766 results about "Consensus" patented technology

A distributed indexing and resolution architecture is disclosed for decentralized systems requiring modular, trust-scoped mutation control and dynamic alias governance. The system comprises a plurality of index entries arranged in a parent-child hierarchy, each associated with a structured alias and governed by one or more anchor nodes. Anchors perform localized resolution, mutation validation, and restructuring operations under deterministic policy constraints, enabling semantic scope enforcement and entropy-sensitive adaptation without requiring global consensus or centralized control. The architecture supports scoped alias traversal, asynchronous mutation proposals, and elastic anchor registration based on system state metrics. The indexing substrate may be integrated into heterogeneous infrastructures, including systems comprising distributed software agents, semantic execution platforms, or pseudonymous identity frameworks. Anchors coordinate within defined trust domains to ensure lineage continuity, dynamic rekeying, and semantic integrity across independently governed segments of a decentralized namespace.

The invention discloses a large-model-driven automatic knowledge graph construction method based on a confidence feedback mechanism, and aims to improve the structural accuracy and semantic consistency in a structured triple generation process, and perform structural constraint guidance by using a few-sample prompt mechanism and a cross validation mechanism of a heterogeneous large model. And the control capability of the large language model on the triple format is enhanced, so that format offset and semantic redundancy in the generation process are reduced. And meanwhile, a multi-dimensional confidence evaluation system is constructed, model consensus judgment, semantic rationality analysis and knowledge consistency verification are fused, and refined quantification and screening of triple quality are realized. According to the method, a confidence backtracking feedback strategy is introduced, a generation-verification-optimization closed-loop process is constructed, the expression and correction capability of the system on a complex knowledge structure is enhanced, the dependence on an external API is effectively reduced, the consumption of computing resources is reduced, and the operation efficiency of the system and the feasibility of engineering deployment are remarkably improved.

The invention discloses a vehicle-mounted controller firmware upgrading method, which relates to the technical field of intelligent networked automobiles, and comprises the following steps of: accurately describing a dependency relationship between versions by introducing a directed acyclic graph, providing a clear topological sorting basis for an upgrading process, and improving the upgrading efficiency. The system function conflict and disorder caused by disordered upgrading sequence are fundamentally avoided; a distributed consensus protocol is utilized to ensure that each controller achieves state coordination before upgrading, so that the overall robustness of a multi-controller cluster is effectively improved when the multi-controller cluster faces network delay or individual node abnormity, and upgrading failure or version bifurcation caused by the fact that part of nodes are not ready is avoided; through the combination of the group-level binding token and the atomic switching mechanism, the controller group with a strong function dependency relationship can be ensured to be effective and updated as a unified transaction unit, and the safety and reliability of cross-domain function linkage are remarkably enhanced.

The invention relates to the technical field of distributed storage verification, and discloses a storage information verification system based on a consensus mechanism. The system comprises a consensus network communication module, a storage feature analysis module, a verification decision core module, a time sequence prediction module, a decision compensation module and a verification execution engine module. The consensus network communication module is connected with a distributed storage node and receives a storage verification request; the storage feature analysis module extracts multi-dimensional feature vectors of the target data to form a feature descriptor set; the verification decision core module is combined with an embedded consensus verification space and dynamic confidence coefficient constraint condition operation to output an initial verification decision scheme; the time sequence prediction module divides a time window and generates a prediction feature descriptor set; the decision compensation module carries out deviation compensation according to the result to obtain an optimization scheme; and the verification execution engine module sends an instruction to trigger the distributed nodes to execute verification operation. A dynamic verification system constructed by the system adapts to dynamic characteristics and heterogeneous environments of distributed storage.

Various aspects of the disclosure relate to automated testing for application programming interfaces (APIs). A dynamic API validation computing system leverages a generative AI model to dynamically generate a multitude of data sets and rules for use during API validation activities. A federated byzantine agreement mechanism performs the validation of each API using the generated test cases and test data. A generator engine incorporates a generative AI model that may be trained on a large corpus of API metadata and / or data characteristics to predict data patterns and / or validation rules for each of the APIs under test. The generator engine may also predict a structure and format of requests based on the training model inputs. Multiple Test cases for an API created through use of the generative AI model may be distributed and executed on different testing nodes that reach a consensus about whether each API has passed or failed.

