A blockchain-based digital modeling collaboration management method and system

Abstract

The application relates to a kind of blockchain-based digital modeling collaboration management method and system, belong to collaboration management technical field, including steps: through the interoperability framework of digital modeling collaboration based on consortium chain is built;Participant BPMS is authenticated through CA identity certificate identity;Task node publishes the cooperation task request and corresponding incentive of new block, Hyperledger blockchain carries out information interaction by calling the smart contract deployed on the consortium chain, realizes modeling collaboration design;Through the execution of all cooperation task requests, complete the digital modeling of target task, determine the model obtained by final consensus as the result of modeling collaboration and publish it.The application realizes the sharing and collaborative development of digital model by establishing the interoperability framework based on blockchain, realizes modeling verification and participant reputation evaluation through consensus mechanism and reputation evaluation, and improves collaboration efficiency.

Description

Technical Field

[0001] This invention belongs to the field of collaborative management technology, specifically relating to a blockchain-based digital modeling collaborative management method and system. Background Technology

[0002] With the advancement of Industry 4.0 and the acceleration of digital transformation, more and more enterprises and organizations are adopting technologies such as digital twins and BIM (Building Information Modeling) to create digital models to simulate and optimize physical assets, production processes, and operational management. However, in complex environments involving multi-party collaboration, digital modeling often requires the participation of multiple parties across departments, organizations, and even regions, which places higher demands on data security, transparency of collaboration, and trust mechanisms.

[0003] Traditional digital modeling collaboration systems typically rely on centralized management platforms, with system operators or third-party service providers responsible for data storage and management. However, this centralized management approach brings problems such as data monopoly, insufficient data privacy protection, and complex access control. Especially when multi-party collaboration is involved, ensuring data authenticity, model validity, and fair participation from all parties is a core challenge.

[0004] Therefore, there is an urgent need to propose a blockchain-based digital modeling collaboration management method and system, which, with its decentralized, immutable and highly transparent characteristics, enables the sharing and collaborative development of digital models and achieves efficient digital modeling collaboration. Summary of the Invention

[0005] To address the aforementioned problems in existing technologies, this invention provides a blockchain-based digital modeling collaborative management method and system. By establishing a blockchain-based interoperability framework, it enables the sharing and collaborative development of digital models. Through consensus mechanisms and reputation assessments, it achieves model verification and participant reputation evaluation, thereby improving collaborative efficiency.

[0006] The objective of this invention can be achieved through the following technical solutions:

[0007] The first aspect of this disclosure provides a blockchain-based digital modeling collaboration management method, comprising the following steps:

[0008] Modeling and design execution: Task nodes publish collaborative task requests and corresponding incentives for new blocks. The Hyperledger blockchain interacts with information by calling smart contracts deployed on the consortium blockchain to achieve collaborative modeling and design.

[0009] The execution modeling design includes the following steps:

[0010] Task Request: The task node first determines the modeling goal based on the digital modeling requirements and generates a collaborative task request and incentive. Then, it sends the collaborative task request and incentive to the Hyperledger blockchain through the REST Server.

[0011] Collaborator matching: Based on the collaborative task request and the reputation of the certified participants, the collaborators for this modeling task are matched, and the matching results are fed back to the Hyperledger blockchain via the REST Server. Collaborative modeling begins when the collaborators confirm to cooperate on the task.

[0012] Blockchain consensus: The historical reputation of collaborative participants is ranked. Collaborative participants are selected from the reputation ranking according to the number of nodes required by the PBFT algorithm. The selected collaborative participants belong to the consensus group. The remaining collaborative participants do not participate in the consensus and only receive messages from the consensus group to synchronize their own state.

[0013] Participant BPMS Reputation Assessment: The participant's BPMS reputation is quantitatively assessed through two dimensions: digital modeling ability and participant behavior.

[0014] Reputation rating classification: Based on the calculated overall reputation of the collaborating participants, the participants are classified into efficient and trustworthy collaborators, ordinary collaborators, and malicious collaborators by setting reputation ranges for the overall reputation.

