284 results about "Asynchronous processing" patented technology

The invention discloses a hydraulic motor fault diagnosis method and system based on heterogeneous asynchronous data fusion, and the method comprises the steps: collecting heterogeneous asynchronous data of a sensor network, carrying out the preprocessing of the data, inputting the data into a parallel dynamic pruning residual network, extracting features, and carrying out the preliminary fusion, thereby obtaining an initial feature plane; and inputting the initial feature plane into a multi-connection neural network, fusing data, extracting features, obtaining a final feature plane, using the fused feature data as a training set, and building a feature classification model to test and evaluate the performance of the feature classification model. According to the method, the limitation of a traditional fusion model in asynchronous processing of high-frequency vibration signals and low-frequency thermodynamic data of a hydraulic system is effectively overcome, the robustness of key fault features in a strong noise environment is remarkably improved, and rapid virtual-real mapping of bench test simulation data and online monitoring data is realized; typical faults such as plunger pair abrasion and valve plate cavitation of the hydraulic motor can be accurately supported, and safety guarantee is provided for equipment life prediction and safety control.

The invention discloses an interactive large-screen visualization system and method based on multi-dimensional data real-time rendering, relates to the technical field of image rendering, and aims to solve the bottleneck problems of a traditional system in the aspects of data throughput efficiency, rendering delay and interactive response. The method comprises the following steps: dividing space blocks by adopting a non-uniform octree, dynamically adjusting the size of the blocks according to data density, and combining a ZSTD + Hoffman hybrid compression algorithm; a CPU-GPU three-level asynchronous processing assembly line is constructed, and task priorities are dynamically adjusted through a fixation point weight algorithm; the master node dynamically allocates LOD parameters, and the slave nodes achieve special-shaped large-screen sub-pixel-level splicing based on a spherical coordinate system model; a Q-learning algorithm is adopted to predict a user operation sequence, and dual-channel bandwidth adaptive allocation is realized in combination with an ASTP protocol. The system comprises a dynamic partitioning module, a pipeline scheduling module, a multi-node cooperation module, an intelligent preloading module and an exception handling module. Real-time interaction visualization of a large amount of data can be realized, the rendering efficiency is improved, and hardware resource occupation is reduced.

The invention provides an agent memory management method and device based on asynchronous processing and a storage medium. The method comprises the following steps: after an interaction event is written into a first storage area, issuing a processing event associated with an event identifier to an event queue, and reading the corresponding interaction event from the first storage area according to the event identifier; when the interaction event passes the importance judgment, converting the interaction event into structured memory data; determining second storage areas based on the type identification field of the structured memory data, and respectively writing the structured memory data into at least one second storage area; and analyzing the query request to obtain a query condition, determining at least one target second storage area based on the query condition, reading structured memory data related to the query request from the target second storage area, performing aggregation processing, and outputting the aggregated memory data to the agent to generate a response result. According to the method, the interaction response delay can be reduced, the model calling cost is reduced, and the memory processing auditing performance is improved.

The invention discloses a self-adaptive multi-sensor fusion SLAM (simultaneous localization and mapping) system implementation method and system, a hierarchical fusion asynchronous architecture with a front-end sensing layer, a middle fusion layer and a rear-end optimization layer is designed, and the front-end sensing layer comprises a feature extraction and matching and timestamp asynchronous processing mechanism. The middle fusion layer comprises sliding of a time window and alignment of data to a time axis, and the rear-end optimization layer comprises a multi-source factor graph model, state estimation, map updating and calculation optimization; a self-adaptive weight adjustment module is arranged between the front-end sensing layer and the middle fusion layer; multi-dimensional evaluation, self-adaptive adjustment and engineering practicability of SLAM spatial positioning mapping are realized; the front-end sensing layer performs data acquisition and preprocessing on each sensor for spatial positioning mapping, and then independently performs feature extraction and matching and timestamp asynchronous processing mechanism implementation. The problem of fusion time sequence synchronization is effectively solved, the environmental adaptability is improved, and the calculation complexity is reduced.

