1134 results about "Message queue" patented technology

According to the artificial intelligence-based data analysis system and method provided by the invention, a set of novel data analysis system architecture is designed, and key technical components such as natural language processing, a large language model, database query optimization, multi-modal visualization and a semantic knowledge graph are fused; data transmission between modules is realized through unified intermediate data objects such as a structured query intention, an analytic tree and a structured query language template object, and asynchronous collaboration is realized through event driving and a message queue mechanism, so that a non-professional user can input an analysis request through a natural language; semantic analysis, structured query language query statement generation, data query and result visualization presentation are automatically completed, the method can be widely applied to data analysis scenes in the industries of government affairs, traffic, finance, education and the like, the data use efficiency is improved, the technical threshold is reduced, and the digital decision-making ability is enhanced.

The invention relates to a production abnormality automatic identification and recovery process control method, which comprises the following steps of S1, realizing second-level synchronization of multi-source heterogeneous data, constructing a real-time data flow pipeline and generating a total-factor production situation data flow through a distributed message queue by adopting a Modbus / TCP protocol analysis algorithm based on industrial Internet of Things edge calculation; through the cooperative effect of industrial protocol analysis and distributed message queues, second-level synchronization of multi-source heterogeneous data is realized, a real-time data flow pipeline is constructed, data acquisition delay is effectively eliminated, the timeliness of anomaly detection is ensured, a dynamic weight distribution mechanism of a rule engine and a long and short-term memory network prediction model is adopted, and the real-time performance of the system is improved. By combining sliding window threshold detection, the accuracy and coverage of anomaly recognition are improved, false alarm and missing alarm caused by a single detection mechanism are reduced, and multi-dimensional root cause tracing is performed by combining a fault mode knowledge base through combined application of time sequence correlation analysis and a causal diagram inference engine.

The invention provides a final consistency processing system and method for transaction messages. The method comprises the following steps: acquiring transaction state metadata and a service message body about a transaction message in a distributed system, storing the service message body into a distributed message queue, and storing the transaction state metadata into a memory database; constructing a transaction state index structure; determining a physical offset based on the business message body, creating a transaction state record in the memory database based on the physical offset, and generating a to-be-rechecked transaction task according to the transaction state record; based on the transaction creation time and the system load factor, determining a rechecking interval, and executing the to-be-rechecked transaction task; when it is detected that the transaction state is changed into a transaction confirmation state from a to-be-confirmed state, pulling a service message body according to the physical offset; and performing double confirmation on the pulled service message body. The problems of performance bottleneck and low recovery efficiency caused by strong coupling of the transaction state and the message body are solved.

The invention relates to the technical field of hydraulic engineering monitoring, and discloses a hydraulic engineering operation risk monitoring management system based on multi-sensor fusion. The system comprises a data acquisition module, a data fusion module, an early warning and instruction generation module, and an instruction distribution and verification and correction module. The data acquisition module acquires structural deformation, water flow pressure and environment temperature and humidity data in real time through multiple types of intelligent sensors; the data fusion module inputs the collected data into a dynamic weighted fusion model, and generates a comprehensive monitoring index in combination with a sensor confidence coefficient weight and a historical data deviation rate; the early warning and instruction generation module triggers multi-stage early warning and generates an equipment regulation and control instruction set according to the comprehensive monitoring index and a preset safety threshold value; the instruction distribution module distributes the instruction to an execution terminal through a distributed message queue; and the verification and correction module checks terminal feedback signals by using a back propagation verification mechanism, and corrects the confidence coefficient weight of the model.

The invention belongs to the technical field of artificial intelligence, and particularly relates to a dialogue message queue management system based on a large model cluster. The system comprises a message preprocessing module, a message router, a plurality of independent priority queues, a resource scheduler, a dialogue state manager and a large model cluster. The message preprocessing module receives an external dialogue request, constructs a metadata object, allocates a priority queue tag, calculates a static score and records a timestamp; the message router distributes the request to a corresponding priority queue according to the label; the resource scheduler executes a scheduling strategy, calculates a dynamic priority score, realizes load balancing, retrieves historical context information from the dialogue state manager, combines a request and a context into a processing task and dispatches the processing task to a large model cluster; the large model cluster returns model response to the resource scheduler, and the dialogue state manager is responsible for context storage and updating. All the components of the system can efficiently process the dialogue message request through close cooperation.