[0015] Furthermore, the participant BPMS reputation assessment includes the following steps:

[0016] Competency Reputation: By quantifying the participants' historical modeling data, the participant's competency reputation is calculated using the following formula:

[0017] ;

[0018] In the formula, For participants i Capabilities and reputation k The number of attributes for capability and reputation assessment. For the weights of each attribute, Quantify the capability and reputation attributes;

[0019] Among them, the capability reputation attribute includes the difficulty level of the participant's historical modeling, model performance, and delivery capability;

[0020] Behavioral reputation: It is obtained by combining consensus reputation, response reputation, and participation reputation. The calculation formula is as follows:

[0021] ;

[0022] In the formula, For participantsi behavioral reputation, , and Consensus and reputation C Response to reputation R and participation in reputation E The scoring weighting coefficient;

[0023] Overall Reputation: By using a weighted average, a participant's competence reputation and behavioral reputation are linearly combined to obtain an overall reputation. Z :

[0024] ;

[0025] In the formula, , Participants i Ability and Reputation and behavioral reputation The scoring weighting coefficient.

[0026] Furthermore, the consensus reputation C The calculation formula is:

[0027] ;

[0028] In the formula, A To ensure the accuracy of consensus among node participants, To ensure that the adjustment parameters are accurately determined by consensus, A The calculation formula is:

[0029] ;

[0030] In the formula, r To submit the correct number of consensus transactions, e To determine the number of incorrect consensus transactions submitted, n To refuse to submit the number of consensus transactions;

[0031] The response reputation R The calculation formula is:

[0032] ;

[0033] In the formula, The average transaction verification time for participants. To influence R The function's rate of decrease parameter;

[0034] The participation reputation E The calculation formula is:

[0035] ;

[0036] In the formula, I The number of times a participant is selected for a consensus group. W The number of times participants collaborated.

[0037] Furthermore, the blockchain consensus also includes the following steps:

[0038] The task request results broadcast by collaborative participants are collected, packaged into blocks to be verified, and consensus is reached on the blocks to be verified through a consensus group. Consensus is reached through a practical Byzantine fault-tolerant algorithm. After obtaining more than two-thirds of the authentication, the block will become a valid block and be stored in the respective blockchains.

[0039] Furthermore, the consensus achieved through a practical Byzantine fault-tolerant algorithm includes the following steps:

[0040] Pre-preparation phase: The blockchain network designates a master node, which broadcasts a pre-preparation message to the entire consensus group, including the master node's signature, block content and number, and digest;

[0041] After receiving the pre-preparation message, the secondary node verifies whether the block's digest and content are valid: if the digest is valid, the secondary node will accept the pre-preparation message and proceed to the next stage; if the digest is invalid, the secondary node will reject the message.

[0042] Preparation phase: In the pre-preparation phase, if each secondary node approves the primary node's pre-preparation message, it will broadcast a preparation message to all other nodes. The preparation message includes the content of the pre-preparation message and the secondary node's signature.

[0043] Each node must collect more than two-thirds of the preparation messages to indicate that a majority of nodes in the network have accepted the block; at this point, the node confirms that the block has been widely accepted and proceeds to the next stage.

[0044] Furthermore, the consensus-building process using a practical Byzantine fault-tolerant algorithm also includes the following steps:

[0045] Commit phase: After the preparation phase is completed, the node will broadcast a commit message to other nodes, indicating that it agrees that the block will eventually be confirmed;

[0046] Each node needs to collect more than two-thirds of the commit messages to indicate that most nodes have given final confirmation to the block;

[0047] When a block is determined to be valid, all nodes will store the block in their local ledgers, and the entire network state will be updated synchronously, thus completing the consensus for this task request in the blockchain network.

[0048] Furthermore, the digital modeling collaborative management method also includes the following steps:

[0049] Establish a collaborative framework: An interoperable framework for digital modeling collaboration is established based on a consortium blockchain. The interoperable framework includes participants BPMS, REST Server, and Hyperledger blockchain.

[0050] The participant BPMS is used to manage and track task progress, resource allocation, and process execution in digital modeling collaboration; the REST Server is used to connect the participant BPMS and the Hyperledger blockchain nodes, enabling the participant BPMS and the Hyperledger blockchain to communicate through a standardized API; the Hyperledger blockchain is responsible for recording and managing transactions, smart contract execution, collaboration records between participants, and auditing business processes in the system.

[0051] Collaboration participant authentication: The participant BPMS obtains identity credentials through CA registration, and then sends a request with verification content to the Fabric network through the REST Server. Peer nodes in the Fabric network verify the identity of the participant BPMS, allocate public and private key pairs, and assign initial reputation to the participant BPMS based on its authentication information.

