1068 results about "Network congestion" patented technology

The invention belongs to the technical field of data transmission, and particularly relates to an SD-WAN low-delay data transmission method and system based on edge computing, a plurality of edge computing nodes are deployed in an SD-WAN architecture, and the edge computing nodes are distributed on a network edge side, close to terminal equipment or a branch mechanism and have data preprocessing and local computing capabilities; monitoring network state parameters of each link in the SD-WAN in real time, wherein the network state parameters comprise delay, bandwidth, packet loss rate and computing resource utilization rate of edge nodes; routing to-be-transmitted data to the target edge node, and if the node has local processing capability, executing data preprocessing or caching operation; otherwise, forwarding the data to an adjacent edge node or a cloud data center; a distributed cache strategy is adopted, when network congestion is detected according to data access frequency and timeliness requirements, non-real-time data is temporarily stored in a local cache, and asynchronous transmission is executed after a link is recovered, so that the method has the effect of providing higher-quality and more reliable network service for a user.

The invention relates to a multi-protocol transmission text data monitoring and warning method and system, and the method comprises the steps: generating a multi-source protocol transmission instance based on dynamic authorization and hardware security verification, and collecting and analyzing text data; a network connection state, a data backlog amount and sensor numerical value content parameters are monitored in real time through multiple threads, and a transmission state and content exception event queue is generated; learning a causal relationship among network congestion, equipment faults and alarm events by using a Bayesian network algorithm, calculating a root cause probability in combination with a dynamic weight distribution strategy, and generating a comprehensive alarm list of priority ranking; on the basis of user feedback data, protocol weights and alarm strategies are adaptively updated, abnormal early warning triggering, data snapshot binding and closed-loop optimization of alarm logs are achieved, and the problems that in a multi-protocol mixed transmission scene, safety adaptability is poor, the monitoring dimension is single, root cause analysis depends on static rules, and strategy updating lags are solved. And the real-time performance, the accuracy and the self-adaptability of data transmission of the industrial Internet of Things are improved.

The invention relates to a deterministic network congestion avoidance flow routing scheduling method, which belongs to the technical field of industrial internet, and comprises the following steps: S1, sensing network congestion based on IFIT flow detection and queue state, and calculating a congestion coefficient; s2, performing planning decision on a traffic routing path based on deep reinforcement learning to avoid congestion; and S3, sinking congestion coefficient calculation and strategy mapping calculation logic to switch hardware by using a P4 programmable data plane to realize localized closed-loop control. Through dynamic path optimization and localization execution, the throughput is remarkably improved, the time delay and jitter are reduced, the intelligent routing mechanism effectively balances the load, and a high-reliability dynamic scheduling solution is provided for a large-scale deterministic network in combination with the deterministic guarantee capability.

The invention relates to the technical field of data transmission processing, in particular to a data transmission method and system based on bird dynamic perception. According to the invention, the group perception vector obtained through the multi-dimensional perception fusion algorithm can comprehensively capture the complex features of the network environment, and compared with a traditional single-dimensional network state monitoring method, the method can significantly improve the accuracy and comprehensiveness of network environment perception. Therefore, the data transmission system can identify network congestion, link quality change, abnormal node state and other conditions more accurately, thereby providing more reliable basic information for subsequent transmission decisions. The group coordination information formed through group coordination analysis processing can effectively solve the problem that all paths in traditional multi-path transmission are lack of coordination, mutual interference and resource conflicts among the paths are remarkably reduced, and the utilization efficiency of overall network resources is improved.

The invention discloses a cross-platform authority unified management method and system based on a multi-WEB system, and the key point of the technical scheme is that the method comprises the steps: obtaining organization structure data of an enterprise system, analyzing the organization structure data, constructing a multi-level tree topology network, forming organization entity topology parameters, analyzing the organization entity topology parameters, and storing the analyzed organization entity topology parameters into a database; according to the scheme, post authority baseline parameters are generated, dynamic optimization of channel selection is achieved by constructing a dual-channel transmission decision maker and combining real-time network state data and an inter-system interaction characteristic score table, and compared with a traditional static configuration mode, the mechanism can achieve dynamic optimization of channel selection according to parameters such as department communication strength, system transmission performance and safety scores. According to the method, the optimal transmission path is automatically selected, network congestion or high-delay nodes are avoided, cross-system adaptation rules are generated through mapping calculation of an authority interface strategy and post authority baseline parameters, the problem of authority granularity difference between different systems is solved, and the accuracy and consistency of authority distribution are ensured.