The invention relates to the technical field of cloud storage, can be applied to business scenes of financial science and technology, medical health and the like, and discloses a load and message queue regulation-based migration method, device, equipment and medium. Monitoring message backlog amount and consumption rate to generate message queue state information, generating migration regulation and control parameters based on the two types of state information, determining concurrency level and issuing rhythm by combining object size classification information, reducing issuing frequency and preferentially scheduling small objects when the message backlog amount is increased and oversize objects exist, and distributing the tasks to the working nodes according to the concurrency level and the issuing rhythm to execute migration, and adjusting migration regulation and control parameters based on execution state updating information. According to the method, concurrency and rhythm are regulated and controlled in real time, object size classification is combined, the problems that traffic is uncontrollable and throughput is affected by large files are solved, and efficient and stable data migration is achieved.

The invention discloses a machine tool running state collection and evaluation method and system, and relates to the field of intelligent machine tools, and the method comprises the steps: collecting machine tool multi-dimensional data through a multi-channel collection device; performing time alignment on different sampling frequency signals by adopting a dynamic synchronization algorithm of clock drift compensation; executing noise suppression, feature extraction and compressed encoding at the edge computing node to generate local state abstract data; sending the abstract data to a central server through a distributed message queue, and realizing multi-application concurrent access based on load dynamic scheduling; and the central server performs fusion analysis on the abstract data by using a multi-modal fusion deep network model, and outputs a health degree index and an overall operation score of the key parts of the machine tool, thereby realizing intelligent evaluation and health prediction of the operation state of the machine tool. The method realizes global perception and intelligent evaluation of the machine tool operation state, and can be widely applied to operation monitoring and health management of high-end numerical control machine tools, complex machining centers and unmanned production lines.

The invention discloses a multi-dimensional data asynchronous calculation method and system based on a dynamic dependency graph, and relates to the field of data processing. The method comprises the following steps: constructing a metadata, logic and instance three-layer separation storage model; analyzing the reference relationship to construct a directed acyclic graph, and generating a calculation priority; monitoring data change, and executing asynchronous serialization calculation through a message queue based on priority; the associated document is automatically updated based on anchor mapping. According to the method, the calculation deadlock and the performance bottleneck of large-scale data in the Web environment are solved, logic decoupling and dynamic expansion are realized, the final consistency of the data is guaranteed, and the high-concurrency throughput and the stability are remarkably improved.

The invention relates to an electric power marketing business abnormity real-time detection method and system based on stream-oriented computation, and belongs to the technical field of electric power system optimizing.The method comprises the steps that data snapshots are extracted from an electric power marketing business system, difference comparison is conducted on the data snapshots and historical snapshots of an intermediate library, and standardized increment events are generated and stored; capturing an incremental event in real time through a data change capturing tool and pushing the incremental event to a message queue; a streaming computation engine consumes the event stream, sequentially performs data cleaning, association with a static dimension table and sliding window statistical feature calculation, and constructs a feature vector; and performing parallel analysis and weighted fusion on the feature vectors based on a business rule base and an online machine learning model to generate a comprehensive risk score, and outputting an abnormal event when the score exceeds a threshold value. According to the method, the problems of exception identification lagging and complex work order process in a traditional batch processing mode are solved, the crossing of the business risk from hour-level detection to minute-level real-time perception is realized, and the timeliness and accuracy of power marketing risk management and control are improved.

The invention discloses a financial monitoring system based on real-time data processing and intelligent analysis, and relates to the technical field of financial information, and the system comprises a bill collection module which employs a configuration API interface, carries high-concurrency data streams through a distributed message queue, carries out the real-time connection of an upstream business system and a financial system, and receives bill detail data; and the analysis and check task arrangement module manages the task dependency relationship based on a directed acyclic graph model, and arranges a data pulling task, a bill general task and a bill check task according to a preset rule. According to the financial monitoring system provided by the invention, the automation and intelligence level of financial management is remarkably improved by integrating real-time data processing and intelligent analysis technologies, the system adopts a configured API interface and a distributed message queue, efficient butt joint with an upstream business system and a financial system is realized, and the financial management efficiency is improved. The real-time performance and accuracy of data receiving are ensured, and the data processing flow is more flexible and controllable.

