83results about How to "Realize dynamic management" patented technology

The invention belongs to the technical field of network transmission, and particularly relates to a time-sensitive network flow routing and scheduling method based on centralized control. Comprising the steps that CNC constructs network topology and generates global topology information; the CUC collects demand information of each to-be-transmitted traffic from each source node and divides traffic priorities according to the demand information; the CNC generates an optimal transmission path for each flow according to the global topological information; the CNC distributes a transmission time slot for each flow and dynamically adjusts the transmission time slot; carrying out synchronous distribution on the optimal transmission path and the transmission time slot, optimizing the transmission time slot and controlling the jitter of the transmission time slot; a scheduling table is generated according to the final distribution result of the paths and the time slots, and the CNC distributes the scheduling table to each network device; when the network state is changed, the scheduling table is dynamically adjusted to realize real-time routing and scheduling of the flow; according to the invention, the dynamic management of the flow priority is realized, the utilization rate of network resources is enhanced, and the service quality and high availability of transmission are ensured.

The invention belongs to the technical field of building construction safety management, and provides a construction safety early warning method and system based on mixed reality, and the method comprises the steps: converting the longitude and latitude of geographic coordinate system data into plane coordinates, and converting the plane coordinates into a local coordinate system of a spatial mapping grid formed by simultaneous positioning and a map construction technology; through coordinate transformation, geographic coordinate system data can be accurately mapped into a model space coordinate system of the mixed reality equipment, the limitation that external high-precision positioning data are difficult to integrate in a traditional mixed reality technology is broken through, and high-precision equipment positioning is realized; meanwhile, an initial weight value is distributed to each grid unit in the space mapping grid, the weight is dynamically adjusted to change the size of the grid, dynamic management of space mapping grid data is achieved, detailed real space mapping grid data can be reserved after initial alignment is carried out through the space mapping capacity of mixed reality equipment, and the space mapping capacity of the mixed reality equipment is improved. And a data basis is provided for subsequent dynamic collision detection.

The invention relates to the technical field of land resource management, in particular to a land resource management method and system based on big data analysis. The method comprises the following steps: acquiring multi-source land resource acquisition data; carrying out asynchronous parallel data acquisition on the multi-source land resource acquisition data so as to generate multi-source land resource real-time acquisition data; performing request-response optimization on the multi-source land resource real-time acquisition data to generate a self-optimization transmission parameter set; performing precision error correction on the standard multi-source land resource real-time data by using the self-optimization transmission parameter set to generate land resource correction data; performing nonlinear feature enhancement processing on the land resource correction data to generate a nonlinear enhanced feature matrix; and performing dimension compression processing on the nonlinear enhanced feature matrix to generate a multi-dimensional spatial-temporal feature matrix. According to the invention, the comprehensiveness and accuracy of land resource management are improved by improving data acquisition, processing, prediction and planning methods.

The invention discloses an enterprise computing power resource allocation scheduling method and system, and particularly relates to the technical field of resource allocation scheduling. A test task is generated by simulating a real scene, scheduling success rate fluctuation features and conflict resolution efficiency features are extracted, scheduling accuracy is evaluated through a machine learning model, and accuracy scheduling, incomplete accuracy scheduling and inaccuracy scheduling are classified according to results; for accurate scheduling, an existing strategy is kept, and continuous monitoring is carried out; for inaccurate scheduling, an algorithm is reconstructed; for incomplete accuracy scheduling, the proportion of the resource pool is dynamically adjusted by predicting the abnormal degree, and the low-priority task is switched to the standby resource pool when the abnormal degree is high, so that the rationality of resource allocation and the scheduling accuracy are remarkably improved, and the real-time performance and the resource utilization efficiency of the key task are guaranteed; and the system scheduling failure rate and the economic loss caused by resource conflicts are reduced.

The invention relates to the technical field of intelligent agriculture, in particular to an irrigation area measurement and control integrated gate intelligent scheduling system and method, and the system comprises a data collection module, a gate control module, a data processing and analysis module, an intelligent scheduling module and a monitoring and early warning module. By integrating a water level sensor, a flow meter, a weather station data interface, a soil humidity sensor and an agricultural satellite data interface, various agricultural data and hydrological data in an irrigation area are collected in real time, and the crop growth condition, the water demand, the rainfall capacity, the evaporation capacity and the like are analyzed by utilizing historical data and models; therefore, an accurate irrigation scheduling strategy is formulated and executed in the intelligent scheduling module, water supply needed by crop growth is ensured, meanwhile, the system monitors agricultural data and hydrological data in an irrigation area in real time through the monitoring and early warning module, a reasonable threshold range is set, early warning can be triggered in time once an abnormal condition occurs, and the system is safe and reliable. And a reliable decision basis is provided for irrigation area management.

