Digital modeling cooperation management method and system based on block chain

Abstract

The invention relates to a digital modeling cooperation management method and system based on a block chain, and belongs to the technical field of cooperation management, and the method comprises the steps: building an interoperation framework of digital modeling cooperation based on an alliance chain; the participant BPMS passes the authentication of the CA identity certificate; a task node issues a collaboration task request and corresponding excitation of a new block, and a Hyperledger block chain performs information interaction by calling an intelligent contract deployed on an alliance chain to realize modeling collaboration design; digital modeling of a target task is completed by executing all cooperation task requests, and a model obtained through final consensus is determined as a modeling cooperation result to be published. According to the method, sharing and collaborative development of a digital model are realized by establishing an interoperation framework based on the block chain, modeling verification and participant reputation evaluation are realized through a consensus mechanism and reputation evaluation, and the collaborative efficiency is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of collaborative management, and specifically relates to a digital modeling collaborative management method and system based on blockchain. Background Art

[0002] With the advancement of Industry 4.0 and the acceleration of digital transformation, more and more companies and organizations are beginning to adopt 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 a complex environment of multi-party collaboration, digital modeling often requires the participation of multiple parties across departments, organizations and even regions, which places higher requirements on data security, transparency of collaboration and trust mechanisms.

[0003] Traditional digital modeling collaboration systems usually 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 authority management. Especially when it comes to multi-party collaboration, how to ensure the authenticity of data, the effectiveness of the model, and fair participation of all parties is a core challenge.

[0004] Therefore, it is urgent to propose a digital modeling collaborative management method and system based on blockchain, which can share and collaboratively develop digital models and realize efficient digital modeling collaboration by virtue of its decentralized, tamper-proof and highly transparent characteristics. Summary of the invention

[0005] In order to solve the above-mentioned problems existing in the prior art, the present invention provides a digital modeling collaborative management method and system based on blockchain. By establishing an interoperability framework based on blockchain, the sharing and collaborative development of digital models are realized. Through the consensus mechanism and reputation evaluation, modeling verification and participant reputation evaluation are realized, thereby improving the collaboration efficiency.

[0006] The purpose of the present invention can be achieved through the following technical solutions: The first aspect of the present disclosure provides a blockchain-based digital modeling collaborative management method, comprising the following steps: Execution modeling design: The task node publishes collaborative task requests and corresponding incentives for new blocks. The Hyperledger blockchain interacts with the smart contract deployed on the consortium chain to implement collaborative modeling design. The execution modeling design includes the following steps: Task request: The task node first determines the modeling target according to the digital modeling requirements and generates collaborative task requests and incentives, and then sends the collaborative task requests and incentives to the Hyperledger blockchain through the REST Server; Collaborative party matching: Match the collaborative participants of this modeling task according to the collaborative task request and the authenticated participant reputation, and feedback the matching results to the Hyperledger blockchain through the REST Server. When the collaborative participants confirm to collaborate on the task, collaborative modeling begins; Blockchain consensus: historical reputation ranking of collaborative participants is performed, and collaborative participants in the reputation ranking are selected according to the PBFT algorithm's requirement for the number of nodes. The selected collaborative participants belong to the consensus group, and the remaining collaborative participants do not participate in the consensus, but only receive messages from the consensus group to synchronize their own status; Participant BPMS reputation assessment: quantitatively assess the participant BPMS reputation through two dimensions: digital modeling capability and participant behavior; Reputation level classification: The collaborative participants are classified into levels based on the calculated comprehensive reputation. By setting reputation intervals for the comprehensive reputation, the collaborative participants are divided into efficient and trustworthy collaborators, ordinary collaborators, and malicious collaborators.

