Industrial Internet of Things node consensus method and system based on network topology heterogeneity
By adopting a consensus method based on network topology heterogeneity in the industrial Internet of Things, regional division and data transaction set construction are solved, the lightweight and low efficiency problems of traditional consensus algorithms in heterogeneous node environments are achieved, efficient data consensus and cross-regional data sharing are achieved, and the overall performance of the industrial Internet of Things is improved.
Patent Information
- Application Number
- CN202510547973.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-04-28
- Publication Date
- 2025-07-08
AI Technical Summary
In the industrial Internet of Things, traditional blockchain consensus algorithms have problems such as lightweight and low efficiency, especially in heterogeneous node environments, which are difficult to meet the needs of lightweight and efficient collaboration. The traditional centralized data management model is difficult to meet the requirements of large-scale and low latency, resulting in serious network congestion and data silos.
Using a consensus method based on network topology heterogeneity, we use regional division of the industrial Internet of Things, setting up main chain and sub-chain representative nodes, building global and regional data transaction sets, conducting parallel consensus on multiple transactions, and combining cross-chain data bidirectional anchoring mechanism to realize cross-regional data sharing and secure storage.
It improves the consensus processing capability and efficiency of the Industrial Internet of Things, reduces computing resource consumption, realizes the consistency and security of the whole network data sharing under heterogeneous networks, solves the problem of data silos, and improves the overall efficiency and data sharing capabilities of the Industrial Internet of Things.
Smart Images
Figure CN120281797A_ABST
Abstract
Description
Technical Field
[0001] The present invention belongs to the technical field of industrial Internet of things, and particularly relates to an industrial Internet of things node consensus method and system based on network topology heterogeneity. Background Art
[0002] The industrial revolution has always been an important driving force for the development of human society. Since the first industrial revolution significantly improved production efficiency by improving production methods, the subsequent second and third industrial revolutions have brought a qualitative leap in productivity. With the rapid development of information technology, the maturity of key technologies such as the Internet of things, big data, artificial intelligence, and cloud computing, and the proposal of Industry 4.0, automation and industrial connectivity have become the core forces driving the fourth industrial revolution. In this context, the Industrial Internet of Things (IIoT), as an important application branch of the Internet of things, has become one of the key technologies supporting Industry 4.0. By connecting various industrial devices, IIoT realizes information interaction, data sharing, and automated control between devices, and is widely used in fields such as intelligent manufacturing, intelligent logistics, and smart grids, becoming an important force in promoting the intelligent and digital transformation of traditional manufacturing industries.
[0003] However, although IIoT has made significant progress in aspects such as automated monitoring, fault diagnosis, and equipment maintenance in the production process, there are still many problems when facing challenges such as large-scale heterogeneous node collaboration, data security, and communication efficiency. First, there is a wide variety of devices in the IIoT network, with obvious performance differences. There are both high-performance computing nodes and low-performance nodes with limited resources, which complicates the requirements for data processing and transmission and makes it difficult to achieve efficient collaboration. Second, with the continuous increase in the number of devices, the traditional centralized data management and control mode is difficult to meet the requirements of large-scale and low latency. In a complex industrial environment, the communication overhead between a large number of devices increases significantly, resulting in network congestion and thus affecting the overall efficiency. In addition, the wide distribution of industrial devices involves multiple supply chains and enterprise entities, and the problems of cross-chain data sharing and system interoperability are gradually emerging. These problems not only inhibit data sharing and information circulation between enterprises and factories, forming "data islands", but also seriously restrict the further development of the industrial Internet of things.
