519results about How to "Avoid congestion" patented technology

The invention discloses an AGV task allocation method and system, and relates to the technical field of automatic navigation trucks, and the method comprises the steps: carrying out the initialization of AGV state information; acquiring environment information in real time through ground sensor equipment; performing priority evaluation on the task instructions, and adjusting task priorities in real time according to emergencies; task merging and splitting are carried out; task allocation is carried out by using an ant colony algorithm, and a task allocation result is output to the corresponding AGV to guide the AGV to execute operation according to the allocated task; an optimal path is planned for each AGV, and path planning is dynamically adjusted in the task execution process of the AGVs; and optimizing a task allocation algorithm by adjusting a pheromone volatilization coefficient. Limited AGV resources are reasonably scheduled by arranging a task instruction obtaining module, a task information processing module and a task planning and distributing module, high environment perception and adaptability are achieved, and task priorities and path planning can be rapidly adjusted.

The invention provides a private domain live broadcast room hotspot prediction and adaptive routing method based on swarm intelligence, and relates to the technical field of data processing, and the method comprises the steps: constructing a dynamic interest community through a dynamic graph neural network, extracting group interaction mode features through a multi-layer graph attention network, and carrying out the group interaction mode features; the method comprises the following steps: generating time sequence correlation features in combination with an improved bidirectional gating loop unit, extracting high-order semantic features, performing hotspot prediction through a multi-task learning framework, constructing a multi-level network topology model according to a prediction result, and performing path exploration in combination with an improved heuristic search algorithm to obtain an optimal transmission path. Flow distribution is carried out through a weighted polling algorithm, a deep learning distributed load balancing controller and a congestion control algorithm are combined, the data transmission rate is dynamically adjusted, and self-adaptive routing pushing of live broadcast content is achieved.

The invention discloses a road traffic signal control system and method, and the method comprises the steps: collecting real-time data through a sensor, a camera and a geomagnetic device, combining historical data with emergency analysis, and predicting a flow mode and a change trend; green light time distribution is dynamically optimized, a fixed timing, inductive and adaptive control strategy is adopted, and traffic light duration and priority adjustment is achieved; through regional cooperation and linkage control, green wave bands and branch intersection red light optimization are set, and peak period traffic signals are intelligently dispatched. A machine learning model is used to predict a flow peak value, environment and accident detection data are combined, a signal lamp period is dynamically adjusted, vehicle waiting time, traffic efficiency, carbon emission and traffic satisfaction are evaluated, and a traffic control strategy is comprehensively optimized. According to the road traffic signal control system and method, the traffic flow in different time periods is predicted by adopting the flow prediction model based on big data analysis and machine learning, and the signal period is adjusted in advance.

The invention relates to the technical field of communication networks, and discloses a service channel time slot allocation method, which comprises the following steps of: 1, acquiring network data in real time from network equipment, the network data comprising bandwidth utilization rate, delay, packet loss rate and service flow type; 2, predicting future network flow fluctuation through a long-short-term memory network model based on historical flow data and real-time network data; and step 3, dynamically adjusting the allocation of time slot resources according to the network flow fluctuation prediction result, and preferentially allocating the time slot resources for high-priority services. According to the method, the dynamic adjustment of the time slot resources is realized by combining the flow prediction of the LSTM model and the Q-learning reinforcement learning algorithm, so that the system can flexibly allocate the resources according to the actual network load condition, the resource waste is reduced, the utilization efficiency of the bandwidth is improved, and the utilization rate of the overall network resources is remarkably improved especially under the condition of high network load.

The invention provides a monitoring video transmission method and system based on wireless communication, and relates to the technical field of monitoring video transmission, and the method comprises the steps: obtaining and preprocessing network state data, the network state data comprising bandwidth, time delay and packet loss rate; establishing a network state prediction model based on the LSTM neural network, and predicting a future network state according to the network state prediction model; based on the future network state, a multi-objective optimization algorithm is adopted to perform transmission path selection; and for the selected transmission path, video coding parameters are adjusted, the coding parameters comprise a code rate, a resolution ratio and a frame rate, and a self-adaptive transmission protocol is adopted to dynamically adjust the transmission rate according to a real-time network state. According to the method, different paths can be dynamically selected, network congestion or degradation is avoided, and the video transmission quality and rate are adaptively and flexibly adjusted according to the current network state, so that stable transmission of the video quality under different network conditions is ensured.