[0007] Furthermore, the participant BPMS reputation assessment includes the following steps: Capability reputation: The historical modeling data of the participants is quantified to calculate the capability reputation of the participants. The calculation formula is as follows: ; In the formula, For participants i The ability and reputation k is the number of attributes evaluated for capability reputation, is the weight of each attribute, Quantify the value of capability reputation attribute; Among them, the capability reputation attributes include the difficulty level of the participant’s historical modeling, model performance, and delivery capabilities; Behavior reputation: It is obtained by combining consensus reputation, response reputation and participation reputation. The calculation formula is as follows: ; In the formula, For participants i Behavioral reputation, , and Consensus reputation C , Response Reputation R and participation reputation E The scoring weight coefficient of Comprehensive reputation: Through weighted average, the ability reputation and behavior reputation of the participants are linearly combined to obtain comprehensive reputation Z : ; In the formula, , Participants i Ability and reputation and behavioral reputation The scoring weight coefficient of .

[0008] Furthermore, the consensus reputation C The calculation formula is: ; In the formula, A is the consensus accuracy of the node participants, The adjustment parameters are accurately determined by consensus. A The calculation formula is: ; In the formula, r To submit the correct consensus transaction number, e The number of transactions with incorrect consensus submitted. n The number of consensus transactions that were refused to be submitted; The response reputation R The calculation formula is: ; In the formula, is the average transaction verification time of participants, For influence R The decreasing speed parameter of the function; Reputation for participation E The calculation formula is: ; In the formula, I is the number of times the participant was selected into the consensus group, W The number of times the participant collaborated.

[0009] Furthermore, the blockchain consensus further includes the following steps: The task request results broadcast by the collaborative participants are collected and packaged into blocks to be verified. The consensus group reaches a consensus on the blocks to be verified. The consensus is reached through the practical Byzantine fault tolerance algorithm. After obtaining more than two-thirds of the certifications, the block will become a legal block and be stored in each part of the blockchain.

[0010] Furthermore, the consensus is reached through the practical Byzantine fault tolerance algorithm, including 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 signature, block content and number, and summary; After receiving the pre-prepare message, the secondary node verifies whether the summary and content of the block are valid: if the summary is valid, the secondary node will accept the pre-prepare message and proceed to the next stage; if the summary is invalid, the secondary node will reject the message; Preparation phase: In the pre-preparation phase, if each secondary node recognizes the pre-preparation message of the primary node, it will broadcast a preparation message to all other nodes. The preparation message includes the content of the pre-preparation message and the signature of the secondary node; Each node needs to collect more than two-thirds of the preparation messages to indicate that most nodes in the network have approved the block; at this point, the node confirms that the block has been widely accepted and enters the next stage.

[0011] Furthermore, the consensus through the practical Byzantine fault tolerance algorithm also includes the steps of: 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 is finally confirmed; Each node needs to collect more than two-thirds of the submission messages, indicating that most nodes have finalized the block; When a block is determined to be legitimate, all nodes will store the block in their local ledgers, and the status of the entire network will be updated synchronously, and the blockchain network will complete the consensus of this task request.

[0012] Furthermore, the digital modeling collaborative management method further comprises the steps of: Build a collaboration framework: Build an interoperability framework for digital modeling collaboration based on the alliance chain, which includes the participant 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 nodes of the Hyperledger blockchain, so that the participant BPMS and the Hyperledger blockchain can communicate through a standardized API; the Hyperledger blockchain is responsible for recording and managing transactions in the system, smart contract execution, collaboration records between participants, and auditing of business processes; Collaborative 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. The Peer node in the Fabric network verifies the identity of the participant BPMS, allocates a public and private key pair, and grants it initial credibility based on the participant BPMS's authentication information; Release the collaborative model: By executing all collaborative task requests, complete the digital modeling of the target task, and determine the final consensus model as the result of the modeling collaboration.

