436 results about "Data delay" patented technology

The invention discloses an industrial scene-oriented data acquisition system and an industrial scene-oriented data acquisition method. According to the invention, through the multi-level dynamic optimization design, the data acquisition efficiency and the system reliability in a complex environment are significantly improved. The system dynamically allocates thread resources based on the real-time communication state of the equipment, realizes stable throughput under a high-concurrency scene in combination with core binding and polling scheduling strategies, and ensures that millisecond-level response is still maintained when 10000-level equipment is accessed. The memory preloading and protocol template technology eliminates jitter during operation, the hierarchical resource isolation mechanism provides deterministic guarantee for key control instructions, and interruption of the production process due to data delay or resource competition is avoided. The data flow delay is further reduced through multi-protocol efficient analysis and intelligent cache management, seamless compatibility of heterogeneous equipment in a hybrid networking scene is supported, and the strict requirements of continuous production industries such as steel and chemical engineering for real-time performance and stability are met.

The invention discloses an electrical switch cabinet detection method based on the Internet of Things, and particularly relates to the technical field of electrical switch cabinets. A sensor is installed inside or outside a switch cabinet, temperature, humidity, current, voltage and gas concentration are collected, data are transmitted to an edge computing node for preprocessing by using a wireless communication technology, the preprocessed data are uploaded to a cloud platform, storage and trend analysis are performed at a cloud end, and the data are analyzed based on big data analysis and an artificial intelligence algorithm. According to the invention, the system can predict potential faults, a user can check the operation state and the prediction result of the equipment in real time through the cloud platform, and carries out the emergency shutdown or equipment scheduling operation remotely according to the early warning information, thereby effectively solving a reliability problem caused by communication interruption or data delay in an existing Internet of Things system, and improving the safety and intelligent level of the monitoring of the switch cabinet.

The invention provides a multi-core heterogeneous system-oriented startup deployment and cooperative processing method, which comprises the following steps of: when the system runs, obtaining startup codes after a master core and a slave core are electrified, respectively obtaining mirror image files of Linux and RTOS (Real Time Operating System) on the basis of synchronous running and storage partition, and running the mirror image files on the master core and the slave core after moving the mirror image files; and after the heterogeneous operating system is loaded, generating an interrupt signal based on inter-core interrupt and a corresponding register through a CLINT module in the main core, and realizing data communication between the main core and each slave core based on the interrupt signal and the shared memory. By means of the method, after the system is powered on, the multiple cores can synchronously run the starting codes, and time delay and uncertainty possibly caused by one-by-one starting of the single cores are avoided; communication and data transmission among multiple cores are realized through interruption and memory sharing, the synchronism and consistency of data are ensured, and misjudgment and decision errors caused by data delay and inconsistency are avoided, so that the real-time performance of the system is remarkably improved.

The invention discloses a smart watch motion data real-time synchronous transmission system, relates to the technical field of data transmission, and solves the problems of data delay accumulation, signal packet loss, sensor data drift and the like through cooperation of a delay evaluation module, a data retransmission management module and a data calibration module. The delay evaluation module records the start time Tsta and the end time Tend of each transmission in real time, calculates an accumulation delay coefficient Llx and compares the accumulation delay coefficient Llx with a delay threshold value Lq so as to trigger a delay alarm; the data retransmission management module detects the packet loss number Dbz through a packet loss statistical calculation unit, and adaptively adjusts a retransmission strategy in combination with a retransmission evaluation unit to ensure the transmission integrity; the data calibration module calculates a sensor drift coefficient Spxs according to a temperature fluctuation factor Te, a noise interference factor En and a historical offset factor Ho, compares the sensor drift coefficient Spxs with a threshold drift Q, automatically adjusts reference parameters of the sensor, and ensures data precision and system stability.

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 high-frequency power data acquisition adaptive frequency and priority processing method and device based on resource load feedback, and a storage medium, and belongs to the technical field of high-frequency power data processing. The method comprises the following steps: acquiring resource load information of a distribution network side intelligent terminal node in real time; according to the real-time resource load information, judging whether a preset sampling period of the power monitoring data needs to be adjusted, if so, dynamically correcting through a double-layer fast and slow ring adjusting mechanism to obtain a final sampling period, and otherwise, maintaining an original period; acquiring power monitoring data acquired by the node in the corresponding sampling period; and on the basis of a preset priority queue grading rule, a tube queue algorithm is utilized to adopt a differential transmission strategy for the data, so that priority processing of different levels of data is realized. The method does not need to depend on a prediction model, and realizes acquisition link elastic control and key data delay guarantee through real-time quantification of node loads, dual-time-domain closed-loop adjustment of a sampling period and hierarchical queue management messages.