The invention discloses an AI-based auxiliary system for clinical teaching of cerebrovascular diseases, particularly relates to the field of disease management, and comprises a multi-modal information summarization module, a feature extraction module, a cross-modal deduction module, a dynamic incremental learning module, a virtual case generation module and a teaching evaluation feedback generation module. According to the AI-based auxiliary system for clinical teaching of cerebrovascular diseases, millisecond-level time domain alignment is carried out through a multi-modal information gathering module, a mapping relation table of image space coordinates and physiological signal timestamps is established, the problem of time sequence deviation caused by asynchronous processing of sub-channels is solved, and time-space alignment of multi-source data is achieved; feature decoupling of images and physiological signals is achieved through a feature extraction module, and relevance between cross-modal features is enhanced; dynamic information of blood flow velocity and blood pressure fluctuation of blood vessels is fused into attention scores through a cross-modal deduction module, and a causal relationship between variables is established, so that time-space consistency of clinical logic during deduction of complex cases is improved.

The invention provides a model quality evaluation optimization method and device for industrial simulation application and a server, and relates to the technical field of simulation application generalization development, and the method comprises the steps: obtaining a to-be-processed geometric model, and carrying out the format detection processing, format conversion processing and asynchronous processing of the geometric model, and determining a target input model; performing grid division processing and finite element analysis processing on the target input model, determining a finite element calculation result, performing local error estimation analysis processing on the finite element calculation result, locally refining a model grid of the target input model, determining a model key region, performing local encryption processing on the key region, and obtaining a local encryption result of the target input model; determining a model output result; and carrying out optimization processing on the model output result through a model quality evaluation optimization system with a layered architecture, and determining an optimized target model output result. The model quality can be remarkably improved.

The invention discloses a data security isolation and sharing framework implementation method for multiple tenants. The method comprises the following steps of performing multi-tenant data isolation design; the method comprises the steps of S1, role-based access control and dynamic authority management design, S3, data sandbox and sharing mechanism design and S4, performance optimization and resource management. S5, a unified security management and monitoring platform, and relates to the technical field of computers.According to the method, multi-tenant data isolation design is adopted, and effective isolation of tenant data is achieved through combination of logic isolation and physical isolation; controlling access of the tenants to the shared data through access control and dynamic authority management of roles; through a data sandbox and a sharing mechanism, the safe operation of the shared data by the tenant is realized; the resource utilization rate is improved through a cache mechanism, load balancing, a resource recycling mechanism and asynchronous processing, and performance optimization and resource management are achieved.

The invention relates to the technical field of data acquisition, in particular to an AOP-based user behavior data acquisition method. The method comprises the following steps: firstly, identifying user behavior related code features by statically analyzing Java source codes of an application program, and constructing a feature template library; during a compiling period, according to a template library identification target method, embedding a point burying instruction by utilizing a byte code enhancement technology, and constructing a monitoring section framework; and during running, dynamically adjusting an execution strategy according to the running state of the application program by virtue of a dynamic rule engine. Meanwhile, an annular buffer area is adopted to asynchronously process user behavior data streams, cache data are managed in a sub-generation mode, and asynchronous processing is triggered when a threshold value is exceeded. The method also constructs an adaptive thread pool model based on a hierarchical thread pool architecture, distributes tasks according to data value weights, monitors the task backlog rate of a high-priority sub-pool, adjusts the sampling frequency or acquisition dimension when the task backlog rate exceeds a threshold value, forms adaptive closed-loop control, and effectively acquires and processes user behavior data.

The invention provides a high-precision satellite navigation positioning method based on Android, and relates to the technical field of positioning navigation and dead reckoning, the compatibility and adaptability of a system are improved by constructing an abstraction intermediate communication interface between an application layer and an Android kernel layer; asynchronous processing is carried out through monitoring callback, so that deep dependence on a kernel is reduced; batch acquisition is realized by adopting an annular buffer area, and the acquisition frequency and the task priority are adjusted in real time according to the motion state of terminal equipment in combination with a dynamic sampling frequency and scheduling mechanism; the method comprises the following steps: constructing a multi-source data fusion model, fusing multi-source data, and synchronously aligning with timestamps to generate accurate position information; the CPU occupancy rate and the energy consumption in the fusion process are monitored in real time, and the sampling frequency and the scheduling mechanism are dynamically optimized in combination with terminal feedback and a preset threshold value, so that the positioning precision and the equipment load are balanced, and high efficiency and high reliability of the system are realized.