[0013] Furthermore, the smart contract includes the following rules: Node entry rules: All participants who join the collaborative blockchain as nodes must undergo identity verification and digital modeling capability assessment; Task request sharing rules: specify the access rights of different participants to digital model data. Matched collaborative participants have the rights 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 comprehensive reputation of the collaborating participants, participants who meet the number of consensus algorithms are selected to form a consensus group for consensus. The remaining collaborating participants do not participate in the consensus, but only receive messages from the consensus group to synchronize their own status.

[0014] A second aspect of the present disclosure provides a blockchain-based digital modeling collaboration management system, which is applied to a blockchain-based digital modeling collaboration management method as described above, including 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 collaborative participants, and building a digital modeling collaboration framework includes the following steps: Identify the participants of digital modeling, who will use the BPMS system for business process management and share data through Hyperledger Fabric; design and deploy the business process management system, and define the business process of digital modeling through BPMS; Configure REST Server to convert the business requests generated by BPMS into a blockchain transaction format recognizable by Fabric and return the results to BPMS; Design according to the smart contract rules, deploy the smart contract to the Fabric network, call the smart contract functions through 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 consensus mechanism of Hyperledger Fabric.

[0015] As a preferred technical solution of the present invention, the digital modeling module is used for version control of the digital model, including model update, version rollback and query of historical models; The smart contract management module is used for the creation, deployment and execution of smart contracts. Each participant automatically processes collaborative tasks through smart contracts, including task allocation, resource sharing and data exchange of the model. At the same time, smart contracts automatically allocate tasks, set conditions for task completion, and monitor the progress of tasks of all parties.

[0016] The beneficial effects of the present invention are: The present invention first builds an interoperability framework based on the alliance chain through the needs of digital modeling collaboration, provides a platform for modeling collaboration, and then authenticates the participants in the modeling and incorporates them into the blockchain network, thereby realizing cross-system collaboration and data sharing. This method ensures the credibility of the collaboration process and the credibility of the data. In the process of collaboration, the collaborators of different task requests are selected by matching the task request attributes and the participant reputation, which enhances the efficiency of collaboration. At the same time, through the group identification mechanism, the number of consensus participants is reduced, thereby improving the consensus speed and stability. In addition, a participant reputation evaluation mechanism is set up during the operation process, and by continuously updating the participant reputation, a consensus group selection basis is provided for modeling collaboration, thereby improving the screening accuracy.

[0017] In the process of participant reputation evaluation, the present invention quantitatively evaluates the participant reputation through two dimensions of digital modeling ability and participant behavior, comprehensively reflects the performance of the participants in actual operations, provides more accurate decision-making data for participant matching and consensus group establishment of subsequent collaborative tasks, and eliminates participants based on updated comprehensive reputation, ensuring the security and stability of the system; at the same time, the participation reputation is added to the reputation evaluation through a consensus mechanism based on the consensus group, which enhances the correlation between the consensus mechanism and the reputation evaluation, realizes fine-grained participant capability and reliability evaluation, effectively avoids the problems of single-point aggregation and collusion attacks, and at the same time improves the efficiency of modeling collaboration based on the division of reputation levels. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0019] Figure 1 A schematic diagram of the steps of a blockchain-based digital modeling collaborative management method provided by an embodiment of the present invention; Figure 2 A schematic diagram of an interoperability framework for digital modeling collaboration provided by an embodiment of the present invention; Figure 3 A schematic diagram of the steps of executing modeling design provided by an embodiment of the present invention; Figure 4 A schematic diagram of the structure of a blockchain-based digital modeling collaborative management system provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0020] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the specific implementation methods, structures, features and effects of the present invention are described in detail below in conjunction with the accompanying drawings and preferred embodiments.

[0021] This embodiment provides a digital modeling collaborative management method based on blockchain, such as Figure 1 As shown, the following steps are included: S1. Build a collaborative framework: Build an interoperable framework for digital modeling collaboration based on the alliance chain, which includes participants BPMS (Business Process Management System), REST Server and Hyperledger blockchain.