[0004] As a decentralized consensus mechanism proposed by Satoshi Nakamoto in 2008, blockchain technology provides new security guarantees for distributed systems. It solves the common trust and security problems in traditional centralized systems. Even if some nodes exhibit malicious behavior, the entire system can still maintain consistency. In traditional blockchain consensus algorithms, the PoW (Proof of Work) algorithm competes to generate new blocks by having nodes perform complex calculations to reach a consensus, while the PoS (Proof of Stake) algorithm allows nodes with more stakes to have a higher probability of generating blocks by staking tokens. The common point of both is that they can effectively prevent tampering and attacks. In traditional blockchain technology, the core element for achieving peer-to-peer network consensus and transactions is the consistency consensus algorithm. However, for the consensus algorithm of traditional chain-style blockchains, to ensure the security and stability of blocks, the block generation speed is slow, the resource consumption is excessive, and the consensus efficiency is low. These problems all lead to the difficulty of applying blockchain in actual industrial fields. Facing these problems, the blockchain consensus algorithm based on the Directed Acyclic Graph (DAG) is more capable. Therefore, introducing DAG into the blockchain has begun to attract the attention of researchers. Blockchains or platforms such as IOTA, Hashgrpah, and Byteball all adopt consensus algorithms based on the DAG structure. Although the DAG consensus algorithm can significantly improve transaction throughput and reduce computing resource consumption, when applying the DAG consensus algorithm in the industrial Internet of Things environment, the following problems still exist: 1) Consensus lightweight problem: In the industrial Internet of Things, device nodes usually have different computing capabilities, communication bandwidths, and storage resources. Many industrial devices, especially small devices with low power consumption and low storage, have limited computing capabilities. Therefore, traditional consensus mechanisms such as PoW and PoS are too complex and resource-consuming, and the DAG-based consensus algorithm still has high requirements for network communication and node devices, unable to meet the lightweight requirements. 2) Low consensus efficiency problem: Blocks in traditional chain structures have serial verification, and the consensus efficiency of their consensus algorithms is low. Although the current DAG architecture can improve transaction concurrency, it often only focuses on the optimization of a single topological structure and lacks a comprehensive analysis of the device topological structure. Summary of the Invention
[0005] The purpose of the present invention is to provide an industrial Internet of Things node consensus method and system based on network topology heterogeneity.
[0006] In the first aspect, the present invention provides an industrial Internet of Things node consensus method based on network topology heterogeneity, which includes the following steps: Step 1: Divide the industrial Internet of Things into regions, and set the initial main-chain representative nodes and sub-chain representative nodes in each region, as well as the comprehensive evaluation values corresponding to the main-chain representative nodes and sub-chain representative nodes; Step 2: Collect transactions with different data characteristics through the main-chain representative node and the sub-chain representative node respectively to construct a global data transaction set and a regional data transaction set; Step 3: Use all nodes in the industrial Internet of Things to vote on all transactions in the data transaction set to obtain the number of votes for each transaction; select multiple transactions from the data transaction set according to the number of votes to construct a block to be consensus; the block to be consensus includes a main-chain block and a sub-chain block; the main-chain block is constructed according to the global data transaction set; the sub-chain block is constructed according to the regional data transaction set; Step 4: Obtain the association evaluation value between the block to be consensus and the already consensus block, and select the parent block of the block to be consensus from the already consensus blocks according to the association evaluation value, and verify the block to be consensus through the parent block. If the verification passes, connect the block to be consensus to the blockchain; among them, the sub-chain blocks form a regional sub-chain, and the main-chain blocks form a whole-network main chain; Step 5: Update the comprehensive evaluation value according to the votes of all nodes on the data transaction set in Step 3, and update the main-chain representative node and the sub-chain representative node in the region according to the updated comprehensive evaluation value; Step 6: Repeat Step 2 to Step 5 to complete node consensus in different time windows.
[0007] Preferably, the transaction data characteristics include regional data and global data.
[0008] Preferably, the process of the regional division is as follows: Randomly select multiple device nodes as root nodes; use the root nodes to broadcast regional division message packets, and according to the network structure of the root nodes, select the device nodes within the preset number of hops to form their respective regions. For the device nodes outside the preset number of hops that have not joined the region, respectively obtain the communication overheads between them and each root node; add the device nodes that have not joined the region to the region where the root node with the smallest communication overhead is located, and forward the regional division message packets to the neighboring device nodes that have not joined the region until all device nodes have completed the regional division.
[0009] Preferably, the communication overhead includes the communication delay, bandwidth and packet loss rate between the device node and the root node.