The invention discloses a label-based digital equipment model dynamic creation method and system, and relates to the field of complex data integration and equipment management technology application in the power industry, and the method comprises the following steps: predefining a general data label model, dynamically configuring a query model, and establishing a database; and constructing a digital equipment data entity and designing a technical process of parallel computing and asynchronous processing. Data standardization is realized, and the query efficiency is improved; through a dynamic configuration mechanism, the system can automatically generate the query model, and the flexibility is improved; through the data entity construction method, different business data can be associated through a standardized model, and the data consistency is improved; according to the method, parallel computing and cache optimization technologies are utilized, and data query and processing are accelerated; according to the method, an incremental updating mechanism is adopted, so that the real-time performance and consistency of data are ensured; according to the method, the creation efficiency, query performance and system flexibility of the equipment model can be remarkably improved, and better technical support is provided for digital transformation of the power industry.

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 invention provides a multi-strategy caching and automatic data generation method and system based on a Node environment, and relates to the technical field of data processing, and the method comprises the following steps: receiving a client request, obtaining a data generation template, constructing a data dependency graph to analyze a field dependency relationship, and determining a field generation sequence by adopting a recursive generation strategy and depth-first search; data validity verification is executed, a data generation thread pool is created by adopting an adaptive load balancing mechanism based on the data dependency graph, and asynchronous processing is realized through double buffer queues, so that the data generation efficiency is improved, the data logic integrity is ensured, and the system resource consumption is reduced.

A cybersecurity data loss prevention service stops users from stealing, or exfiltrating, sensitive data. An endpoint cybersecurity agent coordinates the installation of a browser extension. The browser extension adds content scripts to a web browser that monitor for exfiltration events. The exfiltration events represent a user's browser inputs (such as cut-n-paste or drag-n-drop) that can be used to exfiltrate usernames, passwords, credit card numbers, company secrets, and any other sensitive data. When the browser extension detects any exfiltration event, the browser extension intercepts and synchronously blocks the exfiltration event from the web browser. Moreover, the browser extension sends a duplicate copy of the exfiltration event to the cybersecurity agent for evaluation. If the cybersecurity agent determines that the user's browser inputs should have been allowed, then the browser extension is instructed to trigger the duplicate copy. The web browser thus asynchronously processes the user's browser inputs, albeit slightly delayed.

The invention belongs to the technical field of computer graphic processing, and particularly relates to a computer device for chartlet loading, which comprises a central processing unit provided with a main thread for packaging a chartlet loading request into a task object and pushing the task object into a task queue of the central processing unit; the resource loading thread is used for sequentially pulling the to-be-processed task objects from the task queue in an asynchronous processing mode and reading the mapping files in the task objects through the asynchronous I / O interface; the resource decoding thread is used for decoding the mapping file and uploading texture data obtained by decoding to the graphics processor through an asynchronous interface; a plurality of threads are created in the graphics processor and at least comprise a resource processing thread used for receiving texture data uploaded by a resource decoding thread; and the rendering thread is used for carrying out texture binding on the texture data and carrying out rendering according to an instruction of the main thread after binding so as to draw and generate a corresponding map.

The invention discloses a transaction processing method and device, equipment and a storage medium, and relates to the field of distributed systems, and the method comprises the steps: in a distributed system, determining a target transaction processing period through employing an initial transaction processing period, a system load, the number of to-be-processed transactions, a network condition and a resource utilization condition of distributed nodes, which are determined based on an epoch mechanism; allocating the to-be-processed transaction to a target transaction processing cycle, and controlling the start of the target transaction processing cycle, so that the distributed node performs asynchronous processing on the to-be-processed transaction in the target transaction processing cycle, and a processed transaction is obtained; obtaining a transaction processing state of the distributed node, and determining a to-be-submitted transaction and a to-be-rolled-back transaction from the processed transactions based on the transaction processing state; and when the target transaction processing cycle is ended, submitting the to-be-submitted transaction, and redistributing the to-be-rollback transaction to the target transaction processing cycle for processing. Therefore, the transaction processing efficiency can be improved.

The invention discloses a dynamic partition-based tax form intelligent asynchronous processing and real-time query method, which comprises the following steps of: in response to multiple groups of tax form data, analyzing a characteristic field numerical value to generate a unique request identification code; carrying out numerical processing on the feature field to generate a dynamic partition sub-identifier, and aggregating to generate a dynamic partition combination identifier; matching a target data partition corresponding to the dynamic partition combination identifier through a constructed dynamic partition mapping table, and importing structured form data to form a dynamic partition database; constructing an asynchronous task key value pair, writing the asynchronous task key value pair into an asynchronous message queue, regularly scanning the asynchronous message queue, and when a to-be-processed task is detected, identifying whether the task queue contains a priority mark or not, and dynamically adjusting the execution priority of the task queue; and implementing multi-dimensional tax data query from the dynamic partition database based on real-time query conditions and the optimized task queue. The tedious and low-efficiency manual operation is avoided, and the processing efficiency of the form and the tax data is improved.