The invention discloses a structured data storage method based on natural language transformation, which comprises the following steps of: a system initialization configuration stage: deploying a protocol adapter in a local memory of a PC (Personal Computer) client, and loading natural language processing pipeline configuration parameters; a heterogeneous data acquisition stage: capturing a multi-source text data stream through the protocol adapter, uniformly converting the multi-source text data stream into a standardized data packet, and sending the standardized data packet to a message queue theme; a text cleaning stage: a named entity recognition stage: inputting the pure text data into an NER module deployed with a language model loader; in the conditional feature extraction stage, feature vectors are generated for texts meeting preset conditions on the basis of entity type tags in the entity recognition result; and a consistent storage stage: inserting the entity identification results into a relational database in batches, and updating the entity mapping relationship in the cache. According to the method, the intelligent level of cache management is remarkably improved, and the access fluency of the key data of the user is guaranteed.

The invention relates to the technical field of data processing and storage, in particular to an asynchronous verification and batch storage system and method for high-concurrency voucher data. Certificate verification is executed based on the memory snapshot, and verification time consumption is improved from the millisecond level of database IO to the microsecond level of memory calculation; a batch persistence mechanism enables the throughput of the system to be improved by dozens of times, and a concurrent storage scene of ten thousand-level TPS can be easily supported; the voucher storage response time is reduced from a hundred millisecond level to a millisecond level; the response is immediately returned to the user after the verification is passed, the user almost does not need to wait, and the operation experience is smooth; the introduction of the message queue enables the system to have peak clipping and valley filling capabilities, and can deal with burst traffic leisurely; the multi-node cluster deployment supports horizontal capacity expansion, the fault of a single node does not influence the overall service availability, and the system reliability is improved.

The invention relates to an edge computing network-oriented micro-service and distributed database collaborative deployment system. The system comprises a database copy number dynamic optimization unit which obtains a dynamic optimization strategy of the copy number of a database based on a queuing gradient projection elastic scaling algorithm; a deployment strategy dynamic adjustment unit calculates end-to-end time delay based on the micro-service routing path and the database routing path; calculating a data inconsistency measurement index based on the number of each copy of the database; dynamically adjusting the deployment strategy based on the resource constraint between the end-to-end time delay and the data inconsistency measurement index and the dynamic optimization strategy of the number of copies of the database; the deployment strategy comprises micro-service instance deployment, database copy deployment and optimal routing path selection; according to the MEC scene-oriented distributed database design and fine-grained collaborative deployment optimization method, a message queue, a queuing theory and a Canal database incremental updating mechanism are integrated, and the micro-service application performance and the data query efficiency / reliability are improved.

The invention discloses an asynchronous processing method and device for business process data, and belongs to a distributed system data processing technology, and the method comprises the following steps: S101, receiving a business request message, and persistently storing the business request message in a main message queue; s102, acquiring a to-be-processed message from the main message queue, and locking an associated target data record before executing processing; s103, verifying data consistency based on the version number recorded by the target data, if the version number is matched, executing processing and updating the version number, and otherwise, discarding the message; s104, after successful processing, sending a confirmation instruction deletion message to the main message queue; through persistent storage of the main message queue, a version number verification mechanism and management of the dead message queue, the problem of data inconsistency caused by concurrent operation is effectively prevented, reliable transmission of messages is ensured, loss of service data is avoided, dead message processing efficiency is optimized, and the method has the advantages of ensuring data consistency, preventing message loss and improving system reliability.

The described techniques address issues related to compatibility and cost-effectiveness of in-vehicle networks. The described techniques may utilize security Ethernet-based protocols, for example, without the need to exchange separate key agreement messages and, consequently, meet the stringent starting time requirements for real-time control systems. Additionally, a membership tracking solution may be implemented in which each node within a membership group may request, or “challenge” other nodes with the same group to verify their online status, and this online status may be maintained over time. Finally, a transmission queue management process is described that deletes queued messages only when it is determined that every intended recipient node received the message, thereby providing atomicity. Retained queued messages may then be re-transmitted in accordance with a transmission schedule.