The present invention relates to the technical field of blockchains, and in particular to a blockchain-based multi-partition asynchronous parallel consensus method. The method comprises: constructing a multi-partition asynchronous parallel consensus blockchain system comprising a plurality of partitions and a plurality of guide nodes; for each partition, each ordinary node publishes and broadcasts transaction information in the partition to which it belongs, and each ordinary node collects and stores the transaction information published in the partition to which it belongs; each partition creates a partition block by executing an intra-partition consensus algorithm, and uses a main node to upload the partition block to a guide node; and each guide node sorts the collected partition blocks, and selects one partition block therefrom to execute an inter-partition consensus algorithm. The present invention enables the synchronous intra-partition consensus initiation and execution provided for in existing sharded blockchain systems to now be performed asynchronously, thus improving system parallelism, transaction information processing throughput, and cross-shard communication processing efficiency.

The invention discloses a switch load balancing method based on fuzzy logic control, and the method comprises the following steps: S1, monitoring a network state in real time through quantum sensing equipment, and obtaining related parameters; s2, transmitting the parameters to a fuzzy logic controller for processing; s3, generating a load distribution strategy according to a predefined rule; s4, transmitting the preliminary strategy to each switch node in the block chain network, and recording related data; s5, verifying the data by using a distributed consensus mechanism of the block chain; s6, dynamically evaluating a node trust value based on an enhanced fuzzy trust model, and selecting nodes meeting requirements to participate in a load balancing game decision; s7, carrying out cooperative calculation on the selected nodes by utilizing a game theory cooperation mechanism, and generating a globally optimized load distribution strategy; and S8, optimizing a load distribution strategy through a quantum genetic algorithm, and performing automatic execution through an intelligent contract. According to the method, the advantages of fuzzy logic, the block chain and quantum computing are combined, and the intelligence and safety of load balancing are improved.

The invention discloses a decentralized multi-agent information interaction method and system, and the method comprises the steps: generating a subtask carrying a unique identifier and metadata based on mixed dimension task decomposition, and embedding a global utility function; sub-task-agent mapping is dynamically adjusted through Kafka and Flink, and a utility function weight coefficient is broadcasted; the sub-agent determines an executor through contract network protocol bidding, and performs execution permission arbitration on key resources in combination with a token bucket algorithm; metadata are transmitted by adopting a Gossip protocol, and intermediate data are transmitted by P2P direct connection (abnormal degradation to Kafka); key metadata are synchronized through lightweight Raft consensus, and non-key metadata are merged by adopting CRDT; and after a final result is written in through Kafka, duplicate removal, sorting and aggregation are carried out through Flink, and key states are synchronized through Gossip. According to the method, the problem of message disorder under a hybrid protocol is solved; and high-reliability message transmission and state synchronization are realized by combining the strong consistency bottom of Kafka and the conflict resolution of lightweight Raft and CRDT.

The invention discloses a block chain fragment security expansion method of a trusted state synchronization chain, which realizes state consistency verification between fragments by constructing a Layer1 state synchronization chain, and adopts an unbiased random leader rotation mechanism based on a preorder block signature and an efficient two-stage submission protocol. Three rounds of communication of traditional BFT consensus are compressed into two rounds of parallel processing under a state fragmentation architecture, and a dynamic fragmentation recombination strategy and a state difference synchronization technology are combined, so that the core problems of throughput bottleneck, cross-fragmentation transaction atomicity, attack risk prediction by a leader, reduction of recombination efficiency and the like in a block chain fragmentation system are systematically solved; the parallel transaction processing is realized, the consensus time delay is reduced by 30%, the cross-fragment transaction verification efficiency is improved by 60%, the system throughput is linearly expanded along with the fragment number, and the system security is enhanced through a pledge economic model and a malicious node detection mechanism.

