409 results about "Thread pool" patented technology

The invention relates to a lightweight asynchronous message processing method and system for a high-concurrency scene, and the method comprises the steps: receiving a message request of a client, carrying out the preprocessing of the message request, and generating a to-be-processed message; distributing the to-be-processed message to a multi-level priority queue based on a priority scheduling mechanism; dynamically adjusting the number of core threads and the maximum number of threads of the thread pool according to the resource state data, and forming a thread pool resource configuration scheme of the current scheduling period; dynamically calculating the message processing quantity of the current scheduling batch based on the message accumulation quantity of each priority queue, the thread pool resource configuration scheme, the CPU utilization rate in the resource state data and the JVM heap memory utilization rate; and based on the out-of-heap memory buffer area reference, assigning the to-be-processed message object to a corresponding processing thread to execute a service processing logic until the processing operation of the messages in all the scheduling units is completed. The method has the effect of improving the resource adaptability of the asynchronous message processing architecture.

The invention discloses a cloud hard disk data backup and recovery method and device, electronic equipment and a storage medium, and relates to the technical field of cloud computing. A cloud hard disk is segmented into a plurality of segmentation blocks and a multi-thread parallel processing mode is adopted, a backup and recovery task of a large-capacity cloud hard disk is decomposed into a plurality of sub-tasks to be processed at the same time, and the data backup and recovery efficiency is improved. The operation time is greatly shortened, the number of threads in the thread pool is determined according to the number of the segmentation blocks and the current available computing resources, the utilization rate of the computing resources can be improved, cloud hard disk segmentation strategy parameters can be flexibly configured according to service requirements and cloud hard disk characteristics, data protection requirements in different scenes are met, and the user experience is improved. Consistency verification is carried out on the transmitted data, so that the integrity and consistency of the data in the backup and recovery process are ensured, the data loss risk is reduced, and the purposes of improving the backup and recovery efficiency of the cloud hard disk and enhancing the system reliability and the computing resource utilization rate 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 relates to the technical field of data management, and discloses a dynamic partitioning and priority scheduling method based on time sequence data, which comprises the following steps: collecting time sequence characteristics of an industrial data source through an edge gateway and carrying out structured storage in Redis, the time sequence characteristics comprising collection frequency, historical peak time period and service priority; load indexes are calculated based on time sequence characteristics, and a distributed message system is driven to execute dynamic partition adjustment of pre-judgment type capacity expansion, hot spot precise splitting and low-peak intelligent capacity reduction; and full-link data priority scheduling is realized through production end route isolation, Broker end resource inclination and consumption end thread pool isolation. According to the invention, the dynamic adaptation of the distributed message system resource and the industrial time series data load is realized, the real-time performance of high-quality data is ensured, the integrity of data transmission and the system adaptability are improved, and the problems of poor load fluctuation adaptation, high-quality data delay and easy data loss due to faults in the prior art are effectively solved.

The invention discloses an unmanned ship-oriented task priority scheduling and resource awareness management method, and belongs to the technical field of unmanned ship control. The method comprises the steps of obtaining a task request generated by an unmanned ship system, inputting the task request into a task classifier for task classification and priority allocation, performing real-time monitoring on resources of the unmanned ship system based on a resource perception and threshold grading model, judging an alarm interval where the resources of the current unmanned ship system are located, and sending the alarm interval to the unmanned ship system. Obtaining a target scheduling strategy; allocating each task in the task request to a corresponding thread pool for execution, dynamically adjusting the scheduling of each task according to a multi-thread pool cooperation and preemption mechanism, and dynamically optimizing the load and channel of the unmanned ship system based on a load balancing and channel selection mechanism; feedback information during execution of each task is collected, a target scheduling strategy is adjusted through an adaptive optimization mechanism, and scheduling and resource allocation of each task are updated in real time. The method improves the resource utilization rate of the unmanned ship system.