[0052] Publishing the collaborative model: By executing all collaborative task requests, the digital modeling of the target task is completed, and the model obtained through final consensus is published as the result of the modeling collaboration.

[0053] Furthermore, the smart contract includes the following rules:

[0054] Node joining rules: All participants joining the collaborative blockchain as nodes must undergo identity verification and digital modeling capability assessment.

[0055] Task request sharing rules: Define the access permissions of different participants to digital model data. Matched collaborating participants have the permission to modify or add data, while other participants in the interoperability framework cannot access the current task request data.

[0056] Blockchain consensus rules: Based on the overall reputation of the collaborating participants, participants who meet the requirements of the consensus algorithm are selected to form a consensus group to conduct consensus. The remaining collaborating participants do not participate in the consensus and only receive messages from the consensus group to synchronize their own state.

[0057] The second aspect of this disclosure provides a blockchain-based digital modeling collaborative management system, applied to a blockchain-based digital modeling collaborative management method as described above, including a blockchain network management module, a digital modeling module, and a smart contract management module;

[0058] The blockchain network management module is used to build a digital modeling collaboration framework, authenticate and remove collaboration participants, and the building of the digital modeling collaboration framework includes the following steps:

[0059] Identify the participants in the digital modeling process; these participants will use the BPMS system for business process management and share data through Hyperledger Fabric; design and deploy the business process management system, defining the digitally modeled business processes through the BPMS.

[0060] Configure the REST Server to convert business requests generated by BPMS into a blockchain transaction format that Fabric can recognize, and return the results to BPMS;

[0061] Design the smart contract according to the smart contract rules, deploy the smart contract to the Fabric network, call the smart contract functions through the Fabric-SDK, and verify whether the deployment and functions of the contract are correct;

[0062] Create a Fabric channel suitable for modeling collaboration, add the peer nodes of each participant to the channel, and configure the Hyperledger Fabric consensus mechanism.

[0063] As a preferred embodiment of the present invention, the digital modeling module is used for version control of the digital model, including model updates, version rollbacks, and queries of historical models.

[0064] The smart contract management module is used for the creation, deployment and execution of smart contracts. Each participant uses smart contracts to automatically process collaborative tasks, including task allocation, resource sharing and data exchange. At the same time, smart contracts automatically allocate tasks, set conditions for task completion, and monitor the progress of tasks for each party.

[0065] The beneficial effects of this invention are as follows:

[0066] This invention first addresses the need for collaborative digital modeling by building an interoperability framework based on a consortium blockchain, providing a platform for collaborative modeling. Then, it authenticates the participants in the modeling process and integrates them into the blockchain network, thereby achieving cross-system collaboration and data sharing. This approach ensures the trustworthiness of the collaboration process and the data. During the collaboration process, collaborators with different task requests are selected by matching task request attributes and participant reputation, enhancing collaboration efficiency. Simultaneously, a group identification mechanism reduces the number of consensus participants, thus improving consensus speed and stability. Furthermore, a participant reputation evaluation mechanism is implemented during operation, continuously updating participant reputation to provide a basis for consensus group selection in modeling collaboration, improving the accuracy of the selection process.

[0067] This invention quantifies participant reputation through two dimensions: digital modeling capability and participant behavior, comprehensively reflecting participants' performance in actual operations. This provides more accurate decision-making data for participant matching and consensus group establishment in subsequent collaborative tasks. Furthermore, based on the updated comprehensive reputation, participants are eliminated, ensuring the system's security and stability. Simultaneously, by incorporating participant reputation into the reputation assessment through a consensus mechanism based on consensus groups, the correlation between the consensus mechanism and reputation assessment is enhanced, enabling fine-grained assessment of participant capabilities and reliability. This effectively avoids single-point aggregation and collusion attacks, and the reputation level classification improves the efficiency of modeling collaboration. Attached Figure Description

[0068] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings.

[0069] Figure 1 A schematic diagram illustrating the steps of a blockchain-based digital modeling and collaborative management method provided in an embodiment of the present invention;

[0070] Figure 2 This is a schematic diagram of an interoperability framework for digital modeling collaboration provided in an embodiment of the present invention;

[0071] Figure 3 A schematic diagram illustrating the steps of performing modeling and design according to an embodiment of the present invention;

[0072] Figure 4 This is a schematic diagram of the structure of a blockchain-based digital modeling collaborative management system provided in an embodiment of the present invention. Detailed Implementation

[0073] To further illustrate the technical means and effects adopted by the present invention to achieve the intended purpose, the following detailed description of the specific implementation methods, structures, features and effects of the present invention, in conjunction with the accompanying drawings and preferred embodiments, is provided.

