276 results about "Processing priority" patented technology

A system and method for adaptive real-time multi-modal compression with dynamic resource allocation provides intelligent compression optimization based on continuously monitored device conditions. The system monitors battery level, CPU utilization, and memory availability while classifying incoming multi-modal data streams comprising image, audio, text, and sensor data to determine processing priorities. Multi-objective optimization balances compression efficiency, reconstruction quality, and energy consumption using evolutionary algorithms that generate optimal parameters for an adaptive variational autoencoder. The autoencoder features dynamically selectable processing complexity, adjustable latent space dimensionality, and modality-specific processing layers. The system automatically switches between operational modes including emergency mode triggered by resource constraints, which applies maximum compression settings and intelligent data triage. Continuous learning adapts compression parameters based on observed performance outcomes, improving future optimization decisions. The system enables homomorphic operations on compressed data and provides enhanced compression performance under varying resource constraints across diverse edge computing applications.

The invention relates to the technical field of project management, in particular to a building engineering project construction quality management method and system, and the method comprises the following steps: obtaining a drawing node sequence index and comparing a process stage number, screening compliant nodes, judging the reasonability of a task configuration time sequence, analyzing the deviation of an included angle between a crack angle and a load direction, and recognizing structural abnormality. And aggregating the partition abnormal nodes to form a construction project quality risk distribution section mapping result. According to the method, the structure drawing node sequence is compared with the construction process, it is guaranteed that input data logic is unified, the task configuration reasonability is improved through input time and stage sequence cross check, a stress deviation judgment mechanism is established in the crack direction through vector included angle and load comparison, and structural logic verification of inspection data is achieved; abnormal nodes are identified according to double standards of time compliance and stress deviation, a spatial density model is constructed by combining partition aggregation with an area ratio, building quality risk distribution is accurately presented, and the problem focusing and processing priority judgment capability is enhanced.

The invention provides a construction dynamic twinning method based on the Internet of Things and BIM, and relates to the technical field of digital twinning, and the method comprises the steps: obtaining heterogeneous data streams collected by a sensor, and carrying out the analysis and classification of the data streams, and generating a standardized data set; performing semantic mapping on the standardized data set according to association rules of BIM component identifiers and data attributes to generate a component association data set; decrypting and decompressing the encrypted data packet at the cloud, analyzing the construction progress time sequence data by adopting a distributed computing framework, and generating a deviation detection result; dynamically adjusting a routing rule of a data link according to a deviation detection result, and redistributing a processing priority to optimize link configuration; updating a BIM component state based on the optimized link configuration, and generating a real-time updated digital twin model by adopting cloud computing resources; three-dimensional visual data are extracted from the digital twin model and mapped to a BIM model interface by adopting a rendering technology, so that the monitoring precision and the management efficiency of the construction process are effectively improved.

The invention discloses a two-stage scheduling model and scheduling method based on a heterogeneous multi-core processor, and relates to the technical field of computer science, the model comprises an associated subtask acquisition module used for analyzing a target task and generating a plurality of associated subtasks; the container distribution analysis module executes first-level scheduling and distributes sub-tasks to K task containers; the static priority configuration module performs second-level scheduling on the sub-tasks according to the dependency relationship to generate a processing priority sequence; the container scheduling structure generation module creates a container scheduling structure; the window distribution execution module forms a cyclic scheduling sub-sequence; and the task cross-container dependency processing module performs cross-container dependency management in the task execution process to ensure the scheduling coherence and the execution of the dependency relationship. The technical problems that in an existing heterogeneous multi-core processor, the complex task scheduling efficiency is low, and task execution is unstable are solved, and the technical effect of improving the task scheduling efficiency and the task execution stability is achieved.

The invention relates to the technical field of distributed agent collaboration and graph database query optimization, in particular to a graph query processing method and system based on multi-agent collaboration, and the method comprises the following steps: reasoning a coordination agent to analyze the semantics and intention of user query by using a large language model; a structured multi-agent execution plan is output, and an entity search agent or a relation analysis agent needing to be called is explicitly called; the agent coordinator receives the multi-agent execution plan and selects agents according to task types and task allocation; obtaining a distributed intermediate result set; starting a result aggregation mechanism, and performing typed processing, priority ranking and deduplication merging on the distributed intermediate result set to obtain an arrangement result; and outputting an answer for answering the initial question of the user. The system comprises an agent execution plan output module, a multi-task execution module and an arrangement result reasoning module. According to the method, efficient, extensible and fault-tolerant graph query processing is realized.