The invention relates to a multi-modal interaction-oriented automatic operation backtracking and digital person continuous talking control method and system, and the system comprises an operation snapshot module which records operation nodes through a semantic anchor point marking technology, such as an interface XPath page number and a PPT page number; the interruption detection module is used for capturing a user interruption instruction in real time; the progress prediction engine dynamically adjusts a follow-up demonstration path based on a program; and the continuous talk controller is used for coordinating RPA operation execution, digital human rendering and voice synthesis through a three-level priority thread pool. The problems of inaccurate operation flow backtracking and multi-modal thread conflict after demonstration interruption are solved, the breakpoint continuous talk error is obviously lower than that of a traditional scheme, and the method is suitable for PPT demonstration, cockpit explanation, business system training, course explanation and 3D modeling guidance scenes.

The invention discloses an RDMA asynchronous communication optimization method and system based on a lock-free queue, a medium and a processor, and relates to the technical field of remote communication. The method comprises the following steps: constructing a lock-free annular buffer area at an edge node, registering the lock-free annular buffer area as an RDMA memory area, and configuring a queue and a thread pool; the collection thread concurrently writes data, and the RDMA submission thread asynchronously completes remote transmission based on a buffer area state; and the queue processing thread performs closed-loop linkage transmission and buffer area states through'batch polling-result analysis-state synchronization-exception processing ', and dynamically adjusts the buffer area and queue parameter optimization performance at the same time. The problems that an existing RDMA scheme is poor in thread cooperation, weak in resource adaptation, not timely in state linkage and the like are solved, transmission delay and CPU overhead are greatly reduced, communication stability and the resource utilization rate are improved, and the method is suitable for edge computing and other high-concurrency data interaction scenes.

The invention provides an automatic fault-tolerant propulsion method and system for task execution abnormity and a storage medium, and relates to the technical field of distributed system fault-tolerant control, and the method comprises the steps: task dynamic arrangement: arranging tasks into a serial, parallel or dependent execution mode according to a preset dynamic rule, and realizing task trigger execution through an asynchronous thread pool; performing process monitoring, adding a monitoring annotation to an execution method of each task by using an AOP tangent, and capturing a task execution state in real time; performing abnormal grading processing, and executing a strategy according to a pre-configured three-level processing channel; spreading a dependency state, and automatically updating an associated task state based on a dependency relationship among the tasks: when an upstream task fails, pausing a downstream dependency task and marking the downstream dependency task as a waiting state, and continuing to execute a non-dependency task; and performing global state statistics, calculating a global state in real time through a task state algorithm, if all tasks are completed, marking the tasks as completed, if abnormal tasks exist, marking the tasks as abnormal, and triggering root cause analysis.

The invention discloses a large model training dynamic memory management method based on a multilayer hierarchical cache mechanism, and relates to the technical field of computer system architecture and storage. The method is managed on the basis of a dynamic heterogeneous memory unloading system, and comprises the following steps of: in an initial stage of a training task, constructing a user state access path, establishing a TensorID-LBA mapping table, and performing hierarchical caching and threshold presetting; in the training task running stage, the access popularity of each tensor is evaluated in real time; when occupation of the GPU video memory cache layer exceeds a threshold value or cold data is detected, a dynamic migration strategy is triggered, and the low-frequency tensor is unloaded to a CPU memory cache layer or an SSD storage layer; when the tensor access popularity is improved, automatically migrating back to a high-performance layer through a prediction mechanism; in the process, tensor self-adaptive migration is executed by a user mode I / O thread pool. According to the method, the high-performance I / O stack is constructed in the user mode, and the adaptive tensor unloading and hierarchical caching mechanism of the multi-layer heterogeneous memory is combined, so that the universal deployment of the system is realized.

The invention provides an event processing method, system and equipment based on Internet of Things equipment and a medium, and belongs to the technical field of Internet of Things. The method comprises the following steps: receiving an Internet of Things equipment message through an MQTT Broker, identifying an event type according to a theme, and distributing the event type to a corresponding thread pool; concurrently analyzing the JSON load in each thread pool, and converting the JSON load into a structured data object; caching the data in a batch processing queue in a classified manner, and triggering batch processing based on a queue state; extracting batch data, generating an optimized SQL statement, executing writing, and processing exceptions; screening data based on a routing rule and asynchronously forwarding the data to message middleware; meanwhile, processing parameters are dynamically adjusted according to the equipment state data and the system load. According to the invention, efficient processing of Internet of Things equipment events is realized, and the system throughput, the resource utilization rate and the data processing real-time performance are improved.