[0010] Preferably, the method for obtaining the association evaluation value is as follows: Among them, represents the association evaluation value of the block to be consensus k and the already consensus block j ; represents the number of data transactions of the same type included in the block to be consensus k and the already consensus block j ; Represents the block to be consensus k and the consensus block j contain the same number of parent transactions and ancestor transactions; Represents the number of transactions contained in the block to be consensus k and and represents the weight factor.
[0011] Preferably, in the fifth step, the number of times the full node is selected as the representative node is introduced to update the comprehensive evaluation value.
[0012] Preferably, the main chain block includes block number, block timestamp, block hash value, digital signature, number of transactions, parent block hash value, data sharing transaction list; the sub-chain block includes block number, block timestamp, transaction data characteristics, block hash value, digital signature, number of transactions and transaction data.
[0013] Preferably, in the first step, the comprehensive evaluation value is obtained according to the computing power score and storage score of the full node, the communication delay and communication bandwidth between the full node and the representative node, the network topology type and the path depth.
[0014] Preferably, the regional transaction includes node identifier, data characteristics, transaction timestamp, transaction data, data address, digital signature and transaction hash value.
[0015] In a second aspect, the present invention provides an industrial Internet of Things node consensus system based on network topology heterogeneity, which is used to execute the above-mentioned industrial Internet of Things node consensus method; the industrial Internet of Things node consensus system includes a device layer, an edge layer, a network layer, a consensus layer and an application layer; the device layer is used to generate data and input the generated data into the edge layer for preprocessing; the network layer is used to perform regional division and block construction; the consensus layer is used to achieve consensus operations between different blocks and input the consensus result into the application layer for industrial applications.
[0016] The beneficial effects of the present invention are: 1. By merging data transactions to form a transaction set, designing sub-chain blocks and main-chain blocks based on the transaction set, and conducting sub-chain block and main-chain block consensus according to the divided regions, the present invention realizes multi-transaction parallel consensus, improves the processing ability and consensus efficiency of transactions, and reduces the consumption of computing resources in the industrial Internet of Things consensus process.
[0017] 2. In view of the different network topology characteristics of the industrial Internet of Things, such as tree topology, mesh topology, and hybrid topology, the present invention proposes a regional division method, constructs main-chain blocks and sub-chain blocks based on different regions to control the scale of regional consensus nodes, and improves the consensus efficiency. At the same time, through the cross-chain data two-way anchoring mechanism, the present invention realizes the consensus of the data sharing and trading process of inventory, orders, etc. across regions in the industrial Internet of Things environment, thereby realizing the consistency and security of the whole network data sharing.
[0018] 3. Based on the data communication-related transaction set information between the main chain and sub-chains and multiple sub-chains, the present invention realizes the secure storage and leakage traceability of the records of data sharing within and between factories. At the same time, according to the communication status and physical status such as the network topology structure, node communication delay, communication bandwidth, computing power, and storage status in the region, the present invention proposes a representative node election mechanism under heterogeneous topology structures to select a suitable candidate set and representative nodes of representative nodes. BRIEF DESCRIPTION OF THE DRAWINGS
[0019] Figure 1 It is a schematic diagram of the industrial Internet of Things node consensus system in the present invention.
[0020] Figure 2 It is the overall flowchart of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS
[0021] The present invention will be further described below with reference to the accompanying drawings.
[0022] As Figure 1 shown, an industrial Internet of Things node consensus method based on heterogeneous network topology, and the industrial Internet of Things node consensus system adopted includes a device layer, an edge layer, a network layer, a consensus layer, and an application layer. The device layer is used to generate data and input the generated data into the edge layer for preprocessing; the network layer is used for regional division and block construction; the consensus layer is used to implement the consensus operation between different blocks and input the consensus result into the application layer for industrial applications.
