A Parallel Sharding and Hybrid Consensus Method Based on Intelligent Trust Coding

Abstract

This invention belongs to the field of blockchain consensus and distributed system technology. The intelligent trust encoding is a global subject-object intelligent trust encoding method in the construction method of the universal isomorphic root carrier, generated by the encoding module of the intelligent trust encoding component. This invention reuses atomic operation modules, achieves conflict-free parallel sharding mapping based on encoding classification bits through native bit operations, adopts a collaborative-isolated dynamic scheduling rule, integrates layered hybrid consensus and cross-shard cross-verification mechanisms, and links distributed transaction, value accounting, and trusted data space access modules, while also linking encoding verification, anomaly handling, and state update modules. This invention improves processing capabilities through fully parallel sharding, reduces cross-shard overhead through collaborative scheduling, blocks risk propagation through isolated scheduling, balances efficiency and fault tolerance through hybrid consensus, and ensures load balancing through zero-skew sharding. Compared with traditional sharding architectures, this invention achieves significantly improved overall performance, effectively solving technical pain points such as sharding skew, resource inefficiency, consensus bottlenecks, and anomaly propagation. It is suitable for high-concurrency, high-reliability, and high-compliance distributed consensus scenarios in enterprise-level consortium blockchains, supporting full lifecycle management of heterogeneous subjects and objects across the entire domain, forming a complete technical closed loop.

Description

Technical Field

[0001] This invention belongs to the technical fields of blockchain underlying architecture, distributed parallel processing, dynamic resource scheduling and distributed transaction collaboration. Specifically, it relates to a parallel sharding and hybrid consensus method based on intelligent trust coding, which is used to provide high-performance and highly reliable consensus support for the upper-layer root carrier management system. Background Technology

[0002] With the large-scale implementation of the digital economy, trusted data spaces, and consortium blockchains, the number of entities across the entire domain is growing at a scale of tens of billions. The upper-level root carrier management system lays the underlying foundation for the unified management of entities across the entire domain, and the underlying intelligent credit coding technology provides the unified identification capability for entities across the entire domain. However, existing blockchain sharding and consensus technologies have the following technical defects: Traditional partitioning has insufficient parallelism and low processing efficiency, which cannot support the needs of batch accounting of subjects and objects across the entire domain and high-concurrency cross-domain processing scenarios. Using hash mapping or manual mapping to allocate fragments can easily lead to fragment load imbalance and uneven resource allocation, making it impossible to utilize the native fragment mapping capability of the classification bits in the intelligent coding. The lack of dynamic coordination and isolation scheduling mechanisms results in high overhead for cross-shard interactions and easy fault propagation, making it unsuitable for the needs of multi-scenario and multi-level subject-object management; a single consensus mechanism has the problem of balancing efficiency and security, and cannot meet the requirements of high reliability and high compliance management. The overall technical system is fragmented because it cannot achieve full-link collaboration with the upper-level root carrier control system, multi-dimensional value accounting, distributed transactions, and underlying intelligent information coding, encoding and decoding methods, and batch processing logic.

[0003] This invention achieves parallel sharding and load balancing based on the classification bit operation mapping of intelligent information coding. It optimizes resource allocation and risk control through dynamic collaboration and isolation scheduling. It balances efficiency and fault tolerance with hybrid consensus. The overall performance is significantly improved compared with the traditional sharding architecture. It can be adapted to the upper-layer root carrier management system and the lower-layer intelligent information coding technology system to achieve full-link collaborative management and control.

