654 results about "Packet loss" patented technology

The invention relates to a cooperative control method and system for realizing self-organizing protection of a multi-unmanned aerial vehicle cluster, and the method comprises the steps: M1, enabling the unmanned aerial vehicle cluster to execute a task, obtaining the data information of the remaining power, RSSI signal intensity and IMU attitude of each unmanned aerial vehicle in real time based on an airborne built-in sensor, and acquiring data information of distances and relative speeds of obstacles around the unmanned aerial vehicles in real time based on an airborne external millimeter-wave radar, constructing a dynamic threshold function stop, and if the RSSI signal strength of each unmanned aerial vehicle is greater than the stop, outputting data information of the residual electric quantity and IMU attitude of each unmanned aerial vehicle. According to the method, misjudgment (such as transient packet loss due to electromagnetic shielding) caused by temporary signal interference is effectively avoided, the misjudgment rate is reduced by 40%, unnecessary return or cluster recombination is reduced, continuous task execution is guaranteed, it is ensured that leader handover is completed quickly (at the millisecond level) when a host fails, and the situation that a cluster falls into disorder due to single-point failure is avoided.

Embodiments of this application provide an adaptive data flow transmission method, an apparatus, and a system, relating to the field of communication technologies. The method is used to perform, when a frame rate of a downlink data flow of a service changes, network resource adaptation promptly based on the frame rate of the data flow, to avoid a waste of network resources or a packet loss of media frame data, so as to improve network resource utilization and user experience.

The invention discloses a time delay constrained Internet of Vehicles multi-mode cooperative sensing method and system. The method comprises the following steps: collecting point cloud data and image data, and carrying out feature extraction, fusion and space projection; constructing a two-dimensional convolution neural network, and extracting a position-level importance probability graph and a mask used for screening key information; constructing a benefit estimation neural network and a constraint evaluation neural network, and predicting expected values of system benefits and constraint conditions; meanwhile, an overall strategy selection module is established; the motorcade carries out target identification and calculates rewards based on information interaction so as to obtain a perception experience sample; and updating network parameters based on the perception experience sample to obtain a final overall strategy selection module. According to the method, the transmitting power, the transmission channel and the sensing data area of the vehicle are optimized based on reinforcement learning, a strategy correction mechanism is introduced, a risk strategy of high time delay or high packet loss is dynamically corrected, and target identification deviation and decision errors caused by sensing information delay and wrong transmission are avoided.

The invention discloses a dual-channel adaptive network stability testing method and system, and belongs to the technical field of computer network testing. The system adopts a dual-channel asynchronous communication architecture in which a control channel and a data channel are physically separated, instructions and state information are transmitted through an independent TCP control channel, and high-speed test data streams are transmitted through a UDP or TCP data channel. The method comprises the following steps: dynamically and adaptively adjusting a timeout parameter based on real-time network delay detection; nanosecond constant interval packet sending control is realized by using a high-precision monotonic clock source and busy waiting compensation mechanism; a packet loss detection, positioning and ACK confirmation mechanism based on the serial number is realized in an application layer; and real-time statistical display and idle detection automatic termination are realized through multi-thread parallel processing. According to the invention, the precision, the stability and the adaptive capability of network testing are remarkably improved, and the method is suitable for long-time stability testing in various scenes such as a high-speed Ethernet, a satellite link, an industrial Internet of Things gateway and the like.

The invention discloses a tool face angle real-time prediction method based on ground top drive parameters, and relates to the field of tool face angle real-time prediction, and the method comprises the steps: constructing a model training parameter obtaining experiment bench, and collecting simulation drill string dynamic data under different ground top drive parameter combinations through the bench; calculating an initial tool face angle, and performing unwrapping treatment on the initial tool face angle to obtain real tool face angle time sequence data; constructing a prediction model based on an LSTM neural network by taking the ground top drive parameters and the corresponding real tool face angle time sequence data as training samples; and the RMSE, the MAE, the Rand the prediction accuracy are used as evaluation indexes to verify the reliability of the model prediction performance. The method has the advantages that the top drive parameters located on the ground are adopted to predict the angle of the tool face thousands of meters underground, and data distortion caused by the problems of slow data transmission, large packet loss and the like in the process of transmitting underground signals to the ground is avoided.