This application relates to the field of wireless communication, and provides a communication method and apparatus, and a system, to implement continuous data transmission, thereby improving transmission performance. The method includes: A terminal device determines an available resource set SA corresponding to N pieces of data, where SA is located in a resource selection window, N parameter sets correspond to the N pieces of data, data i corresponds to a parameter set i, N is a positive integer greater than 1, i is an integer greater than or equal to 0 and less than N, and the parameter set i includes at least one of the following parameters: a sending priority prioTX,i, a data delay budget PDBi, a frequency domain resource unit LsubCH,i, or a channel access priority class CAPCi; and sends the N pieces of data on a resource in SA.

The invention relates to the field of intelligent transportation, and discloses a handling equipment management method for intelligent transportation, which comprises the following steps: acquiring an original data stream of handling equipment according to an Internet of Things sensor; performing space-time alignment calibration on the original data stream to obtain a structured operation state data set with equipment space-time relevance; inputting the structured operation state data set into a space-time convolutional network for feature learning; according to the method, the original data stream of the carrying equipment is collected through the Internet of Things sensor, the state data of the equipment can be obtained in real time in combination with the space-time alignment calibration technology, and the space-time relevance of the data is ensured. The accurate real-time monitoring provides a reliable data basis for subsequent decision making, the scheduling problem caused by data delay or inconsistency in a traditional method is avoided, the structural data are input into the space-time convolutional network for feature learning, the operation features of the equipment can be effectively extracted, and the method is suitable for large-scale popularization and application. And accurate input is provided for subsequent dynamic path planning.

The invention relates to the technical field of data acquisition, in particular to a multi-channel intelligent acquisition-based control and acquisition system, which comprises a signal quality evaluation module, a signal optimization adjustment module, an abnormal signal detection module, a resource scheduling control module, a data synchronization adjustment module and a cloud backup strategy module. According to the invention, by analyzing the amplitude and frequency components of the signal in real time, noise and distortion can be identified and corrected in real time, signal processing is optimized, the accuracy and availability of data are improved, the real-time optimization processing of the signal improves the processing quality of the signal, and the high efficiency of data synchronization and cloud backup is ensured; by dynamically adjusting the synchronous bandwidth and period, data changes can be flexibly responded, the risk of data delay and loss is reduced, intelligent detection and resource scheduling of abnormal signals are achieved, the response speed and maintenance efficiency of the system are improved, and the stability and safety of the whole system are improved through accurate resource allocation and timely maintenance response.

The invention discloses a tangelo ecological orchard data management platform, relates to the technical field of agricultural informatization and intelligent management, is used for solving the problem that decision-making efficiency is affected by data delay, and realizes real-time acquisition and classified storage of orchard environment data by arranging a sensor node network and a distributed storage system. Through data preprocessing and feature extraction, the data redundancy is reduced, and the analysis efficiency is improved; an orchard environment change trend is predicted by using a time sequence analysis algorithm, and a scientific basis is provided for resource allocation; the generation of a dynamic resource allocation scheme is realized by introducing an adaptive weight allocation mechanism and a resource priority index; and an interaction module is deployed at the orchard management terminal, so that a user can check data and adjust resource allocation in real time, and the intelligent level of orchard management is improved.

The invention provides a data synchronization method and device for a distributed computer storage system. The data synchronization method comprises the following steps: determining a data concentration ratio of execution data in each data synchronization transaction in a database through a data range and a data increment of each data synchronization transaction; obtaining all synchronous storage nodes of a database in the computer storage system, and determining a node allocation strategy of the database during data synchronization according to the load characteristics of the synchronous storage nodes in the database and the data dependency relationship between the data synchronization transactions; performing dependency quantification on execution conditions of the transactions in the database according to a node distribution strategy and each centralized feature to obtain execution dependency of the transactions in the database; and performing balanced allocation on the synchronous storage nodes of the data synchronization transactions in the database based on the execution dependency. Based on the scheme, the balanced distribution of the synchronous storage nodes in the database can be realized, so that the data delay of the computer storage system in data synchronization can be reduced.

