Cross-border data multi-terminal display interaction system based on digital cockpit and interaction method thereof

Abstract

The invention provides a cross-border data multi-terminal display interaction system based on a digital cockpit and an interaction method thereof. The cross-border data multi-terminal display interaction system comprises a data acquisition module, a data transmission module, a data storage module, a data processing module, a data display interaction module, a user authentication and authority management module, a data sharing and collaboration module and the like. The data acquisition module acquires and preprocesses data from a cross-border multivariate data source; the transmission module adopts a security protocol to guarantee secure transmission of data and can monitor the link state; the storage module constructs a distributed system to store data, and can perform classified management and backup recovery; the processing module processes data by using a big data technology; the display interaction module provides a multi-terminal adaptation interface, a rich visual component and an interaction function; the user authentication and authority management module ensures safe access of data; and the data sharing and cooperation module supports real-time synchronization and conflict processing. Through a CBMTIA algorithm, the system realizes data acquisition integration and preprocessing, encryption security transmission, intelligent terminal identification adaptation, data synchronization and consistency maintenance.

Description

Technical Field

[0001] The present invention relates to the field of multi-terminal display interaction systems, and in particular to a cross-border data multi-terminal display interaction system based on a digital cockpit and an interaction method thereof; Background Art In today's era of accelerating globalization, cross-border business is booming, and enterprises are involved in a large amount of data interaction and processing in the process of cross-border operations. The sources of cross-border data are extensive and complex, covering many business systems, sensors and third-party platforms in different countries and regions. These data sources have significant differences in data format, data standards and data quality, which brings huge challenges to data integration and management. For example, the date format may be different in different countries, some use "MM-dd-yyyy" and some use "dd / MM / yyyy"; the measurement units of numerical data may also be inconsistent, such as currency units, weight units, etc.

[0002] With the popularization of mobile Internet technology, multiple terminal devices (such as computers, tablets, mobile phones, etc.) are increasingly used in cross-border business scenarios. Users expect to be able to access and analyze cross-border data anytime and anywhere on different types of terminals to support their decision-making and business operations. However, different terminal devices have their own characteristics in terms of screen size, resolution, processing power, and interaction methods. This makes it an urgent problem to achieve high-quality display and convenient interaction of cross-border data on a variety of terminals.

[0003] At the same time, cross-border data transmission faces many risks. The complexity and uncertainty of the network environment lead to high data transmission delays and limited bandwidth, which seriously affect the timeliness and availability of data. In addition, data security and privacy protection are crucial. Cross-border data involves laws and regulations of different countries and regions as well as the business secrets of enterprises. It is necessary to ensure the confidentiality, integrity and reliability of data during transmission and storage to prevent data leakage and illegal tampering.

[0004] Existing data processing technologies and systems often fail to fully meet the special needs of cross-border data multi-terminal display and interaction. Some traditional data integration methods cannot effectively cope with the diversity and complexity of data sources when processing cross-border data, resulting in inaccurate and incomplete data integration. In terms of data transmission, conventional transmission protocols and technologies may not provide sufficient security and stability in cross-border scenarios. In terms of multi-terminal adaptation, the lack of intelligent identification and adaptation mechanisms makes it difficult to provide personalized display and interactive experience based on the characteristics of different terminals. Therefore, there is an urgent need for an innovative cross-border data multi-terminal display and interaction system based on a digital cockpit and its interaction method to overcome these challenges and achieve efficient utilization and value maximization of cross-border data. Summary of the invention

[0005] The main purpose of the present invention is to provide a cross-border data multi-terminal display and interaction system based on a digital cockpit and its interaction method, so as to solve the problem that traditional data integration methods cannot effectively deal with the diversity and complexity of data sources when processing cross-border data, resulting in inaccurate and incomplete data integration. In terms of data transmission, conventional transmission protocols and technologies may not be able to provide sufficient security and stability in cross-border scenarios. In terms of multi-terminal adaptation, there is a lack of intelligent identification and adaptation mechanisms, making it difficult to provide personalized display and interactive experience according to the characteristics of different terminals; In order to solve the above technical problems, the technical solution adopted by the present invention is: a cross-border data multi-terminal display and interaction system based on a digital cockpit, the digital cockpit interaction system includes a data acquisition module, a data transmission module, a data storage module, a data processing module, a display and interaction module, a user authentication and authority management module and a data sharing and collaboration module; The data collection module is used to collect data from cross-border data sources; The data transmission module is used to transmit cross-border data using a secure and reliable transmission protocol; The data storage module is used to build a distributed data storage system to store cross-border data; The data processing module is used to process the stored data in real time or offline using big data processing technology; The display interaction module is used to develop display interfaces suitable for a variety of terminals, adopts responsive design, and provides data visualization components; The user authentication and authority management module is used to authenticate users; The data sharing and collaboration module is used to realize data sharing and collaboration among users.

[0006] In the preferred embodiment, the feature is: The cross-border data sources collected by the data collection module include business databases, sensors, and third-party data platforms in different countries and regions; The data collection module collects data through API calls, file transfers, database connection queries, and web crawlers, and performs preliminary cleaning and conversion on the collected data to remove noise data, erroneous data, and unify the data format.

[0007] In the preferred solution, the transmission protocols of the data transmission module include HTTPS and SFTP. The data transmission module establishes a monitoring mechanism for the data transmission link and monitors the data transmission status in real time, including transmission speed, packet loss rate, and delay. For large-scale data transmission, data segmentation and breakpoint resumption technology are used.

[0008] In a preferred embodiment, the distributed data storage system in the data storage module includes a distributed file system or a cloud storage service based on Hadoop; The data storage module stores data in categories, establishes a data warehouse or data lake architecture based on data types, business areas, and time periods, implements data backup and recovery strategies, and performs full and incremental backups regularly; In the preferred embodiment, the visualization components in the interactive display module include charts, reports, and dashboards. The user interaction functions in the display interaction module include data filtering, sorting, drilling, and zooming; The terminals include computers, tablets, mobile phones, and large screens.

[0009] In the preferred solution, the data sharing and collaboration module synchronizes data in real time, using long polling and WebSockets technology to achieve real-time data synchronization; Implement a conflict detection mechanism to automatically select the best solution to resolve conflicts when multiple terminals modify the same data at the same time.

[0010] In the preferred solution, the CBMTIA algorithm is used to realize cross-border data multi-terminal display interaction. The method is: S1. The data acquisition module performs data integration and collects data from data sources in different countries and regions. The data sources include cloud services, databases, and API interfaces. Data preprocessing: cleaning, deduplication, and formatting the collected data to ensure data quality and consistency; S2, Data encryption and secure transmission steps: Data encryption, using the Advanced Encryption Standard AES-256 to encrypt data; Security protocols, using HTTPS, TLS and other security protocols to establish secure data transmission channels; S3, intelligent terminal identification and adaptation step: terminal identification, automatically identifying the user terminal type by analyzing the User-Agent information in the user request, the terminal type includes desktop, tablet, and mobile phone; Adaptation strategy: select the most appropriate display template and layout according to the terminal type; S4, data synchronization and consistency maintenance steps: real-time synchronization, using long polling and WebSockets technology to achieve real-time data synchronization; Conflict detection and resolution, implements a conflict detection mechanism, and automatically selects the best solution to resolve conflicts when multiple terminals modify the same data at the same time.

[0011] In the preferred embodiment, the specific steps of step S1 are: Data collection: Collect data from cloud services, databases, and API interfaces in different countries and regions; For cloud service data, obtain data through the access interface and authentication mechanism provided by the cloud service provider, and use the AWSS3 API to download data; For database data, establish corresponding database connection according to MySQL or Oracle database and write SQL query statements to extract data; For API interface data, construct a legal request and send it to the API server according to the requirements of the API documentation to obtain the returned data. Use the `requests` library to send a GET request to obtain the data. The collected data is stored in a temporary buffer for subsequent processing; Data cleaning: Detect and process missing values; suppose an attribute in the data set is , the number of data points is , the number of missing values ​​is Calculate missing rate , this formula is used to measure the proportion of missing data of a certain attribute in the data set in order to determine the subsequent processing method; like Less than the set threshold , then the mean filling method is used, that is, the mean of the non-missing values ​​of the attribute is calculated , ,in For attributes No. non-missing values, the formula is used to calculate the mean required for mean filling, Fill missing values; like Greater than and less than , a model-based prediction filling method is used, using a linear regression model ,in For and attributes Other related attribute vectors, and are model parameters, is the error term, and the missing values ​​are predicted by the trained model. This formula is the general form of the linear regression model, which is used to predict missing values ​​based on related attributes; like Greater than , then considering the availability of attribute data, it may be necessary to further analyze or discard the attribute; Handle outliers; for numerical data, calculate the deviation of each data point from the mean , set the deviation threshold ;like , the data point is considered an outlier and the neighboring value replacement method is used (or modified according to the business logic of the data); Data deduplication: For structured data, check for duplicates based on the unique identification field of the data; suppose there is records, the unique identification field is ID, and a hash table is constructed , iterate over each record in the dataset and calculate the hash value of its ID ;like If it already exists, it means that the record is a duplicate record and it will be deleted; if it does not exist, Deposit , and keep the record; For unstructured data, similarity detection algorithm is used; text data is converted into feature vectors, using TF-IDF vector representation, ,in Words In the documentation The number of occurrences in |D| is the total number of documents, To contain words The formula is used to calculate the TF-IDF value of words in text data, thereby converting text into feature vectors and calculating the cosine similarity between vectors. ,in and are two feature vectors. This formula is used to measure the similarity between two text data. When the similarity is greater than the set threshold When , it is considered as duplicate data and one of them is retained; Data formatting: unify the date format; traverse the date fields in the data set, use regular expressions to match different date formats, and convert them to a unified format; Unify numerical units; identify numerical values ​​and their units in data, and convert them according to pre-defined unit conversion rules.