The invention provides a low-altitude industry chain information intelligent cooperation and airspace management platform based on federal learning. Through cluster ad hoc network and decentralized federated learning, the method is divided into three stages of data acquisition, data preprocessing and analysis application, low-altitude scene data communication of dynamic topology and static topology is realized, and the efficient communication requirement in a low-altitude operation scene is met. According to the system, differential data transmission strategies are adopted, optimization design is carried out on a single machine, a co-task cluster, a cooperative cluster and a non-cooperative cluster, and the communication efficiency and the resource utilization rate are improved. In the data preprocessing stage, federated learning aggregation of multi-source data fusion, data anonymization and decentralization is combined, and data privacy protection and safe sharing of three parties of industry, university and research are ensured. In the analysis and application stage, low-altitude aircraft task scheduling, airspace flow control and environmental condition evaluation are realized through aircraft analysis, airspace analysis, environmental analysis and digital twinborn technologies.

The invention provides a data transmission optimization method and system based on a satellite channel congestion scene, and belongs to the technical field of satellite communication, and the method comprises the steps: classifying service data, and obtaining different types of data messages; reporting the cache state report to a satellite master station; receiving uplink communication resources distributed by the satellite master station, wherein the uplink communication resources are sent after being distributed by the satellite master station based on the cache state report; determining a channel transmission state of the satellite terminal station based on the uplink communication resources and the service volume in the transmitting cache region; scheduling and sending each type of data messages according to the transmission priorities of the different types of data messages; the transmission priority is determined based on a channel transmission state. According to the invention, in a satellite channel congestion scene, key messages are scheduled preferentially by dynamically adjusting the transmission priorities of different types of data messages, so that the communication efficiency and reliability are improved under limited resources.

The invention provides an electric control box remote data acquisition system based on the Internet of Things, and relates to the technical field of data processing, and the method comprises the steps: obtaining the operation state data of an electric control box through a sensor, transmitting the operation state data through a wireless signal network, obtaining a data frame set, analyzing the data identifier of each data frame, verifying the integrity of the data, and obtaining the data frame set; determining performance parameters of the wireless signal network, detecting whether an abnormal change occurs in the transmission process, generating a solution when the abnormal change occurs, generating a retransmission signal when packet loss occurs in the transmission process, determining a retransmission queue according to the data identifier, and transmitting the retransmission signal according to the retransmission queue when delay occurs in the transmission process. The priority of a retransmission queue and the distribution of network bandwidth are dynamically adjusted, and when signal attenuation occurs in the transmission process, the execution sequence is adjusted according to the operation record and result of a solution by switching a transmission channel and adjusting transmission power. The transmission process of the operation data of the electric control box can be detected.

The invention relates to the technical field of sensor upgrading, in particular to a remote upgrading method and system for a tire pressure sensor. The method comprises the following steps: acquiring real-time state data of a tire pressure sensor; carrying out outlier parameter elimination on the real-time state data of the tire pressure sensor, and carrying out state diagnosis mining, so as to generate a state diagnosis report of the tire pressure sensor; performing upgrade demand prediction based on the tire pressure sensor state diagnosis report, and performing priority upgrade analysis to extract a plurality of upgradable sensors; performing byte-by-byte difference identification on the plurality of upgradable sensors based on preset latest version information, and performing incremental data encapsulation to generate a plurality of incremental upgrading data blocks; acquiring a historical running log of the vehicle; performing dynamic vehicle using behavior analysis and vehicle idle time period prediction on the vehicle historical operation log to generate a plurality of idle prediction time periods; the upgrading efficiency and the safety performance of the tire pressure sensor are improved.

The invention provides an intelligent exhibition hall control method and system based on Internet of all things. The method belongs to the technical field of the Internet of Things, and comprises the following steps: constructing an intelligent exhibition hall network architecture based on the Internet of Things, and wirelessly connecting to a central control platform to form a network environment of Internet of all things; acquiring user identity information through an identity recognition device, and constructing a user identity database; and analyzing user preferences through an intelligent algorithm according to the user identity information in combination with user historical behavior data. According to the method, the identity information and the historical behavior data of the user are analyzed through an intelligent algorithm, personalized exhibition recommendation and exhibition routes can be provided for the user, the user can find interested exhibits more quickly, and therefore the visiting experience is improved.