The invention relates to the technical field of meteorological data visualization, in particular to a meteorological data visualization method and device, electronic equipment and a storage medium. According to the meteorological data visualization method and device, firstly, a lightweight multi-resolution data organization unit is established based on a spatial index, a server-side pre-rendering slice is replaced, the storage pressure is reduced, and the data updating flexibility is improved; secondly, a dynamic thread pool and a load balancing mechanism are adopted, data processing tasks are intelligently decomposed and executed in parallel, client computing resources are fully utilized, the processing efficiency is remarkably improved, then coordinate conversion, interpolation and graph drawing are completed in a working thread through an off-screen rendering engine, calculation and rendering decoupling is achieved, and the system performance is improved. And finally, an incremental updating mechanism and a dirty marking technology are introduced, only local redrawing is carried out on a change area, and a cache multiplexing mechanism is combined, so that global rendering overhead is effectively avoided, and real-time, smooth and high-interactivity visualization of mass meteorological data is realized at a Web end.

The invention provides an online migration management method and device for database hotspot data and a medium, and belongs to the technical field of database migration. The method comprises the following steps: generating a hotspot object list based on hotspot statistical information collected in a preset time period; and according to the hot object list, determining a corresponding online migration task, and allocating the online migration task to a migration thread pool, so that the migration thread pool executes the online migration task based on preset migration strategies corresponding to different granularity levels. In response to an execution instruction of the online migration task, generating a corresponding hotspot object access mapping table, and configuring a preset access agent module to call the hotspot object access mapping table after performing access interception on a client request; and after a data access request from a client is received, determining a target access object corresponding to the data access request based on a preset access agent module, and forwarding the target access object to a corresponding data physical address. Through the method, the hotspot data management efficiency and the service continuity are improved.

The invention provides a concurrent scheduling and fault-tolerant optimization method and a concurrent scheduling and fault-tolerant optimization system for distributed jobs of a Spark application layer. The method comprises the following steps: acquiring a scheduling parameter, and analyzing the parameter to generate a configuration object; dividing data in a starting and ending date range according to business logic based on the configuration object, and generating a discrete data fragment list; based on the discrete data fragment list and the concurrent thread count, creating a thread pool, packaging each discrete data fragment into an independent task, and storing the independent task into a to-be-processed fragment queue; obtaining discrete data fragments through a thread pool working thread, calling SparkSession to execute service processing logic, and submitting a job to a cluster to obtain an execution result; performing judgment processing on the execution result, and recording a task processing state; based on all processing states, an execution report is generated. According to the method, the execution efficiency and the resource utilization rate of the Spark application are remarkably improved.

The invention provides a message sorting method and device, electronic equipment and a program product, original messages are obtained through a distribution thread pool, the messages of the same business process are distributed to the same to-be-sorted queue, a working thread of the sorting thread pool reads the messages and stores the messages in a thread local cache set, the sendability is judged based on the dependency relationship of the messages in the business process, and the message sorting efficiency is improved. The messages meeting the conditions are sent to the subscription queue, and the messages not meeting the conditions are reserved in the cache. According to the mechanism, the problem of disorder of messages of the same service caused by multiple switches and network delay of message middleware is effectively solved, and data inconsistency and service abnormity are avoided; unified sorting logic replaces repeated development of subscribers, so that the system complexity is reduced; through thread pool division, local cache storage and a cache strategy of messages which do not meet conditions, the interaction overhead is reduced, the message orderliness and low delay requirements are considered in a high-frequency transaction scene, and the processing throughput, the real-time performance and the resource utilization rate under high concurrency are improved.

The micro-service processing system provided by the embodiment of the invention comprises an event identification module which is used for defining a business domain event type and registering an event attribute structure; the event bus module constructs a distributed communication network containing a dual-channel message queue, and the event bus module implements partition routing according to event types; the event processing module is composed of an event producer and a consumer which are executed asynchronously, the event producer packages service actions into a standardized event data packet, and the consumer processes subscription events through a thread pool; the event storage module adopts a hierarchical log database for persistence of an event sequence and supports reestablishment of a service state according to a timestamp; and the security control module is used for implementing service authentication and event content encryption on a transmission layer. Through event bus dual-channel design, sender box transaction binding and hierarchical storage optimization, millisecond-level event processing delay is realized while the reliability of distributed transactions is ensured, and second-level state recovery can be realized based on a complete event log when a service fault occurs.