[0012] In the preferred embodiment, the specific steps of steps S2-S3 are: S21. Data encryption and secure transmission: Use the advanced encryption standard AES-256 to encrypt the data; suppose the original data is , divide it into several 128-bit data blocks ; Generate a 256-bit encryption key ,Key generation can use a cryptographically secure pseudo-random number generator to ensure the randomness and confidentiality of the key; For each data block , perform multiple rounds of encryption operations; the encryption process uses the round function of the AES encryption algorithm, which includes four operations: byte replacement SubBytes, row shift ShiftRows, column confusion MixColumns, and round key addition AddRoundKey; The round key is The round key is composed of the master key Generated through the key expansion algorithm. The key expansion algorithm is relatively complex and will not be expanded in detail here. The encryption formula is: ,in For the encrypted ciphertext block, the SubBytes operation replaces each byte in the data block according to a fixed S-box, changes the value of the byte, and increases the nonlinearity of the data; the ShiftRows operation cyclically shifts the rows of the data block to disrupt the position of the bytes; the MixColumns operation confuses the columns of the data block to further spread the changes in the data; the AddRoundKey operation performs an XOR operation on the round key and the data block that has undergone the previous operation to achieve the mixing of the key and the data. This formula fully describes the process of one round of encryption in the AES-256 encryption algorithm. After multiple rounds of such operations, the encrypted ciphertext is finally obtained. ); S21. Select HTTPS or TLS security protocol to establish a data transmission channel. During the TLS protocol handshake, perform key exchange and encryption suite negotiation. Assume that the client and server have private keys respectively. and , public key and ; First, the client sends a client hello message to the server, which contains information such as the list of encryption suites supported by the client. After receiving the message, the server selects a suitable encryption suite and sends the server certificate to the client. The client verifies the legitimacy of the server certificate. If the verification is successful, the client generates a random number , using the server public key Encrypt it , the encryption formula is ,in The modulus associated with the server's public key is used in this formula to encrypt a random number using the public key, ensuring that only the server can decrypt and obtain the random number for subsequent key generation and send it to the server. The server uses the private key Decrypted , and then the server also generates a random number , both parties generate a key based on a predefined key generation function Generate Session Key ; In order to optimize the transmission performance, the encrypted data is compressed during the data transmission process; assuming that the original encrypted data is , the compressed data is C', the compression ratio , where |C| and |C'| are the byte lengths of the original data and the compressed data respectively. This formula is used to measure the compression effect. The larger the compression ratio, the better the compression effect and the smaller the amount of data transmitted. Adopt adaptive compression algorithm to dynamically adjust compression parameters according to the statistical characteristics of data; At the same time, in order to improve transmission efficiency and reduce network latency, multiplexing in HTTP / 2 is used to transmit multiple requests and responses simultaneously on one TCP connection. Suppose the request set is , the response set is , through reasonable flow control and priority allocation mechanism, ensure that important data is transmitted first; S31, terminal identification: when the user initiates a request, obtain the User-Agent information in the request; the User-Agent string is UA, which is parsed; First, define a feature vector To represent the characteristics of the terminal, These can be features such as operating system type, browser type, device model, etc. If the UA contains the string "Windows", then Indicates that the operating system is Windows, otherwise ; If it contains the string "Chrome", then Indicates that the browser is Chrome, and so on; Build a terminal feature library ,in is the feature vector of the known terminal type; calculate the User-Agent feature vector With each feature vector in the feature library Similarity ; Here we use the cosine similarity formula ,in is the feature vector The The formula is used to measure the similarity between two feature vectors. The higher the similarity, the more the terminal type corresponding to the User-Agent matches the terminal type in the feature library. Select the terminal type with the highest similarity as the recognition result; , the identified terminal type is Corresponding terminal type; if the similarity is lower than the set threshold , it is considered that the terminal type cannot be accurately identified and further information or other identification methods may be required; S32, adaptation strategy: select the most appropriate display template and layout according to the identified terminal type; set the display template set to , the layout set is ; For each terminal type , define an adaptation function To measure display template and layout For terminal type The degree of adaptation; the adaptation function can take into account multiple factors, such as screen resolution , screen size ratio , Equipment performance ; For screen resolution , set template The optimal resolution range is , then the resolution adaptation factor ,in is an adjustment coefficient used to control the speed at which the degree of adaptation decreases when the resolution does not match. The formula calculates the adaptation factor based on the degree of match between the screen resolution and the optimal resolution range of the template. The closer to the optimal range, the higher the adaptation factor; For screen size ratio , set template The optimal size ratio is , then the size ratio adaptation factor ,in To adjust the coefficient, the formula calculates the adaptation factor based on the difference between the screen size ratio and the template's optimal ratio. The smaller the difference, the higher the adaptation factor; For device performance , set template The minimum performance required is , then the performance adaptation factor ,This formula calculates the adaptation factor based on the comparison between the actual performance of the device and the minimum performance required by the template. The higher the performance, the higher the adaptation factor; Comprehensive adaptation function ,in , and is the weight coefficient, which is used to adjust the importance of different factors in the adaptation process. By setting the weights reasonably, the influence of certain factors can be emphasized according to actual needs. This formula comprehensively considers factors such as screen resolution, size ratio and device performance to calculate the overall adaptability of the display template and layout to the terminal type; Choose the adaptation function Get the maximum value display template and layout As the final adaptation result, ; Then, the data is rendered and displayed according to the selected display template and layout to ensure the best user experience on different terminals.

[0013] In the preferred embodiment, the specific steps of step S4 are: S41, Real-time synchronization: The client sends a data request to the server and sets a longer timeout period ; Assume the time when the client sends the request is The time when the server receives the request is ; After receiving the request, the server checks whether the data has been updated. If the data has not been updated, the server will keep the connection waiting until the data is updated or the timeout period is reached. Suppose the data update time is ; When data is updated or a timeout occurs, the server sends a response to the client; if it is a data update, the response contains the updated data ; If it is a timeout, the response can include a flag indicating that there is no new data; After receiving the response, if it is a data update, the client will update the local data immediately; if it is a timeout, the client can decide whether to initiate a new long polling request immediately or wait for a period of time before initiating the request according to business needs; Long polling cycle It can be dynamically adjusted according to the data update frequency and business needs; The number of data updates in the second longest poll is , average update interval ,in For the The time of data update, For the The time of the second long polling request. This formula is used to calculate the average data update interval in order to dynamically adjust the long polling cycle. Less than the current long polling period , you can shorten it appropriately ;if Greater than , you can extend it appropriately , to balance server load and data real-time; S42, the client and the server establish a WebSockets connection; during the connection establishment process, a protocol handshake is performed to exchange necessary information; Once the connection is established successfully, the server can actively push data update messages to the client. Suppose the data update event on the server is ,when When this happens, the server immediately sends the updated data Encapsulate into WebSockets message format and send to all clients related to the data; After receiving the WebSockets message, the client parses the message content and extracts the updated data , and update local data; To ensure the stability of the WebSockets connection, the client and server send heartbeat messages periodically. Suppose the time for the client to send heartbeat messages is , the time when the server receives the heartbeat message is , heartbeat delay ;if Exceeding the set threshold , it is considered that there may be a problem with the connection, and the client or server can try to re-establish the connection; S43, conflict detection mechanism: for each data item Maintaining a version vector ,in is the number of terminals that may modify the data item, Indicates terminal For data items The modified version number; initially, all version numbers are ; When the terminal Prepare to modify data items When a pre-modification request is sent to the server, the request contains the terminal What we know now Version vector of ; After receiving the pre-modification request, the server checks the version vector; for each element in the version vector ,if , that is, other terminals have updated versions, indicating that there is a conflict; let the conflict detection function , let the conflict detection function formula be used to determine whether there is a conflict. When it returns If there is a conflict, return , indicating that there is no conflict; If there is a conflict, the server sends a Returns conflict information, including the conflicting version vector and conflicting data items The current value of the terminal You can decide how to handle the conflict based on the conflict information, such as merging the conflict or abandoning the modification; S43, conflict resolution strategy: When a conflict is detected and the data can be merged, the server obtains the data modification timestamp of each conflicting version , is the number of conflicting versions; let data item The merged value is x'. For text data, different versions of text content can be concatenated in the order of timestamps. ,in Indicates the timestamp The formula is used to merge text data with different timestamps, retain all modification history, and facilitate users to view and handle conflicts; When a conflict occurs and cannot be automatically merged, the server pushes the conflict information to the relevant users; the user views the conflict details on the terminal, including the data content of different versions, modification time, modification user and other information; The user selects a version as the final version on the terminal, or manually edits and merges the data; let the version selected by the user be , if it is a manual edit merge, then For the edited result, the terminal sends the result selected by the user back to the server; After receiving the user's selection, the server updates the data item The value of , and update the version vector , add the version number of the corresponding terminal , indicating that the terminal is responsible for the data item An effective modification was made.

[0014] The present invention provides a cross-border data multi-terminal display interactive system based on a digital cockpit and its interactive method. In terms of data processing and management, through a carefully designed data acquisition module, it can comprehensively and accurately obtain data from various cross-border data sources, and use a variety of effective technologies for preliminary processing, which greatly improves the data quality and provides a solid foundation for subsequent analysis. The distributed storage system constructed by the data storage module and the reasonable data storage structure can easily cope with the storage needs of massive cross-border data, realize efficient data management, and the perfect data backup and recovery strategy effectively guarantees the security and availability of data.

[0015] As far as data transmission is concerned, secure and reliable transmission protocols combined with strict data encryption measures, as well as detailed monitoring of transmission links and optimized transmission strategies, not only effectively overcome the problems of high latency and limited bandwidth in cross-border data transmission, but also ensure the confidentiality, integrity and availability of data during transmission, reducing the risk of data leakage and tampering.

[0016] From the perspective of user experience, the diverse authentication and permission management methods ensure data security, and accurately allocate data access levels and operation permissions based on user roles and permissions to meet the needs of different users. Rich and customizable visualization templates, coupled with real-time data update push, enable users to grasp the latest data dynamics in real time and provide timely and accurate information for decision-making. Powerful interactive functions, such as convenient data filtering, drilling and zooming operations, as well as efficient data sharing and collaboration mechanisms, greatly improve the efficiency and depth of user data analysis, promote team collaboration, and enhance overall work efficiency.

[0017] As for the adaptability and scalability of the system, the intelligent terminal identification and adaptation function enables it to automatically select the best display template and layout on different types of terminals, so that users can get a high-quality experience regardless of the device they use. At the same time, the overall system architecture and algorithm design have good flexibility and can be easily adjusted and expanded according to the development of cross-border business and technological progress, which can effectively promote the efficient and stable development of cross-border business and enhance the competitiveness of enterprises in the global market. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The present invention will be further described below in conjunction with the accompanying drawings and embodiments: Figure 1 This is the process of the cross-border data multi-terminal display interaction system and its interaction method based on the digital cockpit of the present invention DETAILED DESCRIPTION Example 1 like Figure 1 As shown, a cross-border data multi-terminal display and interaction system based on a digital cockpit, the digital cockpit interaction system includes a data acquisition module, a data transmission module, a data storage module, a data processing module, a display and interaction module, a user authentication and authority management module and a data sharing and collaboration module; The data collection module is used to collect data from cross-border data sources; The data transmission module is used to transmit cross-border data using a secure and reliable transmission protocol; The data storage module is used to build a distributed data storage system to store cross-border data; The data processing module is used to process the stored data in real time or offline using big data processing technology; The display interaction module is used to develop display interfaces suitable for a variety of terminals, adopts responsive design, and provides data visualization components; The user authentication and authority management module is used to authenticate users; The data sharing and collaboration module is used to realize data sharing and collaboration among users.

