An air-ground collaborative vehicle networking distributed digital twin service trusted sharing method

Abstract

The application discloses a kind of air-ground coordination car networking distributed digital twin service trusted sharing methods, this method is first according to air-ground coordination traffic data type, to car networking distributed digital twin system operation data hierarchical encapsulation and storage.Secondly using authority random equalization consensus algorithm, by air-ground coordination car networking's distributed edge digital twin system to the block generated by data consensus and upload block chain.Finally in edge digital twin system to remote digital twin system request twin service, through directed acyclic graph block chain and interplanetary file system to service record verification, realize the trusted sharing of service between each edge digital twin system in air-ground coordination car networking distributed digital twin system.The application ensures the authenticity and tamper resistance of air-ground coordination car networking distributed digital twin system operation data in cross-node sharing, improves the access efficiency of large-scale data, and provides technical support for car networking and unmanned aerial vehicle cooperation.

Description

Technical Field

[0001] The present invention relates to the technical field of distributed data management for unmanned aerial vehicles (UAVs) and vehicle networks, and in particular to a trusted sharing method for distributed digital twin services in an air-ground collaborative vehicle network. Background Art

[0002] Digital twin technology enables two-way interaction between the physical and digital worlds through real-time data, virtual simulation, and artificial intelligence. It is widely used in manufacturing, transportation, energy, and other fields for real-time monitoring, predictive maintenance, and optimized management. However, as its application scales, digital twin technology faces a series of challenges in distributed data sharing and data reliability. This is especially true in scenarios involving the collaboration of drones and connected vehicles, which places higher demands on the security of data sharing.

[0003] At present, distributed digital twin data sharing technologies are mainly divided into traditional methods based on distributed databases, improved distributed data storage solutions, and technical solutions combined with blockchain. Among them:

[0004] Traditional approaches based on distributed databases (such as Cassandra, MongoDB, and HBase) implement distributed data storage and sharing through technologies such as data sharding, replication, and load balancing to support the high concurrency and big data processing requirements of distributed digital twins for air-ground collaborative vehicle networks. While this approach can meet data sharing requirements to a certain extent, the lack of tamper-proofing and traceability mechanisms in distributed databases leaves data reliability and consistency unsatisfactory. This conflicts with the high-precision data requirements of digital twin systems.

[0005] Improved distributed data storage methods, such as IPFS and HDFS, use distributed file systems to store massive amounts of data while ensuring data accessibility and storage scalability. However, these methods lack built-in trusted sharing mechanisms, making it difficult to ensure the authenticity of data shared by multiple parties in connected vehicle digital twin scenarios, and there is a risk of malicious data injection.

[0006] Digital twin data sharing solutions that integrate blockchain technology. Due to its decentralized, tamper-resistant, and traceable nature, blockchain technology has become a potential solution for data sharing in digital twin systems. Common integration methods include storing data directly on the blockchain or integrating blockchain with a file system to achieve trusted sharing of digital twin data.

[0007] For example, a digital twin data security storage method is authorized in the patent with authorization announcement No. CN 115484032 B, which stores data in the process of digital twin running by using blockchain, can effectively prevent data from being tampered with, and improve the security of data storage. And the digital twin system can read the required data from the blockchain when running, improving the security of data interaction in the system prototype.

[0008] However, directly storing massive data on the blockchain is costly, and the on-chain capacity and processing capacity are limited, which cannot meet the big data and real-time requirements of the air-ground collaborative vehicle networking distributed digital twin system.

[0009] In summary, the existing method still has the problems of insufficient performance and incomplete trustworthiness guarantee in supporting the distributed digital twin scene of unmanned aerial vehicle and vehicle networking collaboration. Therefore, there is an urgent need for a digital twin data sharing scheme with high scalability, high performance, real-time and trustworthiness, to meet the efficient, safe and trustworthy interoperability requirements of massive data in the unmanned aerial vehicle and vehicle networking collaborative scene. SUMMARY

[0010] To solve the above problems, the present application provides an air-ground collaborative vehicle networking distributed digital twin trusted service sharing method, which is a distributed digital twin data management method based on DAG blockchain data trusted storage and authoritative balanced adaptive consensus algorithm, and a distributed digital twin service trusted sharing method for unmanned aerial vehicle and vehicle networking collaboration. It is suitable for digital twin distributed scene of unmanned aerial vehicle and vehicle networking collaboration, solves the technical problems of poor data trustworthiness and unbalanced node usage in data storage and consensus mechanism in the prior art. By designing an adaptive node consensus algorithm, the present application guarantees efficient storage and trusted sharing of data, and improves the overall performance and security of the system.