A communication-middleware-implemented architecture system and control method applicable to an automatic parking planning and control algorithm. By using an SOA concept to perform service-oriented division on data conversion logic, and by optimizing the real-time performance of software by means of EventLoop and dynamic thread pool technology, a high-performance general-purpose middleware solution compatible with a plurality of vendor perception solutions is implemented to ensure the decoupling of an automatic parking algorithm from upstream perception data, such that a vendor can freely access, in the form of a standard part, middleware designed in the present application, thereby greatly shortening a vehicle model adaptation period and reducing the mass production costs for automatic parking.

The invention is suitable for the technical field of vehicle diagnosis, and provides a vehicle diagnosis system and method, and the system comprises a processor which is connected with a plurality of electronic control units (ECUs) of a vehicle and a vehicle diagnosis device, and is used for analyzing a diagnosis configuration file in a preset folder under the condition that the vehicle diagnosis device establishes communication connection with the plurality of ECUs, and sending the diagnosis configuration file to the vehicle diagnosis device; and obtaining diagnosis configuration data of the plurality of ECUs. According to diagnosis business process parameters in the diagnosis configuration data, creating a corresponding software channel for each ECU, and packaging all configuration parameters of each software channel in corresponding straight-through structure examples; and managing straight-through structure instances of all software channels through a pointer array and a thread channel mapping table in the global management structure body. And the server is also used for receiving the global channel configuration parameters through the universal thread pool and matching a corresponding working thread for each software channel. According to the system, synchronous diagnosis of a plurality of ECU systems is realized by establishing a parallel diagnosis architecture, and the efficiency of vehicle diagnosis is improved.

The invention relates to the technical field of communication, in particular to a flow fine control method and system.The method comprises the steps that firstly, flow data of a system are collected in real time, the flow data comprise request frequency, response time, CPU utilization rate, memory utilization rate and thread pool utilization rate indexes, and then the token generation rate is dynamically adjusted based on a flow trend analysis result; generating tokens at regular time according to the adjusted rate, storing the tokens in a token bucket, and checking the state of the token bucket when a request is received: if available tokens exist, consuming the tokens and processing the request, otherwise, refusing or delaying the request, and when the system load exceeds a preset threshold value, triggering a fusing mechanism and pausing a non-key request; according to the method, the request number, the response time, the CPU utilization rate, the memory utilization rate and the thread pool utilization rate are collected in real time, and a mechanism for dynamically adjusting the token generation rate is combined, so that the load change of the system can be accurately sensed, and the problem of dynamic response lag is effectively solved.

The invention provides a multi-channel optimization method of an underlying user mode file system adaptive to KV storage, and relates to the technical field of file system and storage system optimizing.The method comprises the steps that a local channel is distributed for each user thread, and an I / O request is forwarded to a service thread; i / O requests are divided into metadata requests and non-metadata requests according to types, and the metadata requests and the non-metadata requests are processed by a main thread and a service thread respectively; and the service thread performs task scheduling through a lock-free queue and a Work-Stealing algorithm, and dynamically expands a thread pool and binds computing resources according to a channel load. By means of the mode, efficient scheduling and execution of the high-concurrency I / O request in the user mode file system are achieved, thread contention and resource bottleneck are avoided, and the overall performance and response efficiency of a KV storage system in a high-concurrency scene are improved.