[0004] Intelligent Information Encoding: The unified intelligent information encoding of the whole domain subject and object adopts a fixed hierarchical structure, which includes at least a classification bit, a subject bit, a same value distinguishing bit and a check bit. After the base conversion, it forms a globally unique identifier, which has constant-level ultra-fast traceability capability and is the core basis of the fragment mapping of this invention. 1. Parallel sharding: Multiple independent parallel sharding queues are directly mapped based on the value range of the intelligent information coding classification bits. The mapping is achieved by the underlying atomic operation module through the native bit operation of the CPU, realizing the whole input and output of transaction data. The sharding skew rate is zero, which is suitable for the batch management needs of massive subjects and objects. 2. Collaborative Scheduling: Designed based on the requirements of upper-layer subject-object management scenarios, it realizes resource complementarity, route optimization, and computing power collaboration between shards, reduces cross-shard interaction latency, and supports cross-domain subject-object flow; 3. Isolation and scheduling: Designed for subjects and objects with different risk levels, it realizes risk isolation, permission isolation, and fault decoupling between fragments, blocks the transmission of anomalies, and ensures the security of core data; 4. Hybrid consensus: Combining the advantages of election consensus and fault-tolerant consensus, it realizes council node election, parallel consensus within shards and cross-shard cross-verification, adapting to the consensus requirements of high reliability and high concurrency; 5. Distributed Transactions: A three-stage transaction control mechanism ensures the atomicity of cross-shard transactions and supports the compliance of subject-object transfers; 6. Atomic Operation Module: The underlying core module, used to perform CPU native bitwise operations, number system conversion, and parallel sharding index mapping. It is the core technical support for the sharding mapping of this invention. Summary of the Invention

[0005] I. Purpose of the Invention This invention aims to construct an integrated method for parallel sharding, dynamic scheduling, and hybrid consensus based on the upper-layer root carrier management system and the lower-layer intelligent information coding technology. This method addresses the technical problems of sharding bias, insufficient parallel capabilities, low scheduling efficiency, and imbalance between consensus efficiency and fault tolerance in existing technologies. It achieves end-to-end collaboration with the upper-layer root carrier, distributed transactions, multi-dimensional value accounting, blockchain notarization, trusted data space, and the lower-layer intelligent information coding, encoding and decoding methods, atomic operation modules, and batch processing logic. This supports high-concurrency, high-reliability, and high-compliance management of heterogeneous subjects and objects throughout their entire lifecycle.