The invention relates to a high-performance voice processing method, and the method comprises the steps: obtaining voice data transmitted through a network, generating corresponding scene fingerprint information, determining a frame parameter of a lightweight multi-scene adaptation frame, and a corresponding processing parameter, and if the duration of a lost segment is smaller than a preset threshold value, determining that the segment is lost. If yes, generating a corresponding first compensation result according to the acoustic compensation parameter; if the duration is larger than or equal to a preset threshold value, whether the acoustic compensation process and the semantic processing process are performed in parallel or not is judged according to the frame parameters, if not, a corresponding second compensation result is generated, and if yes, a corresponding second compensation result is generated according to the acoustic compensation process and the semantic processing process; and outputting the corresponding target voice transmission data. The definition and the stability of the voice signal in a complex environment can be effectively improved, different compensation modes are flexibly switched or executed in parallel according to the packet loss duration and the resource state, and the effectiveness and the stability of a recovery mechanism are improved.

The invention discloses a robot super-long flexible part carrying method based on a reinforcement learning vibration suppression collaborative algorithm, and aims to solve the problems of coupling dynamics and synchronization in a multi-grabbing-point and multi-robot collaborative carrying process. According to the method, deep Kupman online embedding, a submerged space phase locking loop, prediction consistency constraint and micro-predictable control feedforward are combined, and a multi-agent residual reinforcement learning closed loop and barrier function projection are assisted to ensure safety constraint; the technical effects of phase synchronization and vibration suppression control under the conditions of communication time delay, packet loss and uncertainty, reduction of stress and swing, and improvement of carrying stability, precision and efficiency are achieved.

The invention discloses a communication method for realizing a BMS protocol through Bluetooth, and the method comprises the following steps: S1, a connection establishment stage: 1) after a local device establishes a Bluetooth connection with a slave device, the local device constructs a request instruction for reading a version number according to a predefined BMS communication protocol; and 2) periodically issuing the request instruction to the slave equipment in a first preset period through the Bluetooth feature with the notification attribute. According to the method, the communication reliability is improved, the problems of instability and data packet loss of a Bluetooth channel are effectively solved through instruction issuing based on timing polling and a multi-level overtime disconnection mechanism, and it is ensured that instructions and data are reachable in a complex wireless environment; and on the basis of a BMS protocol framework, end-to-end CRC16 verification from'equipment address' to'data content 'is introduced in a data analysis link, damaged or tampered data frames in a transmission process can be accurately identified and discarded, and system processing errors or missing data are fundamentally avoided.

The invention relates to the technical field of power distribution terminals, and discloses a power distribution terminal automatic joint debugging function integrity and reliability test system, which comprises a co-simulation module for performing closed-loop coupling on a virtual power grid and a tested terminal through deterministic time control and generating a reproducible working condition; the scene arrangement module is used for realizing automatic switching and rollback of cross-domain scenes based on transactional snapshots; and the communication module is used for executing a consistency test on multiple protocols and injecting delay jitter, packet loss and clock drift. The functional integrity and reliability test system for the automatic joint debugging of the power distribution terminal aims to solve the problems of lack of deterministic time control of cross-domain cooperation and insufficient guarantee of state consistency in a digital twin test method. The problems that a test result cannot be reproduced, crosstalk misjudgment is caused by state non-atomicity consistency during multi-scene switching, and faults are difficult to reproduce due to lack of time determinacy replay capability are solved.

The invention discloses an anti-packet loss processing method and system for audio and video data. The method is applied to an articulated naturality web, the articulated naturality web comprises two groups of devices, and the two groups of devices are respectively a receiving end device and a transmitting end device. According to the anti-packet-loss processing method and system for the audio and video data, provided by the invention, through a series of steps of packet loss detection, recovery, error concealment and the like, the audio and video data can be recovered to the greatest extent under the condition of data packet loss, the problems of jamming, fuzzy pictures, discontinuous sound and the like are reduced, and the quality of the audio and video is remarkably improved; forward error correction, interpolation compensation and various error hiding methods are carried out by using redundant data, and lost data packets are processed from different angles, so that the definition and fluency of audios and videos and the fidelity of the audios are ensured; meanwhile, through secondary packet loss detection, the situation that the transmission integrity of the audio and video data packets is affected due to the fact that the packet loss phenomenon is not found in time can be effectively avoided.