[0074] This embodiment provides a blockchain-based digital modeling and collaborative management method, such as... Figure 1 As shown, it includes the following steps:

[0075] S1. Establish a collaborative framework: An interoperable framework for digital modeling collaboration is established based on a consortium blockchain. The interoperable framework includes participants BPMS (Business Process Management System), REST Server, and Hyperledger blockchain.

[0076] It should be noted that a consortium blockchain is a system form between public and private blockchains, and participants must be authenticated or identifiable. In this embodiment, the consortium blockchain uses the Hyperledger Fabric platform, such as... Figure 2 As shown, it includes a participant BPMS, a REST server, and a blockchain; wherein, the participant BPMS is used to manage and track task progress, resource allocation, and process execution in digital modeling collaboration; the REST server is used to connect the participant BPMS and the Hyperledger blockchain nodes, enabling the participant BPMS and the Hyperledger blockchain to communicate through a standardized API; the Hyperledger blockchain is responsible for recording and managing transactions, smart contract execution, collaboration records between participants, and auditing business processes in the system.

[0077] Understandably, participants integrate BPMS with REST Server and blockchain to facilitate information flow through automated data collection, enabling cross-system collaboration and data sharing, thereby improving the efficiency and optimization of digital modeling collaboration.

[0078] S2. Collaboration Participant Authentication: The participant BPMS obtains identity credentials through CA registration, and then sends a request with verification content to the Fabric network through RESTServer. Peer nodes in the Fabric network verify the identity of the participant BPMS, allocate public and private key pairs, and assign initial reputation to the participant BPMS based on its authentication information.

[0079] Understandably, Hyperledger Fabric provides Certificate Authorities (CAs) specifically for managing the identities of participants in the network. The authentication methods are those set by Fabric during network establishment. Participant BPMS sends authentication requests to the Fabric network by calling the Fabric-SDK. Authentication includes CA certificate verification, user account / password verification, and system-set permission verification. Initial reputation is assigned based on an assessment of the participant's digital modeling capabilities.

[0080] S3. Execution of Modeling and Design: Task nodes publish collaborative task requests and corresponding incentives for new blocks. The Hyperledger blockchain interacts with these requests by calling smart contracts deployed on the consortium blockchain, thus achieving collaborative modeling and design. Figure 3 As shown, the specific steps include:

[0081] S31. Task Request: The task node first determines the modeling goal based on the digital modeling requirements and generates a collaborative task request and incentive. Then, it sends the collaborative task request and incentive to the Hyperledger blockchain through the REST Server. The collaborative task request includes a task description, goal, time limit, and required resources.

[0082] Understandably, task requests are encrypted using public keys, and the incentive mechanism is a rational system that reflects the interaction between the incentive subject and the incentive object. When a collaborative task is released, corresponding incentives are set up. The first node to complete the task and pass verification can receive virtual currency as an incentive. The value of the virtual currency is an economic subsidy corresponding to the amount of work done.

[0083] S32. Collaborator Matching: Based on the collaborative task request and the reputation of the certified participants, the collaborators for this modeling task are matched, and the matching results are fed back to the Hyperledger blockchain via the REST Server. Collaborative modeling begins when the collaborators confirm to collaborate on the task.

[0084] S33. Blockchain Consensus: The historical reputation of collaborative participants is ranked. Based on the PBFT algorithm's requirement for the number of nodes, collaborative participants in the reputation ranking are selected. The selected collaborative participants belong to the consensus group, while the remaining collaborative participants do not participate in the consensus and only receive messages from the consensus group to synchronize their own state.

[0085] Understandably, the efficiency of digital modeling collaboration depends on the consensus speed of the consortium blockchain. To improve efficiency, this embodiment increases the consensus speed by reducing the number of consensus participants. The selection of consensus participants is determined by the participant reputation ranking. Therefore, updating the participant reputation is crucial in this embodiment.