[0022] It should be noted that the consortium chain is a system form between the public chain and the private chain, and the participants must be authenticated or identifiable. In this embodiment, the consortium chain 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 nodes of the Hyperledger blockchain, so that the participant BPMS and the Hyperledger blockchain can communicate through a standardized API; the Hyperledger blockchain is responsible for recording and managing transactions in the system, smart contract execution, collaboration records between participants and auditing of business processes.

[0023] It is understandable that the participant BPMS is integrated with the REST Server and blockchain to achieve cross-system collaboration and data sharing through automated data collection for information flow, thereby improving the efficiency of digital modeling collaboration and optimizing collaboration.

[0024] S2. Collaborative 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. The Peer node in the Fabric network verifies the identity of the participant BPMS, allocates a public and private key pair, and grants it initial credibility based on the participant BPMS's authentication information.

[0025] It is understandable that Hyperledger Fabric provides a certification authority (CA, Certificate Authority), which is specifically used to manage the identity of each participant in the network. The verification content is the verification method set by Fabric when the network is established. The participant BPMS sends an identity authentication request to the Fabric network by calling Fabric-SDK. The verification content includes CA certificate verification, user account / password verification, system setting permission verification, etc. The initial credibility is granted based on the evaluation of the participant's digital modeling ability.

[0026] S3, Execution modeling design: The task node publishes the collaborative task request and corresponding incentives of the new block. The Hyperledger blockchain interacts with the smart contract deployed on the alliance chain to realize the collaborative modeling design, such as Figure 3 As shown, the specific steps include: S31. Task request: The task node first determines the modeling goal according to the digital modeling requirements and generates collaborative task requests and incentives, and then sends the collaborative task requests and incentives to the Hyperledger blockchain through the REST Server; wherein the collaborative task request includes task description, goal, time limit and required resources, etc.

[0027] It is understandable that the task request is encrypted by the public key, and the incentive mechanism is to reflect the way in which the incentive subject and the incentive object interact through a set of rational systems. Corresponding incentives are set when the collaborative task is released. The node that completes the task first and passes the verification can obtain virtual currency as an incentive. The value of the virtual currency is the economic subsidy corresponding to the workload.

[0028] S32, Collaborative party matching: The collaborative participants of this modeling task are matched according to the collaborative task request and the authenticated participant reputation, and the matching results are fed back to the Hyperledger blockchain through the REST Server. When the collaborative participants confirm to collaborate on the task, the collaborative modeling begins.

[0029] S33, Blockchain consensus: The historical reputation of the collaborative participants is ranked, and the collaborative participants in the reputation ranking are selected according to the PBFT algorithm's requirement for the number of nodes. The selected collaborative participants belong to the consensus group, while the remaining collaborative participants do not participate in the consensus, but only receive messages from the consensus group to synchronize their own status.

[0030] It is understandable that the efficiency of digital modeling collaboration depends on the speed of alliance chain consensus. In order to improve efficiency, this embodiment increases the consensus speed by reducing the number of consensus participants, and the screening of consensus participants is determined by the participant reputation ranking. Therefore, the update of participant reputation is crucial in this embodiment.

[0031] Collect the task request results broadcast by the collaborative participants, package them into blocks to be verified, and reach consensus on the blocks to be verified through the consensus group; reach consensus through practical Byzantine fault tolerance (PBFT). After obtaining more than two-thirds of the certifications, the block will become a legal block and be stored in each part of the blockchain.

[0032] The PBFT consensus process includes the following steps: 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 summary; After receiving the pre-prepare message, the secondary node verifies whether the summary and content of the block are valid: if the summary is valid, the secondary node will accept the pre-prepare message and proceed to the next stage; if the summary is invalid, the secondary node will reject the message.

[0033] S332, preparation stage: In the pre-preparation stage, if each secondary node recognizes the pre-preparation message of the primary node, it will broadcast a preparation message to all other nodes. The preparation message includes the content of the pre-preparation message and the signature of the secondary node; Each node needs to collect more than two-thirds of the preparation messages (including the messages sent by itself) to indicate that most nodes in the network have approved the block. At this point, the node confirms that the block has been widely accepted and can enter the next stage.