[0023] The industrial Internet of Things node consensus method includes the following steps: Step 1. Regional division According to the heterogeneity of different network topologies, the network topology of the industrial Internet of Things is divided into three types, namely tree topology, mesh topology, and hybrid topology. According to the number of devices in the device layer E and the heterogeneous network topology, the industrial network is divided into multiple regions, and the process is as follows: If , it is considered that the current industrial network is a small network; if , it is considered that the current industrial network is a large network; where is the device threshold. Since a small network adopts a single topology structure of tree topology or mesh topology, and all devices are located in the same topological area, the small network is divided into one area. Since a large network adopts a combination of single network topology and hybrid network topology, and the engineering devices are complex and diverse, in the large network, each device is used as a device node in the factory network, and multiple device nodes are randomly selected as master server nodes (root nodes) within each topological area; the root nodes broadcast area division message packets, and according to the network structure of the root nodes, select N the device nodes within 1 hop count to form their respective areas, N where 1 is the node range that can be reached at most by forwarding through network relay nodes starting from the root node N once; if there are device nodes within 1 hop count of different root nodes, N calculate the communication overhead between the device node and different root nodes respectively, and add it to the area corresponding to the root node with the smaller communication overhead. For device nodes outside 1 hop count that have not joined the area, obtain the communication overhead between them and each root node N respectively, add it to the area where the root node with the smallest communication overhead is located, and forward the broadcast area division message packet to the device nodes in the neighboring unjoined areas until all device nodes have completed area division. The expression of the communication overhead is: (1) where, represents the weight of the communication overhead factor between the device node that has not joined the area i and the root node j ; represents the communication delay between the device node that has not joined the area i and the root node j ; represents the bandwidth between the device node that has not joined the area i and the root node j ; represents the packet loss rate between the device node that has not joined the area i and the root node j .
[0024] If there are new nodes joining the network, the new nodes broadcast and send area division request packets, and the device nodes (surrounding nodes) that receive the area division request packets send area division message packets to the new nodes; obtain the communication overhead between the new nodes and the surrounding nodes, and add the new nodes to the area where the surrounding node with the smallest communication overhead is located.
[0025] Step 2: Construct area transactions Area transactions include node identifiers , Data characteristics features , Transaction timestamp , Transaction data , Data address , Digital signature and transaction hash value . The node identifier is the unique identifier of the device node when joining the industrial Internet of Things. Data characteristics are used to classify transaction data into regional data and global data and construct different data transaction sets; regional data refers to data with low latency requirements generated and used inside a factory or production facility, such as sensor data of industrial equipment, status monitoring of production lines, and sensor data such as temperature, pressure, and vibration of machines; global data refers to data that needs to be shared across multiple regions or the entire supply chain, which can be shared across regions, including data such as production capacity of each production factory, raw material inventory, and finished product inventory; the data characteristic label of regional data is set as A, and the data characteristic label of global data is G. The transaction timestamp is the time point when the transaction is initiated. Transaction data includes device status values, product quantities, and inventory information. The data address is the physical address where the transaction data is stored in the gateway. The digital signature is bundled with the transaction data. Once the transaction data is tampered with, the signature verification will fail, which can prevent the tampering of transaction data. The transaction hash value is the unique identifier of the transaction and can be used as the verification basis for data integrity. After the consensus transaction is established, the hash value will be updated to be used as a record for transaction tracing.
[0026] Step 3: Divide all device nodes into light nodes and full nodes. Light nodes can propose transactions but do not participate in the consensus process; full nodes can participate in the consensus process. When the regional segmentation time interval reaches the preset threshold ε 1, in all regions, randomly select two full nodes around network core nodes such as servers and gateways as the initial representative nodes, namely the main chain representative node and the sub-chain representative node; the representative nodes are based on the communication status and physical status of the full nodes such as communication latency, communication bandwidth, computing power, and storage; divide the full nodes in the region into two parts according to the data characteristics, and calculate the initial comprehensive evaluation value corresponding to such representative nodes according to the main chain representative node and the sub-chain representative node respectively , and its expression is as follows: (2) where, represents the full node and the representative node r 's communication latency; represents the full node and the representative node r 's communication bandwidth; represents the computing power score of the full node ; represents the full node The storage score of Represents a full node i The number of levels in the tree topology; Represents the average number of hops to other nodes in the network; Indicates area i The network topology in is tree-shaped. Indicates area i The network topology in is other types; is the communication delay weight of all nodes; is the communication bandwidth weight of the whole node; is the computing power weight of the full node; Store score weights for full nodes.