The invention discloses a virtual power plant operation management and control method based on a block chain, original power data are compressed into Hash fingerprints to be chained through a collaborative architecture of an edge computing layer and an AI pre-decision module, the block chain network load is effectively reduced, and a dynamic elastic PBFT consensus mechanism adjusts the scale of verification nodes in real time based on transaction types, so that the efficiency is improved. And compared with a traditional fixed node consensus mechanism, the network communication overhead is reduced. And a hash value asynchronous pre-verification technology is adopted, so that the interaction rate of the multi-dimensional power data is improved, and the efficiency is improved compared with that of a conventional data uplink mode. Through the decoupling design of the intelligent contract execution flow and the consensus verification flow and in combination with the pre-decision data cache queue, the resource scheduling instruction issuing time delay is reduced. The block chain transaction throughput is improved and is effectively improved compared with a standard alliance chain architecture, and the technical problems that the consensus mechanism processing transaction speed of an existing block chain is limited and the high-frequency real-time data interaction requirement of a virtual power plant is difficult to meet are successfully solved.

The invention provides a zero-sum game-based distributed elastic consensus optimal control method under denial of service attack of a multi-agent system, and the method specifically comprises the steps: firstly, constructing a multi-agent formation model in which a leader and a plurality of followers cooperatively move through graph theory knowledge and a multi-agent second-order state equation; secondly, in order to reduce the influence of denial of service attack on communication topology, a time-varying weight distributed elastic observer is provided to estimate the state of a leader, and the attacked condition of the leader is considered; then, by constructing an augmentation system, a distributed consistency tracking problem with a leader is converted into a local tracking problem between each follower and a virtual leader thereof; and finally, in order to solve the zero-sum game problem, introducing a Hamiltonian-Jacobian-Ansaxophone equation to realize optimal control input under maximum external disturbance, and realizing algorithm design by using single-evaluation reinforcement learning with experience playback and combining a gradient descent method.

The invention belongs to the technical field of cross-data island consensus, and particularly relates to a cross-data island consensus verification method and system based on credibility scoring. According to the invention, by dynamically evaluating the trust degree of each data island and combining network state fluctuation, real-time verification and abnormal early warning of a consensus result are realized, the stability and safety of cross-data island cooperation are effectively improved, the data consistency is ensured, the data risk caused by network fluctuation is reduced, the self-adaptive capability of the system is enhanced, and the method is suitable for large-scale popularization and application. In the consensus process, historical interaction events and a current cooperation state of a data island are considered, efficient alignment of cross-island features is achieved through a gradient exchange mechanism, a standardized consensus data view is generated, in addition, self-adaptive adjustment of a consensus verification rule is ensured by pre-deploying a trusted execution environment, and the consensus verification efficiency is improved. And the consensus accuracy and efficiency are further improved.

The invention relates to a multi-robot system global flexible preset performance control method under an unknown state and a DoS attack, and belongs to the technical field of multi-robot system control. Aiming at the problems in the prior art that the communication topology is unstable due to attack, the initial error constraint is strict, and the input saturation conflicts with the performance, the following scheme is provided: dynamically reconstructing the attacked communication topology based on a bipartite consensus layering algorithm; designing a global error constraint mechanism fusing the scale function and the tunnel type performance function; constructing a balance control input and performance boundary of the input saturation self-adaptive auxiliary system; and estimating an unknown state and compensating an observation error by adopting a state observer. The method has the technical effects that the DoS attack resistance of the system is enhanced, the global preset performance control of any initial error is realized, the contradiction between input saturation and tracking performance is dynamically coordinated, and the multi-robot collaborative operation under the unbalanced topology is supported.

