36 results about "Congestion detection" patented technology

The present application relates to devices and components including apparatus, systems, and methods for detecting congestion in wireless networks.

The invention discloses a traffic jam detection and early warning method based on an unmanned aerial vehicle video stream, and belongs to the technical field of intelligent traffic. The system is combined with a floating vehicle triggering model, collects road videos in real time through an unmanned aerial vehicle, and realizes high-precision vehicle detection and tracking in combination with improved YOLOv8 and DeepSort algorithms; unmanned aerial vehicle data and floating vehicle GPS data are fused, three elements of traffic flow are quantified, and a dual-mechanism congestion detection model is constructed; respectively utilizing a GRU cooperative traffic wave theory to predict the congestion dissipation duration and utilizing an improved GRU + GCN model to predict the traffic situation; the signal lamps are dynamically regulated and controlled through multi-agent reinforcement learning, and active congestion relieving is achieved. The method has the advantages of wide-area coverage, high-precision perception and intelligent response, and the urban traffic control efficiency is remarkably improved.

The invention provides a congestion control method and device, switching equipment, a medium and a readable storage medium, and is applied to the field of communication. The method comprises the following steps: in response to a received back pressure signal sent by downstream equipment, determining a first congestion value of at least one data packet according to attribute information of the data packets in a first port queue; determining a second congestion value of at least one data stream corresponding to the at least one data packet according to the first congestion value and the priority; under the condition that a target data stream with a second congestion value meeting the congestion condition exists in the at least one data stream, switching a port queue used for forwarding a data packet corresponding to the target data stream from the first port queue to a second port queue; and sending the early warning event to a detection server, so that the detection server controls the rate of sending the data packet corresponding to the target data stream by the upstream equipment according to the congestion detection result for the target data stream under the condition that the detection server forwards the data packet corresponding to the target data stream through the second port queue.

The invention discloses a secure data transmission method based on multi-thread control, and relates to the technical field of network information security, and the method comprises the following steps: extracting a sensitivity identifier from a data packet header, adopting a lookup algorithm to match a preset sensitivity grading table, dividing data into a high-sensitivity type, a medium-sensitivity type and a low-sensitivity type, determining a priority queue distribution proportion according to the sensitivity, obtaining an initial flow shaping parameter, obtaining current network flow data according to the initial flow shaping parameter, analyzing a preset congestion detection threshold value and a historical transmission record, judging a network congestion degree by adopting a token bucket algorithm, and if the congestion degree is higher than the preset congestion detection threshold value, sending the current network flow data to the priority queue; if yes, the token generation rate of the high-sensitivity data is adjusted, and an adjusted traffic shaping strategy is obtained; according to the secure data transmission method based on multi-thread control, the network transmission efficiency can be effectively improved while the data security is ensured, and the method is particularly suitable for a complex network environment in which data with different sensitivities needs to be processed at the same time.

One or more aspects of the present disclosure relate to detecting and mitigating congestion in a storage area network. In embodiments, peer congestion Fabric Performance Impact Notification (FPIN) messages can be used to infer congestion on a target port that has not received a direct congestion FPIN. Upon receiving a peer congestion FPIN for a target port, the embodiments determine if the target port received a direct congestion FPIN. If not, the embodiments infer congestion on the target port based on the peer notification. The embodiments then control messaging to the congested port to mitigate the congestion, such as by adjusting bandwidth limits. This approach enables congestion detection and mitigation even when severe congestion prevents the delivery of direct notifications to the affected port. Accordingly, the embodiments leverage existing FPIN infrastructure and connectivity information to provide a simple, standards-based solution for identifying and addressing congestion issues in storage networks.