The invention provides an advertisement putting dynamic game decision-making method and system based on multi-objective optimization, and the method comprises the steps: obtaining user behavior key data which comprises user visual focus position information; transmitting the user visual focus position information to a multi-target optimization model in a preset decision server, and generating multi-target optimization model input data; analyzing the input data of the multi-target optimization model and a preset game constraint condition by using the multi-target optimization model to generate a multi-target game decision parameter; and carrying out dynamic game deduction calculation based on the multi-target game decision parameters, and generating a dynamic advertisement position adjustment scheme so as to carry out advertisement putting dynamic game decision. According to the method, millisecond data is transmitted to the multi-target optimization model, the problem of strategy oscillation caused by data delay and target conflict in traditional advertisement decision making in a real-time attention scene is solved, and accurate dynamic matching of user focus drift and advertisement display is realized.

The present application relates to the technical field of middleware, and in particular to a cache data semi-synchronization method, comprising comprises the following steps: writing and running a distributed cache proxy layer service using a preset programming language, receiving a read / write command request from an application client, parsing a Key consistent hashing value and sending same to a rear-end Redis sharding node. A master instance parses a message packet, marks a write operation and records same in an AOF file. Upon write to disk, the master instance sends an AOF file transfer command to a slave instance node, and the slave instance acknowledges reception. When receiving a reception response, the master instance updates an acknowledgment offset of the slave node and responds to the client. When network delay is high, data of a master node and a slave node is marked as "asynchronous", and it is automatically downgraded to asynchronous replication. According to the present application, by means of a self-developed Redis kernel, an asynchronous ack mechanism is used to optimize redis to achieve master-slave semi-synchronization, thereby enhancing data reliability of a single point of failure, and eliminating the influence introduced by a native Redis asynchronous replication mechanism such as data delay and data consistency.

The invention discloses a cloud storage data access method and device, and is applied to the technical field of cloud services, the method comprises the following steps: obtaining historical behavior information of a target terminal, the historical behavior information being a parameter associated with a cloud storage data access behavior of the target terminal in a historical time period; target behavior information and a plurality of pieces of target access data of the target terminal are obtained according to the historical behavior information, and the target behavior information is a parameter associated with a cloud storage data access behavior of the target terminal in a future time period; determining multiple pieces of target preloading data according to the target behavior information and the multiple pieces of target access data; carrying out preloading processing on each piece of target preloading data by utilizing the target behavior information to obtain each piece of preloaded target preloading data; and in response to an access instruction of the target terminal, performing access processing on each piece of pre-loaded target pre-loaded data. According to the invention, the data delay of the cloud storage service can be effectively reduced, and the user experience of the cloud storage service is improved.

The invention relates to the technical field of data management, and discloses a dynamic partitioning and priority scheduling method based on time sequence data, which comprises the following steps: collecting time sequence characteristics of an industrial data source through an edge gateway and carrying out structured storage in Redis, the time sequence characteristics comprising collection frequency, historical peak time period and service priority; load indexes are calculated based on time sequence characteristics, and a distributed message system is driven to execute dynamic partition adjustment of pre-judgment type capacity expansion, hot spot precise splitting and low-peak intelligent capacity reduction; and full-link data priority scheduling is realized through production end route isolation, Broker end resource inclination and consumption end thread pool isolation. According to the invention, the dynamic adaptation of the distributed message system resource and the industrial time series data load is realized, the real-time performance of high-quality data is ensured, the integrity of data transmission and the system adaptability are improved, and the problems of poor load fluctuation adaptation, high-quality data delay and easy data loss due to faults in the prior art are effectively solved.