The invention provides a low-delay cross-chain interaction method and device based on asynchronous processing, and the method comprises the steps: a source chain generates a cross-chain message, screens the cross-chain message through an eICN node, and asynchronously transmits the cross-chain message to a target chain; the target link receives and stores the cross-chain message, and temporarily stores the cross-chain message as an unconfirmed state under the condition that the validity of the cross-chain message is not verified; after the source chain confirms a block corresponding to the cross-chain message, the eICN node sends verification data of the block to the destination chain; and the target chain performs validity verification on the cross-chain message in the unconfirmed state based on the verification data, and executes a corresponding cross-chain service logic or deletes an invalid cross-chain message according to a verification result. According to the method, the combination of a cross-chain interaction process and a block chain execution process is realized, and the cross-chain interaction time delay is reduced through asynchronous driving of message transmission and message confirmation.

The invention discloses a volunteer service work order intelligent processing method and system based on multistage classification and similarity matching, and the method comprises the steps: carrying out the differential cleaning of a work order text and case data, constructing a structured template, and carrying out the label mapping coding; through coarse-grained classification of the second-level classification model, triggering fine-grained division of the third-level classification model when a large class is specific and the confidence coefficient is in a preset interval; retrieving associated historical cases based on a semantic similarity algorithm; and constructing a dynamic prompt template according to matched case elements, and calling a large model API to generate a mediation suggestion. Further, a paging mechanism is adopted to asynchronously process the work order, store the result and integrate an exception handling mechanism. According to the method, the work order processing intelligence level can be improved, and the classification and matching efficiency can be optimized. According to the method, field adaptive learning, hybrid index optimization and dynamic Prompt engineering are fused, an intelligent closed loop from work order analysis to mediation suggestion generation is constructed, and the matching efficiency of community service resources and the scientificity of decision making are remarkably improved.

The invention relates to the technical field of data analysis, and discloses an AI-based cloud data intelligent analysis and service management system and method. The system comprises a cloud data priority division module, a resource demand prediction module, a cloud data scheduling scheme generation module and a service management dynamic adjustment module. The method comprises the steps of firstly collecting multi-source cloud data, performing data preprocessing, and then performing data priority division; secondly, introducing a hierarchical asynchronous processing architecture to construct a hierarchical neural network prediction model, and outputting a predicted value according to a data priority; establishing a resource scheduling objective function according to the predicted value, optimizing cloud data scheduling parameters in a resource scheduling process by using a multi-strategy fusion grey wolf algorithm, and generating a cloud data scheduling scheme; and finally, calculating a service management health degree, and establishing a health degree response mechanism closed-loop dynamic adjustment cloud data scheduling scheme. By analyzing and processing the cloud data, the purposes of intelligent analysis and service management are achieved, and the method is accurate and objective.

The invention provides a graph calculation method and device, electronic equipment and a storage medium, and relates to the technical field of data processing. The graph calculation method comprises the steps of determining a node task corresponding to a graph calculation task and a thread pool corresponding to the node task according to real-time system resources and task information of the graph calculation task, so that the thread pool obtains exchange data of other node tasks and node cache data in a cache module; under the condition that the node cache data is not obtained, searching a preset database in an asynchronous mode, and writing the searched node cache data into a cache module, so that the thread pool obtains the node cache data again based on a synchronous mode; and under the condition that the node cache data is obtained, performing multi-thread synchronous calculation according to the node cache data and the exchange data so as to determine a graph calculation result. According to the method and the device, through combination of synchronous processing, asynchronous processing and utilization of the preset database when the cache is missed, the overall efficiency during large-scale data processing is improved.

The invention discloses a centralized to-do processing system and method constructed based on message driving, and aims to solve the problems of dispersed to-do entrances, low processing efficiency and the like of an enterprise multi-service system. The system takes a message drive as a core, acquires to-be-handled data of each service system through an external data acquisition module, encodes the to-be-handled data through a to-be-handled management module, generates a subscription relationship, and intelligently pushes the to-be-handled data to a terminal interaction module by a to-be-handled synchronization module based on user role preference, so as to realize'message searching for people '. The message driving model covers five algorithms of transmission, routing, asynchronous processing and the like, and ensures accurate transmission and efficient processing of messages. The system unifies message formats, supports intelligent reminding and dynamic authority management, and adopts an encryption technology to guarantee safety. An enterprise does not need to reform an original system, one-stop aggregation processing of the to-do tasks can be achieved through lightweight docking, and office efficiency and cooperation experience are remarkably improved.