The application provides a vehicle congestion detection method and system based on multi-source data fusion, equipment and medium, belonging to the field of vehicle congestion detection. The method comprises the following steps: acquiring visual perception data, vehicle positioning data and terminal service instruction data, and mapping to construct a multi-source fusion object; constructing a dynamic operation mask to verify the legality of the multi-source fusion object; removing functional blocking objects; performing logical conflict judgment on the remaining multi-source fusion objects after verification, and marking objects with physical state of static and service intention indication of driving, idle non-parking or operation timeout retention as abnormal retention nodes; calculating node clustering density and tail reverse spread rate, confirming congestion situation and outputting detection results. The vehicle congestion detection method and system based on multi-source data fusion, equipment and medium provided by the application fuse service instructions and physical perception, and accurately distinguish functional blocking from pathological congestion based on logical conflict.

The invention discloses a cross-regional edge node congestion collaborative early warning method based on federated learning. The method comprises the steps of data set construction, federated learning framework initialization, local model training, global model aggregation, congestion detection and congestion early warning. The invention relates to the technical field of cross-regional edge network intelligent monitoring, in particular to a cross-regional edge node congestion collaborative early warning method based on federated learning, which comprises the following steps of: initializing a sequence model at an edge node, constructing local loss combined with binary cross entropy and time sequence smooth punishment, and stably training by Adam and early stop; through weighted average aggregation disturbance parameters based on data volume and loss, performance degradation after fusion is prevented by adopting momentum fusion and a rollback threshold value; and meanwhile, an attention mechanism is embedded to realize joint prediction of probability, severity and duration, cross-regional propagation parameters of the graph neural network are utilized, loss is verified, and invalid sharing is rejected, so that prediction accuracy and timeliness are improved, and node congestion is effectively relieved.

The invention relates to the technical field of highway congestion intelligent detection, and discloses a video AI technology-based highway congestion intelligent detection system, which comprises a video tracking module, a congestion analysis module and a scheduling processing module, and is characterized in that the video tracking module comprises a video data acquisition unit, an error evaluation unit and a source tracking unit; the congestion analysis module comprises a congestion analysis unit and a comprehensive evaluation unit. The scheduling processing module carries out scheduling processing on the video tracking module and the congestion analysis module. According to the system, data are collected in real time through the video tracking module, a congestion source is positioned, meanwhile, the equipment state is monitored, the congestion analysis module is combined with multi-dimensional data to generate a congestion severity coefficient, a quantitative basis is provided for decision making, and the scheduling processing module uniformly coordinates all the modules, so that the advantages of real-time response, high precision, high expandability and the like are achieved, and the system is suitable for popularization and application. The highway traffic efficiency can be obviously improved, the management cost is reduced, and the influence of congestion on the society is reduced.

The invention provides a congestion detection method and device, electronic equipment and a computer readable storage medium, and relates to the technical field of flow analysis. According to the method, the original link data is logically split according to the to-be-detected special line, and a technical path from fine-grained sampling to macroscopic portrait evolution is constructed by combining periodic congestion detection and cross-period aggregation analysis. According to the method, not only is the perception capability of micro burst congestion improved, but also the automatic identification of the congestion time period and the main liability flow thereof is realized in a systematic mode, and more comprehensive and operable insight is provided for network performance management.

The application discloses a kind of based on the naming data network hop-by-hop congestion control method of forwarding path number, including router congestion detection and router congestion control;Router calculates the congestion degree of local router by means of active queue management method.Routers determine local congestion state and update the congestion information of data packet.Downstream adjacent router is based on the number of forwarding path and executes multipath forwarding strategy or interest packet sending rate adjustment strategy.When router executes multipath forwarding strategy, the router calculates the shunt proportion of interest packet flow of current interface according to the congestion information of data packet and forwards flow through current or relatively suboptimal interface.When router executes interest packet sending rate adjustment strategy, the router adjusts the interest packet sending rate of same name prefix according to the congestion information of data packet.The application proposes two router control strategies for the characteristics of multiple-source multipath transmission of named data network, to cope with single-path flow and multi-path flow in network.