The embodiment of the invention provides an Internet of Things control system and method, electronic equipment, a storage medium and a program product, and relates to the technical field of industrial Internet of Things. The system comprises a connection management module used for establishing and maintaining connections between a plurality of Internet of Things devices and a plurality of MQTT servers corresponding to the Internet of Things devices; the dynamic equipment mapping module is used for mapping the data of the Internet of Things equipment to the MQTT server through the configuration file; and the message queue and network disconnection continuous transmission module is used for putting the message into the tail of the message queue to continuously transmit the message if the MQTT client instance corresponding to the Internet of Things equipment is detected to be in a network disconnection state when the message is published to the MQTT server. According to the scheme, dynamic expansion of heterogeneous equipment in the industrial Internet of Things, parallel butt joint of multiple cloud platforms, network disconnection continuous transmission and two-way communication capability are realized.

The invention belongs to the technical field of product production cycle management, and particularly relates to an electronic image-text file remote multi-bin collaborative storage method based on a PLM. Comprising the steps that a 1 + N hybrid storage architecture is constructed, one center bin is deployed in an enterprise headquarter data center and stores full document metadata and latest version files, and N area bins are deployed according to geographic areas and store cache copies and incremental update data of local high-frequency access documents; the remote multi-warehouse document increment synchronization is realized through an intelligent synchronization engine, and the intelligent synchronization engine adopts a content awareness increment synchronization algorithm and a dynamic synchronization strategy based on network quality; version management is realized through a version cooperative control module, and the version cooperative control module is used for establishing a global version number mapping mechanism and a conflict resolution decision tree; cross-warehouse process automation is realized through a cross-warehouse workflow engine, and the cross-warehouse workflow engine integrates a BPM process engine and a message queue; the method can adapt to a remote network environment, and the large file synchronization efficiency is improved.

The invention relates to the field of edge computing, in particular to a primary and secondary fusion complete ring main unit energy efficiency optimization system based on cloud edge collaboration. The system comprises an edge device deployment and data acquisition module used for collecting operation electric parameters and device states and generating a service calling request; the service calling module is used for screening target control parameters under security constraints based on the energy efficiency optimization service package; the data synchronization module unloads the data to a cloud platform through a message queue protocol; the cloud service arrangement module aggregates the data updating service package and issues the data updating service package to the edge; and the real-time control module converts the parameters into instructions to drive equipment to act. A cloud training and edge reasoning collaborative architecture is adopted, the problems that local control lacks adaptivity, edge resources are limited and full-cloud control communication time delay exists are solved, and real-time energy efficiency optimization is achieved.

The invention provides a data decoupling centralized query method and system based on MQ message triggering, and relates to the technical field of data query, and the method comprises the steps of receiving a message queue data change message, constructing a field, dividing check nodes by depending on a directed acyclic graph, carrying out data consistency verification, and pushing a transaction identifier to carry out concurrent operation scheduling. And collecting hotspot information by adopting a Bloom filter to adjust data fragmentation and cache distribution, generating a distributed query routing table, and distributing query requests according to the routing table. According to the method, the data consistency is improved, and the query performance is optimized.

The invention relates to a grayscale request routing method and device based on a message queue, equipment and a medium. In the application, after a message production service receives a request message, if a message agency judges that the request message carries a gray level identifier, an original theme of the request message is modified into a shadow theme to generate a target message, and the target message is sent to a gray level message queue, so that a gray level service in a message consumption service is facilitated; and consuming the corresponding target message from the grayscale message queue through the shadow theme. Visibly, according to the method, the device and the system, the grayscale request carrying the grayscale identifier is identified through the message agent, the original theme of the grayscale request is modified into the shadow theme, and then the shadow theme is stored in the grayscale message queue, so that grayscale request routing based on the message queue can be realized, the grayscale request can be isolated from other online requests in the mode, and the grayscale traffic is prevented from influencing the online user traffic; the message agent is independent of the business program of the message production service, so that the scheme does not need to modify the business code, and the stability of the business code is ensured.