[0019] In the preferred embodiment, the feature is: The cross-border data sources collected by the data collection module include business databases, sensors, and third-party data platforms in different countries and regions; The data collection module collects data through API calls, file transfers, database connection queries, and web crawlers, and performs preliminary cleaning and conversion on the collected data to remove noise data, erroneous data, and unify the data format.

[0020] In the preferred solution, the transmission protocols of the data transmission module include HTTPS and SFTP. The data transmission module establishes a monitoring mechanism for the data transmission link and monitors the data transmission status in real time, including transmission speed, packet loss rate, and delay. For large-scale data transmission, data segmentation and breakpoint resumption technology are used.

[0021] In a preferred embodiment, the distributed data storage system in the data storage module includes a distributed file system or a cloud storage service based on Hadoop; The data storage module stores data in categories, establishes a data warehouse or data lake architecture based on data types, business areas, and time periods, implements data backup and recovery strategies, and performs full and incremental backups regularly; In the preferred embodiment, the visualization components in the interactive display module include charts, reports, and dashboards. The user interaction functions in the display interaction module include data filtering, sorting, drilling, and zooming; The terminals include computers, tablets, mobile phones, and large screens.

[0022] In the preferred solution, the data sharing and collaboration module synchronizes data in real time, using long polling and WebSockets technology to achieve real-time data synchronization; Implement a conflict detection mechanism to automatically select the best solution to resolve conflicts when multiple terminals modify the same data at the same time.

[0023] Basic architecture and module function realization of cross-border data multi-terminal display interaction system and interaction method based on digital cockpit 1. System architecture and module composition 1. Overall system architecture The cross-border data multi-terminal display and interaction system based on the digital cockpit is mainly composed of data acquisition module, data transmission module, data storage module, data processing module, display and interaction module, user authentication and authority management module, and data sharing and collaboration module. These modules work together to realize the full process of cross-border data from collection to display and interaction on multiple terminals.

[0024] 2. Implementation of each module function Data collection module: Data source location and connection: Responsible for accurately locating cross-border data sources in different countries and regions, including business databases, sensors, and third-party data platforms. For different types of data sources, use connection technologies that are compatible with them. For example, for business databases, configure corresponding connection parameters according to the type of database to establish a stable database connection. For sensor data, develop corresponding receiving programs based on the sensor's communication protocol to ensure that data can be accurately received.

[0025] Application of data collection technology: Use a variety of advanced data collection technologies to obtain data. In terms of API calls, conduct in-depth research on the API documents provided by each data source, construct legal requests according to the document requirements, and achieve accurate data extraction. For example, obtain product sales data from the API of an internationally renowned e-commerce platform, including product name, price, sales volume, sales area and other information. File transfer technology is used to collect data stored in files, such as obtaining historical transaction record files from a distributed file system and downloading them through FTP or SFTP protocols. Database connection queries target structured data, write optimized SQL query statements, and extract required data from the database. Under the premise of legality and compliance, web crawler technology is used to collect public web page data, such as industry news on international news websites, trade policies issued by government departments, and other information. By setting reasonable crawling rules, effective data acquisition is ensured.

[0026] Preliminary data processing: Perform comprehensive preliminary cleaning and conversion operations on the collected data. During the cleaning process, accurately identify and process the noise data and erroneous data in the data. For example, by setting a reasonable value range for the data, identify and eliminate obviously erroneous data points, such as records with negative prices in sales data. At the same time, remove duplicate records in the data to ensure the uniqueness of the data. For missing values, choose the appropriate processing method based on the characteristics of the data and business needs. For example, for a small number of missing values ​​in time series data, use linear interpolation to fill them; for data records with a large number of missing attribute values, analyze them according to business logic and may choose to delete or mark them as invalid records. In terms of data conversion, unify the data format and convert date data in different formats into a unified "yyyy-MM-dd" format to facilitate subsequent data processing and analysis. Unify the units of numerical data, such as converting data in different currency units into a unified base currency unit to ensure the consistency of data in terms of dimensions.

[0027] Data transmission module: Selection and configuration of secure transmission protocols: Prioritize the use of secure and reliable transmission protocols such as HTTPS and SFTP to ensure the confidentiality, integrity and availability of cross-border data during transmission. For the HTTPS protocol, configure the digital certificate on the server side to ensure the legitimacy, validity and integrity of the certificate. The certificate contains the server's public key information, which is used by the client to verify the server's identity and encrypt data transmission. During the configuration process, select a suitable encryption suite, such as TLS_ECDHE_RSA_WITH_AES_256_GCM_SHA384, to balance encryption strength and performance. For the SFTP protocol, configure the correct username, password and key file to ensure the security of file transfer.

[0028] Transmission link monitoring and optimization: Establish a real-time monitoring mechanism for the data transmission link, and comprehensively monitor the data transmission status through special monitoring tools or self-developed monitoring modules. Monitoring parameters include key indicators such as transmission speed, packet loss rate, and delay. For example, collect transmission data every 5 seconds to calculate the current transmission speed and packet loss rate. When the transmission speed is lower than the set threshold, automatically adjust the transmission parameters, such as increasing the number of transmission threads or optimizing the data block strategy. If the packet loss rate exceeds the allowable range, immediately start the retransmission mechanism to ensure data integrity. For large-scale data transmission, use data segmentation and breakpoint resume technology. Divide the large data file into multiple smaller data segments, each with a size of 1MB. During the transmission process, if a segment fails to be transmitted, only the segment needs to be retransmitted, without retransmitting the entire file, which improves transmission efficiency and reliability.

[0029] Data storage module: Distributed storage system construction: According to the scale and growth trend of cross-border data, select a suitable distributed data storage system. If the data volume is huge and the scalability requirements are high, the Hadoop-based distributed file system (HDFS) is preferred. When building HDFS, reasonably configure the number of data nodes (set to 10 data nodes according to the data volume and storage requirements), the replication factor (set to 3 to ensure redundant storage and high availability of data), and the block size (set to 128MB to balance data storage and read and write performance). If the enterprise prefers to use cloud services, choose cloud storage services (AWSS3, AzureBlobStorage, etc.), and select the appropriate storage type and storage area according to the access frequency and storage period of the data.

[0030] Data storage structure design and management: Based on multi-dimensional information such as data type, business field, and time period, carefully design the data warehouse or data lake architecture. In the data warehouse, establish a star or snowflake data model to clarify the relationship between the fact table and the dimension table. For example, in the sales data warehouse, the sales order table is the fact table, and the customer table, product table, time dimension table, etc. are dimension tables. They are associated through primary keys and foreign keys to facilitate data query and analysis. For the data lake architecture, data is stored in the original data format to retain the integrity and flexibility of the data, which is convenient for subsequent various types of data analysis and mining. At the same time, implement a complete data backup and recovery strategy, and perform full and incremental backups regularly. Full backups are performed once a week, and incremental backups are performed every day. The backup data is stored in redundant storage devices in different locations to ensure data security. Regularly perform recovery tests on backup data to verify the integrity and availability of backup data and ensure that data can be restored quickly and accurately when data is lost or damaged.

[0031] Data processing module: Selection and application of big data processing technology: Use advanced big data processing technologies, such as Spark and Flink, to process stored data in real time or offline. For real-time data processing tasks, such as real-time monitoring of order data on cross-border e-commerce platforms, use the streaming processing function of Spark Streaming or Flink, set a reasonable processing window size and trigger interval, and ensure that data can be processed in a timely manner. For offline data processing, such as monthly analysis of historical sales data, use Spark's batch processing function to write efficient processing programs for data aggregation, analysis, and mining operations.

[0032] Data analysis and mining operations: During the data processing process, a series of complex data analysis and mining operations are performed. Calculate key indicators, such as sales, profits, market share, customer conversion rate, etc. in cross-border e-commerce business. Through the analysis of historical sales data, mining sales trends, seasonal patterns, and sales differences in different regions and different products. Use machine learning algorithms for predictive analysis, such as using time series analysis algorithms (such as ARIMA models) to predict sales trends for a period of time in the future, providing decision-making basis for the company's production plan and market strategy. At the same time, through cluster analysis algorithms (such as K-Means algorithm), customer data is segmented to identify different types of customer groups to provide support for precision marketing.

[0033] Display interaction module: Development of multi-terminal adaptive display interface: Develop display interfaces suitable for a variety of terminal devices (including computers, tablets, mobile phones, large screens, etc.), adopt responsive design concepts to ensure that the interface can be adaptively displayed on different devices to provide a consistent user experience. For the computer side, use Web technology (HTML5, CSS3, JavaScript) to develop functional and complex Web applications, and make full use of large screen space to display detailed data charts, analysis tools and operation menus. For mobile terminals such as tablets and mobile phones, use mobile application development technology (ReactNative, Flutter, etc.) to design simple and touch-friendly interfaces, optimize touch interaction operations, and facilitate users to quickly obtain and analyze data in mobile scenarios. For large-screen display scenarios, such as the large screen of the enterprise monitoring center, develop a special large-screen display application, use a layout with outstanding visualization effects and high information density, and present key data in an intuitive way, such as displaying global sales distribution, real-time logistics status and other information through a large data screen.

[0034] Data visualization components and interactive function implementation: Provide a rich variety of data visualization components, including various charts, including bar charts, line charts, pie charts, maps, etc., and reports. Users can choose the appropriate visualization component to display data according to their own analysis needs. At the same time, powerful user interaction functions are implemented, such as data filtering function, users can quickly filter out the data of interest by setting filtering conditions; sorting function allows users to sort data according to specified fields; drilling function supports users to gradually deepen from macro data to micro data, such as drilling from global sales data to sales details of a country, region, or specific product; zoom function allows users to adjust the display ratio of data when displaying charts, and view local details or overall trends of data.

