151 results about "Traffic type" patented technology

The invention discloses a TSN scheduling optimization method and device based on flow sensing autonomous learning, equipment and a medium. The method comprises the following steps: deploying a lightweight flow detection module in a switch or a router, and after a controller receives a data request, automatically identifying a newly arrived unknown service flow by using the lightweight flow detection module, and judging whether the newly arrived unknown service flow is a periodic TT flow or an unpredictable burst flow; the controller performs classification management on the identified service flow types, collects topological information and flow requirements of the whole network and issues the topological information and the flow requirements to the terminal nodes through a network management interface; the controller constructs an intelligent queue scheduling task based on the collected network topology information and traffic demand and converts the task into a Markov decision process MDP, network resources, queue states and priorities are used as a state space, a scheduling strategy is used as an action space, a reward function is designed in combination with throughput and delay indexes, and an intelligent queue scheduling task is obtained. Driving a dynamic environment through real-time data and training a DRL model; an enhanced queue scheduling mechanism Pro-CQF is adopted, different priority labels are configured according to classified flow types, and then mixed flow scheduling is carried out; the controller periodically collects time delay, packet loss rate and end-to-end transmission delay indexes and feeds back the indexes to the DRL model, and a scheduling strategy is updated online. According to the method, the traffic sensing and scheduling efficiency is greatly improved in a network environment in which multiple service flows coexist and end-side equipment functions are different, and the reliability and the expandability of the TSN in industrial Internet of Things, edge computing and other high-real-time application scenes are remarkably enhanced.

The invention provides a method and system for judging suspicious traffic in encrypted traffic, and the method comprises the steps: collecting to-be-detected encrypted traffic, and extracting the encrypted traffic features of the to-be-detected encrypted traffic; wherein the encrypted traffic feature comprises a first traffic feature and a second traffic feature, and the second traffic feature comprises domain name popularity; the second traffic feature is determined based on a malicious neighborhood value determined according to the relation graph; the relation graph comprises domain name nodes, entity nodes, edges connecting the entity nodes and edges connecting the entity nodes and the domain name nodes, and the edge attributes of the edges of the relation graph comprise communication related data and traffic types; determining the traffic type of the to-be-measured encrypted traffic based on the encrypted traffic feature of the to-be-measured encrypted traffic, the traffic type including normal traffic and suspicious traffic; and in response to the fact that the traffic type of the to-be-tested encrypted traffic is suspicious traffic, performing subsequent decryption analysis on the to-be-tested encrypted traffic through a decryption DPI module.

The present invention provides according to one of its aspects a method of communication in a wireless network comprising an access point and a plurality of stations, the method comprising, at one of the stations:receiving a trigger frame from the access point, the trigger frame reserving a transmission opportunity on at least one communication channel of the wireless network, the transmission opportunity including random resource units that the stations may access using a contention scheme, wherein the trigger frame includes a first indicator specifying a traffic type of data allowed to be sent on at least one of the random resource units;determining, based on the first indicator, eligible resource units, among the resource units in the reserved transmission opportunity, for the station to contend for access for transmitting data; andtransmitting data on a determined eligible resource unit using a contention scheme.

The invention discloses an internet behavior early warning method and system based on network packet processing, and belongs to the field of network security, and the system comprises gateway equipment, a DPI analysis module, a user portrait module and an early warning module. The gateway equipment is used for capturing user data packets in real time on a network driving layer by using an XDP technology, filtering the captured data packets, and selecting the data packets conforming to a set rule; the DPI analysis module is used for deeply analyzing the selected data packets through a DPI technology and carrying out traffic type marking and classified storage on the data packets of each user according to an analysis result; the user portrait module is used for performing user portrait analysis based on the storage data packet of the user and identifying an abnormal behavior; and the early warning module is used for configuring an early warning rule and a notification mode and giving out early warning aiming at the abnormal behavior of the user. According to the invention, high-speed processing of the data packet can be realized, and on the premise of not sacrificing performance, abnormal behaviors of a user can be accurately identified and timely early warning can be given out.