The invention discloses a coal mine fireproof simulation training method based on a virtual reality technology, relates to the technical field of coal mine fireproof simulation training, is used for solving the problem that a virtual scene and student operation are asynchronous due to sensor data delay or misalignment in the training process, and comprises the following steps: collecting action data of a student in real time; comprise posture change, hand movement and position coordinate information. Seamless synchronization of the sensor and the virtual scene is ensured through the time synchronization algorithm and the dynamic compensation model, and the safety and effectiveness of training are improved. In combination with a sliding window, a prediction algorithm and a redundancy detection mechanism, the system has high fault-tolerant capability, and training continuity and stability are guaranteed. The dynamic path planning under the fire spreading trend is realized by adopting the A * algorithm, and the guidance is quickly adjusted and corrected when the trainee deviates from the path, so that the real-time response capability and the immersion of training are improved, and the trainee is helped to quickly make a decision and act in an emergency.

The invention discloses a satellite angular rate identification method and related equipment, and relates to the technical field of rocket launching, and the method comprises the steps: obtaining a rocket telemetry video frame sequence after satellite-rocket separation; for each frame of image of the rocket telemetry video frame sequence, determining a dynamic image area of the target satellite based on the static area mask; based on a feature detection algorithm, binary descriptors are extracted from dynamic image areas of two adjacent frames of images; based on the binary descriptor, matching corresponding feature point pairs between two adjacent frames of images; estimating a rotation matrix between two adjacent frames of images through an iterative optimization algorithm based on the corresponding feature point pairs; and determining the angular rate of the target satellite according to the rotation matrix and the time interval between the two adjacent frames of images. According to the method, rapid and high-precision identification of the satellite angular rate is realized, the problem that the traditional technology depends on indirect data and is high in delay is solved, task success or failure can be judged in real time, and the launching task evaluation efficiency is improved.

The invention relates to the technical field of data processing, in particular to a carbon asset information security synchronization method depending on an internet cloud platform, and the method comprises the steps: constructing each carbon asset change sequence of each user based on the similar condition of the carbon asset information of each user during two adjacent carbon asset information updating, in combination with the data updating frequency of various kinds of carbon asset information, analyzing the type information influence degree corresponding to each user; constructing the trend matching confidence of each kind of carbon asset information of each user based on the similarity between the carbon asset change sequences of each user and other users; and determining the synchronization priority of the carbon asset information of each user based on the type information influence degree and the trend matching confidence so as to ensure the security and high efficiency of the transmission process, and realizing real-time and high-efficiency information transmission for the security synchronization method of the carbon asset information depending on the Internet cloud platform. The problems of data delay and inconsistency in carbon asset distributed management are solved.

The embodiment of the invention discloses a three-dimensional tennis track real-time reconstruction method and system based on multiple cameras, internal and external parameters and calibration results of the multiple cameras are utilized, respective two-dimensional pixel coordinates are converted into three-dimensional rays, and nodes are positioned in combination with a minimum distance algorithm. According to the embodiment of the invention, the real-time reconstruction of the three-dimensional track of the tennis ball is realized by virtue of the synchronous multi-camera two-dimensional image through the steps of camera accurate calibration, two-dimensional to three-dimensional ray conversion, intersection point calculation and screening, data output and the like. Compared with the prior art, the reconstruction precision is improved through accurate calibration and ray intersection screening; by means of multi-camera data synchronization and simple calculation process, data delay is reduced, and real-time performance is prominent; by means of multi-camera data redundancy and a placeholder mechanism, the robustness in a complex environment is enhanced; the output three-dimensional point data can directly support the functions of ball speed calculation and the like, and the expansibility is good.

The invention specifically relates to a remote safety officer allocation system and method for a pilotless automobile, and relates to the technical field of pilotless automobiles, and the system comprises a vehicle state monitoring and data collection module; a communication and network guarantee module; a security officer resource management module; the task scheduling and dynamic coordination module is configured to perform intelligent task allocation based on vehicle requirements and safety officer states to realize optimal resource allocation; and an emergency response and decision support module. According to the invention, the vehicle state monitoring and data acquisition module fuses data of multi-source sensors such as a laser radar and a camera and high-precision positioning information, realizes no-dead-corner environment perception, and improves the integrity of environment information compared with a traditional scheme; after the edge computing node preprocesses the original data, the cloud data transmission quantity is reduced, satellite double-channel communication redundancy is combined, it is ensured that the emergency instruction transmission delay is reduced, and the response speed is increased compared with a single network scheme; and the accident risk caused by data delay or interruption is reduced.