The invention discloses a block chain-based consensus authentication method and device, electronic equipment and a program product, and relates to the technical field of block chains, and the method comprises the steps: generating a pre-preparation message based on a financial transaction request initiated by a client through a main node, and broadcasting the pre-preparation message to all consensus nodes, part of preparation messages returned by consensus nodes are received through a main node, signatures in the part of preparation messages are aggregated into batch signatures under the condition that the validity verification of the messages is passed, submission information is generated based on the batch signatures, and the submission information is broadcasted to all the consensus nodes. And counting the number of the consensus nodes which pass verification of the aggregated batch signatures, and completing the consensus authentication process of the current batch transaction under the condition that the number of the consensus nodes reaches a preset node number threshold value. According to the method and the device, the technical problems of low consensus efficiency and complex verification process when the alliance chain adopts a batch processing signature mechanism to perform batch processing in a high-concurrency transaction processing scene in the related technology are solved.

Connection units 200A, 200B connect to a data distribution platform and form a consensus on a contract including an asset and a policy shared among users. Execution units 230A, 230B start a secure isolated execution environment isolated by using an image of an execution environment including a policy execution program that operates according to the contract, and receive and process data according to the contract in the isolated execution environment. At least one of the isolated execution environment, the image of an execution environment, the contract inputted to the isolated execution environment, the data received in the isolated execution environment, and the processing result in the isolated execution environment is remotely attested.

The invention discloses a manufacturing task autonomous negotiation and execution method based on a large language model agent, and the method comprises the steps: constructing a production scheduling agent, an equipment management agent, a material distribution agent and a quality control agent, analyzing a natural language task instruction through the production scheduling agent, and decomposing the natural language task instruction into subtasks; each agent calculates a utility value based on the load rate, the resource matching degree, the estimated completion time and the historical success rate, and performs structured negotiation to achieve a task allocation consensus; a prediction-check-rollback architecture is adopted to generate an action instruction sequence, the sequence is compiled into a time Petri network transition sequence, and reachability verification is carried out based on hard security constraints; production environment data is collected in real time to trigger anomaly detection and re-negotiation, and a formalized security verification and causal anti-factual reasoning parameter updating mechanism is introduced. According to the method, unstructured instruction understanding, autonomous task planning, multi-agent collaborative decision and closed-loop optimization are realized, and the problems of real-time performance, safety and interpretability of a large language model in manufacturing control are solved.

The invention discloses a heterogeneous computing power resource dynamic scheduling system and method based on multi-objective optimization, and the system is deployed in a digital ecological platform complex based on multivariate consensus and embedded intelligent management. Comprising a platform access module, a data acquisition and perception module, a multi-target modeling and optimization module, a dynamic scheduling and execution module and a fault-tolerant mechanism module. The system registers as a computing power scheduling service node through an intelligent contract interface, obtains and verifies the compliance of a computing task, collects heterogeneous computing power resource node state data, and generates a scheduling decision by dynamically adjusting the weight of a target function; evaluating task suitability by using an AMCU suitability scoring model, and executing a scheduling AMCU strategy; according to the method, the technical problems of low resource scheduling efficiency and poor fault-tolerant capability in a heterogeneous computing power environment are solved, and the system throughput and the resource utilization rate are improved.

The embodiment of the invention provides a block chain consensus processing method and device, a computer readable medium and equipment. The block chain consensus processing method comprises the following steps: obtaining a performance score of a block chain node and current block chain information; generating a verifiable random number of the block chain node according to the current block chain information and a private key of the block chain node; according to the performance score of the block chain node, generating a selection threshold corresponding to the block chain node, the selection threshold being used for determining whether the block chain node can be used as a consensus node; and if the verifiable random number of the block chain node and the selection threshold satisfy a set size relationship, selecting the block chain node as a consensus node. According to the technical scheme provided by the embodiment of the invention, the randomness of consensus node selection can be improved, so that the stability of the block chain system can be improved on the premise of ensuring that the block chain system has relatively high consensus performance.

According to the intelligent traffic charging data consensus system based on the block chain, a dynamically optimized hybrid consensus mechanism is adopted, a node election algorithm and a fragment consensus strategy are designed in combination with traffic flow features, and high concurrent processing capacity is achieved. The system ensures non-tampering and traceability of charging data through technologies such as credible data acquisition, intelligent contract automatic execution, hierarchical storage architecture and the like, and meets the real-time supervision requirement at the same time. A specially designed privacy protection module protects sensitive information of a user on the premise of ensuring supervision transparency, and a proposed cross-chain reconciliation protocol effectively solves the problem of multi-region collaborative charging.