The invention discloses a power distribution network fault differentiation operation and maintenance first-aid repair decision recommendation method, system and device based on a knowledge graph and a medium, and belongs to the technical field of operation and maintenance recommendation, and the method comprises the steps: obtaining the real-time monitoring data of a power distribution network, and constructing a fault feature data set; based on the fault feature data set, combining with a power distribution network knowledge graph to identify a historical fault entity; extracting a corresponding operation and maintenance first-aid repair strategy from the historical fault entity, presetting an evaluation index, and calculating a strategy effect score; evaluating a fault processing priority; and sorting the candidate first-aid repair strategies according to the strategy effect score and the fault processing priority, and screening and outputting a target operation and maintenance strategy suitable for the current fault and matters needing attention of the target operation and maintenance strategy. According to the method, the geographic information system is used for positioning the fault, the distance between the fault and the first-aid repair personnel is evaluated, the processing priority is determined in combination with the emergency degree of the fault, resource allocation is effectively optimized, and response efficiency is improved.

The invention relates to the technical field of data exchange, in particular to a markup language-based data exchange method and system, and the method comprises the following steps: determining a processing priority, monitoring a load and adjusting a processing sequence, optimizing IO response time, recognizing a redundant field and evaluating a key risk, and executing key updating based on the number and complexity of data packet labels. And the tag analysis accuracy and efficiency are optimized. According to the invention, through accurate analysis of the markup language in the data packet, scheduling, transmission and analysis in the data exchange process can be optimized, and evaluation of the number of labels, the complexity of the nested structure and the field length can be realized, so that each data packet can dynamically allocate priority according to the characteristics of the data packet, thereby effectively improving the data transmission efficiency, reducing the delay and improving the data exchange efficiency. By monitoring the load and the transmission opportunity of the data packets in real time, the processing sequence of the data packets can be dynamically adjusted, and resource waste caused by overload of the data exchange system is reduced.

The invention discloses a data updating method and device for a water conservancy knowledge graph and a medium, and relates to the field of water conservancy data management, and the method comprises the steps: constructing an initial water conservancy knowledge graph based on a plurality of data sources of water conservancy data; monitoring the plurality of data sources, and judging whether a data change event is triggered or not; when the data change event is triggered, generating a knowledge graph updating task through a preset synchronization rule; when the number of the knowledge graph updating tasks is greater than 1, determining the processing priority of the knowledge graph updating tasks according to the importance of updating graph nodes in the water conservancy knowledge graph, and generating an updating task queue; and executing the update task queue, updating the water conservancy knowledge graph, and recording an update version snapshot. Through unified monitoring of a structured data source, an unstructured data source and an interface data source, the island effect of water conservancy data is broken, and unified linkage updating of cross-modal data such as reservoir attributes, monitoring reports and real-time water levels is achieved.

The invention relates to the technical field of power equipment supply chain management, and discloses a power equipment supply chain collaborative management system based on an alliance chain, comprising an alliance chain network layer: a distributed network composed of a manufacturer node, a supplier node, a logistics node, a detection node and a grid company node, each node maintaining account book consistency through a consensus algorithm; the intelligent contract execution layer comprises an order processing contract, a logistics tracking contract, a quality acceptance contract and a settlement management contract, and supports automatic execution of a business process; and the data management platform is provided with a distributed storage unit, an encryption transmission unit and an authority control unit and is used for realizing encryption storage and hierarchical access of key data. Full-process automation of order matching, production plan generation and logistics tracking is realized through an intelligent contract execution layer, an AI prediction module can pre-judge a demand peak value in advance based on historical data, a node processing priority is optimized in combination with a dynamic consensus algorithm, and manufacturer order response time is compressed.

