203 results about "Traffic type" patented technology

A method is provided for encrypted network traffic analysis. The method includes capturing network traffic data; calculating entropy of said data to classify traffic as encrypted or non-encrypted; applying statistical and sequential feature hybridization on encrypted traffic to extract comprehensive features; analyzing the features using a neural network model to identify encrypted traffic types and detect anomalies; and refining the analysis based on entropy and neural network insights through a feedback loop.

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 relates to the field of network security, and discloses a network abnormal traffic monitoring and attack defense system based on artificial intelligence, which comprises a data preprocessing module used for receiving original traffic data, executing cleaning, duplicate removal and normalization processing, and dividing a processing result into data fragments according to a preset time window; the network flow analysis module is used for receiving the data fragments, performing feature extraction and mode analysis and outputting an analysis result representing the flow abnormal degree, and the analysis result at least comprises a score value representing the overall abnormal degree and a feature vector representing the flow mode feature; the attack judgment module is used for comparing the score value with a preset abnormal threshold value so as to judge whether network abnormal traffic exists or not, if yes, the feature vector is further matched with a pre-constructed abnormal traffic type feature library, and a specific abnormal traffic type is determined according to a matching result; and the attack defense module is used for automatically triggering and executing a corresponding defense strategy.

An operation mode from a plurality of operation modes can be determined (310) based on at least one traffic type originated from a UE. The plurality of operation modes can include at least one group operation mode and an individual operation mode. The at least one group operation mode can support a plurality of UEs grouped into a group of UEs. The at least one group operation mode can support at least one network entity communicating associated messages with the group of UEs including the UE. The associated messages can be associated with the group of UEs. A network entity can be informed (320) of the determined operation mode.

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.

Solutions for service aware proxy-call session control function (P-CSCF) traffic routing include: receiving, at a master P-CSCF in a pool of a plurality of P-CSCFs, internet protocol (IP) multimedia subsystem (IMS) traffic from a device; determining, by the master P-CSCF, a traffic type (e.g., 5G, 4G, SMS, WiFi, etc.) of the IMS traffic from the device; based on at least the traffic type of the IMS traffic from the device, selecting, by the master P-CSCF, a serving P-CSCF from the pool for the device; and forwarding, by the serving P-CSCF for the device, the IMS traffic from the device to an IMS. In some examples, the serving P-CSCF selection also includes loading considerations. In some examples, an alternate P-CSCF is available for failover as the new master P-CSCF. In some examples, a network includes multiple pools of P-CSCFs, with each pool having its own master P-CSCF and alternate P-CSCF.

The invention discloses a differentiated congestion control method based on RDMA (Remote Direct Memory Access) and a hardware controller system. In the invention, a differentiated congestion control algorithm is provided by using the DSCP, so that the limitation of complete fair regulation and control of the traditional congestion control algorithm is broken through, accurate resource allocation for different flow types is realized, and a more efficient bandwidth utilization rate is achieved under the congestion condition; complete hardening of a congestion controller system is realized, a scheme for dynamically supporting all congestion flows in a network and supporting 1024 concurrent congestion flows at most is provided, and the congestion flows in the network can be managed more efficiently to achieve the purpose of relieving network congestion; the data which is read from the host and participates in operation does not need to be stored in the cache, so that the burden of the host is reduced, the performance reduction caused by bus data reading delay is eliminated, the processing speed of the parallel congestion event is remarkably improved, and the delay of rate feedback is reduced.

The invention provides a network traffic classification method, device and equipment based on multi-feature fusion, and belongs to the field of artificial intelligence. The method comprises the following steps: preprocessing traffic data to obtain a traffic grey-scale map; screening a minority class traffic sample set from the traffic grey-scale map; simulating a minority class traffic sample set through a WGAN model, and constructing and generating a sample; supplementing the generated sample into the flow grey-scale map to form a balanced sample set; inputting the balanced sample set into a ViT hybrid model to extract features, and obtaining sequence features; fusing the sequence features based on a cross attention mechanism to obtain a target traffic diagram; and classifying the target flow diagram by utilizing a multi-layer perceptron module of the perceptual layer to obtain a classification result. According to the method, the global features and the local features of the network traffic data can be effectively combined for classification, meanwhile, the model architecture is lightened, the accuracy of the model is improved, and the situation that the number of partial traffic type samples is small can be effectively handled.