The application discloses a large-scale multi-mode traffic parallel simulation method and system based on CPU and GPU, relates to the technical field of traffic control, and comprises the following steps: acquiring traffic road networks to be simulated and multi-mode traffic demand data, dividing the traffic road networks to be simulated and the multi-mode traffic demand data based on a preset dynamic spectrum division algorithm to obtain a multi-mode traffic network division result; performing dynamic congestion detection and information feedback processing on the multi-mode traffic network division result based on a preset cross-process congestion feedback algorithm and an MPI communication optimization strategy to obtain congestion state information; inputting the congestion state information into a pre-established microscopic traffic intelligent agent model to perform microscopic behavior parallel calculation, and outputting microscopic behavior data based on the limitation of a regionalized Bucket communication mechanism; and performing simulation processing based on the microscopic behavior data to obtain a final traffic parallel simulation result, so that the simulation precision and efficiency are significantly improved.

The invention provides an implicit network congestion detection method and system based on a data center, and belongs to the field of data center network performance monitoring. The method comprises the following steps: collecting communication flow at a bypass of each key node or a switch in a data center network, extracting an application layer typical feature, a link layer typical feature and a transmission layer typical feature of each key node, normalizing, and carrying out weighted fusion to obtain a recessive congestion index GQI value; obtaining continuous GQI values of all key nodes within a preset historical duration before the to-be-evaluated moment, and adaptively calculating a GQI dynamic threshold value of each key node based on historical data distribution; setting P continuous time points, and comparing the GQI value of the current key node at the P continuous time points with a GQI dynamic threshold; and if the current GQI value is greater than the GQI dynamic threshold at all P continuous time points, judging that the current key node has hidden congestion. According to the invention, the accuracy and real-time performance of data center network congestion judgment are improved.

The present application relates to the field of communication technology, and provides a network congestion detection and congestion node positioning method and network system. A source end node sends a first type of detection packet and each second type of detection packet of a current detection period to a destination end node; each intermediate node caches the received first type of detection packet to a highest priority sending queue, and determines the priority of the received second type of detection packet and caches to a corresponding sending queue; the destination end node obtains first packet reception statistical data when receiving the first type of detection packet of the current detection period, and calculates network congestion degree in combination with packet sending statistical data in the first type of detection packet; and also obtains second packet reception statistical data when receiving the second type of detection packet of the current detection period, and determines a congestion node in combination with network congestion degree, packet sending statistical data and equipment number in the second type of detection packet. The network congestion degree is accurately quantified and the congestion node is quickly positioned.

The application discloses a computing power network bandwidth estimation method, relates to the technical field of bandwidth estimation, and solves the technical problem of urgently needing a high-precision, low-delay and strong-adaptability available bandwidth estimation method to meet the strict requirement on network transmission efficiency in a cloud game / cloud e-sports scene. The method comprises the following steps: acquiring an RTCP feedback frame of a video stream, performing bandwidth sampling, congestion detection and link capacity detection according to the RTCP feedback frame, and obtaining current bandwidth sampling data, a congestion signal and link capacity; correcting the bandwidth sampling data according to the link capacity to obtain current bandwidth data; if congestion occurs, iteratively calculating the current available bandwidth from a sending end to a receiving end through the congestion signal; and if no congestion occurs, iteratively calculating the current available bandwidth from the sending end to the receiving end through the bandwidth data. The application can improve the utilization rate of bandwidth, reduce delay and be applicable to various scenes.

Implementations for hierarchical telemetry collection with per-layer monitoring in an accelerator interconnect network. In some implementations, a telemetry system comprises devices with protocol-level interface ports managed by management agents. A telemetry collector connects with read-only access and the management agents support at least two subscription modes: one reporting operational state changes upon occurrence, and another reporting per-port telemetry data at a configurable sampling interval. When a device cannot push telemetry, the management agent may poll the device and report the data transparently. In some implementations, each port maintains per-layer telemetry counters comprising physical layer error correction histograms, data link layer flit counters, transaction layer credit utilization histograms, and port performance byte counters. The credit utilization histograms may include bins indicating time at different utilization levels, enabling congestion detection and health assessment. The telemetry may support cross-layer correlation and predictive maintenance.