[0035] User authentication and permission management module: Authentication method integration and implementation: Integrate a variety of advanced user authentication methods to provide users with a convenient and secure login method. The username / password authentication method uses a secure password hashing algorithm (bcrypt or argon2) to store user passwords, ensuring that the passwords are saved in encrypted form in the database to prevent password leakage. When the user logs in, the input password is hashed and compared with the hash value stored in the database for verification. The digital certificate authentication method requires the user to upload a legal digital certificate, and the system confirms the user's identity by verifying the validity of the certificate. Biometric authentication (fingerprint recognition, facial recognition) needs to be integrated with the corresponding hardware devices or software libraries. By collecting the user's biometric information (fingerprint image, facial feature points, etc.) and comparing it with the pre-registered biometric template, the user's identity can be quickly identified and authenticated.

[0036] Permission allocation and management mechanism: Establish a role-based access control (RBAC) model to accurately allocate different data access levels and operation permissions according to the user's role and responsibilities in the enterprise. For example, the system administrator role has full access and management permissions to all data, including operations such as adding, deleting, modifying, querying data, and assigning user permissions; the business manager role can view and analyze data related to the business of this department, but has no right to modify the system configuration and data of other departments; the ordinary employee role can only access and operate specific data related to their own work, such as sales staff can only view the customer and order data they are responsible for. Permission allocation information is stored in the permission database. When a user logs in to the system, the corresponding permission list is obtained according to his role. When the user performs data operations, the system verifies the user's permissions in real time to ensure that the user can only perform operations within his authority, effectively protecting the security and confidentiality of the data.

[0037] Data sharing and collaboration module: Data sharing function implementation: Provide convenient data sharing function to facilitate sharing of data and analysis results between users. Set an obvious data sharing button on the display interface. After the user clicks the button, he can choose a variety of sharing methods. For example, through the email sharing function, the system automatically adds data or reports to the email as an attachment (the user only needs to fill in the recipient address to send it. At the same time, it supports integration with instant messaging tools. Users can send data links directly to designated groups or users to achieve instant sharing. During the sharing process, the system controls the sharing scope based on the user's permissions and the sensitivity of the data to ensure that the data can only be accessed by authorized users.

[0038] Collaborative environment construction and conflict handling: Build a multi-person collaborative work environment that allows multiple users to analyze and operate data at the same time. Through the shared session mechanism, real-time synchronization of data between multiple terminals is achieved. For example, when a user filters or modifies data on his or her terminal, the interface of other collaborative users can be updated immediately to display the latest data status. In order to avoid data conflicts caused by multiple people modifying the same data at the same time, a complete conflict detection mechanism is established. When a conflict occurs (such as two users modifying the same data record at the same time), the system automatically detects the conflict and handles it according to the preset conflict resolution strategy. A common strategy is to give priority to the latest submitted changes based on timestamps or user operation order; for complex conflict situations, the system can prompt users to manually resolve conflicts and provide a comparison view and operation interface of conflicting data to facilitate users to make decisions and handle them, ensuring the consistency and accuracy of data during the collaboration process.

[0039] 2. System initialization and basic configuration 1. System deployment and configuration: The system is deployed on an enterprise-level server, and the server's hardware resources are configured according to the system architecture and module function requirements. For example, in the case of heavy data processing tasks, a high-performance multi-core CPU and large-capacity memory are equipped to ensure that the system can run efficiently.

[0040] Install and configure the required software environment, including operating system, database management system, big data processing framework, and related development tools and libraries.

[0041] 2. Communication and collaboration configuration between modules: Configure the communication interface and protocol between modules to ensure that data can be accurately and efficiently transmitted between different modules. For example, the data acquisition module and the data transmission module use message queues for data transmission to ensure the continuity of data acquisition and the stability of data transmission. The data processing module and the data storage module interact with each other through an efficient database connection pool to improve data reading and writing efficiency.

[0042] Establish a collaborative mechanism between modules and clarify the responsibilities and data flows between modules. For example, after the data acquisition module collects new data, it transmits the data to the data storage module for storage through the data transmission module. The data processing module obtains data from the data storage module for processing, and the processed results are then transmitted to the display interaction module for display. After the user's operation request in the display interaction module is verified by the user authentication and authority management module, it is processed by the corresponding module. The modules work closely together to realize the overall function of the system.

[0043] 3. System startup and basic function testing 1. System startup process: Start the data collection module, initialize the data source connection, start the data collection thread, and start collecting cross-border data. The data collection module obtains data from various data sources according to the preset collection rules and frequency, and stores it in the temporary cache after preliminary processing.

[0044] Start the data transmission module, establish connections with the data acquisition module and the data storage module, start the transmission link monitoring thread, and start monitoring the data transmission status. At the same time, according to the configured security protocol, perform key exchange and encryption suite negotiation, and prepare to receive and transmit data.

[0045] Start the data storage module, initialize the distributed storage system, create a data warehouse or data lake architecture, start data backup and recovery services, and wait for data storage requests.

[0046] Start the data processing module, load the required big data processing technology and algorithm model, connect to the data storage module, and prepare to process the data.

[0047] Start the display interaction module, load the display interface and visualization components adapted to multiple terminals, start the user authentication and authority management module, and wait for user login and operation requests.

[0048] Start the user authentication and permission management module, load user authentication information and permission rules, and prepare to authenticate and verify user logins and operations.

[0049] Start the data sharing and collaboration module, initialize the sharing session management and conflict detection mechanism, and prepare to process data sharing and collaboration requests.

[0050] 2. Basic functional testing: Perform data collection testing, simulate different types of data sources (databases, APIs, files, etc.), check whether the data collection module can accurately collect data, and verify the integrity and accuracy of the data. For example, query specific data from the test database and check whether the collected data is consistent with the data in the database, including data fields, values, data volume, etc.

[0051] Test the data transmission function, check whether the data transmission between different modules is normal, and verify the security and efficiency of the transmission. By sending test data, monitor the monitoring indicators of the transmission link (transmission speed, packet loss rate, delay) to ensure that the data can be transmitted safely and quickly. At the same time, check whether the decryption of encrypted data is correct and verify the confidentiality of the data during transmission.

[0052] Test the data storage module, write and read test data into the storage system, check whether the data storage and retrieval functions are normal, and verify whether the data storage structure and backup and recovery strategy are effective. For example, after writing a batch of test data, retrieve the data through a query statement to check whether the returned data is correct. Simulate data loss and verify the recovery capability of the backup data.

[0053] Test the multi-terminal adaptability of the display interaction module, access the display interface on different types of terminal devices, check whether the interface can be displayed adaptively, and verify whether the visualization components and interactive functions are working properly.

[0054] Conduct user authentication and permission management tests, log in to the system with different user roles, try to perform various data operations, check whether the system correctly controls data access and operations according to user permissions, and verify the effectiveness of the authentication and permission management mechanism. For example, after logging in, an ordinary employee user tries to access data outside of his or her permission scope, and check whether the system denies access and prompts that the permission is insufficient.

[0055] Test data sharing and collaboration functions, simulate multiple users to perform data sharing and collaboration operations, check whether the shared data reaches the recipient correctly, and verify whether the conflict detection and resolution mechanism can effectively handle concurrent operation conflicts. For example, if two users modify shared data at the same time, check whether the system can detect the conflict and handle it according to the preset strategy to ensure data consistency.

[0056] Example 2 Further illustrate with reference to Example 1, Figure 1 The structure shown uses the CBMTIA algorithm to realize cross-border data multi-terminal display interaction. The method is: S1. The data acquisition module performs data integration and collects data from data sources in different countries and regions. The data sources include cloud services, databases, and API interfaces. Data preprocessing: cleaning, deduplication, and formatting the collected data to ensure data quality and consistency; S2, Data encryption and secure transmission steps: Data encryption, using the Advanced Encryption Standard AES-256 to encrypt data; Security protocols, using HTTPS, TLS and other security protocols to establish secure data transmission channels; S3, intelligent terminal identification and adaptation step: terminal identification, automatically identifying the user terminal type by analyzing the User-Agent information in the user request, the terminal type includes desktop, tablet, and mobile phone; Adaptation strategy: select the most appropriate display template and layout according to the terminal type; S4, data synchronization and consistency maintenance steps: real-time synchronization, using long polling and WebSockets technology to achieve real-time data synchronization; Conflict detection and resolution, implements a conflict detection mechanism, and automatically selects the best solution to resolve conflicts when multiple terminals modify the same data at the same time.

[0057] In the preferred embodiment, the specific steps of step S1 are: Data collection: Collect data from cloud services, databases, and API interfaces in different countries and regions; For cloud service data, obtain data through the access interface and authentication mechanism provided by the cloud service provider, and use the AWSS3 API to download data; For database data, establish corresponding database connection according to MySQL or Oracle database and write SQL query statements to extract data; For API interface data, construct a legal request and send it to the API server according to the requirements of the API documentation to obtain the returned data. Use the `requests` library to send a GET request to obtain the data. The collected data is stored in a temporary buffer (such as a memory cache or a local temporary file) for subsequent processing; Data cleaning: Detect and process missing values; suppose an attribute in the data set is , the number of data points is , the number of missing values ​​is Calculate missing rate , this formula is used to measure the proportion of missing data of a certain attribute in the data set in order to determine the subsequent processing method; like Less than the set threshold , then the mean filling method is used, that is, the mean of the non-missing values ​​of the attribute is calculated , ,in For attributes No. non-missing values, the formula is used to calculate the mean required for mean filling, Fill missing values; like Greater than and less than , a model-based prediction filling method is used, using a linear regression model ,in For and attributes Other related attribute vectors, and are model parameters, is the error term, and the missing values ​​are predicted by the trained model. This formula is the general form of the linear regression model, which is used to predict missing values ​​based on related attributes; like Greater than , then considering the availability of attribute data, it may be necessary to further analyze or discard the attribute; Handle outliers; for numerical data, calculate the deviation of each data point from the mean , set the deviation threshold ;like , the data point is considered an outlier and the neighboring value replacement method is used (or modified according to the business logic of the data); Data deduplication: For structured data, check for duplicates based on the unique identification field of the data (such as the primary key); records, the unique identification field is ID, and a hash table is constructed , iterate over each record in the dataset and calculate the hash value of its ID ;like If it already exists, it means that the record is a duplicate record and it will be deleted; if it does not exist, Deposit , and keep the record; For unstructured data, similarity detection algorithm is used; text data is converted into feature vectors, using TF-IDF vector representation, ,in Words In the documentation The number of occurrences in |D| is the total number of documents, To contain words The formula is used to calculate the TF-IDF value of words in text data, thereby converting text into feature vectors and calculating the cosine similarity between vectors. ,in and are two feature vectors. This formula is used to measure the similarity between two text data. When the similarity is greater than the set threshold When , it is considered as duplicate data and one of them is retained; Data formatting: unify the date format; traverse the date fields in the data set, use regular expressions to match different date formats, and convert them to a unified format; Unify numerical units; identify numerical values ​​and their units in data, and convert them according to pre-defined unit conversion rules.