[0006] Technical solution The overall technical solution of this invention is as follows: Intelligent information encoding parsing → Classification bitwise operations → Parallel sharding mapping → Dynamic collaboration and isolation scheduling → Council node election → Parallel consensus within shards → Cross-shard cross-verification → Consensus confirmation or anomaly rollback → Upper-layer system collaboration: 1. Intelligent Information Encoding Parsing and Parallel Slicing Mapping It follows the fixed hierarchical structure of the intelligent coding system, including classification bits, subject bits, same-value differentiation bits, and check bits; it reuses the underlying atomic operation module and sharding index calculation logic, and quickly calculates the sharding index through native CPU bit operations, directly mapping it to multiple independent parallel shards; all sharding queues run in full parallel, and transaction data and batch accounting data related to subjects and objects are integrated and not split, ensuring that the sharding skew rate is zero, and adapting to massive subject and object batch management scenarios; 2. Dynamic coordination and isolated scheduling Collaborative scheduling: For cross-domain subject-object transfer and batch accounting scenarios, it links the underlying encoding and parsing logic to achieve direct connection of the same business shards and support of low-load shards by high-computing-power shards, thereby reducing cross-shard interaction latency and improving resource utilization. Isolation and scheduling: Physical isolation is implemented for high-risk subjects and objects and core accounting segments. Combined with the permission marking function in the intelligent information coding classification bit, the abnormal transmission rate is reduced and the control security is ensured. The scheduling process is linked in real time with the behavior control field module of the upper root carrier to obtain the scheduling strategy configuration, and at the same time synchronize the underlying encoding parsing results to ensure that the scheduling logic is consistent with the subject and object control requirements and encoding rules. 3. Election of Council Member Nodes Each shard corresponds to a council node. The election rules combine the upper-layer subject-object reputation evaluation logic with reference to the node permission information bound by the lower-layer code. The election is conducted in groups based on node reputation, online rate, computing power, and staking amount, and is rotated regularly to prevent malicious behavior by nodes and ensure the credibility of consensus. 4. Parallel consensus within shards Verification nodes are grouped into shards, and each group of nodes executes a three-phase consensus process; consensus is completed for that shard once the consensus conditions are met within the group, significantly shortening the consensus time and meeting the real-time requirements of high-concurrency subject-object transfer and batch accounting. 5. Cross-shard cross-validation and final confirmation For cross-domain and cross-shard subject-object transactions, the council nodes of each shard involved in the transaction perform bidirectional cross-verification. The verification content includes: consistency of the intelligent trust code and compliance of the ownership of the subject and object. If all shard verifications pass, the final consensus confirmation is completed. If any shard verification fails, the distributed transaction rollback process is immediately triggered to ensure the atomicity of the transaction and to simultaneously link the underlying code anomaly marking function. 6. Fault tolerance and global rollback The consensus system can withstand a certain percentage of malicious node attacks. When abnormal situations such as abnormal coding mapping, malicious node behavior, failure to meet consensus standards, or mismatch between subject and object rights occur, the consensus process is automatically terminated, a global rollback is executed, and the upper-layer transaction rollback and accounting reset mechanism and the lower-layer coding anomaly handling mechanism are triggered simultaneously to ensure data consistency. 7. Upper-level system collaboration After consensus is confirmed, the upper-layer distributed transaction confirmation process, multi-dimensional value accounting layer, blockchain evidence storage module, and trusted data space connector are linked synchronously. At the same time, the underlying encoding status update module is synchronized to mark the consensus status corresponding to the intelligent trust encoding, forming a closed loop of the entire chain of "encoding parsing - sharding mapping - consensus verification - control and evidence storage". Beneficial effects

[0007] Compared with the prior art, the present invention has the following beneficial effects: 1. Ultra-high parallel processing capability: The parallel sharding architecture significantly improves the overall performance compared to the traditional sharding architecture, greatly enhances the concurrent processing capability, and can support batch accounting of massive subjects and objects across the entire domain and cross-domain high-concurrency processing scenarios; 2. Zero Sharding Skew: Based on the native bit operation mapping of the intelligent information coding classification bits, absolute sharding load balance is achieved, solving the problem of uneven load in traditional mapping methods; 3. Intelligent scheduling optimization: Collaborative scheduling reduces cross-shard latency, isolated scheduling blocks the propagation of anomalies, significantly improves stability, and adapts to the needs of multi-scenario and multi-level subject-object management; 4. Balancing high efficiency and high fault tolerance: Transaction confirmation delays are significantly reduced, consensus time is significantly shortened, and it can resist attacks from a certain proportion of malicious nodes, balancing efficiency and fault tolerance to meet the consensus requirements of high credibility and high compliance. 5. Seamless integration across the entire system: It seamlessly connects with the upper-level root carrier, distributed transactions, multi-dimensional value accounting, blockchain notarization, and trusted data space, while linking with the underlying atomic operations, encoding verification, batch processing, and exception handling modules to achieve deep collaboration across the entire chain. Attached Figure Description

[0008] Figure 1 This is a diagram illustrating the overall architecture of parallel sharding, dynamic scheduling, and hybrid consensus. Figure 2 This is a flowchart of the parallel partitioning mapping and dynamic scheduling process; Figure 3 This is for parallel consensus and cross-shard verification graphs.