The invention discloses a cross-regional vehicle-mounted network switching method and system based on digital twinning, and a medium. The method comprises the following steps: constructing a cloud side end digital twinning network architecture; acquiring vehicle state data and traffic environment sensing data through the terminal sensing layer; carrying out data aggregation on the vehicle state data and the traffic environment perception data through edge computing nodes to obtain a local digital twinborn model; meteorological data, operator base station data and a local digital twinborn model are integrated through a cloud digital twinborn center to obtain a global digital twinborn model, and the traffic congestion condition and the network congestion condition of each road network region in a future time period are predicted according to the global digital twinborn model. Determining a network switching strategy according to the traffic congestion condition and the network congestion condition; and performing a network switching decision on the target vehicle through the edge computing node. According to the method, the timeliness and accuracy of cross-regional vehicle-mounted network switching are improved, so that the stability and reliability of the vehicle-mounted network are improved, and the method can be applied to the technical field of the Internet of Vehicles.

The invention relates to the technical field of network communication, and discloses an intelligent control method and system of a switch. The method comprises the following steps: receiving a heterogeneous data stream in a target network domain; performing data processing by using a preset flow feature aggregation model, and generating a flow dynamic pressure field distribution diagram and a protocol priority mapping matrix; constructing an adaptive scheduling threshold model, and generating a multi-target flow control instruction set; a cascade effect is simulated based on a network congestion chained conduction model, and collaborative routing parameters are optimized; and iteratively optimizing through a mixed integer programming framework, and outputting a network scheduling action sequence to a switch control engine. The system correspondingly comprises a data receiving module, a data processing module, an instruction generation module, a simulation optimization module and an instruction output module. According to the method, heterogeneous data can be effectively processed, congestion can be accurately predicted, flow control can be optimized, the overall performance of the network can be improved, and communication requirements in a complex network environment can be met.

The invention relates to the technical field of power distribution network operation optimization, and discloses an intelligent power distribution network distributed power scheduling system based on edge computing, which comprises a data acquisition and preprocessing module, an edge computing and local scheduling module, an SDN network control module, an application layer global scheduling module and a scheduling execution and control module, according to the invention, by introducing the edge computing node, local preprocessing of data and generation of a preliminary scheduling strategy are realized, delay of data transmission to the central server is significantly reduced, and the system can dynamically adjust the scheduling priority in combination with the improved particle swarm optimization algorithm, so that the scheduling efficiency is improved. Three core indexes of renewable energy utilization rate, power distribution network loss and voltage stability are comprehensively considered, and a more accurate and efficient local scheduling strategy is generated. And meanwhile, the SDN network control module ensures that high-priority data can still be efficiently transmitted when the network is congested by calculating a link priority coefficient, so that the real-time performance and the reliability of the system are further improved.

The invention provides a data acquisition method and device based on an industrial internet identification analysis system, which are applied to the technical field of industrial internet, and are used for realizing data grading processing by acquiring data and priority parameters and distributing transmission queues according to the priority parameters; the method comprises the following steps: compressing and coding data, evaluating the quality of a wireless channel, selecting a transmission path, avoiding an interference channel, determining a retransmission strategy by combining a data priority and a network congestion state when transmission fails, receiving a data packet at an edge computing node according to the retransmission strategy, and uploading the data packet after local processing. The pressure of a core system is dispersed by utilizing edge computing power, and the overall data processing time delay can be reduced. Therefore, according to the method, through the steps of data priority distinguishing, data compression, channel quality evaluation, intelligent retransmission strategy, edge computing application and the like, the beneficial effect of anti-interference and low-delay data transmission in a wireless communication factory environment is achieved.

The embodiment of the invention provides a data transmission method and device of Internet of Things equipment, electronic equipment and a storage medium, and relates to the technical field of Internet of Things, and the method comprises the steps: obtaining business data collected by the Internet of Things equipment, and determining the target business priority of the business data; acquiring network index data of communication equipment connected with the Internet of Things equipment; performing data volume prediction according to the service data to obtain a corresponding predicted data volume; performing transmission mode selection according to the predicted data volume and the network index data to obtain a first transmission strategy for the service data; and issuing the first transmission strategy to the Internet of Things equipment, so that the Internet of Things equipment transmits the service data according to the first transmission strategy, thereby optimizing the data transmission mode, realizing dynamic adjustment of the transmission strategy, improving the network adaptability, improving the success rate of data transmission, and reducing the probability of network congestion.