The invention discloses a software query information management method and system, and belongs to the technical field of software information security, and the method specifically comprises the following steps: after a query request of a user is received, creating a dynamic topology network architecture according to semantic features of query contents; creating a virtual query container corresponding to the dynamic topological network in the isolated memory space, wherein the virtual query container generates a dynamic encryption channel bound with the current topological structure; dynamically embedding user permission labels into topological network nodes through an attribute-based encryption algorithm, and establishing a mapping relation between permission characteristics and network paths; when distributed query is executed in the virtual query container, the topological node connection weight is dynamically adjusted according to the real-time network load; before a query result is fed back to a user, data elements are recombined based on a reverse entropy value of an original topology network architecture; and when an abnormal access feature is detected, triggering a topological network structure dynamic failure mechanism.

The invention relates to the technical field of intelligent traffic, in particular to an intelligent road cone traffic early warning system. The problems that in the prior art, an intelligent road cone is single in function, and warning strategies cannot be intelligently adjusted according to real-time road conditions and construction environment changes are solved. The intelligent road cone is arranged and used for being deployed on a road construction or accident site to warn vehicles, collecting road environment information through a sensor and conducting risk assessment and early warning on the vehicles according to the detected vehicle information; the control center is used for integrating the monitoring information of the intelligent road cones and dynamically adjusting a placement scheme and an early warning strategy of the intelligent road cones; and the user terminal is used for receiving the early warning information from the intelligent road cone and the control center and sending an alarm to a user. Through cooperation of the intelligent road cone, the control center and the user terminal, effective safety early warning and guidance are ensured to be performed on vehicles passing through the construction area during construction, accident risks are reduced, and traffic management efficiency is improved.

The invention discloses a garbage truck real-time monitoring and remote scheduling method based on the Internet of Things, and the method comprises the following steps: S1, collecting the real-time data of the operation state of a garbage truck, and carrying out the preprocessing of the real-time data; s2, constructing a task prediction model based on an improved adaptive graph neural network, and generating a preliminary task distribution matrix and a path planning scheme; s3, optimizing the preliminary task allocation matrix and the path planning scheme by adopting an improved PPO algorithm; s4, the optimized task allocation matrix and the path planning scheme are sent to a garbage truck vehicle-mounted terminal, and the task completion rate and the path deviation value are calculated; s5, the operation state of the garbage truck is monitored in real time, and the monitoring result and the operation state data are transmitted to the cloud Internet of Things platform; and S6, dynamically updating the scheduling instruction. According to the method, the Internet of Things, the adaptive graph neural network and the improved PPO algorithm are fused, intelligent scheduling and real-time optimization of the garbage truck are realized, and the method has the advantages of high efficiency, stability and low-cost operation.

The invention discloses a multi-link fusion method and system based on an SD-WAN (Secure Digital Wireless Area Network) technology, which can timely discover and deal with the condition of network failure or performance reduction by monitoring network state parameters of a plurality of network links in real time, and is helpful for ensuring reliable network connection at any time point, thereby improving the reliability and the stability of the network, and improving the reliability and the reliability of the network. By dynamically adjusting distribution of data traffic, the optimal link combination can be selected for data transmission, so that congestion is avoided, delay is reduced, the packet loss rate is reduced, the utilization rate of network bandwidth is maximized, the data transmission efficiency is remarkably improved, the routing optimization step can quickly respond to service changes by utilizing flexibility and programmability of the SDN technology, and the service quality is improved. According to the method, the continuity and the high efficiency of services are ensured by optimizing data transmission routes, existing network resources can be fully utilized through multi-link fusion and intelligent scheduling, excessive dependence on a single link or an expensive high-performance link is avoided, and reduction of network construction and operation and maintenance cost is facilitated.

The invention provides a memory resource access method and device, an address translation method and device, electronic equipment and a storage medium. According to the embodiment of the invention, a virtual machine management component can be used for firstly obtaining a direct memory access request of external equipment to a memory resource mounted under a virtual machine; and searching a target physical address corresponding to the target virtual address of the target memory resource from the data processing unit, so that the external equipment accesses the target memory resource by accessing the target physical address. Wherein a physical address translated by the virtual machine management component for the virtual address of the memory resource in advance is stored in the data processing unit, and the data processing unit performs data communication with the virtual machine management component through a communication drive simulated in the virtual machine management component. By adopting the scheme, the congestion of the shared memory resource (IOTLB) of the memory management unit possibly caused by excessive address query can be avoided, the consumption of the shared memory resource is reduced, and the utilization rate of the shared memory resource is improved.