[0011] The technical solution adopted by the present application to solve the above technical problems is:

[0012] An air-ground collaborative vehicle networking distributed digital twin service trusted sharing method, comprising the following steps:

[0013] S1, classifying and packaging the running data of the vehicle networking distributed digital twin system according to the air-ground collaborative traffic data type.

[0014] S2, classifying and storing the classified and packaged data on the distributed edge server; the original data of large-scale data is stored in the interplanetary file system (IPFS), and the packaged data is stored on the blockchain based on directed acyclic graph (DAG).

[0015] S3. Based on the data after hierarchical storage, the distributed edge digital twin system of the air-ground collaborative vehicle network uses an authoritative random equilibrium consensus algorithm to reach a consensus on the blocks generated by the data and upload them to the blockchain to achieve reliable data recording.

[0016] S4. After the edge digital twin system requests the twin service from the remote digital twin system, the service record is verified through the directed acyclic graph (DAG) blockchain and IPFS system to achieve trusted sharing of services between each edge digital twin system in the distributed digital twin system of the air-ground collaborative vehicle network.

[0017] Furthermore, step S1 is specifically as follows: the distributed digital twin system of the UAV and the Internet of Vehicles uses a unified encapsulation format to encapsulate all operating data to standardize the data structure and adapt to data storage and access requirements of different scales. The encapsulation of each piece of data includes four main steps: calculating the timestamp, performing system signature, classifying data, and processing the data content. First, the timestamp is calculated. The timestamp records the generation or encapsulation time of the air-ground collaborative traffic data in the edge area, ensuring that the system can manage and trace the temporal sequence of the data; secondly, the EDT signs the traffic data. The signature identifies the source node or subsystem of the data, which is used for data verification and anti-tampering, ensuring the credibility and uniqueness of the traffic data during sharing and transmission; then, the distributed digital twin data of the Internet of Vehicles can be divided into sensor data, simulation data, derivative data, service request data, control data or status data, etc., to facilitate the system to quickly identify the functions and characteristics of the data. Finally, the encapsulated data content is differentiated according to the size of the data. For large-scale traffic data such as sensor data, simulation data, and derived data, the data body stores the hash value of the original data or the storage address in a distributed file system (such as IPFS). This not only reduces the direct storage burden on the blockchain, but also ensures the integrity and verifiability of the data through the hash value. For small-scale traffic data such as service request data, control data, and status data, the original data content is directly stored in the data body, facilitating direct access by the system, ensuring data credibility and reducing access latency.

[0018] Furthermore, step S2 is specifically as follows: hierarchically storing the hierarchical packaged data in the distributed edge server network. In this process, the system will classify the data according to the data type to ensure that the system maintains efficiency and scalability during storage and access.

[0019] For large-scale traffic data such as sensor data, simulation data, and derived data, the original data is stored in the IPFS (InterPlanetary File System) distributed file system. IPFS, as a decentralized distributed storage solution, can effectively store and share large-scale data, reduce the burden of data storage in traditional blockchain networks, and ensure data availability and persistence through content addressing and redundant storage. To ensure the integrity and authenticity of the data, the original data stored in IPFS generates a hash value, and the hash value or storage address is recorded in the blockchain, facilitating subsequent quick positioning and access.

[0020] All encapsulated data will be stored on a DAG (Directed Acyclic Graph) based blockchain. Compared with traditional blockchains, DAG blockchains have higher throughput and lower latency, making them very suitable for data transmission and processing in digital twin systems. The DAG structure avoids the bottlenecks of traditional chain block storage, improves the efficiency of data chaining, and ensures fast storage and access of large-scale data. Data stored on the blockchain not only ensures data security and integrity, but also facilitates verification and auditing.

[0021] Further, the DAG-based blockchain uses a voting mechanism to resolve conflicting blocks. The DAG structure may conflict during data upload and block generation, such as multiple uploads of the same data after malicious modification. A voting mechanism is used to solve this problem, the core of which is to determine the final selected block through voting between nodes. After generating a block, each node initiates a vote to other nodes in the network, and nodes vote on the blocks they receive according to the recursive voting algorithm, and the voting results reflect which block has higher trust in the network. When a block conflicts, nodes will select the block with the majority of votes as the trusted block based on the voting results.