The invention relates to the technical field of computer network communication and intelligent control, and discloses a switch configuration method and system based on AI adaptive congestion control, and the method comprises the steps: collecting the multi-dimensional feature data of a network in real time through a data plane programmable pipeline of a switch, and transmitting the multi-dimensional feature data to an AI intelligent decision engine through an encryption channel; based on the multi-dimensional feature data, executing congestion prediction, strategy generation and interpretability analysis through an AI intelligent decision engine to obtain a congestion control regulation and control strategy; converting the congestion control regulation and control strategy into an executable switch configuration command, and issuing the executable switch configuration command to switch hardware to dynamically adjust congestion control parameters of the switch; and acquiring the network performance index after configuration execution, calculating the profit value of the congestion control strategy, and updating the model weight of the AI intelligent decision engine based on the profit value. According to the invention, the adaptability of the network to dynamic loads and complex scenes is effectively improved, delay and packet loss are reduced, and the operation and maintenance complexity is reduced.

A method, computer program product, and computing system for processing a plurality of packets transmitted from a first computing device to a second computing device. A packet sequence number associated with each packet is identified. An error-detecting code representation is generated using the packet sequence number of each packet. A packet that is missing from the plurality of packets is identified. A packet loss pattern associated with the plurality of packets is identified by comparing the error-detecting code representation with a plurality of entries of a high probability loss pattern memory table.

The invention relates to a flow control method and device based on a dynamic queue weight and a global overflow bucket. The method comprises the following steps: distributing network messages to corresponding message queues according to a preset classification rule; dynamically generating the queue weight of each queue according to the real-time queue state of each queue; calculating virtual completion time of each queue based on the queue weight; determining a target message to be sent according to the virtual completion time; when the number of the tokens in the queue where the target message is located is insufficient, the tokens are called from a global overflow bucket; and sending the target message based on the called token. According to the flow control method and device based on the dynamic queue weight and the global overflow bucket, time delay can be reduced, packet loss can be reduced, the utilization rate of network resources can be improved, burst flow processing can be optimized, real-time service experience can be guaranteed, token waste can be avoided, and queue bandwidth allocation can be balanced.

The invention discloses a low-voltage transformer area electric energy meter time synchronization method and system based on swarm intelligence, and relates to the technical field of intelligent power grid and power distribution automation. The method comprises the steps that a transformer area acquisition terminal issues reference time, and each electric energy meter collects neighborhood information through neighbor electric energy meter bidirectional message exchange; jointly estimating the clock skew and the drift rate by adopting a consistency algorithm; introducing a time-varying weight calculated according to SNR, a message success rate and historical stability to suppress the influence of an inferior link and an abnormal node; the virtual synchronization time is output through software compensation on the service side; and adjusting the synchronization period interval and the convergence step length in a linkage manner according to a double-threshold self-adaptive rule. According to the scheme, deviation and drift rate rapid convergence and stable noise suppression are realized in a time-varying and easy packet loss environment, communication energy consumption is reduced, time jump caused by hardware callback is avoided, and the method has the advantages of high precision, strong robustness and large-scale deployment.

The invention relates to the technical field of Internet of Things communication, and particularly discloses an Internet of Things communication equipment data transmission packet loss compensation optimization method and system, and the method comprises the steps: obtaining a data packet transmission sequence, and obtaining the receiving state identifiers and transmission timestamps of a plurality of data packets according to the data packet transmission sequence; and acquiring network transmission quality parameters, and acquiring a received signal strength value sequence, a network jitter value sequence and a data packet delay fluctuation value sequence in a continuous time window according to the network transmission quality parameters. According to the method, by dynamically obtaining the multi-dimensional network transmission quality parameters in the continuous time window and calculating the actual loss probability value, misjudgment caused by a fixed threshold value is avoided, reliable recovery of the data flow is achieved in combination with a prediction compensation mechanism and consistency verification, and the problem of packet loss caused by network fluctuation in the environment of the Internet of Things is effectively solved.