[0058] (I) In-depth application of CBMTIA algorithm in data collection and preprocessing stage (S1) 1. Refined operations of data integration When collecting data from data sources (cloud services, databases, API interfaces) in different countries and regions, for cloud service data, it is necessary not only to obtain data based on the access interface and authentication mechanism provided by the cloud service provider, but also to consider the interface differences and data format characteristics of different cloud service providers. For example, for AWSS3 cloud storage service, in addition to using its API for data download operations, it is also necessary to deal with possible version control, data encryption and other related configurations. When collecting data from a database (such as MySQL or Oracle), optimize the database connection establishment process according to the characteristics of the database. For example, for high-concurrency data collection requirements, adjust the parameters of the database connection pool (such as the maximum number of connections, the minimum number of connections, the connection timeout, etc.) to improve the efficiency of connection acquisition. For API interface data, in addition to constructing legal requests according to the requirements of the API documentation, it is also necessary to establish a request caching mechanism to avoid frequent repeated requests for the same data and reduce the pressure on the API server.

[0059] When the collected data is stored in a temporary cache area (such as a memory cache or a local temporary file), an intelligent cache management strategy is used. The storage location and validity period of the data in the cache are dynamically adjusted according to the frequency of use and timeliness of the data. For example, for data that is frequently used recently and updated less frequently, it is stored in a high-speed cache area (such as the LRU cache in the memory) and its validity period is extended; for data that is frequently updated but not used frequently, it is stored in a low-speed cache area (such as the local disk cache) and its validity period is shortened to improve cache utilization and data access efficiency.

[0060] 2. Strengthening measures for data preprocessing Data cleaning: When detecting and processing missing values, in addition to calculating the missing rate and selecting a processing method based on the threshold, it is necessary to further analyze the distribution pattern of the missing values. For data with missing values ​​in a specific pattern (such as data with missing time periods in a time series), use targeted filling methods, such as interpolation filling based on historical data trends. When calculating the mean required for mean filling, consider the weight factor of the data, give higher weights to data with higher importance, and improve the representativeness of the mean. For model-based prediction filling methods (such as linear regression models), not only should other attribute vectors related to the attributes be selected, but feature engineering processing should also be performed, such as standardizing and normalizing the attributes to improve the accuracy of model predictions.

[0061] When dealing with outliers, in addition to calculating the deviation from the mean and setting the threshold, it is also necessary to combine the data distribution and business logic. For data that conforms to a specific distribution (such as normal distribution), an outlier detection method based on multiples of the standard deviation is used (for example, data outside 3 times the standard deviation is considered an outlier). At the same time, an outlier knowledge base is established to record common outlier types and their possible causes, so that more accurate corrections can be made based on business logic. For example, for abnormally high or low prices in sales data, reasonable corrections can be made based on product pricing strategies and market conditions.

[0062] Data deduplication: For structured data duplication detection, when constructing hash tables, optimize the selection of hash functions and hash conflict handling mechanisms. For example, use a more efficient MurmurHash function and combine it with the open address method or linked list method to handle hash conflicts to improve duplication detection efficiency. At the same time, for large-scale structured data, adopt a block duplication detection strategy to divide the data into several blocks and perform duplication detection in memory separately to reduce memory usage.

[0063] For similarity detection of unstructured data (such as text data), when using TF-IDF vector representation, adjust the calculation method of word frequency and inverse document frequency according to the characteristics of text data. For example, for long text data, reduce the weight of high-frequency words to highlight the contribution of low-frequency but important keywords to text similarity. When calculating cosine similarity, introduce semantic similarity calculation methods (such as those based on semantic libraries such as WordNet) to improve the accuracy of similarity detection and better identify text data with similar semantics but different expressions as duplicate data.

[0064] Data formatting: When unifying the date format, in addition to using regular expressions to match different date formats, it is also necessary to establish a date format conversion mapping table to record the conversion rules between common date formats to improve conversion efficiency. At the same time, for incorrect values ​​in date data (such as values ​​that do not conform to date format specifications), they should be repaired or marked as invalid dates based on context information and business logic.

[0065] When unifying numerical units, in addition to converting according to pre-defined unit conversion rules, a dynamic update mechanism for unit conversion needs to be established. As business develops and data sources change, unit conversion rules should be updated in a timely manner to ensure the accuracy of data units. At the same time, for data that cannot be directly converted (such as different types of measurement units that have no direct conversion relationship), data standardization is performed to convert them into dimensionless values ​​for subsequent analysis.

[0066] 2. Efficient implementation of the CBMTIA algorithm in the data encryption and secure transmission phase (S2) 1. Optimized operations for data encryption: When using the Advanced Encryption Standard AES-256 to encrypt data, in addition to using a cryptographically secure pseudo-random number generator, additional measures are required to enhance the randomness of the key when generating a 256-bit encryption key. For example, factors such as system time and user-specific information can be used as seed values ​​to generate a more random key. When performing multiple rounds of encryption operations on a data block, the number of encryption rounds is dynamically adjusted based on the sensitivity and security requirements of the data. For highly sensitive data, the number of encryption rounds is increased to improve encryption strength; for general data, the number of encryption rounds is appropriately reduced to balance encryption performance and efficiency.

[0067] During the encryption process, optimize the implementation of operations such as byte replacement (SubBytes), row shift (ShiftRows), column confusion (MixColumns), and round key addition (AddRoundKey). For example, use hardware acceleration technology (such as the CPU's AES-NI instruction set) to accelerate these operations and increase the encryption speed. At the same time, perform integrity verification on the encrypted ciphertext, use a hash function (such as SHA-256) to calculate the hash value of the ciphertext, and transmit the hash value together with the ciphertext. The receiver verifies the hash value before decryption to ensure that the ciphertext has not been tampered with during transmission.

[0068] 2. In-depth strategies for security protocol selection and optimization: When selecting HTTPS or TLS security protocols to establish data transmission channels, in addition to the regular key exchange and encryption suite negotiation during the TLS protocol handshake, multiple verifications of the server identity are required. For example, in addition to verifying the server certificate, the authenticity of the server identity can be further ensured by verifying the server's domain name resolution records, IP address range and other information to prevent man-in-the-middle attacks.

[0069] When the client verifies the legitimacy of the server certificate, a certificate trust chain cache mechanism is established to reduce the time overhead of certificate verification. At the same time, a real-time monitoring mechanism is established for certificate updates and revocations to ensure that the client can obtain the latest certificate status information in a timely manner. During the key exchange process, the appropriate key exchange algorithm (such as ECDHE or RSA) is selected based on the performance of the client and server. For terminal devices with lower performance, the key exchange algorithm with less computational effort is preferred to improve handshake efficiency.

[0070] In order to optimize transmission performance, when compressing encrypted data, in addition to using adaptive compression algorithms to adjust compression parameters according to data statistical characteristics, targeted compression is also required in combination with data types. For example, in the case of a large amount of text data, dictionary-based compression algorithms (such as LZ77, LZ78, etc.) are used to improve the compression ratio; for multimedia data such as images and audio, special multimedia compression algorithms (such as JPEG2000, HEVC, etc.) are used to minimize the impact on data quality while ensuring compression effects.

[0071] When using the multiplexing technology in HTTP / 2, optimize the flow control and priority allocation mechanism. Dynamically adjust the flow priority and transmission order according to the real-time requirements and importance of the data and the network conditions of the terminal device. For example, for data with high real-time requirements (such as stock market data), give it the highest priority to ensure its priority transmission; for terminal devices with poor network conditions, reduce the concurrency of data transmission to avoid network congestion and improve the stability of data transmission.

[0072] 3. Accurate implementation of the CBMTIA algorithm in the smart terminal identification and adaptation phase (S3) 1. Improvement of terminal identification precision: When obtaining and parsing the User-Agent information in the request, in addition to defining the operating system type, browser type, device model and other features, it is necessary to further explore more valuable features. For example, extract the display-related features such as the device's screen resolution, pixel density, color depth, and the device's CPU architecture, memory size, storage capacity and other hardware performance features to build a richer feature vector.

[0073] When building a terminal feature library, it is necessary not only to collect feature vectors of known terminal types, but also to perform cluster analysis on the feature vectors. Terminal devices are divided into different categories based on the similarity of feature vectors, and a hierarchical terminal type classification model is established. When calculating the similarity between the User-Agent feature vector and each feature vector in the feature library, in addition to using the cosine similarity formula, other distance measurement methods (such as Euclidean distance, Manhattan distance, etc.) can also be combined for comprehensive judgment to improve the accuracy of terminal recognition. At the same time, for cases where the similarity is low but may belong to a new type of terminal, an automatic learning mechanism is established to add new feature vectors to the feature library to continuously improve the terminal recognition capability.

[0074] 2. Personalization of adaptation strategy: When selecting the most appropriate display template and layout based on the identified terminal type, in addition to comprehensively considering factors such as screen resolution, screen size ratio, and device performance, the user's personalized preferences must also be considered. For example, a user preference model is established to record the user's selection habits and interactive operation habits (such as commonly used filtering conditions, sorting methods, etc.) for display templates and layouts during historical use, and user preferences are used as one of the important factors of the adaptation function.

[0075] When defining the adaptation function, in addition to setting the adaptation factor for screen resolution, size ratio and device performance, the network status of the terminal device must also be considered. For terminal devices with slow network speeds, priority is given to display templates and layouts with small data volumes and fast loading speeds to avoid a decline in user experience due to network delays. At the same time, according to the characteristics of different types of data (such as text data, chart data, map data, etc.), the calculation method of the adaptation function is optimized to ensure that the data displayed on different terminals has the best readability and visualization effect.

[0076] When selecting the display template and layout that maximizes the adaptation function, in addition to selecting the optimal solution, alternative solutions must also be provided. When the optimal solution cannot be used for some reason (such as template file damage, network failure causing template loading failure, etc.), it will automatically switch to the alternative solution to ensure the stability and reliability of the system. In addition, when rendering and displaying data, the rendering algorithm is optimized according to the performance of the terminal device. For example, for devices with lower performance, simplified rendering effects are used (such as reducing the animation effects of charts, reducing the high definition of pictures, etc.) to increase the rendering speed and ensure a smooth user experience on different terminals.