[0022] The specific rules of the recursive voting algorithm are as follows: when two blocks conflict, first, the conflicting blocks vote for themselves; second, if both conflicting blocks are ancestor blocks of a block, the block votes the same as the previous round of voting; then, if only one conflicting block is an ancestor block of a block, the block votes for the ancestor conflicting block; finally, if neither conflicting block is an ancestor block of a block, the block's vote is determined by the votes of all its descendant nodes. Ultimately, the block with the most votes will be recognized as the legal block, and the other will be marked as a conflict block.

[0023] Further, the DAG-based blockchain uses a trusted set to represent trusted blocks. The trusted set refers to a set of verified and trusted blocks that are considered reliable through certain mechanisms and can play a key role in the blockchain network. The generation process of the trusted set is as follows: first, traverse all blocks, and add non-conflict blocks to the preliminary trusted set; second, add conflict blocks to the conflict set, and use the recursive voting algorithm to vote for trusted blocks from the conflict blocks and move them to the preliminary trusted set; finally, filter blocks with time exceeding a specified threshold from the preliminary trusted set, and form the trusted set.

[0024] Further, step S3 is specifically: designing and using an Authority of Random Balance (AoRB) consensus algorithm to reach consensus on the DAG blocks generated by the data of the air-ground collaborative V2X distributed digital twin system and upload. In this step, the distributed digital twin system effectively allocates node resources through the AoRB consensus algorithm, ensures that each node has a fair opportunity to participate in the consensus process, avoids excessive load on a single node, and improves consensus efficiency and security; and the node activity sequence is determined by the system running state, and the actual node activity sequence is random, which enhances the attack resistance.

[0025] In the air-ground collaborative distributed digital twin system, multiple edge traffic domain digital twins (EDTs) work together to build a comprehensive and real-time virtual mapping of the physical system. The edge traffic domain digital twin (EDT) is a digital twin system deployed on the edge of the V2X network, including a number of traffic entities such as drones, vehicles, and roads, and their digital virtual bodies. Each EDT is responsible for running the edge traffic digital twin system and encapsulating data according to S2 during operation. The encapsulated data is used to generate blocks of the DAG blockchain through the blockchain node, and after reaching consensus with other nodes through the AoRB consensus algorithm, it is uploaded to the blockchain.

[0026] Further, the air-ground collaborative V2X distributed digital twin system can be represented as: DDTS = {EDT i |1≤i≤n}, wherein: DDTS represents a set of air-ground collaborative V2X distributed edge traffic domain digital twin systems, containing n edge traffic domain digital twin (EDT) instances, each EDT i represents an independent edge digital twin unit.

[0027] The DAG blockchain can be represented as: G = (B, E), wherein: B = {b i |1≤i≤m} represents a set of blocks, each b i represents a block; E = {(b i,b j )|b i ,b j ∈B} represents the directed edge between blocks, if there is an edge (b i ,b j ), it represents that the block b i directly quotes (or confirms) the block b j , and the block b i is the tail block of the block b j .

[0028] The blockchain node numbered i in the AoRB consensus algorithm can be represented as node i (c i ), where c i represents the number of blocks generated by the node. The blockchain nodes are divided into two categories: one is a set of twin nodes D j , representing the nodes occupied by the edge digital twin EDT j ; the other is a set of global free nodes F, representing the nodes not occupied by any EDT. The set of blockchain nodes can be represented as where

[0029] The AoRB consensus algorithm can be divided into a node initialization phase and a runtime consensus phase. The node initialization phase is to initialize the blockchain nodes after the entire DDTS has completed the preparatory work, specifically: create a blockchain node and set the uploaded block count to 0 (c i = 0), generate a set of twin nodes {D j |1≤j≤n} and a set of global free nodes F.

[0030] The runtime consensus phase in the AoRB consensus algorithm starts when the DDTS starts, and each EDT performs the same process. Taking EDT j as an example, specifically: EDT j submits the running data to the least used node node in the set of twin nodes D j , node collects data and encapsulates, generates a block b and broadcasts when reaching the specified condition, removes node from D j , removes the least used node node * from F and moves it to D j , and moves node to F; the nodes in D k,k≠j verify the block, and if the verification rate is not lower than the set verification threshold, upload the block to the DAG blockchain G. Otherwise, do not upload.

[0031] Further, step S4 is specifically: when the edge EDT requests the traffic twin service from the remote EDT system, the service record is verified through the DAG blockchain and the IPFS system to ensure the credibility of the traffic data sharing across the EDT. Specifically, to achieve service credible sharing between EDTs, the shared twin service includes the following steps.