The invention relates to the technical field of inter-city cargo splicing and loading, in particular to an inter-city cargo splicing and loading transportation path optimization algorithm based on large model optimization, and solves the problems that in the prior art, an optimization algorithm based on a large model generally relates to a complex calculation process and needs a large amount of calculation resources and time, and especially in a real-time path planning scene, the calculation process is complicated. And the calculation delay can influence the transportation efficiency. The invention discloses an inter-city cargo splicing transportation path optimization algorithm based on large model optimization. The algorithm comprises data collection and preprocessing, model construction and training, algorithm optimization and verification, path optimization calculation, result evaluation and feedback, and algorithm deployment and application. According to the method, various possible transportation paths are analyzed and compared through an algorithm, the optimal path is selected, unnecessary detour and waiting time is reduced, so that the transportation efficiency is improved, and the algorithm can perform intelligent scheduling and reasonable arrangement of transportation vehicles and routes according to real-time traffic conditions, cargo demands, vehicle states and other information.

The invention, which relates to the technical field of digital information transmission, discloses an AI technology-based digital information transmission sharing operation and maintenance platform comprising a data acquisition module, an AI intelligent analysis module, a frequency spectrum dynamic allocation module, a data classification and transmission optimization module, and a storage adaptation module. According to the method, the spectrum resource utilization efficiency and the transmission stability are optimized, the platform can accurately master the spectrum use condition in real time through the AI real-time spectrum sensing and dynamic frequency allocation technology, the platform can quickly identify idle spectrums and dynamically allocate optimal frequencies for different services in the face of a complex and changeable wireless environment, spectrum congestion and interference are avoided, and the service quality of the system is improved. The fluency of bandwidth and time delay sensitive services is guaranteed, and the transmission interruption risk is reduced.

The invention discloses a multi-locomotive path planning method and system based on a Q-learning algorithm, and relates to the technical field of iron-steel interface locomotive path planning, and the method comprises the steps: obtaining environment data, building a transportation system environment model, and defining states and actions; performing path optimization on the vehicle path through a Q-learning algorithm to obtain an initial path plan; and the central control system receives the key information in real time, and dynamically adjusts vehicle path planning in real time through a Q-learning algorithm. According to the method, through learning and optimization of the Q-learning algorithm, the central control system can find the shortest path, the transportation time and distance are reduced, and the transportation efficiency is improved; the path planning is dynamically adjusted through the central control system, so that the congestion and conflicts of track routes are avoided, and the smoothness of the transportation process is ensured; by using the Q-learning algorithm, the method can adapt to a dynamically changing environment, and normal operation of the system can be ensured even if an accident occurs.

The invention relates to the field of multimedia communication regulation and control, and particularly discloses an intelligent scheduling type emergency command vehicle multimedia communication system which reduces the interference of the surrounding environment of an emergency command vehicle on multimedia communication by surveying the communication environment of an accident site and analyzing the suitable parking position of the emergency command vehicle. Network switching test and fault early warning are carried out on the communication equipment of the emergency command vehicle, so that the normal network communication and service are prevented from being influenced by the fault of the communication equipment; the network load of the wireless communication of the emergency command vehicle is detected in real time, and the bandwidth is dynamically adjusted and allocated according to the load condition of the network, so that the network congestion is avoided, and the stability of the multimedia communication system of the emergency command vehicle during high-load operation is ensured; the communication quality of the wireless communication link of the emergency command vehicle is monitored in real time, and the satellite communication link is switched in time when the communication quality is poor, so that the uninterrupted communication is ensured, and the communication reliability of a multimedia communication system in a complex environment is improved.

The invention relates to the field of robot collaborative optimization, in particular to an industrial robot collaborative optimization system. Comprising the following steps: creating a task distribution matrix, optimizing the task distribution matrix by adopting a multi-objective optimization strategy, setting constraint conditions, and introducing a self-adaptive feedback adjustment mechanism to obtain an optimized task distribution matrix; and performing path optimization based on the optimized task allocation matrix. The problems that a fixed or simple scheduling algorithm is adopted for existing task allocation, and overload of part of industrial robots is likely to be caused; a dynamic feedback adjustment mechanism for resource consumption and state of the industrial robot is lacked, and optimization of task allocation cannot be performed according to real-time load and resource state of the industrial robot; the technical problems that path planning is prone to falling into a local optimal solution, and an industrial robot may frequently select a fixed path when executing a task, resulting in path resource competition and overall efficiency reduction are solved.