[0086] The task request results broadcast by collaborative participants are collected, packaged into blocks to be verified, and consensus is reached on the blocks to be verified through a consensus group. Consensus is reached through practical Byzantine fault tolerance (PBFT). After obtaining more than two-thirds of the verification, the block will become a valid block and be stored in the respective blockchains.

[0087] The PBFT consensus process includes the following steps:

[0088] S331, Pre-preparation phase: The blockchain network designates a master node, which broadcasts a pre-preparation message to the entire consensus group, including the master node signature, block content and number, and digest;

[0089] After receiving the pre-preparation message, the secondary node verifies whether the block's digest and content are valid: if the digest is valid, the secondary node will accept the pre-preparation message and proceed to the next stage; if the digest is invalid, the secondary node will reject the message.

[0090] S332. Preparation Phase: In the pre-preparation phase, if each secondary node approves the primary node's pre-preparation message, it will broadcast a preparation message to all other nodes. The preparation message includes the content of the pre-preparation message and the secondary node's signature.

[0091] Each node must collect more than two-thirds of the preparation messages (including its own) to indicate that a majority of nodes in the network have accepted the block. At this point, the node confirms that the block has been widely accepted and can proceed to the next stage.

[0092] S333, Commit Phase: After the preparation phase is completed, the node will broadcast a commit message to other nodes, indicating that it agrees that the block will eventually be confirmed;

[0093] Each node must collect more than two-thirds of the commit messages, indicating that a majority of nodes have given final confirmation to the block. At this stage, if enough commit messages are successfully collected, the node considers the block to have passed the consensus process and can be written to its local blockchain ledger.

[0094] Once a block is deemed valid, all nodes store it in their local ledgers, and the entire network state is synchronized and updated. At this point, the blockchain network has completed the consensus for this task request.

[0095] Understandably, this process ensures that consensus on each new block in the blockchain network is achieved through collaboration among multiple nodes, and that any Byzantine fault will not affect the final system consistency, thus ensuring the reliability, security, and decentralization of the blockchain; at the same time, consensus based on selected consensus groups improves the efficiency of digital modeling collaboration.

[0096] S34. Participant BPMS Reputation Assessment: The participant's BPMS reputation is quantitatively assessed through two dimensions: digital modeling ability and participant behavior. This includes the following steps:

[0097] S341. Competency and Reputation: By quantifying the participants' historical modeling data, the participant's competency and reputation are calculated using the following formula:

[0098] ;

[0099] In the formula, For participants i Capabilities and reputation k The number of attributes for capability and reputation assessment. For the weights of each attribute, This is a quantified value for the ability and reputation attribute.

[0100] Among them, the capability reputation attribute includes the difficulty level of the participant's historical modeling, model performance, and delivery capability.

[0101] S342. Behavioral Reputation: Obtained by combining consensus reputation, response reputation, and participation reputation, calculated using the following formula:

[0102] ;

[0103] In the formula, For participants i behavioral reputation, , and Consensus and reputation C Response to reputation R and participation in reputation E The scoring weighting coefficient.

[0104] Among them, consensus credibility C The calculation formula is:

[0105] ;

[0106] In the formula, A To ensure the accuracy of consensus among node participants, To ensure that the adjustment parameters are accurately determined by consensus, A The calculation formula is:

[0107] ;

[0108] In the formula, r To submit the correct number of consensus transactions, e To determine the number of incorrect consensus transactions submitted, n To refuse to submit the number of consensus transactions.

[0109] Responding to reputation R The calculation formula is:

[0110] ;

[0111] In the formula, The average transaction verification time for participants. To influence R The function's rate of decrease parameter.

[0112] Participate in reputation E The calculation formula is:

[0113] ;

[0114] In the formula, I The number of times a participant is selected for a consensus group. W The number of times participants collaborated.

[0115] S343. Comprehensive Reputation: Comprehensive reputation is obtained by linearly combining the participants' ability reputation and behavioral reputation through a weighted average. Z :

[0116] ;

[0117] In the formula, , Participants i Ability and Reputation and behavioral reputation The scoring weighting coefficient.

[0118] It should be noted that in the interoperability framework of this embodiment, the reputation evaluation result of the participant BPMS directly reflects its contribution status to the collaborative task. The reputation evaluation is dynamic. With the completion of each collaborative task, the participant's reputation will be updated according to the actual performance and used for level classification and collaborator matching, so as to better manage and optimize the collaborative relationship between participants and improve collaboration efficiency.