A congestion control method, apparatus, and system are provided, and pertain to the field of network technologies. The method includes: A first device obtains a first packet. The first packet includes congestion detection indication information and a congestion information field. The congestion detection indication information indicates a device to obtain congestion information corresponding to the device. The congestion information field is used to carry the congestion information. The first device obtains, based on the congestion detection indication information, congestion information corresponding to the first device. The first device updates the congestion information field based on the congestion information corresponding to the first device. In this application, the congestion information field in the first packet can carry a large amount of congestion information, so that an end-side device performs accurate congestion control based on the congestion information carried in the congestion information field.

A method and system for constructing a time-series attention model for electricity prices that integrates grid congestion information is disclosed. The method includes: collecting grid state, market state, and electricity price data, and constructing a dataset using window partitioning; building a grid congestion detection and vector fusion module to determine grid congestion status and generate congestion state feature vectors, fusing these feature vectors with grid state vectors and market state vectors to form exogenous variables; constructing a time-series attention network to perform feature mapping on exogenous variables, embedding vectors into endogenous and exogenous variables, and obtaining electricity price prediction results after fusion using a dual attention mechanism; training and validating the grid congestion detection and vector fusion module and the time-series attention network; and testing the grid congestion detection and vector fusion module and the time-series attention network validated in step 4 using a test set. This invention can improve the accuracy and stability of electricity price prediction under complex operating scenarios.

The invention provides a grain and oil production line tracking detection method and system, and relates to the technical field of grain and oil production data analysis. The method comprises the following steps: collecting historical grain and oil production data of a plurality of subareas in a grain and oil production line based on Internet of Things equipment, and constructing a local accumulation chain of each subarea; identifying a production acceleration event in the historical grain and oil production data, generating congestion resistance data of each subarea, performing real-time congestion detection on a plurality of subareas in the grain and oil production line, and determining a production deviation state of each subarea; and constructing a real-time accumulation chain of each partition, determining candidate abnormal partitions, and performing congestion diffusion influence detection on each candidate abnormal partition according to the congestion resistance data to obtain a congestion diffusion detection result of the grain and oil production line. According to the invention, the accuracy and reliability of grain and oil production line congestion detection are improved.

The invention particularly relates to a dynamic congestion sensing hierarchical scheduling method and device based on reconfigurable computing, and the method comprises the steps: constructing a hierarchical tree-shaped scheduling structure, and mapping a node scheduling algorithm and a congestion algorithm to a reconfigurable computing module; performing congestion identification on the dequeued and enqueued queues based on a mapping congestion algorithm; when an enqueue application is received, the messages are classified according to a congestion detection result; calculating priority and sending time information of the dequeued application queue elements; queue elements are pushed into the scheduling sub-lists according to the priorities, ordered insertion of the priorities and sending time of the queue elements is completed in the sub-lists, the elements which meet the sending time and have the highest priorities are extracted, and the scheduling sub-lists and information of corresponding pointers are updated during pushing and extraction. According to the invention, dynamic adjustment of the scheduling strategy is supported, dynamic and efficient sharing of intelligent differential congestion control and computing resources is realized, and the scheduling efficiency of complex multi-service traffic in high-speed network equipment is improved.

The application discloses a kind of interconnection network round-trip delay measurement method and device, wherein the method includes: timing control module counts to threshold, indicates frame processing module group configuration measurement request frame, write frame sequence number and configure corresponding mark, frame group configuration is allowed after completion and sends frame, timing control module synchronously records first time stamp, frame processing module stores frame sequence number into queue buffer module;After receiving response frame, frame processing module checks mark, extracts frame sequence number and response end's threshold difference value representing response time, is associated with transmission to queue buffer module;After buffer module completes frame sequence number matching check, timing control module extracts the difference value, records fourth time stamp, obtains round-trip delay by combining the difference value of first, fourth time stamp and the difference value of response end.The application realizes whole-process measurement by underlying hardware circuit, can capture nanosecond level network change in real time, guarantees the real-time performance of congestion detection and the accuracy of congestion control, improves the operation efficiency of cluster.