[0032] The edge EDT initiates a twin service request and records: the edge EDT sends a twin service request to the remote EDT according to the traffic task demand, including service type, request parameter, timestamp, and edge EDT signature information. After the request is encapsulated into a standardized data packet, it is broadcast through the blockchain network. At the same time, the edge EDT generates a corresponding traffic service access record, including the unique identifier of the request, the hash value of the request content, and the timestamp, and stores the record in the edge for subsequent verification and use.

[0033] The remote EDT responds to the traffic twin service request and records: after receiving the traffic service request, the remote EDT parses the request content and performs the twin service operation according to the specific task. After the service is completed, the remote EDT encapsulates the service result, including the hash value of the response content, the execution timestamp, and the service status, and records the information in the DAG blockchain.

[0034] The edge EDT receives the traffic twin service result and verifies: first, the edge EDT extracts the corresponding service record hash value from the DAG blockchain after receiving the service response from the remote EDT, and compares it with the hash value in the response to verify the authenticity of the service response content. Secondly, the edge EDT not only verifies the remote record, but also further verifies whether the real traffic data is used in the service process, by partially replaying or logically checking the key data operations, to ensure that the remote service does not tamper or ignore the use of key data. In addition, the time stamp information and the service execution time range are combined in the service verification to check whether the remote traffic service completes the task within a reasonable time range, further confirming the credibility of its service behavior. If the verification is passed, the edge EDT will accept the service result and complete the data sharing operation; if the verification fails, the service response is rejected and an exception is recorded, and the network may also broadcast the service dishonesty behavior to maintain the credibility and security of the entire system.

[0035] Compared with the prior art, the beneficial effects of the present application are:

[0036] (1) A unified encapsulation format improves the standardization of data management for the digital twin system of the air-ground collaborative vehicle network. The present invention adopts a unified data encapsulation format, and by clarifying the composition of the data type, timestamp, system signature and data ontology, the operating data of the distributed digital twin system of the air-ground collaborative vehicle network has a highly standardized structure when stored and accessed. The data type identification function is clear, which improves the efficiency of traffic data classification and recognition, and is particularly suitable for complex and diverse twin system scenarios. The timestamp and system signature not only realize the precise management of the temporal nature of traffic data, but also ensure the authenticity and anti-tampering ability of the data in cross-node sharing, laying a trustworthy foundation for data flow and traceability.

[0037] (2) Hierarchical storage of traffic twin data to optimize the storage and access efficiency of the Internet of Vehicles. In view of the different scales and types of data generated by the collaboration between drones and the Internet of Vehicles, the present invention achieves efficient utilization of storage resources through a hierarchical storage mechanism. For large-scale traffic twin data, the original data is stored in the IPFS system and uploaded to the chain in the form of hash values; for small-scale traffic twin data, it is directly stored in the blockchain. This hierarchical design reduces the storage pressure of the blockchain, and at the same time, combined with the content addressing and distributed redundancy characteristics of IPFS, ensures the reliability and scalability of data storage, and improves the access efficiency of large-scale data.

[0038] (3) The DAG blockchain ensures data credibility and improves throughput and real-time performance in traffic scenarios. The introduction of voting mechanisms and trusted sets solves the problem of conflicting blocks that may occur in DAG. Through majority node voting and trusted block screening, data consistency and reliability are ensured. The DAG-based blockchain architecture breaks through the performance bottleneck of the traditional chain block structure, supports the parallel generation and storage of multiple blocks, significantly improves the system's throughput and processing efficiency, and provides technical support for the collaboration between the Internet of Vehicles and drones.

[0039] (4) The authoritative random equilibrium consensus algorithm improves fairness and anti-attack capabilities. The AoRB consensus algorithm designed in this invention balances the load of blockchain network nodes by dynamically allocating blockchain node resources, while ensuring that all nodes have fair opportunities to participate in the consensus process. This design not only improves the overall efficiency of the system, but also enhances anti-attack capabilities by randomizing the order of node activities, reducing the potential threat of malicious nodes. Especially in the scenario where the Internet of Vehicles and drones work together, the AoRB algorithm effectively balances the node load and ensures the stability and security of the twin system.