The invention discloses a network data distribution method and system based on big data and a storage medium, and relates to the technical field of big data storage. The big data-based network data distribution method and system and the storage medium comprise the following steps of S1, collecting synchronous data in a machine tool data synchronization process, and performing data cleaning and standardization processing on the synchronous data; s2, dividing original machine tool data into a plurality of original blocks, calculating an estimated value of the number of redundant blocks, adding metadata attached to the redundant blocks to the original blocks, and then asynchronously sending the original blocks; s3, receiving and caching the synchronous data block, recovering original data through decoding and verification, calculating a synchronous reliability evaluation value, and adjusting a redundancy strategy based on the synchronous reliability evaluation value; and S4, calculating a synchronization abnormity evaluation value according to the synchronization data and the synchronization reliability evaluation value, performing abnormity grading according to the synchronization abnormity evaluation value, and adjusting a synchronization strategy. The problem that data consistency is seriously influenced by packet loss when edge nodes synchronize data is solved.

The invention relates to the technical field of bus duct thermal protection, in particular to a bus duct thermal protection method and system based on intelligent monitoring, and the method comprises the steps: obtaining a packet loss delay bandwidth generation state label, calling an unstable link collection path node congestion rate port number to generate a scheduling table, collecting a temperature rise rate displacement, calculating a thermal slope and combining field disturbance to obtain a trigger value, and comparing thermal triggering with thermal accumulation to identify a high-temperature-sensitive section mark, and calling the mark to compare a cutoff threshold value to generate a starting result. By collecting multi-dimensional data such as packet loss, delay and bandwidth for dynamic analysis, the state of a communication link can be evaluated in real time, an unstable link can be found, an accurate triggering boundary value is generated by combining parameters such as thermal load, electric field intensity and harmonic waves, cooling or power-off protection is started in time by matching with a heat flow trend before a high-temperature-sensitive area appears, and the reliability of the system is improved. Response lag of a traditional technology is avoided, an intelligent response mechanism is innovated to achieve accurate and flexible thermal protection, stable and safe operation of equipment is guaranteed, and overheating accidents are reduced.

The invention discloses a selective retransmission function test method, device and system for remote direct memory access, a medium and a product, and relates to the technical field of network tests.The method comprises the steps that when message features of a received test message are successfully matched with a packet loss rule, redirection processing is carried out on the test message so as to achieve controllable discarding, and the message features of the test message are successfully matched with the packet loss rule; according to the method and the device, the selective retransmission function is triggered, and the release rule corresponding to the test message takes effect to ensure that the subsequent corresponding retransmission message can be normally forwarded, so that only the first transmission of the original message is intercepted, the retransmission message is released, and the purpose of controllable packet loss is achieved; and finally, the selective retransmission function is evaluated according to the redirected message information in the function test process and the message receiving information of the message receiving end, so that the technical problems that the test packet loss is uncontrollable and the accurate test requirement is difficult to meet in the related technology can be solved, and the test efficiency is improved. The technical effects of accurate and controllable verification and performance evaluation of the selective retransmission function are achieved.

The invention discloses an immersive video perception transmission method based on implicit integrated viewport prediction and representation learning code rate decision, and relates to the technical field of immersive video transmission and intelligent content perception coding optimization. In order to solve the problems of insufficient viewport prediction generalization, non-adaptive user preference modeling and poor stability under network disturbance in the prior art, the invention provides a method for establishing an implicit integrated viewport prediction model of a multi-input-output structure by collecting user head motion trail and view field thermodynamic diagram data; constructing a code rate decision engine of mutual information constraint by combining representation learning and reinforcement learning, and realizing tile-level dynamic code rate allocation according to a prediction result and user preference; introducing an adversarial training mechanism of bandwidth jitter and packet loss disturbance to enhance robustness; and end-to-end adaptive optimization is realized by adopting cloud, edge and terminal collaborative deployment. The method is suitable for a high-bandwidth and low-delay scene, the definition of a core visual area can be guaranteed, meanwhile, the bandwidth is remarkably saved, and the user experience continuity is improved.

Disclosed is a method and device for dynamically modifying radio access network (RAN) configuration at a user plane during a RAN layer processing. The method comprises determining a data packet loss ratio during a transmission of a plurality of data packets via a transmission channel. The method further comprises comparing the determined data packet loss ratio with a first threshold value to determine good channel conditions. Based on a result of comparison, the method comprises determining whether a current condition of the transmission channel is reliable or unreliable. Further, the method comprises incrementing a timestamp corresponding to a time at which the current condition of the transmission channel is determined as reliable. Subsequently, the method comprises dynamically modifying the RAN configuration at the user plane upon a determination that the incremented timestamp value is greater than the second threshold value.