The present application relates to devices and components including apparatus, systems, and methods for detecting congestion in wireless networks.

The application provides a data center-based implicit network congestion detection method and system, and belongs to the field of data center network performance monitoring.The method comprises the following steps: collecting communication traffic at each key node or switch in a data center network, extracting application layer typical features, link layer typical features and transmission layer typical features of each key node, normalizing, and then weighting and fusing to obtain an implicit congestion index GQI value;obtaining continuous GQI values of all key nodes within a preset historical time length before an evaluation time point, and adaptively calculating a GQI dynamic threshold value of each key node based on historical data distribution;setting P consecutive time points, comparing the GQI values of the current key node at the P consecutive time points with the GQI dynamic threshold value; and if the current GQI value is greater than the GQI dynamic threshold value at all the P consecutive time points, it is determined that the current key node has implicit congestion.The application improves the accuracy and real-time performance of data center network congestion determination.

The invention relates to the technical field of intelligent drainage, and discloses a rain sewage pipe network congestion detection method and system.The method comprises the steps that pipe network water level flow, historical water level flow and external environment working condition data of key nodes of a pipe network are obtained; obtaining a hydraulic characteristic vector according to the pipe network water level flow and the historical water level flow; obtaining a hydraulic state change track according to the hydraulic characteristic vector; obtaining a deviation quantitative index according to the hydraulic state change track and a pre-constructed pipe network reference model; according to the deviation quantitative index, obtaining a fluctuation classification label; obtaining a congestion credibility score according to the fluctuation classification label and a pre-stored historical congestion record; according to the congestion credibility score and the external environment working condition data, obtaining an alarm instruction signal; and obtaining a congestion detection result according to the alarm instruction signal. The method can improve the precision of pipe network congestion detection.

The application discloses a kind of based on the safe data transmission method of multithread control, it is related to network information security technical field, the method includes extracting sensitivity identification from data packet head, using lookup algorithm matches preset sensitivity classification table, data is divided into high sensitivity, medium sensitivity and low sensitivity three categories, according to the sensitivity, priority queue distribution proportion is determined, obtains initial traffic shaping parameter, according to initial traffic shaping parameter, obtain current network traffic data, analyze preset congestion detection threshold and historical transmission record, using token bucket algorithm judges network congestion degree, if congestion degree is higher than preset congestion detection threshold, then adjust the token generation rate of high sensitive data, obtain adjusted traffic shaping strategy;The safe data transmission method based on the multithread control of this application can effectively improve network transmission efficiency while ensuring data security, especially suitable for complex network environment needing to handle different sensitivity data simultaneously.

The invention discloses a congestion management method, electronic equipment, a storage medium and a program product, and belongs to the technical field of communication. The method comprises the following steps: sending a congestion detection packet to a source spraying node according to a preset detection period in response to the fact that the unused time of a target entropy marked as congestion exceeds a threshold value; the target entropy marked as congestion is at least packaged in the congestion detection packet, and the source spraying node determines a congestion spraying path of the congestion detection packet through the target entropy marked as congestion, and sprays the congestion detection packet based on the congestion spraying path; and in response to a detection response packet of the received congestion detection packet and a congestion mark in the detection response packet indicating that congestion does not exist, marking the target entropy marked as congestion as non-congestion, thereby improving the utilization rate of network resources.