[0119] S35. Reputation Rating Classification: Based on the calculated comprehensive reputation of the collaborating participants, a rating system is established, dividing the collaborating participants into highly efficient and trustworthy collaborators, ordinary collaborators, and malicious collaborators by setting reputation ranges for the comprehensive reputation.

[0120] Among them, efficient and reliable collaborators are used for consensus groups and master node elections; ordinary collaborators are used to participate in modeling and collaborative transactions; and malicious collaborators are directly removed to improve the security of the system.

[0121] Smart contracts include the following rules:

[0122] (1) Node joining rules: All participants who join the collaborative blockchain as nodes must undergo identity verification and digital modeling capability assessment;

[0123] Understandably, based on the node entry rules, participants can only enter the system and conduct transactions after passing identity authentication and capability assessment. The digital modeling capability assessment analyzes the difficulty and model performance of the modeling tasks submitted by participants.

[0124] (2) Task request sharing rules: specify the access permissions of different participants to digital model data. Matched collaborating participants have the permission to modify or add data, while other participants in the interoperability framework cannot access the current task request data.

[0125] By controlling participant permissions based on task request matching results, the system's security and efficiency can be improved, and resource allocation can be optimized and task completion quality can be enhanced.

[0126] (3) Blockchain consensus rules: Based on the comprehensive reputation of the collaborating participants, participants who meet the requirements of the consensus algorithm are selected to form a consensus group to conduct consensus. The remaining collaborating participants do not participate in the consensus and only receive messages from the consensus group to synchronize their own state.

[0127] By establishing consensus groups, the number of consensus participants is reduced, thereby improving the efficiency and quality of consensus.

[0128] S4. Publish the collaborative model: By executing all collaborative task requests, complete the digital modeling of the target task, and publish the model obtained from the final consensus as the result of the modeling collaboration.

[0129] This embodiment also provides a blockchain-based digital modeling collaboration management system, such as... Figure 4 As shown, it includes a blockchain network management module, a digital modeling module, and a smart contract management module.

[0130] The blockchain network management module is used to build a digital modeling collaboration framework, authenticate and remove collaboration participants, and the building of the digital modeling collaboration framework includes the following steps:

[0131] Identify the participants in the digital modeling process. These participants will use the BPMS system for business process management and share data through Hyperledger Fabric.

[0132] Design and deploy a Business Process Management System (BPMS) to define digitally modeled business processes.

[0133] Configure a REST Server as middleware between BPMS and Hyperledger Fabric, responsible for converting business requests generated by BPMS into blockchain transaction formats that Fabric can recognize, and returning the results to BPMS;

[0134] Design the smart contract according to the smart contract rules, deploy the smart contract to the Fabric network, call the smart contract functions through the Fabric-SDK, and verify whether the deployment and functions of the contract are correct;

[0135] Create a Fabric channel suitable for modeling collaboration, add the peer nodes of each participant to the channel, and configure the Hyperledger Fabric consensus mechanism.

[0136] The digital modeling module is used for version control of the digital model, including model updates, version rollbacks, and queries of historical models, ensuring that all participants can use the same version of the model during the collaboration process.

[0137] The smart contract management module is used for the creation, deployment and execution of smart contracts. Each participant uses smart contracts to automatically process collaborative tasks, such as task allocation, resource sharing and data exchange. At the same time, smart contracts can automatically allocate tasks, set conditions for task completion, and monitor the progress of tasks for each party.

[0138] This invention first addresses the need for collaborative digital modeling by building an interoperability framework based on a consortium blockchain, providing a platform for collaborative modeling. Then, it authenticates the participants in the modeling process and integrates them into the blockchain network, thereby achieving cross-system collaboration and data sharing. This approach ensures the trustworthiness of the collaboration process and the data. During the collaboration process, collaborators with different task requests are selected by matching task request attributes and participant reputation, enhancing collaboration efficiency. Simultaneously, a group identification mechanism reduces the number of consensus participants, thus improving consensus speed and stability. Furthermore, a participant reputation evaluation mechanism is implemented during operation, continuously updating participant reputation to provide a basis for consensus group selection in modeling collaboration, improving the accuracy of the selection process.