The invention relates to a three-in-one network Internet of Things card automatic switching method. The switching method comprises the following steps: collecting state parameters of a plurality of operator networks; constructing a signal space topology model of the target area, predicting each operator network according to the signal space topology model, and calculating a comprehensive quality score of each operator network according to a preset multi-dimensional weighted evaluation model so as to establish standby communication links of other to-be-switched networks; calculating a corresponding switching income index according to the comprehensive quality score and a historical switching record of the currently used network, and generating a corresponding network switching instruction; and calculating a communication performance change result before and after switching of the network switching instruction so as to perform adaptive adjustment on weight parameters in the multi-dimensional weighted evaluation model. The method can predict and complete switching in advance before signal attenuation or network congestion, avoids communication interruption, dynamically optimizes a decision according to the use history and switching cost, and achieves a network switching control effect with both performance stability and economical efficiency.

The invention provides an electric energy load real-time data acquisition and analysis method based on a low-cost scheme, and the method comprises the following steps: constructing a distributed data acquisition network, employing a combined hardware architecture of a current / voltage sensor and a low-power-consumption MCU, and achieving the data acquisition optimization through a dynamic sampling rate adjustment mechanism, when the load fluctuation exceeds a set threshold value, the sampling rate is automatically increased, when the load is stable, the sampling rate is reduced to a calibration sampling rate, and a Kalman filtering algorithm is adopted to carry out real-time data preprocessing; a three-level data transmission system is established, the three-level data transmission system comprises an edge acquisition node layer, a convergence gateway layer and a cloud processing layer, an optimized AODV routing protocol is adopted among nodes to construct a star-shaped and net-shaped hybrid network topology, and an optimal transmission path is dynamically selected according to the signal strength and the network congestion condition; a differentiated QoS transmission strategy is designed, and data is divided into three priorities of fault alarm data, real-time monitoring data and historical data.

The invention relates to the technical field of remote control, in particular to an intelligent device remote cooperative control method and system based on the Internet of Things, and the method comprises the following steps: monitoring and adjusting the CPU utilization rate and memory usage of an intelligent device based on an Internet of Things platform, optimizing the data collection and network resource distribution, and improving the intelligent device remote cooperative control efficiency. By analyzing equipment performance and a network load balance index, equipment connection priority ranking and task load management are realized, and task execution and connection frequency is dynamically adjusted, so that real-time task requirements are met, and system efficiency is improved. According to the method, the performance index of the equipment is monitored in real time, the data transmission interval is dynamically adjusted, the data processing speed is remarkably increased, resource waste is reduced, efficient use of network resources is ensured through real-time load analysis and optimization of network nodes, the problem of data delay caused by network congestion is avoided, and in the aspect of equipment connection management, the data transmission efficiency is improved. An intelligent priority decision mechanism allows the key device to quickly access the network in an emergency.

The invention discloses a communication equipment fault intelligent diagnosis method and device, equipment and a medium. The method comprises the steps of collecting equipment operation logs in real time, and extracting an abnormal point set; clustering the abnormal points, and matching a hardware fault, a software error and a network congestion type in combination with a preset mode library; dimensionality reduction is carried out on temperature, voltage and current sensor data based on principal component analysis, and a time-synchronized fusion feature vector is constructed; analyzing features and abnormal modes, and outputting potential fault points; associating the classification model to generate a fault priority by extracting the dynamic characteristics of the network flow; and a dependency network is constructed in combination with Bayesian reasoning, so that accurate fault positioning is realized. The system supports incremental learning, updates an abnormal mode library and automatically expands a knowledge base. Through multi-dimensional data fusion and spatio-temporal feature joint modeling, the problems that a traditional method depends on manual rules and is high in false alarm rate are solved, and the method is suitable for complex scenes such as a 5G base station and a data center.