The invention provides a multi-task multi-satellite telemetry data efficient processing method and system and electronic equipment, and relates to the technical field of satellite ground telemetry data processing. Comprising the following steps: dynamically allocating a task plug-in to an optimal computing node based on a resource state evaluation result of each computing node in a server cluster; uploading task registration information to a configuration center, and storing telemetering parameter configuration information contained in the information in a memory database in a key-value pair form; according to the distributed task plug-in, task telemetering data is led from a specified information source, and step-by-step subdivision is carried out on the data based on a data shunt model; and extracting a telemetering source packet based on the obtained telemetering data flow of each frequency band, and distributing a telemetering source packet analysis task through a thread pool. And on the basis of the telemetering parameter configuration information, utilizing the parameter resolving virtual thread to resolve all parameters in the source packet in parallel. The defect that high-code-rate telemetry data cannot be efficiently processed in real time in a multi-task and multi-satellite scene is overcome.

The invention discloses an HTTP (Hyper Text Transport Protocol) multi-level automatic authentication data migration method and system based on multi-task scheduling, the method realizes automatic two-way synchronization between an HTTP data source and various target storage systems through a configuration mode, and comprises the following steps: constructing a nested authentication model supporting automatic refreshing of a dynamic token, abstracting a Token refresh protocol into a configurable HTTP interface for calling, and realizing secure update of an authentication state through atomic operation; establishing a multi-dimensional parallel response verification mechanism, performing intelligent judgment based on multi-condition combination of HTTP state codes, response headers and response body fields, and accurately extracting target data through a JSON path expression; a second-level time window scheduling strategy is adopted, and high-frequency data migration in a continuous pulling mode and a timing interval mode is achieved through a thread pool and a timer; through the recursive configuration design, the defects that a traditional tool is single in authentication mode and difficult to expand are overcome, and the efficiency and reliability of enterprise-level data integration are improved.

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.

The invention provides a file co-processing method and system based on distributed multithreading and dynamic sub-libraries, and relates to the technical field of file data processing, and the method comprises the steps: obtaining a to-be-processed file, and generating a file list according to batch information; a production-consumer model is adopted, a producer main thread scans a file list, a task queue is generated, a consumer thread pool concurrently executes downloading tasks, and the maximum concurrency number is controlled through semaphore; file data are uniformly distributed to a plurality of physical storage nodes on the basis of a fragment routing algorithm, real-time updating of a mapping relation between fragments and instances is managed by utilizing a dynamic routing table, resources are preferentially allocated to high-priority file tasks on the basis of a service routing strategy, and the tasks are dynamically allocated to specified database fragments; multi-file parallel processing on a processing node is realized through a three-stage parallel model, dynamic Feign calling is carried out on a service instance dynamic route and a weight load, multi-state table state synchronous updating is carried out based on a two-stage state machine, and a processing log is saved.

The invention belongs to the technical field of data processing, and discloses a data batch processing method, device and equipment and a storage medium, and the batch processing method comprises the steps: obtaining all tasks classified into a preset target category, and forming a target task set; setting target identification information corresponding to the target category, and associating the target identification information to each task in the target task set; submitting each task in the target task set to a thread pool; for a target task in the target task set, after the target task is successfully submitted to the thread pool, obtaining a task tracking object corresponding to the target task; and when the execution state of the target task determined according to the task tracking object is execution abnormity, performing rollback on each task in all the target task sets corresponding to the target identification information. The method can be applied to business management systems of financial science and technology, medical health and the like, and solves the technical problem that high batch task processing efficiency and state consistency cannot be ensured at the same time.

The invention discloses an automatic test analysis method and system for an intelligent cockpit large model, and relates to the technical field of test analysis, when a thread pool adjustment mechanism is triggered, resource data of a thread pool in a test process of a test case is obtained, and the state uncertainty of the thread pool is calculated; obtaining all test task relationship dependency data corresponding to the test case to calculate a task dependency degree; according to the state uncertainty of the thread pool and the task dependency degree, calculating a non-regulation degree; and judging whether to adjust the thread pool according to the non-regulation degree to adjust the state of the thread pool in the automatic test of the intelligent cockpit large model. According to actual judgment, in the automatic testing process of the intelligent cockpit large model, when a thread pool adjusting mechanism is triggered, whether the state of the thread pool needs to be adjusted truly or not can be judged, unnecessary frequent adjustment is avoided, the phenomena of waste of system resources and reduction of execution efficiency are reduced, the stability of the system is ensured, testing tasks are scheduled in order, and the testing efficiency is improved. The stability of the test process is ensured.