[0034] S333, Commitment phase: After the preparation phase is completed, the node will broadcast a commit message to other nodes, indicating that it agrees that the block is finally confirmed; Each node needs to collect more than two-thirds of the commit messages, indicating that most nodes have finally confirmed the block. At this stage, if enough commit messages are successfully collected, the node will determine that the block has passed the consensus process and can be written into the local blockchain ledger.

[0035] When a block is determined to be legitimate, all nodes will store the block in their local ledgers, and the state of the entire network will be updated synchronously. At this point, the blockchain network has completed the consensus of this task request.

[0036] It is understandable that this process ensures that the consensus of each new block in the blockchain network is achieved through the collaboration of multiple nodes, and any Byzantine errors will not affect the final system consistency, ensuring the reliability, security and decentralization of the blockchain; at the same time, consensus based on the screened consensus group improves the efficiency of digital modeling collaboration.

[0037] S34. Participant BPMS reputation assessment: Quantitatively assess the participant BPMS reputation through two dimensions: digital modeling capability and participant behavior, including the following steps: S341. Capability reputation: Calculate the participant's capability reputation by quantifying the historical modeling data of the participant. The calculation formula is as follows: ; In the formula, For participants i The ability and reputation k is the number of attributes evaluated for capability reputation, is the weight of each attribute, Quantify the value of capability reputation attribute.

[0038] Among them, capability reputation attributes include the difficulty level of participants' historical modeling, model performance, and delivery capabilities.

[0039] S342, Behavior reputation: It is obtained by combining consensus reputation, response reputation and participation reputation. The calculation formula is as follows: ; In the formula, For participants i Behavioral reputation, , and Consensus reputation C , Response Reputation R and participation reputation E The scoring weight coefficient of .

[0040] Among them, consensus credibility C The calculation formula is: ; In the formula, A is the consensus accuracy of the node participants, The adjustment parameters are accurately determined by consensus. A The calculation formula is: ; In the formula, r To submit the correct consensus transaction number, e The number of transactions with incorrect consensus submitted. n The number of consensus transactions that were refused to be submitted.

[0041] Response Reputation R The calculation formula is: ; In the formula, is the average transaction verification time of participants, For influenceR The function's decreasing speed parameter.

[0042] Participation Reputation E The calculation formula is: ; In the formula, I is the number of times the participant was selected into the consensus group, W The number of times the participant collaborated.

[0043] S343. Comprehensive reputation: Through weighted average, the ability reputation and behavior reputation of the participants are linearly combined to obtain the comprehensive reputation. Z : ; In the formula, , Participants i Ability and reputation and behavioral reputation The scoring weight coefficient of .

[0044] It should be noted that in the interoperability framework of this embodiment, the reputation evaluation results of the participant BPMS directly reflect 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 actual performance, which will be used for level division and collaborator matching, so as to better manage and optimize the collaborative relationship between participants and improve collaboration efficiency.

[0045] S35, reputation level classification: according to the calculated comprehensive reputation of the collaboration participants, the collaboration participants are classified into efficient and trustworthy collaborators, ordinary collaborators, and malicious collaborators by setting reputation intervals for the comprehensive reputation; Among them, efficient and trusted collaborators are used for consensus groups and master node elections; ordinary collaborators are used to participate in modeling collaborative transactions; malicious collaborators are directly eliminated to improve the security of the system.

[0046] Smart contracts include the following rules: (1) Node entry rules: All participants who join the collaborative blockchain as nodes must undergo identity verification and digital modeling capability assessment; It is understandable that according to the node entry rules, participants can enter the system and conduct transactions only after passing identity authentication and capability assessment. The digital modeling capability assessment is achieved by analyzing the difficulty and model performance of the modeling tasks submitted by the participants.