[0077] 4. Reliable guarantee of CBMTIA algorithm in data synchronization and consistency maintenance phase (S4) 1. Stable implementation of real-time synchronization: When the client sends a data request to the server and sets a timeout, in addition to responding based on the time the server receives the request and the time the data is updated, a request retry mechanism must also be established. When a request times out or fails due to network failures, the retry time interval is automatically determined according to the exponential backoff algorithm, and multiple retries are performed to improve the success rate of data synchronization.

[0078] In the long polling process, in addition to dynamically adjusting the long polling cycle according to the data update frequency, it is also necessary to optimize the resource management on the server side. For long polling requests that have not been responded to for a long time, the server resources should be released in time to avoid resource waste. At the same time, a heartbeat detection mechanism is established between the client and the server. During the long polling waiting process, heartbeat packets are sent regularly to ensure the validity of the connection and prevent connection interruption due to network fluctuations.

[0079] When the client and server establish a WebSockets connection, in addition to exchanging necessary information during the protocol handshake, identity authentication and authorization operations are also required. Ensure that only legally authorized clients can establish a WebSockets connection to prevent illegal connections and data leakage. After the connection is successfully established, optimize the mechanism for the server to push data update messages. According to the amount of data update and the client's receiving ability, adopt appropriate push strategies (such as batch push, incremental push, etc.) to improve data push efficiency and reduce network overhead.

[0080] In order to ensure the stability of WebSockets connection, in addition to sending heartbeat messages regularly, a connection abnormality recovery mechanism needs to be established. When the heartbeat delay exceeds the threshold or the connection is interrupted, it automatically attempts to re-establish the connection and restore the data synchronization status. At the same time, load balancing is performed on WebSockets connections. According to the load of the server, the client connection is distributed to the server node with lighter load, which improves the overall performance and stability of the system.

[0081] 2. Effective execution of conflict detection and resolution: When maintaining a version vector for each data item, in addition to recording the modified version number of the terminal on the data item, it is also necessary to record relevant information such as the modification time and the modifying user. When the terminal is ready to modify the data item and sends a pre-modification request, in addition to including the version vector, it is also necessary to provide a modification intention description (such as the reason for the modification, the expected modification content, etc.) so that the server can better judge the conflict situation and provide more targeted conflict resolution suggestions.

[0082] After receiving the pre-modification request, the server checks the version vector to determine the conflict. In addition to comparing the version number, it also needs to conduct a comprehensive analysis based on the modification time and modification intention. For cases where the modification time is similar and the modification intention does not conflict, an automatic merge operation is attempted. For example, for modifications that add different comments to the same data item at the same time, the comments can be merged together to avoid unnecessary conflict prompts.

[0083] When a conflict occurs and the data can be merged, in addition to splicing text data in timestamp order, for other types of data (such as chart data, structured data, etc.), formulate corresponding merge rules based on the data structure and business logic. For example, for chart data, merge calculations can be performed based on the statistical characteristics of the data (such as average, sum, etc.); for structured data, row-level merge or update operations can be performed based on the primary key or unique identifier.

[0084] When a conflict occurs and cannot be merged automatically, the server pushes the conflict information to the relevant users. In addition to providing conflict details, it also needs to provide conflict resolution suggestions and tools. For example, provide data comparison tools to facilitate users to intuitively view the differences between different versions of data; provide conflict resolution wizards to guide users to choose appropriate solutions based on business needs, and improve the efficiency and accuracy of users in handling conflicts. After the user selects a version or manually edits and merges data, when the server updates the value and version vector of the data item, in addition to updating the version number of the corresponding terminal, it also needs to record the data modification history to facilitate subsequent auditing and tracing.

[0085] The cross-border data multi-terminal display and interaction system based on the CBMTIA algorithm has been further improved and perfected in all aspects, which can better cope with various challenges in cross-border data processing, provide more efficient, safe and intelligent display and interaction services, and meet the needs of enterprises for data management and decision support in global business scenarios. In actual applications, enterprises can flexibly adjust and apply these optimization measures according to their own business characteristics and technical environment to achieve the best system performance and user experience.

[0086] Example 3 Further illustrate with reference to Example 1, Figure 1 The structure shown in FIG. 1 is shown in FIG. 1 , and the specific steps of steps S2-S3 are as follows: S21. Data encryption and secure transmission: Use the advanced encryption standard AES-256 to encrypt the data; suppose the original data is , divide it into several 128-bit (16-byte) data blocks ; Generate a 256-bit encryption key ,Key generation can use a cryptographically secure pseudo-random number generator to ensure the randomness and confidentiality of the key; For each data block , perform multiple rounds of encryption operations; the encryption process uses the round function of the AES encryption algorithm, which includes four operations: byte replacement SubBytes, row shift ShiftRows, column confusion MixColumns, and round key addition AddRoundKey; The round key is The round key is composed of the master key Generated through the key expansion algorithm. The key expansion algorithm is relatively complex and will not be expanded in detail here. The encryption formula is: ,in For the encrypted ciphertext block, the SubBytes operation replaces each byte in the data block according to a fixed S-box, changes the value of the byte, and increases the nonlinearity of the data; the ShiftRows operation cyclically shifts the rows of the data block to disrupt the position of the bytes; the MixColumns operation confuses the columns of the data block to further spread the changes in the data; the AddRoundKey operation performs an XOR operation on the round key and the data block that has undergone the previous operation to achieve the mixing of the key and the data. This formula fully describes the process of one round of encryption in the AES-256 encryption algorithm. After multiple rounds of such operations, the encrypted ciphertext is finally obtained. ); S21. Select HTTPS or TLS security protocol to establish a data transmission channel. During the TLS protocol handshake, perform key exchange and encryption suite negotiation. Assume that the client and server have private keys respectively. and , public key and ; First, the client sends a client hello message to the server, which contains information such as the list of encryption suites supported by the client. After receiving the message, the server selects a suitable encryption suite and sends the server certificate to the client. The client verifies the legitimacy of the server certificate. If the verification is successful, the client generates a random number , and encrypt it using the server's public key , the encryption formula is ,in The modulus associated with the server's public key is used in this formula to encrypt a random number using the public key, ensuring that only the server can decrypt and obtain the random number for subsequent key generation and send it to the server. The server uses the private key Decrypted , and then the server also generates a random number , both parties generate a key based on a predefined key generation function Generate Session Key ; In order to optimize the transmission performance, the encrypted data is compressed during the data transmission process; assuming that the original encrypted data is , the compressed data is C', the compression ratio , where |C| and |C'| are the byte lengths of the original data and the compressed data respectively. This formula is used to measure the compression effect. The larger the compression ratio, the better the compression effect and the smaller the amount of data transmitted. Adopt adaptive compression algorithm to dynamically adjust compression parameters according to the statistical characteristics of data; At the same time, in order to improve transmission efficiency and reduce network latency, multiplexing in HTTP / 2 is used to transmit multiple requests and responses simultaneously on one TCP connection. Suppose the request set is , the response set is , through reasonable flow control and priority allocation mechanism, ensure that important data is transmitted first; S31, terminal identification: when the user initiates a request, obtain the User-Agent information in the request; the User-Agent string is UA, which is parsed; First, define a feature vector To represent the characteristics of the terminal, These can be features such as operating system type, browser type, device model, etc. If the UA contains the string "Windows", then Indicates that the operating system is Windows, otherwise ; If it contains the string "Chrome", then Indicates that the browser is Chrome, and so on; Build a terminal feature library ,in is the feature vector of the known terminal type; calculate the User-Agent feature vector With each feature vector in the feature library Similarity ; Here we use the cosine similarity formula ,in is the feature vector The The formula is used to measure the similarity between two feature vectors. The higher the similarity, the more the terminal type corresponding to the User-Agent matches the terminal type in the feature library. Select the terminal type with the highest similarity as the recognition result; , the identified terminal type is Corresponding terminal type; if the similarity is lower than the set threshold , it is considered that the terminal type cannot be accurately identified and further information or other identification methods may be required; S32, adaptation strategy: select the most appropriate display template and layout according to the identified terminal type; set the display template set to , the layout set is ; For each terminal type , define an adaptation function To measure display template and layout For terminal type The degree of adaptation; the adaptation function can take into account multiple factors, such as screen resolution , screen size ratio , Equipment performance ; For screen resolution , set template The optimal resolution range is , then the resolution adaptation factor ,in is an adjustment coefficient used to control the speed at which the degree of adaptation decreases when the resolution does not match. The formula calculates the adaptation factor based on the degree of match between the screen resolution and the optimal resolution range of the template. The closer to the optimal range, the higher the adaptation factor; For screen size ratio , set template The optimal size ratio is , then the size ratio adaptation factor ,in To adjust the coefficient, the formula calculates the adaptation factor based on the difference between the screen size ratio and the template's optimal ratio. The smaller the difference, the higher the adaptation factor; For device performance , set template The minimum performance required is , then the performance adaptation factor ,This formula calculates the adaptation factor based on the comparison between the actual performance of the device and the minimum performance required by the template. The higher the performance, the higher the adaptation factor; Comprehensive adaptation function ,in , and is the weight coefficient, which is used to adjust the importance of different factors in the adaptation process. By setting the weights reasonably, the influence of certain factors can be emphasized according to actual needs. This formula comprehensively considers factors such as screen resolution, size ratio and device performance to calculate the overall adaptability of the display template and layout to the terminal type; Choose the adaptation function Get the maximum value display template and layout As the final adaptation result, ; Then, the data is rendered and displayed according to the selected display template and layout to ensure the best user experience on different terminals.

[0087] Highly secure data transmission: Through the combination of AES-256 encryption and security protocols (HTTPS / TLS), as well as optimized key exchange and encryption suite negotiation mechanisms, the confidentiality, integrity and authenticity of cross-border data during transmission are ensured, effectively preventing data from being stolen, tampered with or forged.

[0088] Accurate terminal identification: Based on feature vector analysis and cosine similarity calculation of User-Agent information, it can accurately identify different types of terminal devices, including various combinations of operating systems, browsers, and device models, improving the accuracy and reliability of terminal identification.

[0089] Intelligent adaptation strategy: The adaptation function takes into account multiple factors such as screen resolution, size ratio and device performance. It can select the most appropriate display template and layout according to the actual situation of the terminal, realizing a personalized user experience. Whether on a desktop computer, tablet or mobile phone, it can provide clear, beautiful and efficient data display and interactive interface.

[0090] Optimized transmission performance: Adaptive compression algorithm and multiplexing technology are used to improve data transmission efficiency and reduce network delay while ensuring data security. It is especially suitable for situations where the network environment is unstable and bandwidth is limited during cross-border data transmission, ensuring that data can reach the terminal device in a timely and accurate manner.