A lead-sync log record is used to synchronize the replication logs of follower shards to the leader shard. In response to a failure to determine that there is a consensus for a database transaction commit operation after a shard server becomes a new leader, the new leader shard performs a sync operation using the lead-sync log record to synchronize replication logs of the follower shards to the replication log of the new leader. A shard server identifies a first transaction having a first log record but not a post-commit log record in the replication log, defines a recovery window in the replication log starting at the first log record of the identified first transaction and ending at the lead-sync log record, identifies a set of transactions to be recovered, and performs a recovery action on the set of transactions to be recovered.

The invention relates to the technical field of power equipment state monitoring and data security, and discloses a power equipment supply chain data sharing method based on a block chain, and the method comprises the following steps: S1, data collection and standardization: collecting sensor data of power equipment in real time, and carrying out the standardization processing; s2, dynamic entropy threshold calculation: dynamically calculating a data entropy threshold based on an information geometry theory; s3, verification mode decision making, wherein quantum chaos random walk data sampling or full-amount zero-knowledge proof verification is triggered according to entropy threshold decision making; and S4, anti-tamper certificate construction: constructing an anti-quantum hash chain for the sampled data and carrying out distributed anti-tamper coding. According to the method, through dynamic entropy threshold adaptation and quantum chaos sampling, accurate improvement of anomaly detection sensitivity is realized, based on Reed-Solomon fragmentation and algebraic verification, it is ensured that data can still be completely recovered when being partially tampered, and security and throughput efficiency are balanced by using block chain evidence storage and improvement of PBFT consensus.

The invention provides an optimization method for proposal node selection of a consensus algorithm of a carbon Popingness block chain, and belongs to the technical field of carbon Popingness block chains. The optimization method comprises the following steps: starting a new era through a node, counting candidate node information, calculating a mathematical mean value and a standard deviation of a consensus efficiency score to identify an outlier node; evaluating the network performance of candidate nodes by applying a carbon popularity performance prediction model and a dynamic memory adjustment function, generating a proposal node list after removing outlier nodes, performing transaction verification and state verification by verification nodes, executing a multi-round voting verification process by a consensus algorithm, and adding consensus participation points for participation nodes, and after the block is submitted, each node sends a score list to the next height proposal node and writes the scoring data into the block head part, and through the complete node selection and consensus verification process, the technical problems that the proposal node selection efficiency is low and the nodes with abnormal performance cannot be effectively excluded in the block chain consensus algorithm are solved.

The invention discloses a lightweight block chain node consensus mechanism optimization method, and relates to the technical field of block chains. According to the method, the computing power of the lightweight nodes is accurately evaluated through a hierarchical verification aggregation algorithm, efficient participation of the lightweight nodes in a resource-constrained environment is realized, a transaction set is divided into a plurality of subsets by adopting a transaction verification fragmentation strategy, and verification results are aggregated by utilizing a Merkel tree aggregation verification technology; in addition, a dynamic storage management strategy is established, the depth of locally stored historical data is dynamically adjusted according to the node storage capacity, and network storage and retrieval are performed through a distributed hash table; the bottleneck problem of storage and network transmission is effectively solved, and the network bandwidth utilization efficiency and the storage management flexibility are improved.

The invention relates to an anti-quantum distributed asynchronous random beacon method and system. The method comprises: a distribution stage of executing an anti-quantum asynchronous verifiable secret sharing method; an asynchronous common subset protocol is executed, distribution nodes corresponding to received effective secret shares serve as input, and a node set i with the size of t is consensus; executing a reconstruction stage of the anti-quantum asynchronous verifiable secret sharing method, reconstructing the secret value of each node in the set I, and if the reconstructed secret value is invalid, rejecting the node from the set I; and outputting the XOR sum of the secret values of the nodes in the set I as a public random number. According to the method, distributed generation of public random numbers is supported, the single-point fault problem is avoided, the system security can be ensured in an asynchronous network, and quantum computer attacks can be resisted.