[0040] (5) Service process comprehensive record and verification capability, enhance the credibility of data sharing. In the verification link of cross-EDT service, the edge EDT not only verifies the hash value and timestamp of the data, but also checks the service behavior in depth through simulating the key computing process. This full-link verification mechanism effectively prevents data tampering and service fraud behavior. For example, the local EDT can verify whether the UAV path planning or vehicle fleet dynamic adjustment task is truly executed, and through the logical check of the service result combined with the original data stored by IPFS and the blockchain record. This mechanism significantly improves the service process credibility in the cooperation of UAV and vehicle networking, effectively prevents data tampering and service fraud behavior, and provides credible service guarantee for intelligent transportation system.

[0041] The application will be explained in detail below in combination with the drawings and specific embodiments. BRIEF DESCRIPTION OF DRAWINGS

[0042] Figure 1 The data encapsulation flowchart of the air-ground collaborative vehicle networking distributed digital twin system provided by the application;

[0043] Figure 2 The data hierarchical storage schematic diagram of the air-ground collaborative vehicle networking distributed digital twin system of the application;

[0044] Figure 3 The block structure diagram of the DAG blockchain of the application;

[0045] Figure 4 The consensus flowchart of the authoritative random equilibrium consensus algorithm provided by the application;

[0046] Figure 5 The air-ground collaborative vehicle networking distributed digital twin service credible sharing flowchart provided by the application. DETAILED DESCRIPTION

[0047] In order to facilitate the understanding of the application, the application will be described more fully below with reference to the related drawings, which show several embodiments of the application. However, the application can be realized in different forms and is not limited to the embodiments described herein. On the contrary, these embodiments are provided to make the disclosed content of the application more thorough and comprehensive.

[0048] Embodiment: An air-ground collaborative vehicle networking distributed digital twin service credible sharing method, comprising:

[0049] Step 1. According to the air-ground collaborative traffic data type, the air-ground collaborative vehicle networking distributed digital twin system running data is hierarchically encapsulated before storage, and is parsed and accessed when using data.

[0050] Step 2. Traffic data is stored in a hierarchical manner in the distributed edge server network according to the data scale; large-scale data is stored in the Interplanetary File System (IPFS), and encapsulated data is stored on the Directed Acyclic Graph (DAG) based blockchain.

[0051] Step 3. Using the authoritative random equilibrium consensus algorithm, the upload and consensus of the operation data of the air-ground collaborative vehicle networking distributed digital twin system in the blockchain are realized.

[0052] Step 4. After the edge digital twin system requests a twin service from a remote digital twin system, the service record is verified through the DAG blockchain and IPFS system, realizing the trusted service sharing between each edge digital twin system in the air-ground collaborative vehicle networking distributed digital twin system.

[0053] In the above step 1, the distributed digital twin system of unmanned aerial vehicles and vehicle networking collaboration is divided into multiple traffic edge digital twin systems, each edge system is responsible for data encapsulation of devices in a specific area, such as Figure 1 As shown in the figure, it mainly includes the steps of generating timestamp, EDT signature, classification and generating encapsulation package.

[0054] For the data in the EDT running process, a data timestamp is generated. The timestamp is used to record the exact time of an event or data collection, usually in UTC time (Coordinated Universal Time) or local time format, common formats include ISO 8601 standard (for example 2024-11-20T15:30:00Z) and Unix timestamp (seconds since January 1, 1970). In Python programming language, you can use the datetime module to generate ISO 8601 format timestamp, and use the time module to generate Unix timestamp.

[0055] Further, to ensure the security and integrity of the data, an EDT signature needs to be generated for each piece of data when encapsulating. EDT signature is a unique identifier generated by encryption algorithm (such as hash algorithm), which is used to verify the source of data and prevent tampering. EDT signature contains data source (such as device ID or EDT ID), timestamp and data content, generated by SHA-256 hash algorithm like "5d41402abc4b2a76b9719d911017c592", which can ensure the integrity and non-tamperability of the data.

[0056] Further, in the air-ground collaborative vehicle networking distributed digital twin system, the data generated by different data sources have their own characteristics, so the data sources are pre-encoded and classified, and different operations are performed according to the number in data packaging and analysis. In this embodiment, the data sources can be divided into six types of S, M, D, R, C and T. Among them, S represents sensor data, M represents simulation data, D represents derivative data, R represents request data, C represents control data, and T represents state data. According to this classification, large-scale data includes S, M and D, and small-scale data includes R, C and T. Each type of data is added with a subscript to further classify the type, for example, S1 represents the first type (speed) sensor data.