The method for determining the maximum allowable communication data delay of a multi-agent formation system solves the problem of how to effectively determine the maximum allowable communication data delay, and belongs to the field of multi-agents. The present invention includes: S1, obtaining the parameters and iteration step ΔT of the pilot-follower multi-agent formation system; S2, calculating the block matrices C and E; S3, initializing the number of iterations f=1, setting the initial value of the time lag variable d0=ΔT; S4, substituting d0 into the determination condition, calculating the feasible solution of the determination condition, if there is a solution, go to S5, if there is no solution, reduce the iteration step ΔT, go to S2, or replace the Laplace matrix of the communication topology and the communication matrix of the pilot and follower, and go to S3; S5, updating the iteration step f=f+1; S6, d f‑1 =fΔT, d f‑1 Substitute the judgment conditions and calculate the feasible solutions to the judgment conditions. If there is a solution, go to S5. If there is no solution, the maximum communication delay d M is (f‑1)ΔT.

The invention provides an intelligent all-in-one machine with a body, a system and an operation method, and belongs to the technical field of industrial automation and robot control systems.The all-in-one machine comprises an automation system IDE module, an automation system driving module, a robot body driving module and a function supply module, the function supply module is used for providing a data acquisition function, a simulation task execution function, a model training function and a model reasoning function with time synchronization for the robot body driving module according to a control command which can be executed by the robot; the intelligent all-in-one machine solves the problem of time synchronization between the all-in-one machine and the robot, between the acquisition module and the robot and between the acquisition module and the multi-frequency sensor data, and ensures that the time synchronization between the acquisition module and the robot and between the acquisition module and the multi-frequency sensor data is realized in the sensor data acquisition, model reasoning and task execution processes through accurate timestamp management and a multi-level time synchronization mechanism. Millisecond-level time alignment of data of all the modules can be achieved, and control errors caused by time drift and data delay are effectively avoided.

The invention discloses a digital dangerous cargo transportation supervision system and method, belongs to the technical field of vehicle supervision, and aims to solve the problems that in digital dangerous cargo transportation, loading and unloading links are insufficient in authenticity verification, abnormal fluctuation in the transportation process is difficult to recognize in real time, and abnormal handling response is delayed. After a dangerous cargo transportation electronic waybill is obtained, loading and unloading scene verification is completed by delimiting a compliance area, shooting an initial scene image and dynamically constructing an image flow sequence, and a carrying password is generated for cargo encryption storage and unloading unlocking; a passing route is segmented, a vehicle operation base line is established based on historical data, data delay and loss are distinguished by monitoring the conformity and transmission interval of transportation data and the base line, abnormal fluctuation is recognized, and early warning is triggered; and during early warning, a target verification position is selected based on positioning, and the vehicle is guided to the verification area to complete abnormity verification. And cheating behaviors in loading and unloading links are avoided, transportation risks are identified, abnormities are quickly handled, and dangerous cargo transportation safety and supervision efficiency are effectively improved.

The invention discloses a reinforcement learning training acceleration system and method based on adaptive tensor parallelism, and relates to the technical field of artificial intelligence, and the system comprises an offline measurement module which constructs a system performance database before training; the reasoning execution module is used for executing an autoregressive reasoning task of the model in an RLHF generation stage and is responsible for collecting running state data of model reasoning in real time; the delay prediction module is used for estimating the residual generation time overhead of the model under different candidate tensor parallelism degrees and the switching time overhead required for completing one-time tensor parallelism degree switching in a generation stage in real time based on the system performance database and the operation state data; the switching control module is used for calculating predicted total delay under different candidate tensor parallelism degrees, and generating a switching control signal and sending the switching control signal to the switching execution module when a triggering condition is met; the acceleration system realizes a mechanism of generating stage tensor parallelism dynamic adjustment.

The invention provides a display panel and a display device. The display panel comprises a first screen body and a second screen body, the first data lines are electrically connected with the first screen body, extend in the first direction and are located in the first screen body; the second data lines are electrically connected with the second screen body, and the second data lines extend in the first direction; and the control module is located at one end of the first screen body, and the first data line and the second data line are electrically connected with the control module. According to the display panel provided by the invention, the situation that the first screen body and the second screen body share a data line, data delays of different areas in the first screen body have large differences, and consequently display of the first screen body is uneven is avoided, the display uniformity is improved, and the display effect of the display panel is improved.