The invention discloses a multi-link aggregated cloud native network system and a flow scheduling method. The system comprises an application sensing layer, a virtual link layer and a physical link layer, the application sensing layer is connected with the virtual link layer and used for analyzing network traffic to be distributed to obtain features of the network traffic, and the features comprise traffic types, priorities and bandwidth requirements; the virtual link layer is connected with the physical link layer, and is used for detecting the states of the plurality of links to obtain the state information of the plurality of links, and determining the flow distribution strategy of the plurality of links based on the characteristics and the state information; and the physical link layer is used for carrying out flow distribution on the plurality of links based on the flow distribution strategy. According to the invention, the technical problem that the traditional cloud native network depends on single link transmission, so that network congestion is easy to occur when the service flow is increased sharply is solved.

Systems and method are disclosed for adaptive and / or autonomous traffic control. In one illustrative implementation, there is provided a method for processing traffic information. Moreover, the method may include receiving data regarding travel of vehicles associated with an intersection, using neural network technology to recognize types and / or states of traffic, and using the neural network technology to process / determine / memorize optimal traffic flow decisions as a function of experience information. Exemplary implementations may also include using the neural network technology to achieve efficient traffic flow via recognition of the optimal traffic flow decisions.

The invention provides a CSQF-based wide area network mixed flow scheduling method and system and an electronic device, and the method combines the scheduling demands of a TT flow and an AVB flow through the reasonable division of a periodic resource block, guarantees that the timeliness requirement of the TT flow is satisfied, and provides a flexible bandwidth allocation strategy for the AVB flow. And a dynamic period scaling mechanism is introduced to adapt to the change of the network load, and conflicts among different traffic types are reduced through a sliding window preemption strategy, so that the overall scheduling effect of the mixed traffic is optimized.

The invention discloses a processing method, a communication device and a storage medium, and the processing method comprises the steps that a first device determines an effective message 1 time domain resource in response to meeting a first condition; through the technical scheme of the invention, a resource determination mechanism for autonomously initiating the random access of the DO-A is defined so as to support the DO-A traffic type.

The embodiments of the present disclosure provide a method for identifying abnormal traffic drop, and a device, a storage medium and a program. The method comprises: determining a target traffic type corresponding to a target network device port, and a traffic threshold value corresponding to the target traffic type; sequentially collecting real-time traffic values of the target network device port within first time slices at a set first time slice granularity; if a plurality of first real-time traffic values collected within a plurality of consecutive first time slices are all lower than the traffic threshold value, determining as a plurality of second real-time traffic values lower traffic values among real-time traffic values which are collected prior to the plurality of first real-time traffic values; and if a statistical value of the plurality of second real-time traffic values is greater than the traffic threshold value multiplied by a set multiple, determining that the plurality of first real-time traffic values correspond to an abnormal traffic drop event. The identification based on traffic types and setting different traffic threshold values for different traffic types improve the accuracy of abnormal traffic drop identification.

The invention discloses a traffic hub passenger flow prediction method, system and device based on big data, and relates to the technical field of data processing. The method comprises the following steps: determining a traffic transfer type of a first traffic hub; a passenger flow prediction model is constructed for a traffic transfer type through flow-direction prediction of a single traffic type and interaction prediction of multiple traffic types, and the passenger flow prediction model is deployed in a traffic management system in an embedded mode and comprises a first prediction layer, a second prediction layer and an integrated output layer which are fully connected; and receiving a prediction task, combining real-time passenger flow monitoring data, transferring to a passenger flow prediction model to carry out hierarchical cascade directional triggering and decision making, determining a passenger flow prediction result, converting the passenger flow prediction result into a passenger flow guide graph, and carrying out terminal equipment visualization and congestion early warning management. The technical problems of low traffic hub passenger flow prediction accuracy and difficulty in coping with multi-traffic-type interaction scenes in the prior art are solved, and the technical effects of improving passenger flow prediction precision and system response efficiency are achieved.

