaction type based on the pairing success rate, the changes in the role of the session initiator, and the message flow concentration degree.

[0068] Furthermore, the data interaction system of the smart grid fusion terminal based on multi-protocol adaptation is also used to: determine the interaction type as two-way when the effective pairing ratio is greater than or equal to the first threshold and there is a change in the role of the session initiator; and determine the interaction type as one-way when the effective pairing ratio is less than the first threshold and the concentration of the message flow is higher than the direction threshold.

[0069] Furthermore, the data interaction system of the smart grid fusion terminal based on multi-protocol adaptation is also used to: calculate data dependency, time overlap, and resource contention based on the interaction behavior characteristics; the data dependency is obtained by performing read / write dependency calculation on the intersection data point set of the interaction data between the two parties; the time overlap is obtained by constructing an active intersection interval of the interaction data between the two parties and calculating the ratio of the length of the active intersection interval to the window length; the resource contention is the absolute value of the intersection and union of the resources required for interaction between the two parties; and the data dependency, time overlap, and resource contention are weighted and averaged to obtain the interaction coupling index.

[0070] Furthermore, the data interaction system for the smart grid fusion terminal based on multi-protocol adaptation is also used for: loading the baseline configuration set corresponding to the interaction type based on the protocol adaptation template, including a bidirectional interaction type baseline configuration set and a unidirectional interaction type baseline configuration set; dynamically adjusting the baseline configuration set according to the interaction coupling degree index, and outputting a protocol adaptation strategy, wherein the protocol adaptation template includes protocol resource scheduling parameters, status parameters, cache parameters, and protocol mapping level.

[0071] Furthermore, the data interaction system of the smart grid fusion terminal based on multi-protocol adaptation is also used to: configure multiple adjustment step sizes corresponding to multiple preset coupling degree index intervals; identify the matching coupling degree index interval in which the interaction coupling degree index is located, and adjust the baseline configuration set according to the adjustment step size corresponding to the matching coupling degree index interval.

[0072] Furthermore, the data interaction system for the smart grid fusion terminal based on multi-protocol adaptation is also used for: the status parameters including session hold duration, transaction hold depth and status timeout threshold, the cache parameters including cache capacity, cache refresh cycle and cache retention duration, and the protocol mapping level including complete semantic mapping level, partial semantic mapping level and aggregate semantic mapping level.

[0073] Furthermore, the data interaction system of the smart grid fusion terminal based on multi-protocol adaptation is also used to: when the protocol executor detects a change in the interaction type, reload the corresponding baseline configuration set, and update the protocol adaptation strategy according to the reloaded baseline configuration set.

[0074] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The data interaction method and specific examples of the smart grid converged terminal based on multi-protocol adaptation in the foregoing embodiment 1 are also applicable to the data interaction system of the smart grid converged terminal based on multi-protocol adaptation in this embodiment. Through the foregoing detailed description of the data interaction method of the smart grid converged terminal based on multi-protocol adaptation, those skilled in the art can clearly understand the data interaction system of the smart grid converged terminal based on multi-protocol adaptation in this embodiment. Therefore, for the sake of brevity, it will not be described in detail here.

[0075] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0076] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of this application and its equivalents, this application also intends to include such modifications and variations.

Claims

1. A data interaction method for a smart grid converged terminal based on multi-protocol adaptation, characterized in that, The method includes: Acquire multi-source protocol communication data from the smart grid integration terminal and construct a set of multi-protocol data interaction tasks; Interaction behavior features are extracted for each data interaction task in the multi-protocol data interaction task set, and the interaction type is identified according to the interaction behavior features. The interaction type includes bidirectional interaction type and one-way interaction type. The interaction behavior characteristics are analyzed to obtain the interaction coupling index; Define a protocol adaptation template, and generate a protocol adaptation strategy corresponding to the interaction type and the interaction coupling index based on the protocol adaptation template. The protocol adaptation template includes protocol resource scheduling parameters, status parameters, cache parameters, and protocol mapping level. The protocol executor performs protocol conversion of the multi-protocol data interaction task set using the protocol adaptation strategy.

2. The data interaction method for a smart grid fusion terminal based on multi-protocol adaptation as described in claim 1, characterized in that, The method for extracting interaction behavior features for each data interaction task in the multi-protocol data interaction task set includes: For each data interaction task, at least one message sample from an interaction sequence window is obtained within the sampling time window; Parsing the message samples yields interaction behavior features, including communication mode features, timing features, and payload features. The communication mode features characterize the message direction of the interaction task, the role of the session initiator, and whether there is a response pairing. The timing features characterize the average message interval, interval jitter, and periodic window of the interaction task. The payload features characterize the type code, data length distribution, and frequency of change of key fields of the interaction task.