The invention relates to an address resolution protocol message sending method and device, computer equipment, a readable storage medium and a program product, relates to the technical field of networks, and can maintain the stability of de-stacking network communication. The method comprises the following steps: determining a plurality of member interfaces aggregated through a server logic interface; the plurality of member interfaces correspond to different message receiving devices; determining a network congestion index corresponding to the logic interface according to the network monitoring data of the plurality of member interfaces, and adjusting an initial index threshold according to the network monitoring data to obtain a current index threshold; if the network state is determined to be a normal state according to the network congestion index and the current index threshold, sending an address resolution protocol message to a plurality of message receiving devices according to a normal processing mode; and if the network state is determined to be a congestion state according to the network congestion index and the current index threshold, sending address resolution protocol messages to a plurality of message receiving devices for multiple times according to a preset time interval through a plurality of member interfaces.

The invention relates to the technical field of power system control, solves the problems of network attack, limited bandwidth and transmission delay of a power system in a signal transmission process and conservative DET parameter selection and controller design, and particularly relates to a power system dynamic event triggered load frequency control method under Dos attack and random delay. Comprising obtaining a continuous time system parameter matrix; setting an event triggering threshold function; state parameters facing Dos attack and random time delay conditions are set; constructing a state feedback controller; and collaborative design optimization is carried out by applying a GA optimization algorithm. Compared with a traditional control method, the method has the advantages that on the premise of ensuring the stability of the system, by optimizing event triggering conditions, the communication requirement and bandwidth occupation are remarkably reduced, the utilization efficiency of communication resources is improved, network congestion and delay possibly caused by frequent communication are reduced, and the service life of the system is prolonged. And the operation efficiency of the whole power system is improved.

The invention relates to an ultra-high-speed large-flow Ethernet data generation system and method. The system comprises a software unit and an FPGA unit. The software unit is used for generating stream template data and issuing the stream template data to the FPGA unit; the stream template data comprises stream template configuration items and dynamic configuration parameters; the flow template configuration item comprises protocol header information, scheduling configuration information, frame length configuration information and load configuration information; the dynamic configuration parameters comprise dynamic jump configuration information, routing table configuration information and the like; and the FPGA unit is used for storing, reading and calculating the issued stream template data, realizing intra-frame jump value calculation, message and IP head checksum generation, Ethernet frame construction and transmission. Through combination of software and hardware methods, the demand quantity of hardware resources can be reduced, the consumption of logic resources of the FPGA unit can be reduced, the phenomena of high and low speed operation environments, network congestion and the like in the existing network can be simulated, and diversified simulation environments can be provided.

The invention relates to the technical field of communication networks, in particular to a dynamic resource allocation method and system for an industrial 5G network. The method comprises the following steps: acquiring industrial terminal data; identifying network congestion nodes based on industrial terminal data; detecting a link congestion fault according to the network congestion node, and determining a bandwidth utilization rate; allocating spectrum resources based on the bandwidth utilization rate; performing frequency spectrum slicing on the frequency spectrum resources, and determining a flow load amount; adjusting load balance according to the traffic load, and generating a load resource report; dynamically adjusting time slot allocation by using a load resource report, and determining a task priority; task scheduling simulation is executed according to the task priority, and if congestion occurs, a congestion snapshot is stored; reducing scheduling conflicts according to the congestion snapshots, releasing bandwidth resources, and determining available network slice capacity; power resources are dynamically adjusted based on available network slice capacity. The bandwidth utilization rate and the task scheduling efficiency of the industrial 5G network are improved based on the communication network technology.

The invention relates to the technical field of rail transit communication, and discloses a communication network optimization method and device for rail transit. According to the communication network optimization method and device for rail transit, the quality of the communication link is regulated and controlled according to the real-time state of train operation, the stability of data transmission can be guaranteed, the reliability of the communication network in the train operation process is improved, accurate transmission of key data such as train operation control is guaranteed, and the service life of the communication network is prolonged. Traffic is regulated and controlled according to load distribution of network nodes of a track area, network congestion of a hot spot area can be effectively relieved, network loads are balanced, the utilization efficiency of network resources is improved, network operation is smoother, normal development of various services is guaranteed, access priority is regulated and controlled according to different service requirements, and the service quality is improved. Therefore, the emergency message can be transmitted preferentially, the timeliness and the efficiency of emergency handling are improved, and the safety and the emergency response capability of the rail transit system are enhanced.