The invention provides a multi-modal content generation AI model construction method and device based on a diffusion model, and relates to the technical field of content generation. The method comprises a multi-source data processing module, a modal priority analysis module, a serialized modal processing module, a diffusion parameter adaptive adjustment module, an interactive feedback integration module and a collaborative output adjustment module. According to the method, multi-modal data input is integrated, model parameters are dynamically adjusted, information entropy is used for evaluating the information amount of the data, the processing priority is set according to the information amount, the recognition capacity of the model for data importance is enhanced, the model parameters are adjusted in real time to adapt to the characteristics of different data modalities, and the accuracy of data processing is improved. And the generation parameters are dynamically adjusted through user feedback, so that the generated content better fits the actual demand and preference of the user, and the consistency and integration of the content are ensured, the attraction of the content is improved and the propagation effect of the content is enhanced by coordinating the style, theme and emotion of the output content.

The invention provides an integral shopping mall order rolling processing optimization method and system based on big data, and the method comprises the steps: employing a dynamic priority adjustment mechanism for a conflict order list, and adjusting the order processing priority based on the user behavior track data, including historical exchange preference, and obtaining a resource distribution scheme; integrating the order sequence through a queue reordering mechanism, reordering based on the resource allocation scheme to obtain a final processing sequence, preferentially executing the high-priority request, and maintaining the queue stability at the same time; if residual conflicts exist in the final processing sequence, supplementary resources are extracted from a preset standby inventory through a standby resource set scheduling mechanism, a complete execution plan is obtained, and the plan covers all order processing paths; and on the basis of the complete execution plan, monitoring the order processing progress, and obtaining a stable operation order flow through progress tracking and anomaly detection, real-time state feedback and iterative adjustment.

The invention relates to the technical field of automatic operation and maintenance of a power system, in particular to an automatic operation and maintenance method and system for plant-station equipment based on a knowledge graph, and the method comprises the steps: collecting static ledger data, real-time operation data and historical operation and maintenance data of the plant-station equipment, constructing a multi-dimensional association knowledge graph, creating a digital twinborn body for target equipment in a plant station, and carrying out the operation and maintenance of the plant-station equipment. Establishing a bidirectional data channel between the digital twin and a corresponding equipment entity node in the knowledge graph; and based on a state evaluation rule and a fault propagation path model preset in the knowledge graph, performing real-time health state evaluation on the target equipment by using the state evaluation rule and the fault propagation path model to generate a health index, and when an abnormality is monitored, tracing along the topological relation between the electrical connection and the equipment in the knowledge graph, the fault source is positioned, the confidence probability is calculated, risk level evaluation and processing priority ranking are carried out according to the confidence probability, an operation and maintenance diagnosis work order containing an execution time sequence is obtained, and the fault reason can be quickly traced and positioned.

The invention discloses a table-level data classification and grading method and system based on big data, and relates to the technical field of table-level data classification and grading. According to the scheme, second-level sensitive table grading response is achieved through streaming incremental calculation and dynamic semantic coupling; a finite-state machine and a Hash fingerprint technology accurately capture table structure and content mutation, and traditional batch processing delay is avoided; the multi-modal fusion model synchronously analyzes topological features and semantic vectors, and the field-level sensitivity misjudgment problem is solved; the timeliness weight mechanism guarantees real-time evaluation of a dynamic association table relationship, and is particularly suitable for a high-frequency change scene in a big promotion period; and the asynchronous architecture design isolates the calculation load, so that the processing priority of the core price list is effectively guaranteed.

Instead of a system that does not address host buffer fragmentation or saturation, utilize a different metric for command prioritization. Commands are re-ordered and prioritized based on the number of outstanding host buffers that will be released on command completion, thereby limiting and / or reducing the physical address fragmentation and host memory overhead. Command processing priority will take the number of host memory page segments represented by the command into consideration.

An artificial intelligence priority notification method and a related apparatus. The method comprises: a terminal generating first information, the first information being used to indicate a processing priority of a data unit, wherein the processing priority is used to allocate processing resources to the data unit, and the data unit is used for AI inference and / or training tasks; and, the terminal sending the first information. Hence, in this method, the terminal or a server can mark a processing priority of a data unit for an AI task, so that a network side can allocate processing resources on the basis of the processing priority, thereby improving the utilization of processing resources of the network and alleviating the problem of computing power shortage.