The invention relates to the technical field of power system control, and discloses a flexible load control technical method based on a high-current switch built-in electric energy meter, which comprises the following steps: monitoring current and voltage in real time, and inputting data into a fuzzy logic control system; formulating a fuzzy rule, and judging a current state through fuzzy logic control; implementing a safe load removal and reset strategy for a super-capacitance power utilization scene, and executing an overcurrent opening operation; setting a maximum load threshold value according to different power utilization environment characteristics, and formulating a load control strategy; and a multi-stage power control scheme is implemented, and a load control security authentication mechanism is established. According to the method, electricity utilization characteristic research in typical application scenes is carried out, a load flexible control technology is researched in combination with a switch built-in scheme, a multi-scene and multi-cost control strategy is made through multi-stage power control, overcurrent opening and self-adaptive closing functions, flexible control over power consumers is achieved, and the electricity utilization management level is improved.

The invention aims to provide a reinforcement learning-based dynamic connection optimization method for high-frequency wire harnesses of new energy equipment, and relates to the technical field of new energy, and the method comprises the steps: 1, collecting the operation data of each battery module of the new energy equipment, and building a state vector in combination with the high-frequency wire harness characteristic data of each high-frequency wire harness in the new energy equipment; 2, calculating a predicted temperature distribution vector based on the state vector and the temperature distribution vector; based on the state vector, the high-frequency wire harness stress and the predicted temperature distribution vector, constructing a state space and an action space of a reinforcement learning model; 3, defining a reward function of the reinforcement learning model; and completing dynamic connection optimization of the high-frequency wire harness in an iterative optimization mode. According to the invention, the stability, the energy efficiency and the safety of the system are obviously improved, and the service life of the high-frequency wire harness and the connection point is effectively prolonged.

The invention provides a tunnel construction progress dynamic management method and system, and the method comprises the steps: obtaining a key construction path with the longest construction period in a plurality of project construction paths in a tunnel construction project; inputting the rate influence factor data of each sub-construction project into a pre-trained tunnel construction rate prediction model, outputting a construction rate prediction value of each sub-construction project, and dividing the workload of each sub-construction project by the corresponding construction rate prediction value to obtain a predicted construction period of each sub-construction project, adding to obtain a tunnel predicted construction period of the tunnel construction project and determining a construction plan date; dynamically setting a plurality of monitoring time points according to supervision requirements of a tunnel construction project, and calculating a current progress deviation rate and a dynamic target construction period deviation rate of each monitoring time point to obtain a construction period delay index; and judging the construction progress of the tunnel construction project at each monitoring time point according to the construction period delay index, and performing prompting and early warning so as to guide and adjust the subsequent construction progress of the tunnel construction project.

The invention relates to the technical field of greening management, in particular to an urban greening state monitoring method and system based on digital mirror image information, and the method comprises the steps: collecting the real-time live-action data of a designated city, combining the real-time operation rule of the city, and generating a virtual city update mirror image through a digital twinborn technology; extracting digital mirror image information in a specified time period from the virtual city updated mirror image to obtain greening state mirror image data, and generating a virtual city greening state by analyzing the mirror image data; further detecting the greening state of the virtual city, generating greening state early warning information, and feeding back the greening state early warning information to the real city to determine a monitoring area and a monitoring index; and performing live-action monitoring on the designated area of the real city, collecting and analyzing monitoring data to obtain an actual monitoring result of the alarm area, and synchronizing the actual monitoring result to the virtual city update mirror image. Dynamic monitoring and bidirectional feedback of the greening state are realized, and technical support is provided for fine management and scientific decision-making of urban greening.