[0139] This invention quantifies participant reputation through two dimensions: digital modeling capability and participant behavior, comprehensively reflecting participants' performance in actual operations. This provides more accurate decision-making data for participant matching and consensus group establishment in subsequent collaborative tasks. Furthermore, based on the updated comprehensive reputation, participants are eliminated, ensuring the system's security and stability. Simultaneously, by incorporating participant reputation into the reputation assessment through a consensus mechanism based on consensus groups, the correlation between the consensus mechanism and reputation assessment is enhanced, enabling fine-grained assessment of participant capabilities and reliability. This effectively avoids single-point aggregation and collusion attacks, and the reputation level classification improves the efficiency of modeling collaboration.

[0140] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A blockchain-based method for collaborative management of digital modeling, characterized in that: Includes the following steps: Modeling and design execution: Task nodes publish collaborative task requests and corresponding incentives for new blocks. The Hyperledger blockchain interacts with information by calling smart contracts deployed on the consortium blockchain to achieve collaborative modeling and design. The execution modeling design includes the following steps: Task Request: The task node first determines the modeling goal based on the digital modeling requirements and generates a collaborative task request and incentive. Then, it sends the collaborative task request and incentive to the Hyperledger blockchain through the REST Server. Collaborator matching: Based on the collaborative task request and the reputation of the certified participants, the collaborators for this modeling task are matched, and the matching results are fed back to the Hyperledger blockchain via the REST Server. Collaborative modeling begins when the collaborators confirm to cooperate on the task. Blockchain consensus: The historical reputation of collaborative participants is ranked. Collaborative participants are selected from the reputation ranking according to the number of nodes required by the PBFT algorithm. The selected collaborative participants belong to the consensus group. The remaining collaborative participants do not participate in the consensus and only receive messages from the consensus group to synchronize their own state. Participant BPMS Reputation Assessment: The participant's BPMS reputation is quantitatively assessed through two dimensions: digital modeling ability and participant behavior. Reputation rating classification: Based on the calculated overall reputation of the collaborating participants, the participants are classified into highly efficient and trustworthy collaborators, ordinary collaborators, and malicious collaborators by setting reputation ranges for the overall reputation. The participant BPMS reputation assessment includes the following steps: Competency Reputation: By quantifying the participants' historical modeling data, the participant's competency reputation is calculated using the following formula: ； wherein, is the capability reputation of the participant k is the number of attributes of the capability reputation evaluation, is the weight of each attribute, is the quantified value of the capability reputation attribute; Among them, the capability reputation attribute includes the difficulty level of the participant's historical modeling, model performance, and delivery capability; Behavioral reputation: It is obtained by combining consensus reputation, response reputation, and participation reputation. The calculation formula is as follows: ； In the formula, the behavior reputation of the participant, , and are respectively the scoring weight coefficients of the consensus reputation C, the response reputation R and the participation reputation E.​ Comprehensive Reputation: A comprehensive reputation Z is obtained by linearly combining the participants' ability reputation and behavioral reputation through a weighted average. ； In the formula, , are the scoring weight coefficients of the ability reputation and the behavior reputation of the participant , respectively. The digital modeling collaborative management method also includes the following steps: Establish a collaborative framework: An interoperable framework for digital modeling collaboration is established based on a consortium blockchain. The interoperable framework includes participants BPMS, REST Server, and Hyperledger blockchain. The participant BPMS is used to manage and track task progress, resource allocation, and process execution in digital modeling collaboration; the REST Server is used to connect the participant BPMS and the Hyperledger blockchain nodes, enabling the participant BPMS and the Hyperledger blockchain to communicate through a standardized API; the Hyperledger blockchain is responsible for recording and managing transactions, smart contract execution, collaboration records between participants, and auditing business processes in the system. Collaboration participant authentication: Participant BPMS obtains identity credentials through CA registration, and then sends a request with verification content to the Fabric network through REST Server. Peer nodes in the Fabric network verify the identity of participant BPMS, allocate public and private key pairs, and assign initial reputation based on the participant BPMS's authentication information; Publishing the collaborative model: By executing all collaborative task requests, the digital modeling of the target task is completed, and the model obtained by final consensus is determined as the result of the modeling collaboration and published. The smart contract includes the following rules: Node joining rules: All participants joining the collaborative blockchain as nodes must undergo identity verification and digital modeling capability assessment. Task request sharing rules: Define the access permissions of different participants to digital model data. Matched collaborating participants have the permission to modify or add data, while other participants in the interoperability framework cannot access the current task request data. Blockchain consensus rules: Based on the overall reputation of the collaborating participants, participants who meet the requirements of the consensus algorithm are selected to form a consensus group to conduct consensus. The remaining collaborating participants do not participate in the consensus and only receive messages from the consensus group to synchronize their own state. 