3. The data interaction method for a smart grid fusion terminal based on multi-protocol adaptation as described in claim 2, characterized in that, The method for identifying interaction types based on the aforementioned interaction behavior characteristics includes: Perform response pairing detection based on the aforementioned interaction behavior characteristics to obtain the pairing success rate; Extract the change of the session initiator's role in valid pairings with a success rate greater than the preset target. Extract the message flow concentration degree that is less than the preset success rate, where the message flow concentration degree is the proportion of unidirectional flow in the total number of messages; The interaction type is identified based on the pairing success rate, changes in the role of the session initiator, and the concentration of message flow.

4. The data interaction method for a smart grid fusion terminal based on multi-protocol adaptation as described in claim 3, characterized in that, The method for identifying interaction types based on the matching success rate, changes in the role of the session initiator, and the concentration of message flow includes: When the effective matching ratio is greater than or equal to the first threshold and there is an alternation of the session initiator role, it is determined to be a two-way interaction type; When the effective pairing ratio is less than the first threshold and the message flow concentration is higher than the direction threshold, it is determined to be a one-way interaction type.

5. The data interaction method for a smart grid converged terminal based on multi-protocol adaptation as described in claim 1, characterized in that, The method for analyzing the interactive behavior characteristics to obtain the interaction coupling index includes: Data dependency, temporal overlap, and resource contention are calculated based on the interaction behavior characteristics. The data dependency is obtained by calculating the read / write dependency of the data point set of the intersection of the interaction data of both parties. The temporal overlap is obtained by constructing the intersection active interval of the interaction data of both parties and calculating the ratio of the length of the intersection active interval to the window length. The resource contention is the absolute value of the intersection and union of the resources required by the interaction of both parties. The data dependency, time overlap, and resource competition are weighted and averaged to obtain the interaction coupling index.

6. The data interaction method for a smart grid fusion terminal based on multi-protocol adaptation as described in claim 5, characterized in that, The method for generating a protocol adaptation strategy based on the protocol adaptation template, corresponding to the interaction type and the interaction coupling index, includes: Based on the protocol adaptation template, load the baseline configuration set corresponding to the interaction type, including the baseline configuration set for bidirectional interaction type and the baseline configuration set for unidirectional interaction type; The baseline configuration set is dynamically adjusted based on the interaction coupling degree index, and a protocol adaptation strategy is output. The protocol adaptation template includes protocol resource scheduling parameters, status parameters, cache parameters, and protocol mapping level.

7. The data interaction method for a smart grid converged terminal based on multi-protocol adaptation as described in claim 6, characterized in that, The method for dynamically adjusting the baseline configuration set based on the interaction coupling index includes: Configure multiple adjustment steps corresponding to multiple preset coupling degree index ranges; Identify the matching coupling index range in which the interaction coupling index is located, and adjust the baseline configuration set according to the adjustment step size corresponding to the matching coupling index range.

8. The data interaction method for a smart grid fusion terminal based on multi-protocol adaptation as described in claim 6, characterized in that, The state parameters include session hold duration, transaction hold depth, and state timeout threshold; the cache parameters include cache capacity, cache refresh cycle, and cache retention duration; and the protocol mapping level includes full semantic mapping level, partial semantic mapping level, and aggregate semantic mapping level.

9. The data interaction method for a smart grid fusion terminal based on multi-protocol adaptation as described in claim 1, characterized in that, When the protocol executor detects a change in the interaction type, it reloads the corresponding baseline configuration set and updates the protocol adaptation strategy based on the reloaded baseline configuration set.

10. A data interaction system for a smart grid converged terminal based on multi-protocol adaptation, characterized in that: The steps for implementing the data interaction method for a smart grid fusion terminal based on multi-protocol adaptation as described in any one of claims 1 to 9 include: The multi-protocol data interaction task set construction module is used to acquire multi-source protocol communication data from the smart grid converged terminal and construct a multi-protocol data interaction task set. The interaction type identification module is used to extract interaction behavior features for each data interaction task in the multi-protocol data interaction task set, and identify the interaction type according to the interaction behavior features. The interaction type includes bidirectional interaction type and unidirectional interaction type. The interaction coupling degree index acquisition module is used to analyze the interaction behavior characteristics to obtain the interaction coupling degree index. The protocol adaptation strategy generation module is used to define a protocol adaptation template and generate a protocol adaptation strategy corresponding to the interaction type and the interaction coupling index based on the protocol adaptation template. The protocol adaptation template includes protocol resource scheduling parameters, status parameters, cache parameters and protocol mapping level. The protocol conversion execution module is used to perform protocol conversion of the multi-protocol data interaction task set through the protocol execution machine in accordance with the protocol adaptation strategy.

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