The embodiment of the invention provides a network-on-chip routing method and device, a storage medium and electronic equipment, and relates to the technical field of computers, and the method comprises the steps: determining a neighbor node of a first node according to a relation between the first node and a destination node; the first node is a sender of a data packet, and the destination node is a receiver of the data packet; and acquiring congestion information of the neighbor node, and selecting a transmission path of a data packet according to the congestion information. Therefore, the related neighbor nodes are selected according to the relationship between the first node and the target node, and the transmission path of the data packet is selected based on the congestion condition of the neighbor nodes, so that the network congestion problem is relieved through dynamic sensing and path selection, the path diversity is improved, the congestion is reduced, and the network congestion rate is improved. Therefore, the communication efficiency and the working performance of the network-on-chip are improved.

The invention relates to the technical field of artificial intelligence, and discloses an internet television regulation and control method and device, a storage medium and electronic device.The method comprises the steps that network topology data, real-time performance parameters, user behavior data and environment data of nodes of an internet television are collected in real time through a space-time hypergraph convolutional network, a dynamic hypergraph model is constructed, and the network topology data of the nodes of the internet television, the real-time performance parameters of the nodes of the internet television and the environment data of the nodes of the internet television are obtained; extracting a spatial feature matrix and a time feature matrix of the nodes of the Internet television; performing feature fusion on the spatial feature matrix and the time feature matrix to generate a congestion probability prediction result of each node of the Internet television; and based on a congestion probability prediction result, combining historical flow data, generating a resource allocation optimal strategy by using multi-target Bayesian optimization, and training and updating a congestion prediction model by using a lightweight federated incremental learning framework. The Internet television regulation and control method provided by the invention is further improved in the aspects of network congestion prediction precision, real-time performance, energy consumption and the like.

The invention discloses a communication method of vehicle-mounted TBOX equipment, which relates to the technical field of equipment communication and comprises the following steps of: initializing a communication module of the vehicle-mounted TBOX equipment; performing channel selection by using a communication module to obtain channel information; performing spectrum allocation according to the channel information to obtain spectrum information; performing data encryption transmission according to the frequency spectrum information to obtain encrypted data; performing integrity verification on the encrypted data to obtain complete data; performing network load prediction according to the complete data to obtain a prediction result; adjusting the bandwidth according to the prediction result to obtain bandwidth data; and performing data packet priority management according to the bandwidth data. According to the method, the prediction accuracy and the overall communication efficiency are improved, the data transmission sequence can be flexibly adjusted according to the real-time network environment, the transmission reliability of key data is improved, and the risk of important information loss or delay caused by sudden network congestion is reduced.

A scheduling method for managing network congestion includes: determining, in response to link congestion in a network, a plurality of queue pairs (QPs) on a congested link in the network; determining, from the plurality of QPs on the congested link, a target QP for scheduling out from the congested link; determining a target traffic-forwarding path based on traffic of links in the network, the target traffic-forwarding path being configured for forwarding traffic of the target QP; determining a changed route of the target QP based on a target address of the target QP and the target traffic-forwarding path; and delivering the changed route to a target source local area network access (LA) device of the target QP, the target source LA device being configured to output, based on the changed route, the traffic of the target QP through the target traffic-forwarding path.

The invention belongs to the technical field of power systems, and more particularly relates to a quick-start network congestion control method suitable for a power system, which ensures the accuracy and reliability of data by collecting and preprocessing power equipment and network flow data. Then, a traffic prediction model is trained by using the preprocessed data, and the model can accurately predict the network traffic in a period of time in the future, thereby providing a basis for real-time decision making. In the starting process of the power system, network congestion detection is carried out in combination with real-time network state and equipment state data, and potential congestion risks are found in time. And finally, dynamically adjusting a flow scheduling and control strategy based on a network congestion detection result and a prediction result of the flow prediction model, thereby optimizing resource allocation and avoiding an improper decision. The series of steps ensure that network congestion can be timely and accurately dealt with under the condition that the network state is rapidly changed, and the efficiency and the stability of rapid starting of the power system are improved.