The invention provides an asynchronous parallel-based service processing method, system and device and a storage medium, and the method comprises the steps: initializing a service context object according to a service type identifier in a request; a preprocessing rule script corresponding to the service type is loaded and executed through a dynamic rule engine, and parameter verification, service pre-check and context initialization are carried out; a plurality of asynchronous processing rule scripts corresponding to the service types are loaded and executed in parallel, each asynchronous processing rule script corresponds to one service task and is packaged into an asynchronous task, the asynchronous tasks are executed in parallel, and a result is written into a service context object; and loading and executing a result processing rule script corresponding to the service type through a dynamic rule engine, aggregating results of the different step tasks, and generating and returning a service response after applying a final service logic. Parallel processing can be realized through a three-stage asynchronous processing architecture, multi-core CPU resources are fully utilized, and the throughput and response speed of the system are improved.

The invention provides an Internet of Things event center distributed alarm processing method based on Redis Stream, belongs to the field of Internet of Things (IoT) data processing, and realizes millisecond-level event processing by utilizing the high-performance streaming consumption capability of the Redis Stream and combining a distributed rule matching engine and a cross-device data dynamic association mechanism. Comprising the following steps that: Internet of Things terminal equipment writes data into Redis Stream according to a stream: Model: DeviceId mode to form an independent data stream; an event consumer reads the data from the stream, performs matching based on a preloaded rule, and supports cross-device linkage calculation through a metadata relation table and an SQL template; real-time duplicate removal and full-life-cycle management are carried out on alarm events through a dual convergence mechanism based on a database and a cache, and repeated alarms are eliminated; and finally, through multi-channel push and push state write-back, a closed-loop alarm system is constructed. The system adopts a layered architecture, comprises an event acquisition layer, a rule processing layer, an event management layer, a push service layer and an asynchronous processing layer, has the characteristics of high throughput, strong orderliness and high reliability, and can effectively improve the alarm processing efficiency and accuracy in a large-scale Internet of Things scene.

The invention discloses an API (Application Program Interface) paging query method based on a streaming data request, and relates to the technical field of data processing. Comprising the following steps: 1, generating a data identifier and a vernier; 2, performing paging request and data acquisition; 3, data updating and consistency processing are carried out, wherein when the data of the data source is updated, the server maintains a data change log; when a paging request is processed, the server performs consistency check and adjustment on returned data according to the data change log and the vernier; 4, streaming data processing and real-time guarantee are carried out, specifically, for continuous streaming data requests, the server adopts an asynchronous processing mechanism, the requests are put into an asynchronous task queue to be processed, and meanwhile a temporary response is returned; the server asynchronously obtains the data in the background, and pushes the paging data to the client after the data is asynchronously obtained; 5, a cache mechanism is optimized, specifically, the server is provided with multiple levels of caches, and paging data with frequent requests and small data changes are preferentially obtained from the caches; and when the data of the data source changes, the cache is updated in time.

The invention relates to the technical field of artificial intelligence and distributed computing, in particular to a multi-agent-based asynchronous collaboration method and system, and the method comprises the following steps: S1, user input and intention analysis; s2, task decomposition and asynchronous distribution; s3, asynchronous processing of the sub-agents and generation of an intermediate result; s4, result aggregation and standardized output; s5, result output interacts with user feedback; according to the invention, a decoupling cooperation mechanism of the main control agent and the plurality of functional sub-agents is introduced at the architecture level, and an asynchronous concurrence and cache control strategy is combined, so that efficient cooperation and smooth data transmission among the multiple agents are realized, the result accuracy is ensured, the overall throughput and the interaction response speed of the system are remarkably improved, and the system performance is improved. Through a multi-agent asynchronous cooperation architecture, the processing efficiency and reliability of complex interaction tasks are effectively improved, and high universality and commercial application value are achieved.