[0027] Step 4: Collect transactions with different data characteristics through the main chain representative node and the sub-chain representative node respectively; when the transaction collection time interval reaches the preset threshold ε 2. After that, when the device node publishes the data transaction, it broadcasts it to the other full nodes in the area. The representative nodes in the area collect transactions with the same data characteristics according to the data characteristics, package them, obtain data transaction sets with different data characteristics, and broadcast them to all full nodes in the area; the sub-chain representative nodes collect transactions with data characteristics of regional data to form a regional data transaction set; the main chain representative nodes collect transactions with data characteristics of global data to form a global data transaction set; the transactions in the data transaction set are arranged in the order of the time when the full nodes receive the transactions; if there is a conflict in the transaction data of different transactions in the data transaction set, the transactions with later timestamps in the data transaction set are removed.
[0028] When a full node receives a data transaction set, it compares the transaction data in the data transaction set with its own historical transaction data. If there is no conflict between the two, it will vote in favor, otherwise it will vote against and feedback to its corresponding representative node. The representative node obtains the transaction based on its own status credit weight. Number of votes , whose expression is: (3) in, Represents a full node voting weight; Represents a full node For transactions If you vote in favor, it means you accept the data transaction. , otherwise the transaction is rejected. ; m is the number of full nodes.
[0029] Compare the number of votes for different transactions with the voting threshold For comparison, if , then the transaction is confirmed and passed; among them, ; represents the threshold parameter. The representative node retains the transactions in the data transaction set that are confirmed and passed, forming a set of verified transactions. The transactions that are not confirmed will be retained in the next time window for continued confirmation. Transactions that cannot be confirmed within the n round time window will be cancelled.
[0030] Step Five: Construct the regional block Pack the set of verified transactions into a regional block (block to be consensus) in the state of waiting for consensus; the regional block includes the main chain block and the sub-chain block; the main chain block is composed of the global data transaction set; the sub-chain block is composed of the regional data transaction set. The main chain block includes the block number R_id, block timestamp R_timestamp, block hash value R_hash, digital signature R_signture, number of transactions TS_number, hash value of the parent block B_fhash, and data sharing transaction list. The sub-chain block includes the block number N_id, block timestamp B_timestamp, transaction data characteristics (A / G), block hash value B_hash, digital signature B_signture, number of transactions T_number, and transaction data Tran_set. The block number is a logical identifier assigned by the system to identify the generation order of the block; the block timestamp identifies the time point when the block is constructed; the block hash value is calculated from the hash value of the block header information and the transaction information collected in the block, and is the unique identifier of the block; the block header information includes the block timestamp, hash value of the parent block, and block digital signature; the digital signature is the signature of the representative node that packs the block, used to verify the legality of the block; the number of transactions is the number of transactions in the transaction set within the time window. When the transaction load is too high, the time window can be shortened , otherwise the time window is extended ; the hash value of the parent block is the updated new hash value after referring to the hash value of the parent block to ensure the order of the blocks; the data sharing transaction list includes the hash value of the transaction, the transaction data address, the IDs of the two parties to the transaction, and the transaction time.