[0047] (2) Task request sharing rules: specify the access rights of different participants to the digital model data. Matching collaborative participants have the right to modify or add data, while other participants in the interoperability framework cannot access the current task request data. By controlling the permissions of participants based on task request matching results, the security and efficiency of the system can be improved, and resource allocation can be optimized and the quality of task completion can be improved.

[0048] (3) Blockchain consensus rules: Based on the comprehensive reputation of the collaborating participants, a consensus group is formed to select the number of participants that meet the consensus algorithm requirements. The remaining collaborating participants do not participate in the consensus, but only receive messages from the consensus group to synchronize their own status.

[0049] By establishing a consensus group, the number of consensus participants is reduced, and the efficiency and quality of consensus are improved.

[0050] S4. Release the collaborative model: By executing all collaborative task requests, the digital modeling of the target task is completed, and the model obtained by the final consensus is determined as the result of the modeling collaboration and released.

[0051] This embodiment also provides a digital modeling collaborative management system based on blockchain, such as Figure 4 As shown, it includes a blockchain network management module, a digital modeling module and a smart contract management module.

[0052] The blockchain network management module is used to build a digital modeling collaboration framework, authenticate and remove collaborative participants, and building a digital modeling collaboration framework includes the following steps: Identify the participants of digital modeling, who will use the BPMS system for business process management and share data through Hyperledger Fabric; Design and deploy business process management systems (BPMS), and define digitally modeled business processes through BPMS; Configure REST Server as the middleware between BPMS and Hyperledger Fabric, responsible for converting the business requests generated by BPMS into a blockchain transaction format recognizable by Fabric, and returning the results to BPMS; Design according to the smart contract rules, deploy the smart contract to the Fabric network, call the smart contract functions through 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 consensus mechanism of Hyperledger Fabric.

[0053] The digital modeling module is used for version control of the digital model, including model update, version rollback and query of historical models, to ensure that all participants can use the same version of the model during the collaboration process.

[0054] The smart contract management module is used for the creation, deployment and execution of smart contracts. Each participant automatically processes collaborative tasks through smart contracts, such as model task allocation, resource sharing, data exchange, etc. At the same time, smart contracts automatically allocate tasks, set conditions for task completion, and monitor the progress of tasks of all parties.

[0055] The present invention first builds an interoperability framework based on the alliance chain through the needs of digital modeling collaboration, provides a platform for modeling collaboration, and then authenticates the participants in the modeling and incorporates them into the blockchain network, thereby realizing cross-system collaboration and data sharing. This method ensures the credibility of the collaboration process and the credibility of the data. In the process of collaboration, the collaborators of different task requests are selected by matching the task request attributes and the participant reputation, which enhances the efficiency of collaboration. At the same time, through the group identification mechanism, the number of consensus participants is reduced, thereby improving the consensus speed and stability. In addition, a participant reputation evaluation mechanism is set up during the operation process, and by continuously updating the participant reputation, a consensus group selection basis is provided for modeling collaboration, thereby improving the screening accuracy.

[0056] In the process of participant reputation evaluation, the present invention quantitatively evaluates the participant reputation through two dimensions of digital modeling ability and participant behavior, comprehensively reflects the performance of the participants in actual operations, provides more accurate decision-making data for participant matching and consensus group establishment of subsequent collaborative tasks, and eliminates participants based on updated comprehensive reputation, ensuring the security and stability of the system; at the same time, the participation reputation is added to the reputation evaluation through a consensus mechanism based on the consensus group, which enhances the correlation between the consensus mechanism and the reputation evaluation, realizes fine-grained participant capability and reliability evaluation, effectively avoids the problems of single-point aggregation and collusion attacks, and at the same time improves the efficiency of modeling collaboration based on the division of reputation levels.