The invention discloses a communication network fault diagnosis method and related equipment based on multi-modal vector fusion, and the method comprises the steps: carrying out the vector structuring processing of historical heterogeneous telecommunication operation and maintenance data through a multi-modal vectorization engine, and obtaining a historical multi-modal vector set; performing vector fusion processing on the historical multi-modal vector set through a vector fusion center to obtain a historical multi-modal fusion vector; an alarm message queue in a telecommunication network is monitored through a diagnosis decision module, and if an unknown composite fault is detected from the alarm message queue, cosine similarity calculation is carried out on a current fault fusion vector corresponding to the unknown composite fault and a historical multi-mode fusion vector in a hierarchical storage module; and outputting a network fault diagnosis decision result. According to the method, the accuracy and comprehensiveness of network fault diagnosis can be improved, efficient data storage, retrieval and diagnosis decision are realized, the operation efficiency and diagnosis capability of the system are improved, and the method can be widely applied to the technical field of communication network operation and maintenance.

The invention provides a red envelope grabbing method, system and device in a high-concurrency scene and a storage medium, and the method comprises the steps: receiving a red envelope creation request, synchronously deducting the account fund of a sender, pre-distributing the amount by using a double mean value algorithm, generating an amount list, and storing the list, an inventory counter and a user deduplication set into Redis. And when a grabbing request is received, executing Redis Lua script atomization operation: verifying user de-duplication, checking red envelope inventory, deducting the inventory after the red envelope inventory passes, popping up money from a list, and recording grabbing information. If the script is executed successfully, judging that grabbing succeeds, generating a success message to a message queue, and asynchronously updating the balance of the receiver and recording a flow by the consumer. And a grading reconciliation mechanism is adopted to ensure that the robbing record is consistent with the fund flow. And after the red envelope is sent for a preset time, scanning the unscrambled amount and returning the unscrambled amount to the sender account. According to the invention, a high-performance, high-reliability, safe and flexible red envelope grabbing system can be constructed.

The invention provides an invoicing data asynchronous concurrent processing method and system based on a message queue, and the method comprises the steps: receiving invoicing application data of a business system through a tax platform, carrying out the basic format verification of the invoicing application data, asynchronously pulling an invoicing application message from a message queue through a consumption cluster composed of one or more message consumers, and transmitting the invoicing application message to a server; judging whether all the preset service rules are met or not; if all the preset business rules pass the verification, pushing the verified invoicing application data to a tax center, and initiating an automatic invoicing request; generating a final result of invoicing processing; and persistently storing a final result of invoicing processing in a database or a distributed cache, and feeding back the final result to a service system through an asynchronous notification mechanism. Complete decoupling of requests and processing is realized, the throughput and concurrency capability of the system are effectively improved, the stability and fault tolerance of the system are enhanced, the maintainability and flexibility are improved, the impact on a downstream system is reduced, and elastic expansion and automatic operation and maintenance are supported.

The invention belongs to the technical field of data processing, and discloses an active intelligent operation and maintenance monitoring method for a data center, which comprises the following steps: step 1, component modeling and topology configuration; 2, carrying out distributed health detection and data acquisition; 3, performing real-time health assessment and anomaly detection; 4, performing intelligent alarm and root cause analysis; 5, unified operation and maintenance and closed-loop control are carried out; and step 6, dynamically optimizing the intelligent operation and maintenance strategy. According to the method, a monitoring object and a dependency relationship are clarified through component modeling and topological configuration, and specific scenes, such as multi-mode acquisition, active detection, index pulling, log analysis, coverage message queue theme accumulation and database connection pool exhaustion, of distributed health detection are combined. The quantitative health score is calculated based on the preset scoring model, and by combining with the dynamic baseline learned by the ARIMA or LSTM algorithm, the module abnormity can be actively detected in different periods and weekly updating, and the problems of fault discovery lagging and incomplete monitoring coverage are solved.