An apparatus, method, and computer program product are provided for generating a frame associated with a shared transmission opportunity (TXOP). The frame indicates at least one of (i) whether a station (STA) can communicate during the shared TXOP with (a) the apparatus or (b) the apparatus and one or more other STAs, (ii) a maximum duration of the shared TXOP during which the STA can communicate, or (iii) at least one of one or more permissible traffic types that can be communicated during the shared TXOP or one or more permissible streams that can be communicated during the shared TXOP. The apparatus, method, and computer program product further provide for transmitting the frame to the STA.

The invention relates to the technical field of Internet of Vehicles, and discloses an Internet of Vehicles communication stability optimization method and system based on multichannel connection multiplexing, and the system comprises a proxy service module, a terminal interaction module, a connection multiplexing module, a base station monitoring module, a load balancing decision module, and a strategy optimization module. The method comprises the following steps of: deploying a multi-thread proxy service at an edge node adjacent to a base station, constructing a surviving global shared connection pool, and realizing cross-thread security access by using a read-write lock; the terminal sends a request containing a target server IP and a TLS session identifier to the virtual IP entry through a TLS 3.1 + encryption protocol, so that the three-way handshake delay is avoided; a base station switching event is synchronously detected, a dynamic load balancing mechanism is triggered, health scores and weight factors are calculated in real time, and requests are distributed according to flow types. According to the method, handshake delay is shortened, communication continuity is improved, the problem of request packet loss is solved, and a high-reliability communication infrastructure is provided for an intelligent network connection vehicle.

Methods, systems, and devices for wireless communications are described. A UE may obtain, via an application program interface (API), an indication of an application type of an application at the UE and information including an indication of performance requirements associated with the application, an indication of a traffic type associated with the application, an indication of whether the performance requirements are being met, an indication of quality of service (QoS) information associated with a packet data unit (PDU) session established for communication by the application, an indication of a network slice associated with the PDU session, an indication of a power consumption of the UE, an indication of whether a power budget of the UE is being met, or any combination thereof. The UE may communicate one or more wireless signals via a subset of multiple antennas of the UE based on the application type or the information.

The application discloses a traffic transmission method and device, computer equipment and a storage medium. It belongs to the technical field of communication. The method can specifically include the following steps: after receiving to-be-transmitted traffic, determining a current transmission path and a traffic type of the to-be-transmitted traffic. First path quality information of the current transmission path is determined. Based on the traffic type and the first path quality information, first path feasibility of the current transmission path is determined. According to the first path feasibility and the current transmission path, a target transmission path is determined. The to-be-transmitted traffic is transmitted based on the target transmission path. The application can not only determine path quality information, but also determine path feasibility in combination with the traffic type, so that the quality of a communication service is effectively ensured, and user experience is improved while path quality monitoring is realized.

The invention relates to the technical field of network technology communication, in particular to a data transmission method and device, computer equipment and a storage medium. The method comprises the following steps: receiving a to-be-transmitted data packet sent by a source node; determining a transmission path corresponding to the to-be-transmitted data packet according to a source address, a destination address and a protocol type packaged in the to-be-transmitted data packet under the condition that the to-be-transmitted data packet is determined to be the target traffic type; wherein the source address is determined according to the partition key and the queue pair number corresponding to the data packet to be transmitted; and transmitting the data packet to be transmitted to the destination node through the transmission path. According to the invention, the load balancing of the transmission path is realized, the transmission efficiency of data transmission is improved, and the congestion of data transmission caused by the increase of the data volume is prevented.

The invention discloses a network flow classification method and device based on multi-modal feature fusion, and the method comprises the steps: obtaining network flow data, extracting an IP address as a node, and constructing a communication graph; time modal features and event modal features are extracted for each node, and standardization processing is carried out on the time modal features and the event modal features; the time modal features and the event modal features are aligned; fusing the two types of aligned features; performing multi-layer neighbor sampling and hierarchical aggregation on the communication graph by using a graph neural network model to obtain structure-enhanced node features containing multi-hop neighbor information, inputting the node features into a linear classifier, outputting a category probability, selecting a category with the maximum probability as a prediction result, and performing iterative training to obtain a classification model; and mapping the classification model to a data plane of the programmable switch to realize online reasoning of the data packet. According to the method, high-precision identification of various network traffic types is realized by fusing the spatial modal, time and event modal characteristics.