[0057] Further, in the running process of the distributed digital twin system, the packaging process of the original data needs to be operated hierarchically according to the type coding of the data. For the large-scale data with type coding S, M and D, these data are periodically collected and the hash value thereof is calculated using the SHA-256 hash algorithm. The period of data collection and hash calculation is set according to the system requirements, which can be hours, days or other time intervals meeting the specific application requirements. For the small-scale data with type coding R, C and T, the original data is directly taken as the content in the data packaging package, without the need for hash calculation.

[0058] Through this hierarchical packaging method, the system can adopt different storage and processing strategies according to the size and characteristics of the data, thereby ensuring the integrity, security and real-time performance of the data. The data analysis process is the reverse process of the data packaging process, which is performed when the node or edge digital twin system verifies the data or service.

[0059] In step 2, the data is stored hierarchically according to the size of the data. In this process, the system classifies the data according to the size and type of the data to ensure the efficiency and scalability of the system in the storage and access process.

[0060] As shown in the accompanying Figure 2 For the large-scale data with type coding S, M and D, the original data is stored in the IPFS (InterPlanetary File System) distributed file system. In order to ensure the integrity and authenticity of the data, the original data stored in the IPFS generates a hash value for subsequent quick positioning and access. The generated hash value is packaged by the process described in step 1. For the small-scale data with type coding R, C and T, the data is directly packaged. The packaged data is stored on a blockchain based on a directed acyclic graph (DAG).

[0061] The DAG blockchain is implemented based on a Python DAG module, uses the networkx library to build a DAG structure, and uses the py cryptodome library to process encryption and signature operations. In this embodiment, each block is represented by a Block class, which includes the size, version, timestamp, data content, hash value of the previous block, hash value of the current block (Merkle tree root), etc. of the block. The block structure is shown in the accompanying Figure 3 With this information, the block can be connected to other blocks as a node in the DAG graph.

[0062] The DAG blockchain uses a voting mechanism to solve conflicting blocks. The DAG structure may conflict during data uploading and block generation, for example, the same data is uploaded multiple times after being maliciously modified. To solve this problem, a voting mechanism is introduced into the DAG blockchain. The voting mechanism checks whether there is a conflict with the existing block when a new block is chained. When there is a conflict, the new block and the conflicting block are input, the existing block is voted, and the high-priority block is output as the trusted block, and the other block is marked as a conflict block.

[0063] The DAG blockchain uses a trusted set to represent trusted blocks. The trusted set is obtained by a trusted set generation algorithm, which inputs the entire DAG blockchain, generates a trusted set based on the voting algorithm, and outputs.

[0064] In step 3 above, the Authority of Random Balance (AoRB) consensus algorithm is designed and used to realize the consensus uploading of data in the distributed digital twin system. In this embodiment, the parameters and process of the AoRB algorithm are set as follows:

[0065] The air-ground collaborative Internet of Vehicles distributed digital twin system is divided into four edge digital twins, numbered EDT1 to EDT4. The distributed digital twin system can be represented as: DDTS = {EDT i |1≤i≤4}. When the system is initialized, 25 DAG blockchain network nodes are created, represented as Node = {node i |1≤i≤25}, and any node i is initialized node i (c i = 0) for subsequent balanced selection strategy.

[0066] Further, after the initialization of the DAG blockchain network nodes is completed, the twin node set of each EDT and the global free node set need to be generated as shown in the accompanying Figure 4 Each EDT twin node set is set to 5, i.e. contains 5 DAG blockchain network nodes. The twin node set of any EDT i is represented as |D i |=5. The size of the global free node set is also set to 5, expressed as |F|=5.

[0067] Furthermore, when the air-ground collaborative vehicle network distributed digital twin system is running, the AoRB consensus algorithm is also synchronously Figure 4 The authoritative equilibrium consensus cycle shown. Each EDT selects an authoritative node to generate a new block. The selection condition is the blockchain network node that generates the least number of blocks. For example, the authoritative node selected by D1 is Indicates the number of blocks generated in D1 c i The smallest node. x After a new block is generated and broadcast, the least used free node is selected and locked first. Then node x Move from D1 to F, and finally move node y Move from F to D1, and the cycle ends. The next block generation starts again from selecting the authoritative node.

[0068] Furthermore, the nodes in the blockchain network i,i≠x Receive node node x After the block is broadcast, press Attach Figure 4 The structure and content of the block are verified as shown. Once the verification passes, the locally cached copy of the blockchain is updated and the results are notified to other nodes. Nodes in the blockchain network periodically broadcast their local copies of the blockchain to ensure consistency across the entire network.