The invention discloses an industrial intelligent installation and adjustment platform construction and performance optimization method based on digital twinning, and relates to the technical field of intelligent manufacturing and digital twinning, and the method comprises the following steps: building a unified time-frequency auditing base line, carrying out the continuous sampling of Ethernet switch route refresh pulse and programmable logic controller synchronization rhythm, and obtaining a unified time-frequency auditing base line; extracting a time drift curve, and constructing a time consistency reference surface; and executing causal playback based on the time consistency reference plane, reconstructing a frame sequence change track before and after the interruption of the communication chain, extracting a time sequence dislocation fingerprint and a packet loss link, and generating a pseudo operation risk distribution diagram. According to the method, through establishment of a time consistency reference surface, causal playback, sequence consistency check, time difference injection and evidence chain construction, microsecond-level beat synchronous control and pseudo operation identification are realized, and through combination of phase traction and a reversible time grid, abnormal chain fusing and self-healing are realized. And the real-time performance, the stability and the intelligent level of the digital twin installation and adjustment system are comprehensively improved.

The invention discloses an underwater acoustic image transmission method combining feature extraction and semantic compression, which relates to the technical field of data transmission, and comprises the following steps: a sending end performs semantic feature extraction on an original underwater acoustic image to obtain a semantic feature set; performing compressed encoding on the semantic feature set to generate compressed semantic data; transmitting the compressed semantic data to a receiving end through an underwater acoustic channel; and the receiving end decodes the received compressed semantic data, restores the semantic feature set, and performs image reconstruction and / or task identification based on the semantic feature set. The method comprises the following steps: performing semantic feature extraction on an underwater acoustic image through a sending end, and converting pixel data into a semantic feature set; the data volume is significantly reduced through compression coding, so that the method adapts to the limited bandwidth of an underwater acoustic channel; and the receiving end performs image reconstruction or direct task identification based on the restored semantic features. According to the method, efficient and reliable transmission of image data in a low-bandwidth and high-packet-loss underwater acoustic environment is realized, and effective maintenance and task availability of semantic information are ensured.

The invention discloses a multi-unmanned aerial vehicle cluster stochastic prediction control method and device based on anti-saturation and packet loss compensation, and the method comprises the steps: building a closed-loop control model of a stochastic system based on a pilot-following multi-unmanned aerial vehicle cluster architecture; through a Markov chain modeling data transmission packet loss process, a forgetting factor is introduced to design a packet loss compensation strategy after random data is randomly lost so as to correct a closed-loop control model of a random system; aiming at the corrected closed-loop control model of the following stochastic system, constructing an anti-actuator saturation control law through convex representation of a saturation function, and further constructing a saturation-limited following stochastic augmentation prediction model; solving a predictive control problem on line based on a random augmentation predictive model; and the control performance index is controlled through rolling optimization, the gain of the feedback controller is updated, and anti-saturation random prediction control following with random following in a packet loss environment is realized. According to the method, the coupling influence of data transmission packet loss and actuator saturation can be effectively solved, and the system performance weakness caused by single problem processing is avoided.

The invention relates to a high-fidelity generative video stream transmission system based on a visual base model, which belongs to the field of image communication, and is characterized in that a visual enhancement-oriented generative codec is designed, and high-fidelity video reconstruction under a high compression ratio is realized through an asymmetric space-time compression strategy and time sequence consistency enhancement; a resolution scaling module is provided, the calculation complexity is remarkably reduced through a video super-resolution recovery module of adaptive resolution control and joint optimization, and real-time high-definition video processing is achieved; and constructing a network adaptive video stream transmission controller, an intelligent token discarding mechanism based on semantic importance and a mixed packet loss processing strategy to realize code rate scalable control and robust transmission under network fluctuation.

A system for optimizing network traffic distribution including a control plane connected to a data plane. The control plane includes one or more processors and memory storing instructions that, when executed by the one or more processors, cause the control plane to: implement a reinforcement learning module configured to: model a network state space comprising interface characteristics and traffic characteristics; define an action space for allocating specific flows to specific interfaces; establish a reward function that encourages efficient utilization of bandwidth while penalizing packet loss, latency, and jitter; learn optimal flow-to-interface allocations based on the modeled state space, action space, and reward function; and implement a flow allocation module configured to generate flow allocation policies based on the learned optimal flow-to-interface allocations. The data plane including one or more network devices configured to route network traffic flows based on the implemented flow allocation policies.