The invention relates to the technical field of multi-network connection, in particular to a Raman optical fiber amplifier remote monitoring system based on multi-network connection. Multiple different network connection modes are achieved through the multiple network connection units, flexible transmission and remote monitoring of data are achieved, a proper network interface can be automatically selected for data transmission according to the current network environment, and the flexibility and stability of network connection are guaranteed. According to the method for packaging the data frames of the different network media on the data link layer, the integrity and effectiveness of the data on the different transmission media are ensured, the system complexity is reduced, and the data transmission efficiency and the system response speed are improved. Especially in a multi-network connection environment, the optimized data link layer processing module can effectively reduce data delay and improve the real-time monitoring capability of the system. Wide area network transmission of data is realized through an MQTT protocol, and safe transmission and real-time monitoring of remote data are ensured.

The invention provides a multi-working-condition dynamic adaptive ship hybrid power dispatching system, which is applied to the technical field of ship power systems and energy management, and comprises a data exchange module, a working condition module, a hybrid power generation module and an energy management module, wherein the data exchange module realizes cross-protocol data analysis and unified timestamp packaging, and ensures the consistency and real-time performance of data exchange between modules; the working condition module is used for collecting ship working conditions and generating working condition conversion signals, an EMS in the energy management module is used for calculating a scheduling strategy, and the hybrid power generation module executes power distribution and charge-discharge control of the diesel generator set, the axle generator and the battery pack according to the scheduling strategy. Through the data exchange module, the problems of data delay and errors caused by complex protocol fusion and non-uniform clocks are solved, and the dynamic adaptation and response capability of the ship under complex working conditions is effectively improved.

The invention discloses a third-party cloud service data synchronization processing method and system based on a timed task, and the method carries out the attribute configuration of the timed task through a management interface, and the objects of the attribute configuration comprise execution time, frequency, a third-party cloud service data source and target system information. Storing the object of the attribute configuration in an attribute database; when the timed task is triggered, acquiring data from a third-party cloud service in an asynchronous mode, storing the data to a local cache, and recording a data identifier; synchronizing the processed data to a target system by adopting an incremental synchronization strategy according to the data identifier, and performing conflict detection and conflict resolution in the synchronization process; the execution state of the timed task is monitored in real time, and if the execution state of the timed task is abnormal, a report is generated and automatic retry is tried. According to the method, the problems of resource waste, data delay, system performance reduction, data conflict loss and the like confronted by third-party cloud service data synchronous processing in the prior art are solved.

The invention is suitable for the field of vehicle-road cooperation, and provides a real-time intelligent data stream analysis and management method and system, and the method comprises the steps: obtaining multi-type data streams transmitted by a vehicle terminal, roadside equipment and a cloud platform in a vehicle-road cooperation scene; assigning priority levels to the multi-type data streams; carrying out parallel processing on the data streams with different priorities by adopting a self-adaptive analysis algorithm, and extracting environment perception features, vehicle state features and traffic event features; performing integrity and accuracy verification on the analyzed feature data through a real-time verification model, marking abnormal data and triggering a correction mechanism; according to the priority level and a data quality evaluation result, dynamically distributing, calculating and transmitting targeted resources, and pushing effective feature data to a corresponding decision node to support real-time response; priority transmission of key data is guaranteed through dynamic priority scheduling, abnormal data is verified and corrected in real time, and the problems of poor multi-source data fusion, key data delay and the like are effectively solved.

The invention discloses a communication method and device related to a time delay state report. The method comprises the following steps: under the condition that a first condition is met, a first device triggers reporting of DSR and starts a first timer; the first condition at least comprises that data of which the residual scheduling time delay is less than a time delay threshold exists in the LCG, and the first timer is not operated; the DSR is used for reporting information related to the data delay. By the method, a first device may run a first timer in the event that reporting of DSR is triggered. In the embodiment of the invention, in the running period of the first timer, the reporting of the DSR is not triggered, so that the repeated reporting of the DSR can be avoided, the waste of uplink resources caused by the repeated reporting of the DSR can be avoided, the uplink resources are saved, and the signaling overhead is reduced.