[0069] The process of the present invention is as follows Figure 5 As shown in the above step 4, when the edge EDT requests the twin transportation service from the remote EDT, the service record is verified through the DAG blockchain and IPFS system to ensure the credibility of data sharing across EDTs. In this embodiment, it is mainly divided into three steps: the edge initiates the service request, the remote responds to the service request, and the edge receives and verifies the result.

[0070] In the edge EDT initiates the twin service request phase, the edge EDT needs to complete a task (for example, real-time analysis of simulated data), and when the edge local processing is completed, it initiates a twin service request to the remote EDT. The data analysis service request in the embodiment contains the following contents: service type, request parameter, timestamp, signature. The values of each item are data analysis, data range, 2024-11-21T12:30:00Z, and SHA256 signature code. Then, the request is encapsulated into a standardized data packet and broadcasted through the DAG blockchain network. Finally, the edge EDT generates a service access record when sending the request, and the record content includes: unique identifier, hash value, taking values of REQ-15445 and SHA256 hash code respectively.

[0071] Further, in the remote EDT responds to the twin service phase, after the remote EDT receives the service request, it parses the request content and executes the specified operation according to the service type and parameter. For example, in the embodiment, after receiving a traffic data prediction request, the remote EDT loads the specified model to simulate and predict the request data. After the remote EDT service execution is completed, the service result is generated, containing content hash, timestamp, service status, taking values of SHA256 hash code, UTC time, and success respectively. At the same time, the result is hierarchically encapsulated and stored.

[0072] Further, in the edge EDT verifies the service phase, the edge EDT verifies the received service result by using the DAG blockchain and the IPFS file system. In the embodiment, the encapsulated data is accessed from the DAG blockchain to calculate the hash of the original data and compare it with the data on the chain to verify the authenticity of the data. In addition, the remote computing process can also be verified, for example, there is a calculation of the difference between two batches of data in the remote service, and the edge can sample the calculation of the difference between the data and compare it with the service record for verification.

Claims

1. A trusted sharing method for distributed digital twin services in an air-ground collaborative vehicle network, characterized in that: The steps include: S1. Based on the data type of air-ground collaborative traffic, hierarchical packaging of the operating data of the distributed digital twin system of the Internet of Vehicles; S2. hierarchically storing the hierarchically packaged data in the distributed edge server network; S3: Based on the hierarchically stored data, the distributed edge digital twin system of the air-ground collaborative vehicle network uses an authoritative random equilibrium consensus algorithm to reach consensus on the blocks generated by the data and upload them to the blockchain; S4. After the edge digital twin system requests the twin service from the remote digital twin system, the service record is verified through the directed acyclic graph (DAG) blockchain and the IPFS system to achieve trusted sharing of services between the edge digital twin systems in the distributed digital twin system of the air-ground collaborative vehicle network. The specific implementation process is as follows: Step 4.

1. Edge EDT initiates and records a twin service request: The edge EDT sends a twin service request to the remote EDT based on the traffic task requirements, including the service type, request parameters, timestamp, and edge EDT signature. The request is encapsulated into a standardized data packet and broadcasted through the blockchain network. The edge EDT generates a corresponding traffic service access record, including the unique identifier of the request, the hash value of the request content, and the timestamp, and stores the record at the edge. Step 4.2: The remote EDT responds to the traffic twin service request and records it: After receiving the traffic service request, the remote EDT parses the request content and performs the twin service operation according to the task. After the service is completed, the remote EDT encapsulates the generated service result, including the hash value of the response content, the execution timestamp, and the service status, and records it in the DAG blockchain. Step 4.3: The edge EDT receives and verifies the traffic twin service result: First, after receiving the service response from the remote EDT, the edge EDT extracts the corresponding service record hash value from the DAG blockchain and compares it with the hash value in the response to verify the authenticity of the service response content; Secondly, the edge EDT also verifies whether real traffic data is used in the service process, and ensures that the remote service has not tampered with or ignored the use of key data by partially replaying or logically checking key data operations; in addition, the service verification also combines timestamp information and service execution time range to check whether the remote service completes the task within a reasonable time range and confirm the credibility of its service behavior; if the verification passes, the edge EDT will accept the service result and complete the data sharing operation; if the verification fails, the service response will be rejected and the exception will be recorded, and the dishonest service behavior will be broadcast to the network.