[0031] Step Six: Consensus stage Based on the network topology, obtain the correlation evaluation value of the transaction information between the block to be consensus and the consensus block through the representative node , to evaluate the correlation with the consensus block, and its expression is: (4) Among them, represents the correlation evaluation value of the block to be consensus k and the consensus block j ; Indicates the block to be consensus k and the number of data transactions of the same type included in the consensus block j ; Indicates the block to be consensus k and the number of the same parent transactions and ancestor transactions included in the consensus block j ; Indicates the number of transactions included in the block to be consensus k in, and Indicates the weight factor
[0032] If the associated evaluation value exceeds the preset threshold , then the consensus block j is used as the parent block of the block to be consensus k , and a virtual connection is established to achieve virtual chain-up. The representative node of the block to be consensus broadcasts a submission request to the parent node (the full node in the parent block), requesting the parent node to verify the validity of the block to be consensus. After each parent node receives the request, it verifies the block header information of the block to be consensus and returns a verification message. When the number of parent nodes that pass the verification reaches more than 2 / 3 of the total number of parent nodes, it indicates that the block has passed the consensus verification. The dotted connection between the block to be consensus and the consensus block that passes the verification will be converted into a solid line, indicating that the block has successfully chained up and the consensus process is completed
[0033] In this embodiment, the sub-chain blocks form a regional sub-chain, and the main-chain blocks form a whole-network main chain
[0034] Step Seven: Update the representative node According to the voting situation of the full nodes on the data transaction set, recalculate the comprehensive evaluation value of the full nodes in the region , which is expressed as follows (5) Among them, indicates the number of approval votes cast by the full node within the time window indicates the number of opposition votes cast by the full node within the time window indicates the weight parameter
[0035] To avoid a single representative node serving as the representative node too many times continuously, update the comprehensive evaluation value of the full node according to the number of times the full node is selected as the representative node . The updated comprehensive evaluation value is expressed as follows (6) Among them, Indicates the maximum threshold.
[0036] When the number of times all full nodes are selected as representative nodes is greater than or equal to the maximum threshold Then, the number of times all full nodes are selected as representative nodes is reset to 0. The comprehensive evaluation values of the full nodes are sorted in descending order, and the full nodes corresponding to the top 30% of the comprehensive evaluation values are selected to form a candidate set of representative nodes. A full node is randomly selected from the candidate set of representative nodes as the representative node to participate in the subsequent efficient consensus.
[0037] If a device node sends a cross-chain data sharing request to the representative node in the corresponding area, then a two-way cross-chain data anchoring based on the main-chain DAG is performed to achieve data sharing between the main chain and sub-chains, and between sub-chains. The method for two-way cross-chain data anchoring based on the main-chain DAG is as follows: 7-1. The device nodes within the area send the transaction data requirements M to the representative node in this area, which is defined as follows: (7) Among them, source_chain represents the sending chain identifier; target_chain represents the target chain identifier of the message, timestamp represents the timestamp when the message is generated, payload represents the specific content of the cross-chain transaction, proof represents the validity proof of the transaction, that is , represents the private key signature operation of the initiating node, represents the data M hash value.
[0038] 7-2. The representative node queries the target block according to the sorting of the area identifiers and timestamps in all blocks T target , that is (8) Among them, Query represents the query function initiated in the main-chain block; DAG represents the main-chain block; represents the target sub-chain block; represents the target transaction hash value; A target represents the target transaction address.
[0039] 7-3. Through the transaction data hash value and transaction data address obtained from the target block, the cross-regional nodes obtain the transaction data through the following operations: (9) Among them, Represents specific transaction data, Access Represents the acquisition function of transaction data, DAG_part Represents the identifier of the region.
[0040] 7-4. Cross-regional nodes obtain specific transaction data After that, for the hash value of the obtained transaction data Compare it with the hash value stored in the DAG, and pass The verification function verifies whether the transaction data conforms to the formula rules within the region to ensure the legality of cross-chain data. If the verification fails, repeat the above process until the verification passes, complete the two-way anchoring of cross-chain data, and record the relevant data transaction process through the main chain block consensus, so as to achieve trusted data sharing.
[0041] Step Eight: Repeat Steps Four to Seven to complete the consensus of device nodes at different time periods.
[0042] The above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Other modifications or equivalent replacements made by those of ordinary skill in the art to the technical solutions of the present invention shall be covered within the scope of the claims of the present invention as long as they do not depart from the spirit and scope of the technical solutions of the present invention.