[0091] The CBDSADA algorithm can effectively solve the problems of cross-border data in terms of secure transmission and multi-terminal adaptive display, and provide strong technical support for cross-border data multi-terminal display interaction based on the digital cockpit. In practical applications, the parameters in the algorithm (such as similarity threshold, adaptation function weight coefficient, etc.) can be adjusted and optimized according to actual conditions to further improve the performance and adaptability of the algorithm.

[0092] Example 4 Further illustrate with reference to Example 1, Figure 1 The structure shown in FIG. 1 is shown in FIG. 1 , and the specific steps of step S4 are as follows: S41, Real-time synchronization: The client sends a data request to the server and sets a longer timeout period ; Assume the time when the client sends the request is The time when the server receives the request is ; After receiving the request, the server checks whether the data has been updated. If the data has not been updated, the server will keep the connection waiting until the data is updated or the timeout period is reached. Suppose the data update time is ; When data is updated or a timeout occurs, the server sends a response to the client; if it is a data update, the response contains the updated data ; If it is a timeout, the response can include a flag indicating that there is no new data; After receiving the response, if it is a data update, the client will update the local data immediately; if it is a timeout, the client can decide whether to initiate a new long polling request immediately or wait for a period of time before initiating the request according to business needs; Long polling cycle It can be dynamically adjusted according to the data update frequency and business needs; The number of data updates in the second longest poll is , average update interval ,in For the The time of data update, For the The time of the second long polling request. This formula is used to calculate the average data update interval in order to dynamically adjust the long polling cycle. Less than the current long polling period , you can shorten it appropriately ;if Greater than , you can extend it appropriately , to balance server load and data real-time; S42, the client and the server establish a WebSockets connection; during the connection establishment process, a protocol handshake is performed to exchange necessary information; Once the connection is established successfully, the server can actively push data update messages to the client. Suppose the data update event on the server is ,when When this happens, the server immediately sends the updated data Encapsulate into WebSockets message format and send to all clients related to the data; After receiving the WebSockets message, the client parses the message content and extracts the updated data , and update local data; To ensure the stability of the WebSockets connection, the client and server send heartbeat messages periodically. Suppose the time for the client to send heartbeat messages is , the time when the server receives the heartbeat message is , heartbeat delay ;if Exceeding the set threshold , it is considered that there may be a problem with the connection, and the client or server can try to re-establish the connection; S43, conflict detection mechanism: for each data item Maintaining a version vector ,in is the number of terminals that may modify the data item, Indicates terminal For data items The modified version number; initially, all version numbers are ; When the terminal Prepare to modify data items When a pre-modification request is sent to the server, the request contains the terminal What we know now Version vector of ; After receiving the pre-modification request, the server checks the version vector; for each element in the version vector ,if , that is, other terminals have updated versions, indicating that there is a conflict; let the conflict detection function , let the conflict detection function formula be used to determine whether there is a conflict. When it returns If there is a conflict, return , indicating that there is no conflict; If there is a conflict, the server sends a Returns conflict information, including the conflicting version vector and conflicting data items The current value of the terminal You can decide how to handle the conflict based on the conflict information, such as merging the conflict or abandoning the modification; S43, conflict resolution strategy: When a conflict is detected and the data can be merged, the server obtains the data modification timestamp of each conflicting version , is the number of conflicting versions; let data item The merged value is x'. For text data, different versions of text content can be concatenated in the order of timestamps. ,in Indicates the timestamp The formula is used to merge text data with different timestamps, retain all modification history, and facilitate users to view and handle conflicts; When a conflict occurs and cannot be automatically merged, the server pushes the conflict information to the relevant users; the user views the conflict details on the terminal, including the data content of different versions, modification time, modification user and other information; The user selects a version as the final version on the terminal, or manually edits and merges the data; let the version selected by the user be , if it is a manual edit merge, then For the edited result, the terminal sends the result selected by the user back to the server; After receiving the user's selection, the server updates the data item The value of , and update the version vector , add the version number of the corresponding terminal , indicating that the terminal is responsible for the data item An effective modification was made.

[0093] Strong real-time performance: Through the combination of long polling and WebSockets technology, the client can be notified in time when the data is updated, ensuring that the data on different terminals are always synchronized. Users can obtain the latest cross-border data in real time, improving the timeliness and accuracy of decision-making.

[0094] Accurate conflict detection: The conflict detection mechanism based on version vectors can accurately detect conflicts when multiple terminals modify the same data at the same time, avoid the spread of data inconsistency problems, and ensure data integrity and consistency.

[0095] Flexible conflict resolution: It provides a timestamp-based merge strategy and a user-selected strategy to meet the conflict resolution requirements of different types of data and different business scenarios. Simple mergeable data can be processed automatically, and complex conflicts can be handled by users, which improves the flexibility and availability of the system.

[0096] High stability: The heartbeat mechanism ensures the stability of long polling and WebSockets connections, which can promptly detect and recover possible connection interruptions, ensure the continuity of data synchronization, and reduce data synchronization failures caused by network fluctuations and other reasons.

[0097] In practical applications, the algorithm can be further optimized and expanded according to the characteristics of cross-border data and business needs, such as optimizing the storage and management of version vectors to improve the efficiency of conflict detection; adding more conflict resolution strategies to meet the needs of different users and business scenarios. At the same time, in the process of data synchronization, data encryption and secure transmission need to be considered to ensure the security of cross-border data.

[0098] The above-mentioned embodiments are only preferred technical solutions of the present invention and should not be regarded as limitations of the present invention. The protection scope of the present invention should be the technical solutions recorded in the claims, including equivalent replacement solutions of the technical features in the technical solutions recorded in the claims; that is, equivalent replacement improvements within this scope are also within the protection scope of the present invention.

Claims

1. A cross-border data multi-terminal display and interaction system based on a digital cockpit, characterized by: The digital cockpit interactive system includes data acquisition module, data transmission module, data storage module, data processing module, display interaction module, user authentication and authority management module and data sharing and collaboration module; The data collection module is used to collect data from cross-border data sources; The data transmission module is used to transmit cross-border data using a secure and reliable transmission protocol; The data storage module is used to build a distributed data storage system to store cross-border data; The data processing module is used to process the stored data in real time or offline using big data processing technology; The display interaction module is used to develop display interfaces suitable for a variety of terminals, adopts responsive design, and provides data visualization components; The user authentication and authority management module is used to authenticate users; The data sharing and collaboration module is used to realize data sharing and collaboration among users.

2. According to claim 1, the interactive method of the cross-border data multi-terminal display interactive system based on the digital cockpit is characterized by: The cross-border data sources collected by the data collection module include business databases, sensors, and third-party data platforms in different countries and regions; The data collection module collects data through API calls, file transfers, database connection queries, and web crawlers, and performs preliminary cleaning and conversion on the collected data to remove noise data, erroneous data, and unify the data format.

3. According to claim 1, a cross-border data multi-terminal display and interaction system based on a digital cockpit is characterized by: The transmission protocols of the data transmission module include HTTPS, SFTP, The data transmission module establishes a monitoring mechanism for the data transmission link and monitors the data transmission status in real time, including transmission speed, packet loss rate, and delay. For large-scale data transmission, data segmentation and breakpoint resumption technology are used.

4. According to claim 1, a cross-border data multi-terminal display and interaction system based on a digital cockpit is characterized by: The distributed data storage system in the data storage module includes a distributed file system or a cloud storage service based on Hadoop; The data storage module stores data in classified forms, establishes a data warehouse or data lake architecture based on data type, business field, and time period, implements data backup and recovery strategies, and performs full and incremental backups on a regular basis.

5. According to claim 1, a cross-border data multi-terminal display and interaction system based on a digital cockpit is characterized by: The visualization components in the interactive module include charts, reports, and dashboards. The user interaction functions in the display interaction module include data filtering, sorting, drilling, and zooming; The terminals include computers, tablets, mobile phones, and large screens.

6. According to claim 1, a cross-border data multi-terminal display and interaction system based on a digital cockpit is characterized by: The data sharing and collaboration module synchronizes data in real time, using long polling and WebSockets technology to achieve real-time data synchronization; Implement a conflict detection mechanism to automatically select the best solution to resolve conflicts when multiple terminals modify the same data at the same time.

7. The interactive method of the cross-border data multi-terminal display interactive system based on the digital cockpit according to any one of claims 1 to 6, characterized in that: The CBMTIA algorithm is used to realize cross-border data multi-terminal display interaction. The method is: S1. The data acquisition module performs data integration and collects data from data sources in different countries and regions. The data sources include cloud services, databases, and API interfaces. Data preprocessing: cleaning, deduplication, and formatting the collected data to ensure data quality and consistency; S2, Data encryption and secure transmission steps: Data encryption, using the Advanced Encryption Standard AES-256 to encrypt data; Security protocols, using HTTPS, TLS and other security protocols to establish secure data transmission channels; S3, intelligent terminal identification and adaptation step: terminal identification, automatically identifying the user terminal type by analyzing the User-Agent information in the user request, the terminal type includes desktop, tablet, and mobile phone; Adaptation strategy: select the most appropriate display template and layout according to the terminal type; S4, data synchronization and consistency maintenance steps: real-time synchronization, using long polling and WebSockets technology to achieve real-time data synchronization; Conflict detection and resolution, implements a conflict detection mechanism, and automatically selects the best solution to resolve conflicts when multiple terminals modify the same data at the same time.