The invention relates to the technical field of remote sensing image on-orbit real-time processing, in particular to a low-redundancy-rate image segmentation method and system based on an FPGA, and the method comprises the steps: determining the maximum physical size of a target object; calculating a first maximum pixel value occupied by the target type object in the remote sensing image according to the maximum physical size of the target type object; performing correction calculation on the maximum physical size according to the side-sway angle during satellite imaging to obtain the maximum physical size of the target object after side-sway distortion is considered; calculating a second maximum pixel value occupied by the target type object in the remote sensing image according to the maximum physical size of the target type object after side-sway distortion is considered; taking the maximum value from the first maximum pixel value and the second maximum pixel value as an overlapping region setting value; setting an overlapping region setting value as a sliding window segmentation step length; and carrying out sliding window segmentation on the segmented sub-graphs according to the sliding window segmentation step length. According to the method and the device, the minimization of the overlapped region of the segmented sub-images is realized, the segmentation redundancy rate is reduced, and the data storage and transmission quantity is reduced.

The invention discloses a database access method and device for preventing user data leakage in a container, and the method comprises the steps: a business service sends a connection establishment request to a database service; a database side vehicle service hijack connection establishment request which has the same POD with the business service and is different from the business service in a container contai ner; the database side vehicle service analyzes a database protocol, modifies a user name and a password in the connection establishment request, and forwards the modified connection establishment request to the database service; the database service performs user name and password verification based on the modified connection establishment request, and returns a response after the verification is passed; and the database side vehicle service receives the response of the database service and forwards the response back to the business service, and the business service establishes database connection with the database service. According to the invention, the database side vehicle service is introduced between the business service and the database service, all database connection requests are intercepted, and the business service does not need to know the user name and password of the database when connecting the database, so that the leakage of certificates is avoided.

The application provides a multi-agent cooperative task state management and abnormal backtracking method and system, relates to the technical field of artificial intelligence, and comprises the following steps: obtaining interaction data, state data and execution logs, constructing an initial task knowledge graph based on an ontology model, establishing a bidirectional causal chain by using a Bayesian network to form a dynamic knowledge graph, analyzing state migration rules when an abnormality is detected, identifying a propagation node, constructing an abnormal propagation subgraph, generating an influence chain, determining a recovery priority and triggering state rollback. The method can quickly trace the abnormal source, effectively control abnormal diffusion, and improve system robustness and task recovery efficiency.

The invention discloses a guide vane wear prediction method and system based on deep learning, and belongs to the technical field of mechanical fault prediction and maintenance, and the method comprises the steps: collecting real-time sensor data of guide vanes, and integrating historical wear data of similar guide vanes; identifying similar features of similar guide vanes, extracting key wear modes through the similar features, and establishing corresponding prediction models for different guide vanes; and based on the extracted features and the prediction model, analyzing the wear condition of the guide vane, and providing a wear prediction result. Through comprehensive monitoring and data analysis, the accuracy of guide vane wear prediction is improved, and the reliability of equipment operation is ensured. Through a real-time alarm system, dynamic management of different wear degrees is realized, maintenance work is effectively guided, fault risks are reduced, the service life of equipment is prolonged, and the operation and maintenance efficiency is improved. According to the invention, the abrasion problem can be prevented in advance, and the normal operation and safety of the water turbine are guaranteed.

The invention relates to an elevator control method and device based on multiple scenes and computer equipment, and relates to the technical field of intelligent linkage. The method comprises the steps that body characteristics, a target floor and passenger flow information of an elevator waiting object in an elevator waiting hall are obtained, elevator use requirements are analyzed, and a scheduling scheme is determined. And after the elevator waiting hall outputs the guide information, the resident and external elevator waiting objects are identified by using the elevator climbing video data, resident building linkage data are generated based on historical behaviors of the resident objects, and customized behavior guide is provided. And for an external object, external building linkage data is generated according to the elevator waiting behavior of the external object and is analyzed and managed by the monitoring center. By the adoption of the method, dynamic elevator control and elevator linkage can be achieved, and elevator dispatching accuracy and dynamic management of building passenger flow are further achieved.

The invention discloses a network asset risk monitoring management system and method, and relates to the technical field of network asset management, and the method comprises the steps: collecting the data of network assets in real time according to preset network asset parameters; constructing asset risk analysis characteristics according to the network asset parameters, preprocessing the data of the network assets, and calculating values of the asset risk analysis characteristics according to the preprocessed data of the network assets; asset risk analysis features are combined to form feature vectors, and a comprehensive risk coefficient is calculated through multi-dimensional nonlinear combination and weight adjustment; and setting a threat level threshold according to the comprehensive risk coefficient, judging the risk level of the current asset, and executing a monitoring management strategy according to the risk level. Through real-time dynamic monitoring, multi-dimensional risk feature analysis, a flexible risk level adjustment mechanism and accurate threat identification and response, an efficient, accurate and flexible security risk management method is provided for network assets, and the accuracy of risk assessment and the response capability of management are effectively improved.