The invention discloses a banking business post authority management method and device, equipment and a medium, and relates to the technical field of computers. Comprises: generating a post permission allocation request based on a service scene; executing a risk pre-check operation based on the post permission allocation request, and if pre-check is passed, configuring a temporary permission for the permission applicant according to a preset minimum permission principle; collecting operation behaviors and operation environment data of the permission applicant in real time, and generating a target risk score; generating an operation risk level of the permission applicant based on the target risk score by using a preset risk grading response mechanism so as to execute a corresponding permission management operation, and generating a corresponding permission change instruction at the same time; and synchronizing the permission change instruction to each service system through a preset message queue, and uploading the key operation log containing the permission change record to a preset block chain. Therefore, risk real-time blocking and authority life cycle management can be realized in banking business, and business compliance is improved.

The invention discloses a port field knowledge graph automatic construction method based on cooperation of multiple intelligent Agents, and the method comprises the steps: processing structured data, semi-structured data and non-structured data of a port field through intelligent Agents with an autonomous decision-making capability, and achieving the entity recognition, relation extraction and knowledge fusion; a plurality of intelligent Agents with the cooperation function are used for executing knowledge discovery, new knowledge verification, conflict detection, knowledge fusion and graph updating tasks respectively, cooperative communication among the intelligent Agents is achieved through a message queue, and dynamic evolution of a knowledge graph is completed; processing the knowledge graph by adopting a customized knowledge graph embedding method and a semantic fusion algorithm designed for professional terms and knowledge structures in the port field; and storing the processed knowledge graph data based on a distributed architecture, wherein the distributed architecture supports high concurrent processing and real-time response. According to the method, the port domain knowledge graph can be efficiently and automatically constructed.

The invention discloses a queue system message accumulation processing method and device and electronic equipment, and relates to the technical field of distribution.The method comprises the steps that operation data of a queue system are collected based on a preset frequency adjusting mechanism, and a first index, a second index and a third index of the queue system are determined based on the operation data, the first index is a depth deviation degree of a message queue determined through logarithm compression operation, the second index is consumer saturation of the queue system, the third index is a message growth rate of the queue system calculated based on a dual time window, and an index entropy value of the queue system is determined based on the first index, the second index and the third index. And performing decision processing on the queue system based on the index entropy. According to the method and the device, the technical problem of high false alarm rate of early warning for message accumulation in the prior art in the process of monitoring the queue system is solved.

A device can provide a unified and scalable multiprocessor communication framework that enables communication between multiple processor cores in a multicore device. For example, the device may be configured to perform data payload management using a Smart Message Queue (SMQ) and / or shared memory. Additionally or alternatively, the communication framework may enable the processors to communicate with each other and / or peripherals of the device while abstracting details of various communication protocols, hardware interfaces, and / or the like. For example, the communication framework may provide a common interface for applications, enabling a first application associated with a processor to establish a connection to any processor and / or peripheral without knowing details of a communication protocol for each connection.

The invention provides a data fusion analysis method and device in a stream batch mixed mode and electronic equipment, and relates to the technical field of data processing. The method is applied to a data fusion analysis system in a stream batch mixed mode. The data fusion analysis system in the stream batch mixed mode comprises a data source layer, a message queue layer, a calculation layer and a query engine layer. The method comprises the following steps: acquiring real-time data and batch data from a data source layer; inputting the real-time data into a calculation layer through a message queue layer for real-time calculation to obtain a real-time calculation result; the batch data are directly input into a calculation layer for offline calculation, and an offline calculation result is obtained; and jointly writing the real-time calculation result and the offline calculation result into a query engine layer so as to uniformly query the real-time data and the batch data in the query engine layer. By means of the method, unified query of historical data and real-time data can be achieved.

The invention provides a personnel behavior monitoring method and device, electronic equipment and a medium, and effectively solves the problems of incomplete supervision mechanism, fuzzy execution standard and risk early warning lag of an existing disinfection supervision system for a breeding house. The method comprises the steps that a configured image acquisition module triggers a target event and pushes the target event to a first message queue; the edge calculation module monitors a target event, acquires a target video clip acquired by the configured image acquisition module in real time, and extracts a plurality of key frame pictures from the target video clip; controlling a pre-trained behavior detection model to recognize the multiple key frame pictures from multiple recognition dimensions to obtain corresponding dimension results, and integrating the dimension results to obtain a recognition result; and the recognition result is pushed to a result display module, so that the result display module analyzes the recognition result and generates warning information, and behavior monitoring of the target person is ended based on the warning information.