The invention provides a communication method and device, and belongs to the technical field of communication, in the method, a network element at a network side, such as a first network element, can obtain network congestion information of a service flow so as to determine the possibility of congestion of a current network and execute supervision. For example, after the network congestion degree is increased, if the possibility of network congestion has reached that an application side needs to adjust the transmission of the service flow to reduce the possibility, if the first network element determines the application side by monitoring the transmission of the service flow and adjusts the transmission of the service flow, the first network element determines the application side by monitoring the transmission of the service flow. If not, the transmission can be managed and / or controlled, so that network congestion is avoided, fairness between services is guaranteed, and the use experience of a user is guaranteed.

Techniques for adaptively adjusting retry limits and modulation and coding scheme (MCS) thresholds are provided. A first network device receives a traffic flow from a second network device via a wireless network. The first network devices analyzes the traffic flow to identify a network service associated with the traffic flow. The first network device examines one or more predefined network service policies to determine one or more characteristics of the network service. The first network device detects a network congestion within the wireless network. Responsive to detecting the network congestion, the first network device switches to a congestion management mode, which further comprises that the first network device determines one or more network transmission settings for the traffic flow based on the one or more characteristics, and communicates the one or more network transmission settings to the second network device.

Described herein are systems and methods for programmable, hardware-accelerated congestion monitoring and / or control. At least one circuit can configure a plurality of hardware circuits with one or more rules that, when satisfied, cause the plurality of hardware circuits to generate one or more congestion events indicative of congestion in a network. The at least one circuit can receive the one or more congestion events generated by the plurality of hardware circuits based on one or more network signals in the network satisfying the one or more rules. In response to receipt of the one or more congestion events from the plurality of hardware circuits configured with the one or more rules to detect the congestion in the network, the at least one circuit can analyze the one or more congestion events to address the congestion in the network. Various other methods, systems, and computer-readable media are also disclosed.

The invention discloses a wireless data uploading method and system for an industrial internet of things, and relates to the field of wireless data processing, and the method comprises the steps: firstly, comprehensively considering the inherent service attributes of data to determine the initial service priority of the data; meanwhile, terminal side sensing data and global network state data obtained from the gateway are fused, and a more accurate and comprehensive network quality score is calculated through double-source information. Finally, the initial priority and the network quality are dynamically combined according to the two key dimensions, and a final transmission strategy is generated. According to the method, a data uploading decision is no longer static and one-dimensional, but a two-dimensional dynamic decision which can be adaptively adjusted according to a real-time network condition, so that the sending opportunity or mode of the high-priority data is intelligently adjusted when the network is congested, the blocking of key services due to blind sending is effectively avoided, and the service quality is improved. And the robustness and the high efficiency of data uploading in a complex industrial environment are ensured.

The invention relates to the technical field of video data compression and transmission, and particularly discloses a multi-modal video data compression and transmission method, which comprises the following steps of: firstly, extracting a feature set of multi-modal video data, dynamically evaluating a feature priority based on the feature set, and then, carrying out differential compression on different priority modals by adopting a hierarchical compression strategy, and finally, screening available paths through historical transmission data, matching path intervals in combination with modal priorities, monitoring a network state in real time, dynamically judging a transmission state, and quickly switching to a suboptimal path in case of abnormality. According to the method, through dynamic feature priority evaluation, a hierarchical compression strategy and real-time transmission path monitoring and switching, the defects of a traditional method in the aspects of compression efficiency, transmission quality and real-time adaptability are overcome, the influence of network congestion or faults on the transmission quality is effectively avoided, and the compression efficiency, the transmission quality and user experience are remarkably improved.

The invention belongs to the technical field of audio and video transmission, and relates to an audio and video transmission method and system with a self-adaptive network bandwidth, and the method comprises the steps: collecting audio and video signals through an audio and video coding assembly, generating coding data based on preset coding index parameters, and storing the coding data in an audio and video coding cache; millisecond-level real-time bandwidth sensing is realized through a local dynamic bandwidth sampling technology, so that the dependence on feedback of a receiving end is thoroughly eliminated, and the lagging phenomenon caused by delay is radically reduced; and a multi-level network state discrimination mechanism is constructed by further combining the two indexes of the data transmission cache utilization rate and the transmission rate, the network state is refined into four levels, and the strategy is dynamically adjusted, so that the congestion control response precision is remarkably improved. Under a network congestion scene, through intelligent filtering of non-key frames, shortening of an I-frame interval and reduction of redundant data transmission, key picture continuity and audio stream continuity are guaranteed preferentially, and the problems of network burden and service quality reduction caused by traditional full-amount transmission are solved.