The invention relates to a coupler system based on MECHATROLINK-III and a communication method, the system comprises a MECHATROLINK-III master station, a MECHATROLINK-III special cable, a MECHATROLINK-III coupler and a plurality of plug-in IO modules, the MECHATROLINK-III coupler is used for managing all the plug-in IO modules in a slot so as to carry out ordered IO input and output, and the plug-in IO modules are used for carrying out plug-in IO input and output. The communication module is used for carrying out communication interaction between IO data of the whole coupler system and a MECHATROLINK-III master station; and the MECHATROLINK-III coupler is integrated with a plurality of control units or execution units. The MECHATROLINK-III coupler has the advantages that the communication stability and the communication efficiency are guaranteed while the cost of the MECHATROLINK-III coupler system is reduced.

The invention relates to the technical field of network security analysis, in particular to a big data network signal security early warning system. The system comprises a network signal big data stream transmission module, a network signal ratio difference detection module, a network signal division result safety early warning module and a network signal abnormity safety response module. Data acquisition equipment can be deployed at an entrance and an exit of each network equipment, and network signal data real-time acquisition and big data stream type transmission conversion can be carried out, so that a network signal big data stream can be obtained; carrying out time sequence flow size and access frequency statistical analysis on the network signal big data flow, and carrying out network signal ratio difference detection division and abnormal safety early warning processing at the same time to generate a network signal abnormal safety early warning signal; and uploading the network signal abnormity safety early warning signal to a cloud platform to carry out abnormity safety response processing so as to generate a network signal abnormity safety response protection strategy. According to the invention, network signal abnormity can be efficiently monitored in real time and early warning can be provided.

The invention relates to the technical field of intelligent traffic, in particular to a vehicle guiding method and system for an unattended highway. The invention discloses a vehicle guiding method for an unattended highway. The method comprises the following steps: S1, acquiring road image information and vehicle information on the highway in real time; s2, performing road section division according to the road image information and a historical congestion area, and analyzing each branch road section by using a mobile calculation formula to obtain an abnormal road section; s3, analyzing the behaviors of vehicles in each abnormal road section to obtain the lane changing times of the expressway entrance; and S4, performing planning guidance on the buffer road section according to the road image information of the expressway entrance. According to the method, the vehicle behavior in the abnormal road section is analyzed, the switching frequency of the expressway entrance is obtained, the buffer road section is further planned and guided, and the vehicle flow in the buffer area can be efficiently guided to avoid congestion through the dynamic analysis of the vehicle behavior and the intelligent planning of the divided road sections.

The invention provides a communication method of multi-application communication based on a serial interface and a storage medium, the communication method is applied to a protocol stack of multi-application communication, a hardware layer of the protocol stack uses an asynchronous full-duplex serial interface, and the communication method comprises the following steps: establishing a point-to-point transmission channel between applications through the asynchronous full-duplex serial interface; a sending end sets sending numbers for data packets, the data packets are packaged into data frames through a data link layer of a protocol stack, and the data frames are sequentially sent through a transmission layer of the protocol stack according to priorities of point-to-point transmission channels of different applications in all the applications; and the receiving end receives the data frame and verifies the transmission integrity of the data packet according to the sending number. The technical problems that the design of an existing communication method in a multi-chip ECU board is complex, and communication of multiple applications in two chips through one interface cannot be achieved are solved.

The invention provides a network adjustment method and device, electronic equipment and a storage medium, and relates to the technical field of data processing, and the method comprises the steps: obtaining the network performance information of each routing port at the current moment; wherein the network performance information comprises priority flow control message information of the routing port; inputting the network performance information of each routing port into a network congestion evaluation model, and outputting first real-time network congestion degree information of each routing port; and calculating the network weight information of each routing port based on the first real-time network congestion degree information of each routing port, so as to carry out distribution adjustment on the port flow of each routing port according to the network weight information.