[0057] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any form. Although the present invention has been disclosed as a preferred embodiment as above, it is not used to limit the present invention. Any technical personnel in this field can make some changes or modify the technical contents disclosed above into equivalent embodiments without departing from the scope of the technical solution of the present invention. However, any brief modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention are still within the scope of the technical solution of the present invention.

Claims

1. A digital modeling collaborative management method based on blockchain, characterized by: The following steps are involved: Execution modeling design: The task node publishes collaborative task requests and corresponding incentives for new blocks. The Hyperledger blockchain interacts with the smart contract deployed on the consortium chain to implement collaborative modeling design. The execution modeling design includes the following steps: Task request: The task node first determines the modeling target according to the digital modeling requirements and generates collaborative task requests and incentives, and then sends the collaborative task requests and incentives to the Hyperledger blockchain through the REST Server; Collaborative party matching: Match the collaborative participants of this modeling task according to the collaborative task request and the authenticated participant reputation, and feedback the matching results to the Hyperledger blockchain through the REST Server. When the collaborative participants confirm to collaborate on the task, collaborative modeling begins; Blockchain consensus: historical reputation ranking of collaborative participants is performed, and collaborative participants in the reputation ranking are selected according to the PBFT algorithm's requirement for the number of nodes. The selected collaborative participants belong to the consensus group, and the remaining collaborative participants do not participate in the consensus, but only receive messages from the consensus group to synchronize their own status; Participant BPMS reputation assessment: quantitatively assess the participant BPMS reputation through two dimensions: digital modeling capability and participant behavior; Reputation level classification: The collaborative participants are classified into levels based on the calculated comprehensive reputation. By setting reputation intervals for the comprehensive reputation, the collaborative participants are divided into efficient and trustworthy collaborators, ordinary collaborators, and malicious collaborators.

2. According to a blockchain-based digital modeling collaborative management method according to claim 1, it is characterized by: The participant BPMS reputation assessment includes the following steps: Capability reputation: The historical modeling data of the participants is quantified to calculate the capability reputation of the participants. The calculation formula is as follows: ； In the formula, For participants i The ability and reputation k is the number of attributes evaluated for capability reputation, is the weight of each attribute, Quantify the value of capability reputation attribute; Among them, the capability reputation attributes include the difficulty level of the participant’s historical modeling, model performance, and delivery capabilities; Behavior reputation: It is obtained by combining consensus reputation, response reputation and participation reputation. The calculation formula is as follows: ； In the formula, For participants i Behavioral reputation, , and Consensus reputation C , Response Reputation R and participation reputation E The scoring weight coefficient of Comprehensive reputation: Through weighted average, the ability reputation and behavior reputation of the participants are linearly combined to obtain comprehensive reputation Z : ； In the formula, , Participants i Ability and reputation and behavioral reputation The scoring weight coefficient of .

3. According to a blockchain-based digital modeling collaborative management method according to claim 2, it is characterized by: The consensus reputation C The calculation formula is: ； In the formula, A is the consensus accuracy of the node participants, The adjustment parameters are accurately determined by consensus. A The calculation formula is: ； In the formula, r To submit the correct consensus transaction number, e The number of transactions with incorrect consensus submitted. n The number of consensus transactions that were refused to be submitted; The response reputation R The calculation formula is: ； In the formula, is the average transaction verification time of participants, For influence R The decreasing speed parameter of the function; Reputation for participation E The calculation formula is: ； In the formula, I is the number of times the participant was selected into the consensus group, W The number of times the participants collaborated.

4. According to a blockchain-based digital modeling collaborative management method according to claim 1, it is characterized by: The blockchain consensus further includes the following steps: The task request results broadcast by the collaborative participants are collected and packaged into blocks to be verified. The consensus group reaches a consensus on the blocks to be verified. The consensus is reached through the practical Byzantine fault tolerance algorithm. After obtaining more than two-thirds of the certifications, the block will become a legal block and be stored in each part of the blockchain.