The invention relates to the field of computer science and technology, and discloses an adaptive consensus method for unmanned aerial vehicle edge calculation. Deploying a permission chain at the edge node and initializing a consensus committee; a reliability index and a response time delay index of each node are maintained through an online learning mechanism; samples are extracted from node posterior distribution based on Thompson sampling, a comprehensive score is calculated in combination with a time delay index, and a consensus committee is dynamically reconstructed through epsilon smoothing and a Gumbel-Top-k algorithm; weighted lot drawing is carried out based on the current committee node weight to determine a main node, and a dual-path view switching mechanism is adopted to guarantee the system activity. The problems of high consensus long tail time delay, poor robustness and privacy disclosure caused by link time varying and node heterogeneity in an unmanned aerial vehicle edge scene are solved, and low-overhead, high-throughput and strong-self-adaption consensus management is realized.

The invention discloses a data processing method and system for bulk commodity order settlement, and particularly relates to the technical field of data processing. Node consensus delay and transaction state synchronization frequency abnormal data of each block chain platform are collected and analyzed, data consistency is predicted in combination with a machine learning model, and transaction state consistency is automatically judged; for the consistency state, the system continues to execute normal settlement; and for the inconsistent state, the Byzantine fault-tolerant algorithm and the intelligent contract are integrated to automatically correct the transaction state inconsistency, so that the operability, stability and settlement accuracy of cross-chain settlement are improved, and the mobility and trust of the supply chain are ensured.

Systems and methods are disclosed to revolutionize blockchain consensus mechanisms by introducing a novel, inclusive framework that enhances efficiency, scalability, and environmental sustainability. Central to this breakthrough are a cluster-based scoring system and a multi-queue dynamic scheduling mechanism, designed to replace resource-intensive consensus models like Proof of Work and Proof of Stake. This approach allows nodes to participate based on merit, determined through an iterative scoring process within clusters, democratizing access, and participation across the blockchain network. The system dynamically adjusts mining complexity as the blockchain evolves, ensuring scalability and reducing energy consumption. A key innovation is the introduction of cooldown periods to prevent dominance by any single node, promoting fairness and security. This decentralized, efficient, and scalable solution paves the way for broader blockchain adoption, maintaining the technology's foundational principles while addressing its traditional limitations.

The invention relates to a computer system data backup technology, and discloses a dynamic high-reliability verifiable backup method and system. Multi-dimensional features such as data entropy and access frequency are extracted and classified into key, important and common data through machine learning; the hierarchical backup strategy comprises key data real-time increment, important data dynamic partitioning and common data period full amount, and edge node loads are dispatched in combination with federal learning; pBFT consensus edge cluster distributed storage is adopted, a backup data hash uplink evidence is stored, and the consistency is regularly verified by a smart contract; parallel processing is carried out according to priorities during recovery, and the integrity is verified through on-chain hash. The problems of static strategies, single-point faults, integrity loss and efficiency are solved, the data reliability is improved, the recovery efficiency and compliance are improved, and the method adapts to high-security scenes such as finance and medical treatment.

The invention discloses a priority-driven Byzantine fault-tolerant non-master consensus optimization method and a priority-driven Byzantine fault-tolerant non-master consensus optimization system. The method is characterized by comprising the steps of building a block chain cluster, constructing a multi-consensus instance structure, selecting an optimal node as a main node to initiate instance proposal, performing multiple rounds of voting to achieve consensus of blocks, performing differentiated processes on different types of consensus blocks, completing receipt and persistence on executed blocks and the like. The system comprises a consensus protocol module, an execution module, a storage module, an authority management module, a lock module, a priority management module, an anchor point processing module and a network communication module. Compared with the prior art, the method has the advantages that the consensus delay is reduced, the system throughput is improved, the fault tolerance and the engineering practicability are good, and the method is particularly suitable for multiple scenes such as an alliance chain, a financial system and a distributed database and is applied to improving the data processing capacity, sharing, tracking and verifying supply data and quickly processing cross-border payment.