Aspects of the present disclosure are directed to modifying use of Restricted Target Wake Up Time Service to restrict broadcasting traffic parameters sets on a per traffic category basis between an access point and an end device in a wireless network. In one aspect, a method includes transmitting, by an access point, a message to an end device connected to the access point, the message identifying for the end device a traffic type restriction policy that the access point has on reporting Restricted Target Wake Time (R-TWT) parameters for a plurality of traffic types; and receiving, from the end device, a separate Broadcast TWT Parameters Set for each one of the plurality of traffic types in accordance with the traffic type restriction policy.

The embodiment of the invention relates to the field of traffic intrusion detection, in particular to an abnormal traffic intrusion detection method and device based on a multi-modal composite sensing architecture. A specific embodiment of the method comprises the following steps: preprocessing data to obtain a traffic characteristic image set; constructing a multi-modal composite sensing model; executing the following classification steps for each traffic feature map in the traffic feature map set: inputting the traffic feature maps into a multi-modal sub-model to obtain a first branch feature map, a second branch feature map and a third branch feature map; inputting to a feature fusion sub-model to obtain fused traffic feature information; inputting into a capsule network sub-model to obtain abnormal traffic characteristic information; and determining each piece of generated abnormal traffic type information as an abnormal traffic type information set. The implementation mode shows remarkable advantages in complex network threat detection, and the robustness of small sample attack category detection is improved.

The invention relates to a traffic analysis method and device, computer equipment, a storage medium and a program product. The method comprises the following steps: analyzing first configuration information configured by management software based on a flow sampling system mainboard of a server, and collecting network flow data; the first configuration information comprises white list configuration information and sampling strategy configuration information; identifying the traffic type of the network traffic data through a traffic mode identification model in the main board of the traffic sampling system and analyzing second configuration information configured by the management software; and performing corresponding processing on the network traffic data based on the identification result of the traffic type and through pre-configured third configuration information. The traffic type of the network traffic data is identified by using the traffic mode identification model, so that the traffic type is accurately identified, and the identification efficiency can be improved.

The application discloses a kind of encryption malicious traffic detection methods based on deep learning, utilize LSTM model to extract the time sequence characteristics of network traffic data, further extract the semantic features of traffic data by BERT model, finally form comprehensive feature representation;Comprehensive feature representation is clustered using DBSCAN algorithm;According to the defined naming rules, the sample label in each cluster is optimized, and the traffic type with similar attack characteristics is classified as a unified label;Construct a graph structure, connect the edge of the optimized traffic sample label and its comprehensive feature representation, and establish edge connection between different clusters according to cosine similarity;Construct a GraphSAGE graph neural network model, aggregate the information of the nodes and their neighbor nodes of the graph structure to obtain the updated feature vector of each node, and use the updated node features for classification processing to identify whether it is malicious encrypted traffic.The application improves the detection accuracy and robustness.

The present application provides a method and apparatus for identifying application types based on traffic characteristics. The method comprises: extracting features from multiple types of traffic feature data corresponding to bidirectional session traffic generated during the operation of a target application based on convolution kernels with different dimensions and weights, obtaining feature result data corresponding to each type of traffic feature data; and identifying the application type of the target application based on each of the feature result data and a preset fully connected layer. The present application can effectively improve the accuracy and effectiveness of identifying application types based on traffic characteristics, reduce the resources required to identify the application type to which traffic belongs, and effectively improve the efficiency of identifying traffic types.