Claims
1. An industrial Internet of Things node consensus method based on network topology heterogeneity, characterized in that: It includes the following steps: Step 1: Divide the industrial Internet of things into regions, and set the initial main-chain representative nodes and sub-chain representative nodes in each region, as well as the comprehensive evaluation values corresponding to the main-chain representative nodes and sub-chain representative nodes; Step 2: Collect transactions with different data characteristics through the main-chain representative nodes and sub-chain representative nodes respectively to construct a global data transaction set and a regional data transaction set; Step 3: Use all nodes in the industrial Internet of things to vote on all transactions in the data transaction set to obtain the number of votes for each transaction; select multiple transactions from the data transaction set according to the number of votes to construct a block to be consensus; the block to be consensus includes a main-chain block and a sub-chain block; the main-chain block is constructed according to the global data transaction set; the sub-chain block is constructed according to the regional data transaction set; Step 4: Obtain the association evaluation value between the block to be consensus and the already consensus block, and select the parent block of the block to be consensus from the already consensus blocks according to the association evaluation value, and verify the block to be consensus through the parent block. If the verification passes, connect the block to be consensus to the blockchain; among them, the sub-chain blocks form a regional sub-chain, and the main-chain blocks form a global main-chain of the whole network; Step 5: Update the comprehensive evaluation value according to the votes of all nodes on the data transaction set in Step 3, and update the main-chain representative nodes and sub-chain representative nodes in the region according to the updated comprehensive evaluation value; Step 6: Repeat Steps 2 to 5 to complete node consensus in different time windows.
2. The industrial Internet of Things node consensus method based on network topology heterogeneity according to claim 1, wherein: The transaction data characteristics include regional data and global data.
3. A consensus method for industrial Internet of Things nodes based on network topology heterogeneity according to claim 1, characterized in that: The process of the above-mentioned regional division is as follows: Randomly select multiple device nodes as root nodes; use the root nodes to broadcast regional division message packets, and according to the network structure of the root nodes, select device nodes within a preset number of hops to form their respective regions. For device nodes outside the preset number of hops that have not joined the region, obtain the communication overhead between them and each root node respectively; add the device nodes that have not joined the region to the region where the root node with the smallest communication overhead is located, and forward the regional division message packets to neighboring device nodes that have not joined the region until all device nodes have completed regional division.
4. A consensus method for industrial Internet of Things nodes based on network topology heterogeneity according to claim 3, characterized in that: The above-mentioned communication overhead includes the communication delay, bandwidth, and packet loss rate between the device node and the root node.
5. A consensus method for industrial Internet of Things nodes based on network topology heterogeneity according to claim 1, characterized in that: The method for obtaining the above-mentioned association evaluation value is as follows: Among them, represents the associated evaluation value of the block to be consensus and the consensus block; k and j the consensus block represents the number of data transactions of the same type included in the block to be consensus k and j the consensus block; represents the number of the same parent transactions and ancestor transactions included in the block to be consensus k and j the consensus block; represents the number of transactions included in the block to be consensus k and represents the weight factor. 6. The industrial Internet of Things node consensus method based on network topology heterogeneity according to claim 1, characterized in that: In Step 5 above, introduce the number of times all nodes are selected as representative nodes to update the comprehensive evaluation value.
7. A consensus method for industrial Internet of Things nodes based on network topology heterogeneity according to claim 1, characterized in that: The main-chain block includes a block number, a block timestamp, a block hash value, a digital signature, the number of transactions, the hash value of the parent block, and a data sharing transaction list; the sub-chain block includes a block number, a block timestamp, transaction data characteristics, a block hash value, a digital signature, the number of transactions, and transaction data.
8. A consensus method for industrial Internet of Things nodes based on network topology heterogeneity according to claim 1, characterized in that: In Step 1 above, the comprehensive evaluation value is obtained according to the computing power score and storage score of all nodes, the communication delay and communication bandwidth between all nodes and representative nodes, the network topology type, and the path depth.
9. A consensus method for industrial Internet of Things nodes based on network topology heterogeneity according to claim 1, characterized in that: The above-mentioned regional transaction includes a node identifier, data characteristics, a transaction timestamp, transaction data, a data address, a digital signature, and a transaction hash value.
10. An industrial Internet of Things node consensus system based on network topology heterogeneity, characterized in that: For implementing the industrial Internet of Things node consensus method described in claim 1; the industrial Internet of Things node consensus system includes a device layer, an edge layer, a network layer, a consensus layer, and an application layer; the device layer is used to generate data and input the generated data into the edge layer for preprocessing; the network layer is used to perform regional division and block construction; the consensus layer is used to achieve consensus operations between different blocks and input the consensus result into the application layer for industrial applications.