The invention provides a non-intrusive asynchronous processing method based on transaction event monitoring. An asynchronous event is triggered through a transaction event monitor after a database transaction is submitted, it is ensured that asynchronous operation strictly follows a transaction life cycle, and the risk of data inconsistency caused by dislocation of a thread pool task and a transaction time sequence in a traditional scheme is fundamentally avoided; by intercepting a business method carrying asynchronous execution annotations and automatically extracting parameters to generate an asynchronous request event, physical isolation of business logic and an asynchronous mechanism is realized, and architecture pollution is eliminated; and further dynamically routing to an instant execution or persistent execution module according to the policy type annotated and declared, so as to provide elastic execution capability for different service scenes. Therefore, on the premise of guaranteeing transaction atomicity, a zero-intrusive and extensible asynchronous processing framework is constructed, and the reliability and maintainability of the system are remarkably improved.

The invention provides a high-concurrency and high-throughput message consumption deduplication method and device for a distributed message queue, and the method comprises the steps: obtaining a to-be-deduplicated message Key and a service type parameter, processing the synchronous or asynchronous call of a single or batch message, and generating message Key group data containing original grouping information; routing to corresponding memory queues for temporary storage according to service types to form a classification queue structure; the thread pool consumption queue is used for generating batch message Key and service type information through time-limited and batch two-dimensional batch gathering; executing batch duplicate removal in Redis through a Lua script, judging duplicate by using an incr command, and setting expiration time to obtain a processing result; and restoring the result according to the original message group and notifying the thread, and returning the Boolean value or array to the service party. According to the invention, a high-concurrency and high-throughput message deduplication function is realized.

The invention relates to the technical field of electric power system simulation, in particular to an electric power system simulation platform based on hierarchical multi-task collaboration, comprising a support layer which comprises a computer server node and a computer system and is used for decomposing a computing task into subtasks which can be executed in parallel by adopting a tile cutting technology, dynamic resource allocation is realized in combination with a thread pool and a task queue; the management layer comprises a message bus, a data exchange bus, a performance monitoring and analysis module, a computing resource management module, a computing task management module and a computing task scheduling module; the interface layer is used for constructing a multi-rate data exchange interface library and supporting real-time data sharing and cooperative computing of a cross-scale model; and the application layer comprises an electromechanical transient simulation module and an electromagnetic transient simulation module, and the electromechanical transient simulation module and the electromagnetic transient simulation module realize data synchronization and interaction through the interface library. According to the method, efficient coordination of multi-time-scale simulation is realized, and the utilization rate of computing resources and the expansibility of the system are remarkably improved.

The invention relates to a high-concurrency request processing method for reducing Linux kernel resource loss. The high-concurrency request processing method comprises the following steps: receiving a user request and extracting a routing key; the requests are distributed to one fragment in the fixed N fragments through a fragment event executor, each fragment is bound with a single thread and a bounded queue, and the same routing key requests are executed in the same fragment in a strongly sequenced mode according to the enqueue sequence; calling a coprogram state machine to push a business process in the fragment execution thread, and returning a state result of migrating to a next state, keeping a current state or terminating the process through a state processing function; dynamically triggering self-adaptive back pressure based on queue depth or waiting time delay, and adjusting a request submission strategy according to a queue filling rate and exponentially weighted moving average waiting time delay; and submitting the long blocking task to an asynchronous task subsystem, and performing isolated execution through an independent bounded queue and a small concurrent thread pool. The same-key sequence is guaranteed through fragmentation single-thread execution, and thread switching and lock contention are remarkably reduced.

The invention relates to a message processing method under an MQTT protocol, a computer program product and communication equipment, relates to the technical field of Internet of Things, and solves the technical problem of how to ensure transient response of a high-priority message in the MQTT protocol in an extreme scene at present. The method comprises the following steps: receiving a message based on a message queue telemetry transmission protocol; storing the messages in corresponding message queues according to the priorities of the messages; grouping thread pools for processing the messages according to the priorities of the messages; and executing the grouped thread pool to complete the processing of the message in the message queue. According to the scheme of the invention, the instantaneous response of the high-priority message under different network conditions can be ensured.