The invention discloses a computer resource management method and system based on artificial intelligence and a medium, relates to the technical field of computer resource management, and solves the problems that a current computer cannot dynamically manage memory resources, and the high memory resource occupancy rate caused by user behaviors is easily recognized as application program exception. The method comprises the following steps: acquiring real-time memory resource data of a running application program in a computer and historical memory resource data of the computer; performing memory occupation detection analysis on the memory consumption of the computer, and performing detection analysis to obtain a real-time memory consumption index of the computer; detecting and analyzing the real-time memory consumption of each application program in the computer; according to the method, the application abnormal data of the application program is obtained, then the abnormal type of the application program is detected through the application normal data and the application abnormal data, corresponding management is conducted according to the abnormal type of the application program, and dynamic management of memory resources in a computer is achieved.

The invention discloses a charging data management method and device, equipment, a medium and a product, and relates to the technical field of new energy automobiles, the method comprises the steps that a data access request sent by a user side is acquired, and the data access request comprises access data content and an authorization sequence corresponding to the user side; the authorization sequence is a string of digital sequences automatically generated when the user table is created, and the authorization sequence is in one-to-one correspondence with users of the user side; acquiring a data value stored in a pre-created data table based on the authorization sequence, and generating an authorization strategy table corresponding to the user side based on the authorization sequence and the data value; generating an authority list based on the authorization sequence and the authorization strategy table; and performing permission proofreading on the access data content based on the permission list, and responding to a data access request of the user side according to a proofreading result. According to the invention, the confidentiality and security of the charging data of the charging management platform can be improved.

The present invention is applicable to the technical field of new energy, and provides a method and device for load regulation, wherein the method for load regulation includes: collecting real-time microgrid load, electric energy storage capacity of energy storage module and real-time power generation; calculating the electric energy consumption within a preset time period according to the real-time microgrid load; regulating the power generation module, energy storage module and / or main grid to supply power to the microgrid load according to the electric energy consumption, electric energy storage capacity and real-time power generation. This technical solution achieves a significant improvement in the microgrid in terms of supply and demand balance, resource optimization configuration, power supply reliability and safety, and better balances the power supply and demand between the microgrid load and multi-source power supply (power generation module, energy storage module and main grid, etc.).

The invention relates to the field of multi-robot cooperative scheduling, and discloses a multi-robot cooperative scheduling unmanned underground mechanical garage system and method, and the system comprises a hardware subsystem which comprises a transfer robot, a parking space frame, a vertical elevator, and an entrance and exit junction area; the control system is deployed in the central control server, and the control system comprises a multi-layer dynamic data grid generation module which is used for constructing a discretized data grid corresponding to a garage physical space; and the central data calculation module is used for continuously updating the data of each data layer in the multi-layer dynamic data grid according to the real-time state of the garage. In the regional congestion degree and traffic control layer, the congestion index is calculated according to the density, the speed variance and the dispersion in the movement direction of the transfer robot, and the task gravitation modulation coefficient is generated, so that the tendency of the robot to enter the crowded region is reduced, the adaptive dispersion of the traffic flow is promoted, and the continuity of garage operation is maintained.

The present application relates to the technical field of energy management, and especially relates to a water, electricity and gas comprehensive energy management platform for smart city, which comprises an environment sensing module, which is used to determine a typhoon radiation influence area in a target city when the target city enters a typhoon mode; a grid re-partitioning module, which is used to divide a plurality of modified city land blocks; a function area marking module, which is used to obtain a function area mark of a dominant category of each modified city land block; an energy distribution module, which is used to obtain a typhoon day unit electricity minimum reserve benchmark value corresponding to each modified city land block; a hoarding behavior identification module, which is used to determine whether there is energy hoarding behavior, and determine a hoarding behavior category when there is; and an abnormal expansion determination module, which is used to perform abnormal expansion determination to obtain an abnormal expansion determination result when a second duration risk level is obtained. The present application realizes intelligent management of city energy distribution by hoarding analysis and abnormal expansion determination on the typhoon radiation influence area.