The invention provides a differentiated service classification and multi-path traffic scheduling method and system, and belongs to the technical field of network communication, the quintuple, packet size and timestamp characteristics of each data packet are captured in real time, a timestamp is mapped to an image horizontal axis, the packet size is mapped to a longitudinal axis after standardization, and discrete data is converted into a continuous visual mode; classifying the traffic in the network by using a pre-trained classification model, and distributing corresponding service requirements and priorities for each traffic type; distributing an INT data packet for each path, and detecting and monitoring the time delay, throughput and packet loss rate of the path in real time; and selecting an optimal path by adopting a CMAB algorithm in combination with the priority of the flow, the service demand, the real-time performance of the path and historical scheduling feedback. According to the invention, comprehensive path quality evaluation is realized; the high-priority service is ensured to obtain stable and high-quality transmission quality; and the accuracy and robustness of path selection are improved.

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-protocol label switching optimization method and device, equipment and a storage medium, and relates to the technical field of network communication, and the method comprises the steps: obtaining current network flow data and network state data; obtaining a bandwidth utilization rate, a link utilization rate and a network traffic type according to the traffic data of the network; generating optimization parameters based on the network state data, the bandwidth utilization rate, the link utilization rate and the network flow type, wherein the optimization parameters comprise a label allocation table, a target forwarding path and a bandwidth adjustment instruction; and optimizing the multi-protocol label switching network according to the optimization parameters. According to the invention, the optimization of the multi-protocol label switching protocol is completed through intelligent label management, the technical problems of resource waste and congestion delay are solved, and the efficiency and flexibility of the multi-protocol label switching network are improved.

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.

Methods and apparatus for prioritizing data traffic in small-cell wireless system. In one embodiment, the system utilizes “quasi-licensed” CBRS (Citizens Broadband Radio Service) wireless spectrum in conjunction with a wireless communication network (e.g., 3GPP 4G-LTE or 5G-NR-based). A “traffic profile” message is used to prioritize the data traffic. In one variant, the traffic profile message is generated by a Customer Premises Equipment (CPE) such as a CBRS FWA, and includes data related to CPE identification, default bearer identification, number of client devices served by the CPE (e.g., via a wireless router connected to the CPE), traffic type and / or priority level associated with each client device and / or data traffic type, etc. In another variant, the base station provides data services to a plurality of fixed wireless access (FWA) apparatus installed at user or subscriber premises of a network based on prioritization according to the present disclosure.

The invention provides an internet cross-regional traffic settlement method and device and electronic equipment, and the method comprises the steps: obtaining cross-regional traffic data of a plurality of time periods, encrypting the traffic data of the plurality of time periods to obtain corresponding Hash values, enabling the traffic data to at least comprise real-time traffic and a settlement rate, and enabling the real-time traffic and the settlement rate to be different from each other; the traffic types of the real-time traffic include IDC traffic, metropolitan area network traffic and CDN traffic; according to an intelligent contract of the Internet, the traffic data is written into a block chain of the Internet, and the traffic data of each time period comprises a hash value of the traffic data of the current time period and a hash value of the traffic data of the previous time period; and according to the traffic data of each time period of the uplink, determining traffic settlement fees of the plurality of time periods, and paying the traffic settlement fees to the target area. The problem of inaccurate Internet cross-regional traffic fee settlement in the prior art is solved.

The invention relates to a data analysis method and system of a right platform and a terminal, and relates to the technical field of data analysis. When the trigger information is consistent with the preset right use information, acquiring starting information of the GPS system; if the starting information is consistent with the starting information, calling a detection position according to the triggering information and a GPS system; if the starting information is inconsistent with the starting information, acquiring a data transmission type; when the data transmission type is a traffic type, outputting preset prompt information; when the data transmission type is a preset Wi-Fi type, obtaining network parameters of the user terminal; determining a network position and a signal connection distance according to the network parameters; calculating a corresponding position as a detection position according to the network position and the signal connection distance; and determining a right use position according to the detection position and the trigger information, and outputting the right use position to a preset right platform. The method has the effect of improving the accuracy of data analysis of the rights and interests platform.

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.

Various aspects of the present disclosure relate to techniques for multiple bandwidth utilization in a wideband carrier during initial access. An apparatus is configured to partition a wideband carrier into a plurality of bandwidth parts (BWPs), wherein each of the plurality of BWPs is mapped to a device type, a traffic type, or a combination thereof; transmit a first set of information on a first BWP of the plurality of BWPs, wherein the first BWP and the first set of information is common for each of the device types or traffic types; transmit second sets of information on second BWPs of the plurality of BWPs, wherein each of the second BWPs and the second sets of information are configured for a device type or a traffic type; and perform initial access procedure with one or more devices based on the first set of information and the second sets of information.