The invention discloses a communication method and device, network equipment, a storage medium and a program product, relates to the technical field of communication, and can control the problem of data loss so as to guarantee normal operation of a communication network. The method comprises the following steps: receiving a data message from a sending end server; congestion detection is carried out on the first access device to obtain a congestion detection result, and the congestion detection result is used for indicating whether the first access device is congested or not and indicating the data transmission condition when the first access device is congested; and in response to the congestion detection result, indicating that the first access device is congested but the data transmission condition is within a preset congestion range, sending a data message to the receiving end server, and triggering the sending end server to perform speed reduction processing on the data message based on the data transmission condition.

The embodiment of the invention discloses a video code rate adjustment method and device, equipment and a storage medium, and the method comprises the steps: obtaining a cache utilization rate, a current video code rate, the receiving and transmitting time of each data packet, the current time and a transmission state evaluation value, and calculating a risk value based on the current video code rate and a preset upper limit code rate; periodically calculating a link cache utilization rate according to the receiving and transmitting time of each data packet, and periodically calculating an estimated frame delay time according to the current time and the receiving and transmitting time of each data packet; counting a plurality of estimated frame delay times in a preset duration range, generating a data sequence corresponding to the estimated frame delay times based on the calculation sequence, and determining a congestion state according to the link cache utilization rate, the transceiving time of each data packet and the data sequence; and determining a current adjustment strategy according to the congestion state, the transmission state evaluation value, the risk value and a preset adjustment rule, and adjusting the current video code rate based on the current adjustment strategy. The fine granularity and timeliness of congestion detection and the accuracy of code rate adjustment are improved, and the code rate control period is shortened.

The invention discloses a data processing method and device, electronic equipment and a storage medium, and relates to the technical field of data processing. A specific embodiment of the method comprises the steps of receiving a congestion identification instruction, obtaining corresponding conveyor belt information and a time interval, and querying a package transmission video of a conveyor belt in the time interval; identifying parcel transportation features of each parcel in the parcel transmission video, obtaining conveyor belt features and conveyor belt speed of a conveyor belt, and generating a target transmission feature vector corresponding to the conveyor belt; querying each connection conveyor belt connected with the conveyor belt, and determining a connection transmission feature vector of each connection conveyor belt; and inputting the target transmission feature vector and each connection transmission feature vector into a preset identification model to obtain a congestion degree corresponding to the conveyor belt. According to the embodiment, the problems that the package sorting efficiency is reduced and the timeliness of package sorting cannot be guaranteed due to the fact that only the package condition at the outlet of the conveying belt is considered in a congestion detection mode of a sensor and processing is carried out after congestion occurs can be solved.

The application discloses an outdoor communication expansion method based on a 5G network and a Mesh network, and comprises the following steps: receiving a target data packet of a sending end communication through a target network node in a 5G network communication path; obtaining a congestion detection index according to network delay measurement data of the target network node, maximum available bandwidth of the 5G network communication path and an explicit congestion notification marking proportion of each network node in the 5G network communication path; determining a shunt path according to a congestion level of each communication path, a path switching cost, network delay measurement data of each network node and the explicit congestion notification marking proportion of each network node when it is determined that the 5G network communication path is congested according to the congestion detection index; and shunting and transmitting the target data packet to a receiving end according to the Mesh network and the shunt path. The application can adaptively adjust a data communication strategy, can quickly adapt to flow changes, can optimize bandwidth allocation and can enhance flow fairness.

This application provides a congestion control method, apparatus, switching device, medium, and readable storage medium, applicable to the field of communications. The method includes: in response to receiving a backpressure signal from a downstream device, determining a first congestion value for each of at least one data packet based on attribute information of data packets in a first port queue; determining a second congestion value for each of at least one data stream corresponding to the at least one data packet based on the first congestion value and priority; if a target data stream exists in at least one data stream whose second congestion value satisfies the congestion condition, switching the port queue used for forwarding data packets corresponding to the target data stream from the first port queue to the second port queue; and sending a warning event to a detection server, so that the detection server, when forwarding data packets corresponding to the target data stream through the second port queue, controls the rate at which the upstream device sends data packets corresponding to the target data stream based on the congestion detection result for the target data stream.