The invention discloses a data center engineering total package management system and method, and the system can automatically carry out the corresponding adjustment of an engineering progress through the arrangement of a project management module, a warehouse management module, a document management module, a personnel management module and a system management module, achieves the dynamic management of an engineering project, and improves the management efficiency. The management efficiency of the engineering project is improved, meanwhile, the engineering management efficiency is improved, an administrator and a constructor exchange information through the control module, and information communication among departments is facilitated. The invention further relates to a project total package management method. The engineering management efficiency can be improved, an administrator and a constructor exchange information through the control module, information communication among departments is facilitated, the engineering progress can be automatically and correspondingly adjusted, dynamic management of the engineering project is achieved, and the management efficiency of the engineering project is improved.

The embodiment of the invention provides a CPU load management method and device of a Unix system and a computer readable storage medium. The method comprises the following steps: correspondingly registering a target thread task needing to be monitored into an SIGURG signal processing function based on the type of a thread task when an application running in a CPU (Central Processing Unit) of a Unix system creates the thread task according to a use requirement; periodically reading a preset system file in the Unix system, and calculating the actual utilization rate of the CPU processor in the latest period based on CPU processor activity information in the system file; and comparing the actual usage rate with a preset threshold value, when the actual usage rate is greater than the threshold value, sending an SIGURG signal to the target thread task to enable the target thread task to enter an SIGURG signal processing function and turn into a sleep state, and when the actual usage rate is less than or equal to the threshold value, sending an SIGURG signal to the target thread task to enable the target thread task to enter an SIGURG signal processing function and turn into a sleep state. And sending the wake-up condition variable to the target thread task to enable the target thread task to run normally. According to the embodiment, the cost is low, and the dynamic adjustment of the CPU utilization rate can be realized.

The application discloses a memory management method and electronic equipment, and relates to the technical field of computers, including any controller of a target cluster, based on the current memory management parameter of the controller, performing corresponding memory configuration on the controller, and running a preset test case on the controller to obtain the performance index of the controller under the current memory configuration, determining the fitness function value of the controller under the current memory configuration, and then determining the self historical optimal memory management parameter of the controller; if the current iteration number does not reach the iteration number threshold, updating the memory management parameter based on a target update speed, and continuing iteration based on the updated memory management parameter; if the current iteration number reaches the iteration number threshold, performing corresponding memory configuration on the controller based on the self historical optimal memory management parameter of the controller. The application realizes dynamic management of the memory of the controller, and achieves the technical effect of improving the memory utilization rate.

This application provides an intelligent battery swapping cabinet system with early warning of thermal runaway, relating to the field of new energy technology. It includes a data acquisition and labeling module and a location risk analysis module. If the overall hazard level exceeds a preset threshold, a risk judgment basis is constructed based on the degree of location and quantity impact. A weighted analysis method is used to prioritize the processing of each battery, resulting in an intervention target sequence. Based on the intervention target sequence, combined with the risk propagation range and fault propagation path, an emergency process adjustment plan is dynamically generated. The intervention strategy is iteratively updated through real-time monitoring data to determine the final intervention execution path. This intelligent battery swapping cabinet system with early warning of thermal runaway significantly improves the early warning capability and overall safety and reliability of the swapping cabinet under complex operating conditions, reduces the probability of accidents, and enhances the safety assurance level of new energy battery swapping infrastructure.

The present invention relates to a test resource dynamic management system, method and storage medium. The method comprises: obtaining a test task and parsing the test task; obtaining the closedness attribute of each test case; obtaining the dependency relationship of the test case relative to the test resource; executing the test environment required for the test case in the test tool; when applying for the test resources required for the test from the test system in the order of the test case execution, judging whether the required test resources exist in the resource pool, directly allocating them to the test case for use if yes, and requesting the system to allocate new test resources if no; executing the test case using the test tool; and judging whether the test resource is reused in the subsequent test case according to the dependency relationship between the test case and the test resource after the test case is executed, and if yes, reclaiming the test resource, and if not, putting the test resource back into the resource pool.