A first station (STA) transmits to a second STA a first frame indicating a first traffic type that the second STA is allowed to transmit to the first STA while the first STA operates in a first power mode of a power save mode. The first STA receives from the second STA, and while the first STA operates in a second power mode of the power save mode, a second frame; and transitions, in response to the second frame, from the second power mode to the first power mode. The first STA receives from the second STA, and while the first STA operates in the first power mode, a third frame comprising one or more first data frames of the first traffic type.

An apparatus discontinues transmission of a first message of a first traffic type in a first time slot or sub-slot and does not resume the transmission in the first time slot or sub-slot. The apparatus then stores a payload of the first message. The apparatus later fully retransmits the payload in a second time slot or sub-slot after the first time slot or sub-slot.

This disclosure provides systems, methods, and apparatus for access control techniques for restricting access from a user equipment (UE) (102) to a non-terrestrial network (NTN). A network entity, such as a satellite 106B or a terrestrial base station 106A, communicates access control information (130) to the UE indicating that access to the NTN is barred based on a traffic type. There are various mechanisms for indicating barring, traffic type, and relationships with NTN. For example, a network entity may indicate barring via a non-access stratum (NAS), a radio resource control (RRC), or a system information message. In some examples, a network entity transmits a UE (User Equipment) Routing Policy (URSIP) with a Routing Policy (URSIP) rule that includes an indicator indicating barring and a traffic descriptor (TD) describing a type of barred traffic. The UE avoids accessing the NTN based on the access control information (160).

A method has the step of: transmitting a downlink control information message for scheduling an uplink or downlink transmission of a plurality of data pieces of a plurality of traffic types in a single data block via a communication resource, the plurality of traffic types comprising a first traffic type for transmission via a first portion of the communication resource and a second traffic type for transmission via a second portion of the communication second resource.

The invention discloses an Internet of Things private network flow processing method and related equipment. The method comprises the following steps: acquiring session flow between a base station and a terminal and flow direction of the session flow; determining the flow type of the session flow based on the flow direction; when the flow type of the session flow is uplink three-layer session flow, converting a target IP of the session flow into a local private IP, executing downlink packet receiving processing on a flow message, and sending the flow message to the terminal; and when the flow type of the session flow is the downlink three-layer session flow, replacing the local private IP with the target IP of the session flow, and sending the flow data to the terminal. The method can be widely applied to the technical field of network resource scheduling.

The invention discloses a vehicle fault checking method and device, equipment and a medium. The method comprises the following steps: acquiring service flow data and link state data of each link in a vehicle-mounted communication network; classifying the traffic according to the service traffic data of each link to obtain a plurality of service scene traffic categories; monitoring a link health state according to the link state data of each link to obtain a link state evaluation result of each link; determining a routing path according to the link state evaluation result of each link and the traffic type of the service scene of each link; if the link state evaluation result of any link in the links indicates that the link is abnormal, obtaining fault diagnosis data; identifying a fault type and a fault position according to the fault diagnosis data to obtain a fault checking result; and automatically triggering a routing adjustment strategy according to the troubleshooting result, and reporting the troubleshooting result and the routing adjustment strategy to the cloud. According to the invention, the accuracy of vehicle troubleshooting is improved.

The present invention provides according to one of its aspects a method of communication in a wireless network comprising an access point and a plurality of stations, the method comprising, at one of the stations:receiving a trigger frame from the access point, the trigger frame reserving a transmission opportunity on at least one communication channel of the wireless network, the transmission opportunity including random resource units that the stations may access using a contention scheme, wherein the trigger frame includes a first indicator specifying a traffic type of data allowed to be sent on at least one of the random resource units;determining, based on the first indicator, eligible resource units, among the resource units in the reserved transmission opportunity, for the station to contend for access for transmitting data; andtransmitting data on a determined eligible resource unit using a contention scheme.

The embodiment of the invention relates to equipment, a method and a device for coordination of round-trip communication and a computer readable storage medium. The method comprises: receiving an event associated with at least one Quality of Service (QoS) flow of a particular traffic type from the RAN device, wherein the at least one QoS flow is associated with a flow coordination group identifier; and performing coordination for the at least one QoS flow based at least on the event.