The invention discloses a campus equipment operation and maintenance management and control platform based on intelligent control. The platform comprises a detection module, an abnormity analysis module and a fault positioning processing module. The detection module constructs a risk vector and a cobweb coordinate system, and starts a balanced or centralized detection mode according to the cobweb area and the axial value dispersion; the anomaly analysis module judges abnormal components and marks priorities by constructing a component data matrix, analyzing a time sequence and the like; the fault positioning processing module calculates abnormal component correlation, generates a fault feature cluster, matches fault types and sorts and processes a priority sequence; according to the platform, the problems of missing multi-dimensional risk analysis, extensive fault positioning and the like in traditional operation and maintenance are solved, accurate assessment and grading detection of equipment risks, accurate judgment of abnormal components and topological positioning and scientific scheduling of faults are realized, the accuracy and efficiency of campus equipment operation and maintenance are improved, and safe and efficient operation of equipment is guaranteed.

The invention provides a database access method based on an end-side cloud system and related equipment. The method comprises the following steps: constructing the end-side cloud system of a terminal, an edge gateway and a cloud server; deploying an enterprise metadata knowledge base, an AI model and an enterprise database in the end-side cloud system based on customer requirements; receiving a demand prompt word input by a user through an intelligent agent in the terminal; a routing strategy is obtained through an intelligent agent based on deployment situations of an enterprise metadata knowledge base, an AI model and an enterprise database and by taking local gateway processing priority as a criterion; and based on the routing processing strategy, the edge gateway and the cloud server carry out programmed processing on the demand cue word. According to the database access method, the AI model is used for code generation, the development difficulty is reduced, the enterprise metadata knowledge base, the AI model and the enterprise database are flexibly deployed based on customer requirements, the terminal intelligent agent can flexibly route, and the database access method has better adaptability and can better meet the enterprise requirements.

The invention provides an autonomous controllable anti-interference time synchronization method and device based on Beidou, and belongs to the technical field of satellites, and the method specifically comprises the steps: obtaining the distribution data of different time synchronization modes which are determined to be time synchronization deviation time periods in different time periods, and employing the distribution data of the time synchronization deviation time periods which are determined to be time synchronization deviation time periods, determining a time synchronization processing time period and a time synchronization processing priority in the time period, determining a priority time synchronization processing time period by using the time synchronization processing priority, and obtaining time synchronization processing results of different time synchronization modes in the priority time synchronization processing time period; determining an adjustment processing strategy of the priority time synchronization processing period according to correction processing data in the priority time synchronization processing period and the time synchronization processing priority when it is determined that correction processing of the target device needs to be carried out in combination with distribution data of different time synchronization modes in the time synchronization deviation period in the priority time synchronization processing period, and determining the adjustment processing strategy of the priority time synchronization processing period according to the correction processing data in the priority time synchronization processing period and the time synchronization processing priority; therefore, the accuracy of time synchronization processing is improved.

The invention discloses a master control multi-serial port concurrent cooperative communication method, electronic equipment and a storage medium. The communication method comprises the following steps: acquiring a serial port communication speed and a data processing speed; constructing a cache circular queue according to the serial port communication speed and the data processing speed; acquiring at least one piece of data information transmitted from the serial port group; wherein the data information comprises a corresponding serial port identifier; generating an interrupt instruction according to the data information, and sequentially storing the data information at corresponding positions in a cache circular queue according to a serial port identifier of each piece of data information, a preset priority sequence and a write pointer of the cache circular queue; wherein the priority sequence is used for representing the processing priority of each serial port in the serial port group; and extracting the data information from a corresponding position in the cache circular queue according to a read pointer of the cache circular queue, and performing data processing on the data information. According to the invention, data loss of the serial port during communication can be avoided, and the data transmission reliability is improved.

The invention provides a real-time data processing method and system based on edge computing, and relates to the technical field of data processing.The data validity period is calculated through a composite decision model of terminal equipment physical sampling frequency constraint and preset service rules, the signal restoration accuracy requirement and the service scene emergency degree are effectively balanced, and the real-time data processing efficiency is improved. Overtime failure of key data or occupation of non-key data resources is avoided; the data transmission integrity in a bandwidth fluctuation environment is improved through a dynamic window cutting mechanism driven by a real-time network state; optimizing edge computing power load distribution in combination with a routing decision mapping strategy and a processing priority resource ratio; the terminal instruction reliability is improved based on hierarchical control of historical data abnormal value purification and geometric distance measurement; a complete technical chain from data acquisition, self-adaptive transmission cutting, aging precise arbitration and routing resource collaboration to closed-loop control feedback is formed, and the transmission efficiency, the resource utilization precision and the control stability of high-concurrency real-time data processing are enhanced.