The invention provides an OFD archive file retrieval method and system, and the method comprises the steps: receiving file data, and carrying out the authentication verification of the file data; splitting the file into file units and storing the file units into a message queue for asynchronous processing in sequence; extracting text information, table information and picture information in the OFD file to generate comprehensive text information; preprocessing the comprehensive text information, and recording the occurrence frequency of each segmented word and the corresponding page number; creating an index in a search engine cluster, wherein an index field comprises a file ID (Identity), word segmentation content, occurrence frequency and a page number; searching according to an input keyword, and arranging results in a descending order according to the occurrence frequency of word segmentation; and marking the page number of the keyword for retrieval and positioning. The method has the beneficial effects that rapid analysis and preprocessing of large-scale OFD data are realized through asynchronous processing of the message queue and an OCR (Optical Character Recognition) technology; redundancy is reduced through coarse-grained word segmentation during indexing, and recall is enhanced through fine-grained word segmentation during retrieval; the keyword granularity input by the user is adapted, and the retrieval scene adaptability is improved.

The invention relates to the technical field of computers, and discloses a business process processing method and device, equipment, a storage medium and a product, and the method comprises the steps: responding to a middle eigencode asynchronous request of a middle eigencode asynchronous application interface, determining the event type of the middle eigencode asynchronous request, and generating an initialization event; distributing the initialization event to a corresponding service monitor according to an event type based on a middle-eigencode general control monitor, and triggering a robot to process a request to obtain a middle-eigencode processing result; and returning a target medium eigencode corresponding to the medium eigencode asynchronous request according to the medium eigencode processing result. According to the method, real-time triggering and asynchronous processing of the task are achieved through the event-driven mechanism, the monitor module and the robot interface, the method is applied to the middle eigencode query task, the processing efficiency, the resource utilization rate and the system reliability are remarkably improved, meanwhile, the maintenance complexity is reduced, and the requirements of services for processing timeliness and system stability are met.

The invention discloses a multi-type XML (Extensible Markup Language) equipment data processing method and device based on Netty. The method comprises the following steps: constructing a TCP long connection server through a Netty framework to receive a device coding data message; decoding and decompressing the message to obtain XML format data; analyzing the XML data to extract a type identification field; routing the data to a corresponding service processing strategy according to the type identification field; packaging the data into a processing task, and delivering the processing task to a corresponding thread pool for asynchronous processing based on the priority; and finally, converting the processed data into a unified data structure and storing the unified data structure in a database. High-concurrency receiving and processing of equipment data are achieved, multi-type XML message analysis is supported through dynamic routing, key data processing timeliness is guaranteed based on priority scheduling, the data processing throughput is improved by adopting an asynchronous mechanism, and high-concurrency receiving and processing of equipment data are achieved through a unified data conversion standard storage structure. And the efficiency, the real-time performance and the expandability of data processing are remarkably improved.

A high-concurrency storage method and system for massive image files, and a readable medium, relating to the technical field of image file storage. The method comprises: putting a storage request of a user into a message queue and a distributed cache, and performing asynchronous processing on the storage request; taking out, from the message queue, the storage request having undergone asynchronous processing, and allocating the storage request to a thread pool; when threads in the thread pool take out storage tasks from the message queue, performing storage on the basis of the storage tasks; and combining similar storage tasks in the thread pool into a batch processing request, and sending the batch processing request to a server at one time. For a high-concurrency storage request, the throughput and efficiency of a system can be improved; batch processing of similar requests reduces the overheads of requests and increases the storage processing speed; and with the increase of data volumes, the capacity and the processing capability of a storage system are effectively and simply expanded.

The invention provides a firmware management method and system, a storage medium and a program product. The method comprises the following steps: marking a firmware exclusive analysis class in advance through a (at) Firmware Type custom annotation, and defining a multi-product line verification rule by adopting a configuration file in advance; receiving a firmware uploading request, creating a corresponding asynchronous processing task, and temporarily storing a corresponding firmware file to the temporary storage path; obtaining a matched firmware analysis rule in the central rule base, and instantiating a corresponding (at) Firmware Type firmware exclusive analysis class to obtain analyzed firmware data; sequentially executing version preprocessing, dynamic rule matching and version verification on the analyzed firmware data according to a multi-product-line version verification rule; the firmware passing the version verification is intelligently stored; and cleaning the temporary file, and executing physical deletion on the firmware file with the reference return to zero stored in the formal storage path. By means of the technical scheme, the problems that an existing analysis rule is rigid, rule modification is tedious, and the storage utilization rate is low are solved.