8. According to claim 7, the interactive method of the cross-border data multi-terminal display interactive system based on the digital cockpit is characterized by: The specific steps of step S1 are: Data collection: Collect data from cloud services, databases, and API interfaces in different countries and regions; For cloud service data, obtain data through the access interface and authentication mechanism provided by the cloud service provider, and use the AWSS3 API to download data; For database data, establish corresponding database connection according to MySQL or Oracle database and write SQL query statements to extract data; For API interface data, construct a legal request and send it to the API server according to the requirements of the API documentation to obtain the returned data. Use the `requests` library to send a GET request to obtain the data. The collected data is stored in a temporary buffer for subsequent processing; Data cleaning: Detect and process missing values; suppose an attribute in the data set is , the number of data points is , the number of missing values ​​is Calculate missing rate , this formula is used to measure the proportion of missing data of a certain attribute in the data set in order to determine the subsequent processing method; like Less than the set threshold , then the mean filling method is used, that is, the mean of the non-missing values ​​of the attribute is calculated , ,in For attributes No. non-missing values, the formula is used to calculate the mean required for mean filling, Fill missing values; like Greater than and less than , a model-based prediction filling method is used, using a linear regression model ,in For and attributes Other related attribute vectors, and are model parameters, is the error term, and the missing values ​​are predicted by the trained model. This formula is the general form of the linear regression model, which is used to predict missing values ​​based on related attributes; like Greater than , then considering the availability of attribute data, it may be necessary to further analyze or discard the attribute; Handling outliers; For numeric data, calculate the deviation of each data point from the mean , set the deviation threshold ;like , the data point is considered an outlier and the neighboring value replacement method is used (or modified according to the business logic of the data); Data deduplication: For structured data, check for duplicates based on the unique identification field of the data; suppose there is records, the unique identification field is ID, and a hash table is constructed , iterate over each record in the dataset and calculate the hash value of its ID ;like If it already exists, it means that the record is a duplicate record and it will be deleted; If it does not exist, Deposit , and keep the record; For unstructured data, similarity detection algorithm is used; text data is converted into feature vectors, using TF-IDF vector representation, ,in Words In the documentation The number of occurrences in |D| is the total number of documents, To contain words The formula is used to calculate the TF-IDF value of words in text data, thereby converting text into feature vectors and calculating the cosine similarity between vectors. ,in and are two feature vectors. This formula is used to measure the similarity between two text data. When the similarity is greater than the set threshold When , it is considered as duplicate data and one of them is retained; Data formatting: unify the date format; traverse the date fields in the data set, use regular expressions to match different date formats, and convert them to a unified format; Unify numerical units; identify numerical values ​​and their units in data, and convert them according to pre-defined unit conversion rules.

9. According to claim 7, the interactive method of the cross-border data multi-terminal display interactive system based on the digital cockpit is characterized by: The specific steps of steps S2-S3 are: S21. Data encryption and secure transmission: Use the advanced encryption standard AES-256 to encrypt the data; suppose the original data is , divide it into several 128-bit data blocks ; Generate a 256-bit encryption key ,Key generation can use a cryptographically secure pseudo-random number generator to ensure the randomness and confidentiality of the key; For each data block , perform multiple rounds of encryption operations; the encryption process uses the round function of the AES encryption algorithm, which includes four operations: byte replacement SubBytes, row shift ShiftRows, column confusion MixColumns, and round key addition AddRoundKey; The round key is The round key is composed of the master key Generated through the key expansion algorithm. The key expansion algorithm is relatively complex and will not be expanded in detail here. The encryption formula is: ,in For the encrypted ciphertext block, the SubBytes operation replaces each byte in the data block according to a fixed S-box, changes the value of the byte, and increases the nonlinearity of the data; the ShiftRows operation cyclically shifts the rows of the data block to disrupt the position of the bytes; the MixColumns operation confuses the columns of the data block to further spread the changes in the data; the AddRoundKey operation performs an XOR operation on the round key and the data block that has undergone the previous operation to achieve the mixing of the key and the data. This formula fully describes the process of one round of encryption in the AES-256 encryption algorithm. After multiple rounds of such operations, the encrypted ciphertext is finally obtained. ); S21. Select HTTPS or TLS security protocol to establish a data transmission channel; During the TLS protocol handshake, key exchange and encryption suite negotiation are performed; assuming that the client and server have private keys respectively and , public key and ; First, the client sends a client hello message to the server, which contains information such as the list of encryption suites supported by the client. After receiving the message, the server selects a suitable encryption suite and sends the server certificate to the client. The client verifies the legitimacy of the server certificate. If the verification is successful, the client generates a random number , using the server public key Encrypt it , the encryption formula is ,in The modulus associated with the server's public key is used in this formula to encrypt a random number using the public key, ensuring that only the server can decrypt and obtain the random number for subsequent key generation and send it to the server. The server uses the private key Decrypted , and then the server also generates a random number , both parties generate a key based on a predefined key generation function Generate Session Key ; In order to optimize transmission performance, the encrypted data is compressed during data transmission; Assume the original encrypted data is , the compressed data is C', the compression ratio , where |C| and |C'| are the byte lengths of the original data and the compressed data respectively. This formula is used to measure the compression effect. The larger the compression ratio, the better the compression effect and the smaller the amount of data transmitted. Adopt adaptive compression algorithm to dynamically adjust compression parameters according to the statistical characteristics of data; At the same time, in order to improve transmission efficiency and reduce network latency, multiplexing in HTTP / 2 is used to transmit multiple requests and responses simultaneously on one TCP connection. Suppose the request set is , the response set is , through reasonable flow control and priority allocation mechanism, ensure that important data is transmitted first; S31, terminal identification: when the user initiates a request, obtain the User-Agent information in the request; the User-Agent string is UA, which is parsed; First, define a feature vector To represent the characteristics of the terminal, These can be features such as operating system type, browser type, device model, etc. If the UA contains the string "Windows", then Indicates that the operating system is Windows, otherwise ; If it contains the string "Chrome", then Indicates that the browser is Chrome, and so on; Build a terminal feature library ,in is the feature vector of the known terminal type; calculate the User-Agent feature vector With each feature vector in the feature library Similarity ; Here we use the cosine similarity formula ,in is the feature vector The The formula is used to measure the similarity between two feature vectors. The higher the similarity, the more the terminal type corresponding to the User-Agent matches the terminal type in the feature library. Select the terminal type with the highest similarity as the recognition result; , the identified terminal type is Corresponding terminal type; If the similarity is lower than the set threshold , it is considered that the terminal type cannot be accurately identified and further information or other identification methods may be required; S32, adaptation strategy: selecting the most appropriate display template and layout according to the identified terminal type; Let the display template collection be , the layout set is ; For each terminal type , define an adaptation function To measure display template and layout For terminal type degree of adaptation; The adaptation function can take into account multiple factors, such as screen resolution , screen size ratio , Equipment performance ; For screen resolution , set template The optimal resolution range is , then the resolution adaptation factor ,in is an adjustment coefficient used to control the speed at which the degree of adaptation decreases when the resolution does not match. The formula calculates the adaptation factor based on the degree of match between the screen resolution and the optimal resolution range of the template. The closer to the optimal range, the higher the adaptation factor; For screen size ratio , set template The optimal size ratio is , then the size ratio adaptation factor ,in To adjust the coefficient, the formula calculates the adaptation factor based on the difference between the screen size ratio and the template's optimal ratio. The smaller the difference, the higher the adaptation factor; For device performance , set template The minimum performance required is , then the performance adaptation factor ,This formula calculates the adaptation factor based on the comparison between the actual performance of the device and the minimum performance required by the template. The higher the performance, the higher the adaptation factor; Comprehensive adaptation function ,in , and is the weight coefficient, which is used to adjust the importance of different factors in the adaptation process. By setting the weights reasonably, the influence of certain factors can be emphasized according to actual needs. This formula comprehensively considers factors such as screen resolution, size ratio and device performance to calculate the overall adaptability of the display template and layout to the terminal type; Choose the adaptation function Get the maximum value display template and layout As the final adaptation result, ; Then, the data is rendered and displayed according to the selected display template and layout to ensure the best user experience on different terminals.

10. According to claim 7, the interactive method of the cross-border data multi-terminal display interactive system based on the digital cockpit is characterized by: The specific steps of step S4 are: S41, Real-time synchronization: The client sends a data request to the server and sets a longer timeout period ; Assume the time when the client sends the request is The time when the server receives the request is ; After receiving the request, the server checks whether the data has been updated; if the data has not been updated, the server will maintain the connection and wait until the data is updated or the timeout period is reached; let the data update time be ; When data is updated or a timeout occurs, the server sends a response to the client; If the data is updated, the response contains the updated data ; If it is a timeout, the response can include a flag indicating that there is no new data; After receiving the response, if the data is updated, the client will update the local data immediately; if it is a timeout, the client can decide whether to initiate a new long polling request immediately or wait for a period of time before initiating the request according to business needs; Long polling cycle It can be dynamically adjusted according to the data update frequency and business needs; The number of data updates in the second longest poll is , average update interval ,in For the The time of data update, For the The time of the second long polling request. This formula is used to calculate the average data update interval in order to dynamically adjust the long polling cycle. Less than the current long polling period , you can shorten it appropriately ;if Greater than , you can extend it appropriately , to balance server load and data real-time; S42, the client and the server establish a WebSockets connection; during the connection establishment process, a protocol handshake is performed to exchange necessary information; Once the connection is established successfully, the server can actively push data update messages to the client; Suppose the data update event on the server is ,when When this happens, the server immediately sends the updated data Encapsulate into WebSockets message format and send to all clients related to the data; After receiving the WebSockets message, the client parses the message content and extracts the updated data , and update local data; To ensure the stability of the WebSockets connection, the client and server send heartbeat messages periodically. Suppose the time for the client to send heartbeat messages is , the time when the server receives the heartbeat message is , heartbeat delay ;if Exceeding the set threshold , it is considered that there may be a problem with the connection, and the client or server can try to re-establish the connection; S43, conflict detection mechanism: for each data item Maintaining a version vector ,in is the number of terminals that may modify the data item, Indicates terminal For data items The modified version number; initially, all version numbers are ; When the terminal Prepare to modify data items When a pre-modification request is sent to the server, the request contains the terminal What we know now Version vector of ; After receiving the pre-modification request, the server checks the version vector; for each element in the version vector ,if , that is, other terminals have updated versions, which means there is a conflict; let the conflict detection function , let the conflict detection function formula be used to determine whether there is a conflict. When it returns If there is a conflict, return , indicating that there is no conflict; If there is a conflict, the server sends a Returns conflict information, including the conflicting version vector and conflicting data items The current value of the terminal You can decide how to handle the conflict based on the conflict information, such as merging the conflict or abandoning the modification; S43, conflict resolution strategy: When a conflict is detected and the data can be merged, the server obtains the data modification timestamp of each conflicting version , is the number of conflicting versions; let data item The merged value is x'. For text data, different versions of text content can be concatenated in the order of timestamps. ,in Indicates the timestamp The formula is used to merge text data with different timestamps, retain all modification history, and facilitate users to view and handle conflicts; When a conflict occurs and cannot be merged automatically, the server pushes the conflict information to the relevant users; The user can view the conflict details on the terminal, including the data content of different versions, modification time, modification user and other information; The user selects a version as the final version on the terminal, or manually edits and merges the data; let the version selected by the user be , if it is a manual edit merge, then For the edited result, the terminal sends the result selected by the user back to the server; After receiving the user's selection, the server updates the data item The value of , and update the version vector , add the version number of the corresponding terminal , indicating that the terminal is responsible for the data item An effective modification was made.

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