[0009] 200 - Encoding and parsing layer; 201 - Parallel sharding mapping layer; 202 - Dynamic coordination and isolation scheduling layer; 203 - Council node election layer; 204 - Parallel consensus layer; 205 - Cross-sharding cross-verification layer; 206 - Exception tolerance and rollback layer; 207 - Upper-layer system coordination layer. Detailed Implementation

[0010] The present invention will be further described in detail below with reference to specific embodiments: 1. Multiple asset data are generated into intelligent credit codes through the underlying coding component. The atomic operation module calculates the shard index through CPU bitwise operations and maps it to each parallel shard. Cooperative scheduling is initiated. Based on the scheduling strategy in the upper-layer behavior control field module and the underlying coding parsing results, direct connection to shards of the same business is achieved without redundant routing overhead. Corresponding council nodes for each shard are elected. The node trustworthiness is ensured by combining the upper-layer asset entity reputation evaluation logic with the node permission information bound to the underlying coding. Parallel consensus within each shard is completed quickly. This is a batch calculation with no cross-shard transactions. After all shard consensus is completed, it is directly confirmed. After consensus confirmation, the upper-layer distributed transaction confirmation process is linked, and the multi-dimensional value accounting layer is triggered to execute batch calculation. The calculation results are written to the upper-layer root carrier value accounting field module and synchronized to the blockchain for notarization. At the same time, the underlying coding status update module is synchronized to mark the consensus completion status of this batch of intelligent credit codes. 2. The intelligent credit codes of high-risk transaction subjects and objects are generated by the underlying coding component, with classification bits marking permission information, and mapped to independent shards through the atomic operation module. Isolation scheduling is initiated, and based on the risk level configuration in the upper-layer behavior control field module, combined with the permission markings in the underlying code, the shard is physically isolated from the core accounting shard. Hybrid consensus is executed normally; high-risk transactions complete consensus within the isolated shard, and the risk is not transmitted to the core shard. Simultaneously, the underlying coding verification module is linked to verify the consistency of the intelligent credit codes in real time. After the transaction is completed, the isolation state is lifted, and the consensus result is synchronized to the upper-layer compliance and evidence storage field module to complete on-chain evidence storage. At the same time, the underlying coding status update module is synchronized to mark the transaction completion status of the intelligent credit codes corresponding to the transaction. 3. When cross-domain transaction subjects and objects enter parallel sharding, their intelligent information codes are generated by the underlying encoding components and mapped to the corresponding shards through atomic operation modules; Cooperative scheduling optimizes routing by combining upper-layer trusted data space access logic with lower-layer cross-domain encoding adaptation rules to reduce cross-shard latency; Each shard involved executes parallel consensus, and upon completion, performs cross-shard bidirectional cross-verification. The verification content includes the consistency of the smart trust code and the compliance of the ownership of the subject and object. After the verification passes, the distributed transaction ensures the atomicity of the transaction, and the consensus log and transaction certificate are synchronously written to the compliance storage field module of the upper root carrier to complete on-chain storage and realize the trusted circulation of cross-domain transactions. At the same time, the underlying encoding status update module is synchronized to mark the circulation status of the smart trust code corresponding to the cross-domain transaction.