The invention provides a multi-modal data archiving processing system based on cloud computing, and relates to the technical field of data processing, and the system is used for obtaining an archiving request and an archiving task, determining an archiving type, a processing priority and a task number according to the archiving request and the archiving task, recording a memory identifier, an execution path and a cache address of a processing node, and storing the memory identifier, the execution path and the cache address of the processing node; the method comprises the following steps: extracting a structured field group and an unstructured content block of an archiving task, mapping the structured field group according to fields to generate a structure reference table, segmenting the unstructured content block according to a time sequence to generate a content time stream, recording each field mapping and time segmentation operation, and determining a reference relationship between each field mapping and time segmentation operation and a processing node; and determining a task number, a resource state and a data fragment of each processing node to obtain state anchoring data, combining the structure reference table and the content time stream with the state anchoring data into a double-layer archiving component, and archiving the double-layer archiving component. According to the method, content backtracking and operation backtracking can be carried out on the multi-modal data archiving process.

The invention provides a grid governance event management method and system based on an event circulation mechanism, and a medium, and relates to the technical field of data processing, and the method comprises the steps: arranging edge grid nodes for a plurality of grid regions in a target governance region; after receiving and analyzing the first task scheduling strategy uploaded by the first edge grid node, the grid governance holder judges resource scheduling conflicts of concurrent events and calls out M conflict scheduling strategies of M grid governance events; and carrying out resource allocation optimization on the first task scheduling strategy and the M conflict scheduling strategies based on the event processing priority, outputting M + 1 optimized scheduling strategies, and carrying out processing task cross-department distribution. The technical problems that in the prior art, due to the fact that resource allocation cannot be dynamically adjusted, resource scheduling conflicts are likely to be generated under the condition of multi-task concurrence, the event treatment efficiency is low, and the response speed is low are solved, and the technical effects of improving the event treatment efficiency and enhancing the collaborative treatment capacity are achieved.

The invention belongs to the technical field of data association analysis processing, and discloses an industrial control system multi-modal data association analysis method based on a knowledge graph. Comprising the following steps: reading multi-modal data of equipment in an industrial control network; obtaining an initial industrial multi-modal sub-knowledge graph of each device at different time points through the multi-modal data and the mutual influence relationship between the multi-modal data, and further obtaining an initial industrial multi-modal knowledge graph; corresponding nodes in the initial industrial multi-mode knowledge graph are connected according to the physical connection relation between the devices, and a final industrial multi-mode knowledge graph is obtained; according to the connection relation between the nodes in the final industrial multi-mode knowledge graph, obtaining an exception handling priority judgment coefficient of the equipment, obtaining an exception handling priority of the equipment through the exception handling priority judgment coefficient of the equipment, and carrying out exception handling on the equipment according to the exception handling priority of the equipment; and the real-time performance of data association analysis is further improved.

The invention provides a data processing method, system and device and a storage medium, and relates to the technical field of data processing, and the method comprises the steps: receiving a plurality of task creation requests sent by a business system, and creating a plurality of business tasks; generating a first processing sequence of the plurality of business tasks in combination with the processing priority and the association index of each business task; adjusting the first processing sequence according to the resource occupation amount of each business task to generate a second processing sequence; calculating a delay risk index of each business task, and adjusting the second processing sequence according to the delay risk index to generate a target processing sequence; the delay risk index is used for representing the influence degree of the processing delay of each business task on the business; and processing the plurality of service tasks according to the target processing sequence through a preset global task monitor. The method has the technical effects that the scheduling efficiency in a complex service scene is improved, so that the overall performance of the system is improved.

The invention discloses a machining tool management method and system based on a block chain, and the method comprises the following steps: S001, carrying out the precise locking of key time points before and after the sudden change of an order in a cutting process, and generating a time anchor point set; s002, on the basis of the time anchor point set, performing hourly decomposition on the multi-channel sensing signal, extracting temporary order components and conventional business components, and drawing a supply chain loop diagram in a business coupling direction; s003, identifying a high-risk business flow path based on the supply chain loop diagram, and generating a processing priority list at the same time; s004, dynamically adjusting a signal acquisition sequence and a data fusion sequence based on the processing priority list, and carrying out slow change budget distribution on an action threshold value of a service buffer gate; and S005, executing a discrete time slot and discrete period drift arrangement process based on the adaptive dynamic regulation seed, executing reversible time grid rearrangement and carrier gating rotation on each sensing signal channel, and completing stable suppression of temporary order fluctuation backflow.