The invention discloses a building indoor intelligent identification management system based on geographic information, and belongs to the technical field of indoor intelligent identification management, and the system comprises the steps: comprehensively collecting the indoor multi-dimensional information data of a building through integrating laser scanning, Wi-Fi and Bluetooth signal intensity measurement and a built-in sensor of user equipment; using the multi-source data fusion positioning model to calculate user real-time position coordinates, and uploading the user real-time position coordinates to a user terminal; traversing the multi-dimensional information data to obtain the real-time position, advancing direction and speed of the user, and calculating a predicted position coordinate; calculating the distance between the position information of each identifier and the predicted position coordinate, comparing the distance with a preset radius, and judging to obtain a first identifier, and dynamically adjusting the display priority of the first identifier; optimizing and adjusting the size and brightness of the first identifier according to the priority of the first identifier and the indoor environment light intensity; the first identifier is received and displayed through the user terminal, and dynamic updating of the real-time position of the user is achieved.

The utility model provides an intelligent transfer type automatic feeding platform capable of achieving centralized feeding, belongs to the technical field of plastic extruding machine corollary equipment, and solves the problem that a traditional manual feeding mode is insufficient. A feeding transfer layer plate of the feeding platform is erected above the plastic extruding machine through a frame body, and the plastic extruding machine is provided with a feeding port in the vertical direction. A feeding opening is formed in the vertical projection position, corresponding to the feeding opening, of the feeding transfer layer plate, and the feeding opening communicates with the feeding opening; an elevator is arranged on one side of the feeding and transferring layer plate and is used for lifting or descending the ton bag between the ground and the feeding and transferring layer plate; the conveyors are respectively arranged at a ground entrance and exit of the elevator and an entrance and exit of the feeding and transferring layer plate, and are used for inputting and outputting ton bags at the elevator; the AGV trolley is used for transferring ton bags on the feeding transfer layer plate; according to the utility model, the manual intervention can be reduced, the key functions of continuous feeding, energy consumption reduction, material tracking and the like are realized, and the efficiency of the extrusion molding process and the product effect are improved.

The invention discloses a power distribution intelligent management system based on artificial intelligence, and the system comprises an acquisition module which collects the current power utilization data of a power utilization area; the acquisition switching module is respectively connected with the power distribution processing module and the acquisition module; the power distribution processing module is respectively connected with the acquisition switching module and the electric energy conversion module, and controls the acquisition switching module to work so as to send a control signal to the corresponding electric energy conversion module according to the input current power consumption data of the power consumption area; the electric energy conversion module is connected with the energy storage module and controls the energy storage module to charge and discharge according to the control signal; a preset AI model is stored in the power distribution processing module, current power consumption data and historical power consumption data of the power consumption area are input to the AI model, and future power consumption demands and equipment hidden danger information corresponding to the power consumption area are output. And generating a control signal according to the future power consumption demand of each power consumption area, the equipment hidden danger information and the future weather information corresponding to the power consumption area.

The application discloses an adaptive industrial park power equipment intelligent management system, comprising: a park equipment information acquisition module for constructing a mapping relationship between equipment rooms and equipment types; a multifunctional linkage control module for generating a linkage priority list between multifunctional groups; an equipment state evaluation module for constructing an equipment state evaluation model and identifying the state type of the equipment; a linkage control sequencing module for determining the execution sequence of each equipment in the linkage control process; a linkage control execution module for generating an initial linkage control strategy and updating a control topology state; a patrol task management module for executing a patrol task and updating a patrol state and a linkage control instruction; and an equipment alarm and processing module for generating an alarm event list and classifying and distributing alarm information. The application effectively solves the problems of lack of dynamic adjustment of linkage control and low patrol efficiency in traditional power equipment management, and significantly improves equipment operation stability and management efficiency.

The invention discloses a multi-card cluster heterogeneous scheduling method and system based on an event bus, and relates to the technical field of distributed computing and resource management. The method comprises the steps that functions of heterogeneous computing hardware resources are packaged into a plurality of independent services, and each service provides a standardized interface and hides bottom layer hardware details; the computing task is disassembled into a service calling chain formed by a plurality of services according to a preset sequence; receiving, distributing and processing various events generated during system operation through an event bus, wherein the events at least comprise a node calling event, a service scheduling event and an abnormal event; wherein the event is subjected to asynchronous processing by utilizing a dynamically telescopic thread pool, and the node calling event is subjected to flow control. According to the method, the problems that a static and tight coupling mode is usually adopted in a traditional resource management method, upper-layer application development difficulty is large, portability is poor, task reconstruction cost is high, and the method is difficult to adapt to dynamically-changing calculation loads and complex heterogeneous environments are solved.