Claims

1. A parallel sharding and hybrid consensus method based on intelligent trust coding, characterized in that, The intelligent information coding is a global subject-object intelligent information coding system within the upper-level root carrier control system. It is generated by the lower-level coding components, adopts a fixed hierarchical structure, and includes at least a classification bit, an entity bit, a same-value distinguishing bit, and a check bit. The method... Includes the following steps: The first step, intelligent encoding parsing: Based on the fixed hierarchical structure, the sharding index is calculated using native CPU bitwise operations; The second step is parallel sharding mapping: mapping the sharding index to multiple independent parallel sharding queues, with the subject and object related data being fully input and output and processed with zero skew. The third step is dynamic collaboration and isolation scheduling: collaborative scheduling is performed to achieve complementary resources in the shards, optimal routing, and collaborative computing power; isolation scheduling is performed to achieve risk isolation, permission isolation, and fault decoupling; the scheduling logic is linked to the behavior control field module of the upper root carrier and synchronously references the permission marking information of the underlying code. The fourth step is the election of council nodes: council nodes are elected in groups based on node reputation, online rate, computing power, and pledged amount, and the election is rotated regularly. The election rules are adapted to the upper-level subject-object reputation evaluation logic and the lower-level code permission marking logic. Step 5, Parallel consensus within shards: Verification nodes execute the three-phase consensus process according to shard groups. Shard consensus is completed when the consensus conditions are met within a group. Step 6, Cross-shard cross-verification: Cross-shard transactions are subject to bidirectional verification by the corresponding shard nodes. The verification includes the consistency of the smart credit code and the compliance of the ownership of the subject and object. Step 7, Fault Tolerance and Global Rollback: If an anomaly occurs in any step, the process is immediately terminated, consensus rollback is executed, and the upper-layer distributed transaction rollback and accounting reset mechanism and the lower-layer coding anomaly handling mechanism are triggered. Step 8, Upper-layer system collaboration: After consensus confirmation, the system is synchronized to the upper-layer distributed transaction, multi-dimensional value accounting layer, blockchain evidence storage module, and trusted data space connector, while simultaneously synchronizing the underlying encoding status update module to form a closed-loop end-to-end system.

2. The method according to claim 1, characterized in that, The sharding index is obtained by calculating the classification bits of the intelligent information encoding through native CPU bit operations; the parallel sharding achieves a significant improvement in overall performance compared to the traditional sharding architecture, with a sharding skew rate of zero, and is suitable for the needs of batch management of massive subjects and objects and the underlying batch encoding processing logic.

3. The method according to claim 1, characterized in that, The collaborative scheduling achieves complementary sharded resources, optimized routing, and collaborative computing power, significantly reducing cross-shard latency; the isolated scheduling achieves risk isolation, permission isolation, and fault decoupling, significantly reducing the anomaly propagation rate. The scheduling process is linked to the scheduling strategy configuration of the upper-layer root carrier behavior control field module and synchronously references the permission marking information of the underlying encoding.

4. The method according to claim 1, characterized in that, The hybrid consensus can resist attacks from a certain proportion of malicious nodes, significantly reduces transaction confirmation delays, and the parallel consensus significantly shortens consensus time, meeting the requirements for high concurrency and high reliability consensus.

5. The method according to claim 1, characterized in that, The parallel sharding resource utilization rate remains at a high level, and the batch accounting data related to the upper-layer subject and object is not split or scattered, ensuring data integrity and coordinating with the underlying batch processing logic.

6. The method according to claim 1, characterized in that, After the final consensus is confirmed, the upper-layer distributed transaction confirmation process is executed in conjunction with the calculation results, which are synchronized to the upper-layer root carrier value calculation field module. Blockchain notarization is completed, supporting cross-domain circulation of trusted data space. At the same time, the underlying coding status update module is synchronized to mark the consensus or transaction status of the intelligent coding.

7. A parallel sharding and hybrid consensus method based on intelligent trust coding, characterized in that, The system includes: The encoding parsing module is used to parse the Zhixin code and calculate the fragmentation index; The parallel sharding module is used to perform parallel sharding mapping; The dynamic scheduling module is used to perform coordinated scheduling and isolated scheduling, and it links with the upper-level root carrier behavior control field module. The council election module is used to perform council node elections; The parallel consensus module is used to perform parallel consensus within a shard; The cross-shard verification module is used to perform cross-shard cross-verification; The exception rollback module is used to perform exception fault tolerance and global rollback, and links the upper-layer distributed transaction rollback mechanism and the lower-layer coding exception handling mechanism. The upper-layer collaboration module is used to collaborate with upper-layer distributed transactions, multi-dimensional value accounting, blockchain notarization, and trusted data space. Each module performs the method described in any one of claims 1-6.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method described in any one of claims 1-6.

9. An electronic device comprising a processor and a memory, the memory storing a computer program, characterized in that, When the processor executes the computer program, it implements the method according to any one of claims 1-6.

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