2.The blockchain-based digital modeling collaboration management method of claim 1, wherein: The formula for calculating the consensus reputation C is as follows: ； In the formula, A is the consensus accuracy of a node participant, The adjustment parameter for the consensus accuracy is A, and the calculation formula of A is as follows: ； In the formula, r is the number of correct consensus transactions submitted, e is the number of incorrect consensus transactions submitted, and n is the number of consensus transactions rejected. The formula for calculating the response reputation R is: ； wherein is the average transaction verification time for the participants, is a parameter that affects the rate of decline of the R function; The formula for calculating the participation reputation E is as follows: ； In the formula, I represents the number of times a participant is selected for a consensus group, and W represents the number of times a participant collaborates. 3.The blockchain-based digital modeling collaboration management method of claim 1, wherein: The blockchain consensus also includes the following steps: The task request results broadcast by collaborative participants are collected, packaged into blocks to be verified, and consensus is reached on the blocks to be verified through a consensus group. Consensus is reached through a practical Byzantine fault-tolerant algorithm. After obtaining more than two-thirds of the authentication, the block will become a valid block and be stored in the respective blockchains. 4.The blockchain-based digital modeling collaboration management method of claim 3, wherein: The consensus mechanism using a practical Byzantine fault-tolerant algorithm includes the following steps: Pre-preparation phase: The blockchain network designates a master node, which broadcasts a pre-preparation message to the entire consensus group, including the master node's signature, block content and number, and digest; After receiving the pre-preparation message, the secondary node verifies whether the block's digest and content are valid: if the digest is valid, the secondary node will accept the pre-preparation message and proceed to the next stage; if the digest is invalid, the secondary node will reject the message. Preparation phase: In the pre-preparation phase, if each secondary node approves the primary node's pre-preparation message, it will broadcast a preparation message to all other nodes. The preparation message includes the content of the pre-preparation message and the secondary node's signature. Each node must collect more than two-thirds of the preparation messages to indicate that a majority of nodes in the network have accepted the block; at this point, the node confirms that the block has been widely accepted and proceeds to the next stage. 5.The blockchain-based digital modeling collaboration management method of claim 4, wherein: The consensus mechanism using a practical Byzantine fault-tolerant algorithm also includes the following steps: Commit phase: After the preparation phase is completed, the node will broadcast a commit message to other nodes, indicating that it agrees that the block will eventually be confirmed; Each node needs to collect more than two-thirds of the commit messages to indicate that most nodes have given final confirmation to the block; When a block is determined to be valid, all nodes will store the block in their local ledgers, and the entire network state will be updated synchronously, thus completing the consensus for this task request in the blockchain network. 6.A blockchain-based digital modeling collaboration management system applied to the blockchain-based digital modeling collaboration management method according to any one of claims 1-5, characterized in that: It includes a blockchain network management module, a digital modeling module, and a smart contract management module; The blockchain network management module is used to build a digital modeling collaboration framework, authenticate and remove collaboration participants, and the building of the digital modeling collaboration framework includes the following steps: Identify the participants in the digital modeling process; these participants will use the BPMS system for business process management and share data through Hyperledger Fabric; design and deploy the business process management system, defining the digitally modeled business processes through the BPMS. Configure the REST Server to convert business requests generated by BPMS into a blockchain transaction format that Fabric can recognize, and return the results to BPMS; Design the smart contract according to the smart contract rules, deploy the smart contract to the Fabric network, call the smart contract functions through the Fabric-SDK, and verify whether the deployment and functions of the contract are correct; Create a Fabric channel suitable for modeling collaboration, add the peer nodes of each participant to the channel, and configure the Hyperledger Fabric consensus mechanism.

7. The blockchain-based collaborative management system for digital modeling according to claim 6, wherein: The digital modeling module is used for version control of the digital model, including model updates, version rollbacks, and queries of historical models. The smart contract management module is used for the creation, deployment, and execution of smart contracts. Each participant uses smart contracts to automatically process collaborative tasks, including task allocation, resource sharing, and data exchange. It also automatically assigns tasks, sets conditions for task completion, and monitors the progress of tasks for each party.

Images