The invention discloses an extruder capable of assisting in keeping raw materials dry, and relates to the technical field of dryers, the extruder comprises an operation table, a hot extrusion device is mounted on one side of the upper surface of the operation table, a feeding chamber is mounted on one side, close to the hot extrusion device, of the operation table, a drying bin is communicated above the feeding chamber, and a material hopper is fixedly connected to the upper surface of the drying bin; through the arrangement of the air blower, heat generated by the extruding machine can be used for heating the heat of the air blower, and the heated air is used for drying and heating the surface of the arc-shaped spiral flow guide plate again; and the dried water vapor can be recycled into the heat recovery evaporation chamber to be dried again, and the dried gas can be recycled for drying materials, so that power consumption caused by additional use of a heating body can be reduced, energy consumption can be saved, and sustainable use of the equipment can be enhanced.

The invention discloses a PLC data communication control system and method, and relates to the technical field of PLCs, and the method comprises the steps: calculating a first hardware evaluation coefficient and a second hardware evaluation coefficient of a PLC, and further calculating the static weights of all PLCs needing communication; calculating data evaluation coefficients and interruption evaluation coefficients of all the PLCs needing to be communicated, and further calculating dynamic weights of all the PLCs needing to be communicated; according to the static weights and the dynamic weights of all the PLCs needing to be communicated, comprehensive polling weights of all the PLCs needing to be communicated are calculated, polling periods of all the PLCs needing to be communicated are calculated, and a PLC polling table is determined. Communication resources are reasonably distributed, it is ensured that each PLC can complete communication in the polling period of the PLC, network congestion and communication delay are avoided, and the overall efficiency and response speed of a PLC communication system are improved.

The invention discloses a remote upgrading method and system for a concentrator. The method comprises the steps that differential firmware is generated and stored in a distributed file storage module; the block chain network broadcasts the upgrading task to each concentrator node; the concentrator obtains task data and downloads differential firmware; the downloaded differential firmware is verified; and generating and installing new firmware according to the current firmware and the differential firmware. According to the method, a non-tampering record and a safe identity verification mechanism are provided for firmware upgrading by introducing the block chain technology, and the authenticity and integrity of firmware are ensured. Meanwhile, the intelligent contract and distributed file storage technology is adopted, the bandwidth and time needed by firmware upgrading can be effectively reduced, and the upgrading efficiency and reliability are improved. In addition, due to the application of the dynamic bandwidth scheduling algorithm, when multiple concentrators are upgraded at the same time, network resources can be reasonably distributed, network congestion is avoided, and it is ensured that each concentrator can smoothly complete firmware upgrading.

The invention relates to the technical field of metro field data processing, and discloses a metro field multi-scene linkage safety management and control system and method, and the system comprises an access control module, a monitoring module, an illumination module, a passenger flow prediction module, an abnormality detection module, and a security strategy module. Wherein the access control module records real-time passenger flow volume; the monitoring module is used for acquiring a monitoring video of a subway field section; the lighting module is used for controlling the working state of lighting equipment of the subway field section; the passenger flow prediction module is used for calculating a passenger flow prediction value; the anomaly detection module is used for carrying out anomaly detection; the security strategy module selects a security strategy based on the passenger flow volume predicted value and the abnormal alarm signal; according to the invention, through multi-system linkage, intelligent passenger flow management, comprehensive anomaly detection and dynamic illumination control, the safety management level of the metro field is comprehensively improved.

The invention relates to the technical field of high-speed routing, and provides a bandwidth scheduling method and system for high-speed routing switching, and the method comprises the steps: carrying out the distribution of each port of high-speed routing switching equipment according to the network flow, and analyzing the initial bandwidth value of each port based on a distribution result; the bandwidth monitoring module is used for monitoring the real-time bandwidth use condition of each port of the high-speed routing switching equipment to obtain a bandwidth allocation result; and the flow scheduling module is used for generating a flow scheduling strategy based on the bandwidth allocation result, inputting the flow scheduling strategy into the flow scheduling module for configuration, comparing the flow scheduling strategy with the real-time bandwidth use condition monitored by the bandwidth monitoring module to obtain a bandwidth scheduling comparison result, and inputting the bandwidth scheduling comparison result into the bandwidth scheduling optimization module for bandwidth scheduling optimization. By dynamically configuring the traffic scheduling strategy, efficient utilization of bandwidth resources and optimal management of network traffic are realized, and the problems of low bandwidth utilization rate, resource waste and other flexibility insufficiency when the network traffic fluctuates greatly are solved.