5. According to a blockchain-based digital modeling collaborative management method according to claim 4, it is characterized by: The consensus is achieved through the practical Byzantine fault tolerance algorithm, including 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 signature, block content and number, and summary; After receiving the pre-prepare message, the secondary node verifies whether the summary and content of the block are valid: if the summary is valid, the secondary node will accept the pre-prepare message and proceed to the next stage; if the summary is invalid, the secondary node will reject the message; Preparation phase: In the pre-preparation phase, if each secondary node recognizes the pre-preparation message of the primary node, it will broadcast a preparation message to all other nodes. The preparation message includes the content of the pre-preparation message and the signature of the secondary node; Each node needs to collect more than two-thirds of the preparation messages to indicate that most nodes in the network have approved the block; at this point, the node confirms that the block has been widely accepted and enters the next stage.

6. According to a blockchain-based digital modeling collaborative management method according to claim 5, it is characterized by: The consensus through the practical Byzantine fault tolerance 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 is finally confirmed; Each node needs to collect more than two-thirds of the submission messages, indicating that most nodes have finalized the block; When a block is determined to be legitimate, all nodes will store the block in their local ledgers, and the status of the entire network will be updated synchronously, and the blockchain network will complete the consensus of this task request.

7. According to a blockchain-based digital modeling collaborative management method according to claim 1, it is characterized by: The digital modeling collaborative management method further comprises the steps of: Build a collaboration framework: Build an interoperability framework for digital modeling collaboration based on the alliance chain, which includes the participant 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 nodes of the Hyperledger blockchain, so that the participant BPMS and the Hyperledger blockchain can communicate through a standardized API; the Hyperledger blockchain is responsible for recording and managing transactions in the system, smart contract execution, collaboration records between participants, and auditing of business processes; Collaborative 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. The Peer node in the Fabric network verifies the identity of the participant BPMS, allocates a public and private key pair, and grants it initial credibility based on the participant BPMS's authentication information; Release the collaborative model: By executing all collaborative task requests, complete the digital modeling of the target task, and determine the final consensus model as the result of the modeling collaboration.

8. According to a blockchain-based digital modeling collaborative management method according to claim 1, it is characterized by: The smart contract includes the following rules: Node entry rules: All participants who join the collaborative blockchain as nodes must undergo identity verification and digital modeling capability assessment; Task request sharing rules: specify the access rights of different participants to digital model data. Matched collaborative participants have the rights 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 comprehensive reputation of the collaborating participants, participants who meet the number of consensus algorithms are selected to form a consensus group for consensus. The remaining collaborating participants do not participate in the consensus, but only receive messages from the consensus group to synchronize their own status.

9. A blockchain-based digital modeling collaborative management system, applied to a blockchain-based digital modeling collaborative management method as claimed in any one of claims 1 to 8, characterized in that: Including blockchain network management module, digital modeling module and smart contract management module; The blockchain network management module is used to build a digital modeling collaboration framework, authenticate and remove collaborative participants, and building a digital modeling collaboration framework includes the following steps: Identify the participants of digital modeling, who will use the BPMS system for business process management and share data through Hyperledger Fabric; design and deploy the business process management system, and define the business process of digital modeling through BPMS; Configure REST Server to convert the business requests generated by BPMS into a blockchain transaction format recognizable by Fabric and return the results to BPMS; Design according to the smart contract rules, deploy the smart contract to the Fabric network, call the smart contract functions through 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 consensus mechanism of Hyperledger Fabric.

10. A blockchain-based digital modeling collaborative management system according to claim 9, characterized in that: The digital modeling module is used for version control of the digital model, including model update, version rollback and query of historical models; The smart contract management module is used for the creation, deployment and execution of smart contracts. Each participant automatically processes collaborative tasks through smart contracts, including task allocation, resource sharing and data exchange of the model. At the same time, smart contracts automatically allocate tasks, set conditions for task completion, and monitor the progress of tasks of all parties.

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