2. The method for sharing a distributed digital twin service of an air-ground collaborative vehicle network according to claim 1 is characterized in that: The specific implementation process of step S1 is as follows: the distributed digital twin system of the UAV and the Internet of Vehicles uses a unified packaging format to encapsulate all operating data. The packaging of each data includes: calculating the timestamp, performing system signature, classifying the data, and processing the data content, as follows: First, the timestamp is calculated, which records the generation or packaging time of the edge area air-ground collaborative traffic data; secondly, the EDT signs the traffic data, and the signature identifies the source node or subsystem of the data; then, the distributed digital twin data is classified according to performance. The distributed digital twin data of the Internet of Vehicles is divided into sensor data, simulation data, derivative data, service request data, control data or status data; finally, the encapsulated data content is determined according to the data scale.

3. The method for sharing a distributed digital twin service of an air-ground collaborative vehicle network according to claim 2 is characterized in that: The specific implementation process of hierarchical storage in step S2 is as follows: For sensor data, simulation data, and derived data, the data ontology stores the hash value of the original data or the storage address in the distributed file system; for service request data, control data, and status data, the data ontology directly stores the original data content; For sensor data, simulation data, and derived data, the original data is stored in the IPFS distributed file system; all encapsulated data will be stored on a blockchain based on a directed acyclic graph (DAG).

4. The method for sharing a distributed digital twin service of an air-ground collaborative vehicle network according to claim 3 is characterized in that: The blockchain based on the directed acyclic graph (DAG) uses a voting mechanism to determine the selected block through voting among nodes to resolve conflicting blocks. After generating a block, each node initiates a vote to other nodes in the network. The nodes vote on the blocks they receive according to the recursive voting algorithm. The DAG-based blockchain uses trusted sets to represent trusted blocks. A trusted set refers to a group of verified and trusted blocks that are considered reliable. The trusted set generation process is as follows: first, all blocks are traversed and conflict-free blocks are added to the preliminary trusted set. Second, conflicting blocks are added to the conflict set, and the recursive voting algorithm is used to vote on the conflicting blocks to select trusted blocks and move them to the preliminary trusted set. Finally, blocks whose existence time exceeds a specified threshold are screened out from the preliminary trusted set to form the trusted set.

5. The method for sharing a distributed digital twin service of an air-ground collaborative vehicle network according to claim 4 is characterized in that: The specific implementation process of step S3 is as follows: in the distributed digital twin system of drones and Internet of Vehicles, multiple edge traffic domain digital twins EDTs work together to jointly build a comprehensive, real-time virtual mapping of the physical system, wherein the edge traffic domain digital twin EDT is a digital twin system deployed at the edge of the Internet of Vehicles, including several drones, vehicles, roads and their digital virtual bodies; each EDT is responsible for running the edge traffic digital twin system, and during the operation, the data is encapsulated as described in S2. The encapsulated data generates DAG blockchain blocks through blockchain nodes, and is uploaded to the blockchain after reaching consensus with other nodes through the AoRB consensus algorithm.

6. The method for trusted sharing of distributed digital twin services in an air-ground collaborative vehicle network according to claim 5 is characterized in that: The specific implementation process of the AoRB consensus algorithm is as follows: The distributed digital twin system of the air-ground collaborative vehicle network is represented as follows: ,in: Represents a collection of distributed edge traffic digital twin systems for air-ground collaborative vehicle networks, including Edge traffic domain digital twin EDT instances, each Represents an independent edge digital twin unit; The DAG blockchain is represented as: , where the set of blocks , each Represents a block; Indicates directed edges between blocks. If there are edges , then it means block Directly quoted block , block Block on the chain is the tail block of G; The blockchain node numbered i in the AoRB consensus algorithm is represented as ,in Indicates the number of blocks generated by the node; blockchain nodes are divided into two categories: one is the twin node set , indicating that it is edge digital twin The nodes occupied by the node; the other type is the global free node set , indicating a node not occupied by any EDT; the blockchain node set is , ; The AoRB consensus algorithm is divided into a node initialization phase and a runtime consensus phase; The node initialization phase is when DDTS initializes the blockchain node, specifically: creating a blockchain node and setting the upload block count to 0 ( ), generate a twin node set and the global free node set F; The runtime consensus phase begins when the DDTS is started. The execution process of each EDT is the same, specifically: Submitting running data to the twin node set The least used node in , Collect data and encapsulate it, generate block b and broadcast it after meeting the set conditions. from Remove the least used node in F Move out and move in ,Will Move in F; The nodes in the block verify the block. If the verification pass rate is not lower than the set verification threshold, the block is uploaded to the DAG blockchain G, otherwise it is not uploaded.

Images