The invention provides a data transmission verification method and device, electronic equipment and a storage medium, and relates to the technical field of network communication, a unique connection identifier is allocated in a connection establishment stage of two communication parties, and a serial number field is designed as a combination of message length information and a random number; a connection identifier and a serial number field are packaged at the head and the tail of the data message respectively, a type-length-value structure message is carried in the middle of the data message, and the consistency of the connection identifier and the serial number field at the head and the tail of the data message is verified after the received message is de-packaged; and when verification fails, the current connection is terminated, and the connection is triggered to be reestablished to retransmit data, so that the problems that packet loss, data tampering or errors are easy to occur during RoCE data transmission in the prior art, and a traditional verification mode is high in calculation complexity, large in occupied bandwidth and high in reliability can be solved. And a traditional retransmission mode is easy to cause system performance reduction or system abnormity caused by access of a wrong memory address.

The invention discloses a data forwarding method and device for a data center bridging switching protocol, equipment and a storage medium, relates to the technical field of data traffic management, and discloses the data forwarding method for the data center bridging switching protocol, which comprises the following steps: acquiring a preset data center bridging switching protocol set and traffic data; performing standardization processing on the preset data center bridging exchange protocol set to obtain a target data center bridging exchange protocol set; performing traffic classification scheduling according to the traffic data to obtain a target traffic queue; and performing data balanced forwarding according to the target flow queue and the target data center bridging switching protocol set to obtain a target forwarding result so as to complete data forwarding of the data center bridging switching protocol. The technical effects of improving interoperability among different devices, simplifying network management, enhancing performance in a high-density network environment and reducing delay and packet loss are achieved.

The invention relates to the technical field of pipeline detection, in particular to a pipeline leakage detection method and device based on bionic perception, and the device comprises a support frame, two leather cup structures and a plurality of groups of detection assemblies. The supporting frame is of a tubular structure and is arranged in a to-be-detected pipeline. The two leather cup structures are located at the two ends of the supporting frame respectively, and the outer diameter of each leather cup structure is slightly larger than the inner diameter of a to-be-detected pipeline to form interference fit. The multiple groups of detection assemblies are distributed at intervals in the length direction of the supporting frame, and the detection assemblies in the same group are arranged in an annular array around the supporting frame; when the leakage point of the to-be-detected pipeline is located between the two leather cup structures, the pressure between the two leather cups acts on the leakage point, the flow field of the leakage point area is changed, the detection assembly is affected to generate vibration displacement, and therefore the position of the leakage point is judged. The device realizes detection by depending on a flow field change signal accompanied by pipeline leakage, prevents software detection from depending on hardware and being easily influenced by sensor fault packet loss, and is simple in principle and stable in function.

The present disclosure provides a system for predicting customer churn and generating retention strategies. The system includes a data ingestion module that collects and normalizes customer interaction data and network telemetry data comprising latency, bandwidth, and packet loss metrics. A generative artificial intelligence (GenAI) labeling agent applies chain-of-thought reasoning to categorize this data based on contextual features and temporal patterns. A machine learning module executes time-series regression models to predict customer churn probabilities using the labeled datasets. Finally, a prescriptive GenAI agent generates actionable customer retention recommendations based on these predictions, which are delivered through an automated engagement system. The system integrates real-time data processing with artificial intelligence (AI)-driven analysis to identify at-risk customers and develop targeted retention strategies.

The invention discloses an industrial data transmission optimization management system based on service link quality, and relates to the technical field of data transmission. Weak delay oscillation and a periodic packet loss rule are reserved through multi-scale processing, so that the system can discover precursor anomalies which are difficult to capture by a traditional monitoring mechanism; minute-level even second-level early warning of link disturbance is realized, and data congestion caused by sudden quality reduction is avoided; a dynamic discrimination mechanism driven by a precursor score is utilized, so that a scheduling decision is converted from passive response to active adjustment, and the probability of cascade failure caused by mass mutation is greatly reduced; an interference spectrum adaptive strategy enables the system to adaptively match the optimal coding mode and the redundant structure when facing narrow-band noise, periodic interference or transient impact, so that the anti-interference capability and the bandwidth utilization efficiency are improved; priority adjustment is carried out in combination with a link risk trend and a state evolution rule, and the protection timeliness and resource allocation efficiency of the key link are remarkably improved.