The invention discloses an intelligent manufacturing and production management method and system based on big data, and relates to the technical field of food production. Through a historical data analysis unit and a deviation correction unit, a demand prediction model is established by using a big data algorithm, and a prediction deviation rate Pp is calculated in combination with market fluctuation data; by evaluating the prediction deviation rate Pp, the algorithm is optimized to dynamically adjust the prediction model, the market demand prediction error is effectively reduced, the matching of the production plan and the actual demand is ensured, and the inventory overstock and the resource waste are reduced; meanwhile, the data processing delay rate Rd is calculated and evaluated, the system dynamically adjusts the data processing priority according to the evaluation content of the data processing delay rate Rd, it is guaranteed that key data is processed on time, and the production process efficiency is optimized; besides, an integrated efficiency index Ef is calculated and evaluated, and when Ef is smaller than a preset threshold value D, the system gives out an early warning and performs data fusion again, so that data compatibility and consistency are improved, and smooth and reliable data in production management are ensured.

The invention relates to a message processing method and device of an optical network, communication equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: receiving a wireless local area network management and control interface message from optical network master equipment; determining a processing priority corresponding to the wireless local area network management and control interface message according to the message type information of the wireless local area network management and control interface message; distributing the wireless local area network management and control interface message to a message processing queue corresponding to the processing priority; and processing the wireless local area network management and control interface messages in each message processing queue in sequence according to the processing priority sequence corresponding to each message processing queue. By adopting the method, the overall stability of the optical network can be improved.

The invention discloses a cloud networking monitoring video lightweight processing method and a cloud networking monitoring video lightweight processing system based on U-ACE. The core of the method is to construct and operate a multi-task and multi-mode AI core engine U-ACE. The processing flow comprises the following steps of: sensing an input video in real time and judging a processing priority through a sensing and priority decision module PPM of the U-ACE; for high-priority content, a deep analysis and prediction enhancement module APEM of the U-ACE is used for analysis, prediction and enhancement; self-adaptive content compression is carried out on a non-high-priority or non-key area through an intelligent compression module (ICM) of the U-ACE; in combination with user preferences, enhanced display and layered rendering are carried out by using the user preferences of the U-ACE and an intelligent presentation module UPSM; and running parameters and strategies for dynamically adjusting the engine are fed back in real time through an engine self-optimization module ESOM of the U-ACE. The processing efficiency is improved, the resource consumption is reduced, and the key content presentation and the user experience are optimized.

The invention discloses a feedback information processing method and device, computer equipment and a readable storage medium, relates to the field of data processing technology, medical treatment and health and the field of financial science and technology, can accurately understand the essence of customer feedback, avoids subjective deviation and understanding errors possibly occurring in manual analysis, and improves the processing efficiency. The method comprises the following steps: collecting feedback information of a plurality of clients for data preprocessing to obtain feedback information to be processed; based on a preset intelligent analysis module, determining an emotional tendency and demand content corresponding to each piece of to-be-processed feedback information, determining a feedback category and a processing priority according to the emotional tendency and the demand content, and sorting the plurality of pieces of to-be-processed feedback information according to the feedback category and the processing priority corresponding to each piece of to-be-processed feedback information; and based on the sorting result, determining the processing complexity corresponding to each piece of to-be-processed feedback information and a processing flow matched with the processing complexity, and processing the to-be-processed feedback information according to the processing flow.

A communication method and a related apparatus, which relate to the technical field of communications. The method can be applied to a computing node, and comprises: receiving priority indication information of a computing task to be processed, wherein the priority indication information indicates the processing priority of a computing node for the computing task, and the priority indication information is obtained on the basis of at least one of a task requirement of the computing task and subscription data of a terminal device; and on the basis of the priority indication information, scheduling the computing task to a first position of a first queue or a second queue of the computing node, or directly scheduling the computing task to a third queue, wherein the first queue is one of a plurality of different priority queues of the computing node, the second queue is a queue in the computing node that waits to access a coprocessor resource, and the third queue is a queue in a coprocessor in the computing node. The present application can ensure the quality of service for important users or computing tasks requiring a low latency.