56 results about "Network traffic control" patented technology

The invention discloses a private network data security detection method based on big data, and belongs to the field of security detection, and the method comprises the steps: obtaining a real-time data packet from private network traffic, encoding the data packet through a forward error correction code technology, generating redundancy check information, and obtaining an encoded data packet; if a bit error is detected in the transmission process of the coded data packet, requesting a sending end to retransmit a damaged data packet through an automatic retransmission request mechanism to obtain a retransmitted data packet; adjusting the redundancy of a forward error correction code and a trigger threshold of an automatic retransmission request according to the adaptive error correction parameter, generating an optimized error correction scheme, and obtaining a repaired data packet; and aiming at the alarm processing instruction, automatically adjusting a network flow control strategy, limiting the transmission bandwidth of an abnormal destination, updating the sensitive data fingerprint database, and obtaining optimized protection configuration.

The invention provides a network flow control method and system, an engine, a node and related equipment, and relates to the technical field of communication. The method comprises the steps that communication information of a source computing power node is received, and the communication information comprises identification numbers of the source computing power node and a target computing power node and an identification number of a source port selected by the source computing power node; determining an optimal source port and a sending rate of the source computing power node based on the communication information; determining a forwarding path of the source computing power node based on the optimal sending port; configuration information is sent to the source computing power node, and the configuration information comprises the sending rate and the forwarding path. By means of the technical means, the problems that in network data transmission in the related technology, the link bandwidth is not fully utilized, and burst transmission flow cannot be dealt with are solved.

The invention discloses a flow control method based on a neural network, and relates to the technical field of network flow control, and the method comprises the steps: collecting network flow metadata, constructing a standardized feature data set, carrying out the flow data classification and prediction based on a hybrid neural network, generating a differential flow control strategy, and carrying out the strategy optimization and dynamic adjustment; statistical features are extracted by using flow metadata acquired in multiple environments, spatial-temporal feature fusion and attention weighting are carried out in combination with a convolutional neural network and a long-short-term memory network, and network state recognition and flow trend analysis are realized; based on an analysis result, generating a control strategy adaptive to different network environments, and performing strategy optimization and real-time adjustment through reinforcement learning; the problems of accurate flow control and dynamic strategy adjustment in a complex network environment are effectively solved, and the accuracy, the adaptivity and the system stability of flow control are improved.

A method performed by a computer system for use in controlling user plane network traffic in a cloud environment is described. The method includes deploying a temporary container in an executing container group, the executing container group including an application container that executes a packet-processing application, wherein the temporary container includes a network traffic control software that includes a pre-compiled network traffic control program and configuration information, wherein the temporary container, when deployed, executes a client component that is operable to: establish a secure connection to a server component of the packet-processing application and transfer the network traffic control software to the packet¬processing application using the secure connection, wherein the pre-compiled network traffic control program, when executed in the packet-processing application, is operable to control network traffic associated with the packet-processing application.

The invention provides a double-end cooperative network-on-chip flow control method and device and electronic equipment, and the method comprises the steps: receiving first flow counting information synchronously transmitted by a destination end through a rapid signal, and determining second flow counting information of a source end, the source end and the destination end are respectively a starting node and an ending node of a complete link in the network-on-chip; estimating the link state of the network-on-chip according to the first flow counting information and the second flow counting information; and controlling the flow injection rate of the source end according to the link state. According to the method, counting information synchronization of a source end and a destination end is realized by utilizing the characteristics of low cost and high speed of a control signal in the network-on-chip, so that the link state of the network-on-chip is accurately estimated, the process ensures that no obvious flow accumulation exists on a path, bandwidth resource waste caused by excessive speed limitation is avoided, and the link state of the network-on-chip is accurately estimated. Quicker and more accurate flow management is supported; and more timely and accurate flow regulation is realized.

The invention relates to the technical field of computer network flow control, and discloses an intelligent flow control method and device fusing ECMP and priority scheduling, and the method comprises the steps: collecting network flow rate, priority and link load data through a flow monitoring module, a link monitoring module and a priority recognition module; and a prediction algorithm is combined with correlation analysis to obtain a flow distribution prediction value, and the prediction value is corrected. After three-dimensional data points are clustered, similarities under different sequence lengths are analyzed, a weight is formed by combining actual distribution values to obtain a historical prediction value, a final flow distribution prediction value is calculated by integrating a prediction correction value, the historical prediction value and the similarities, and ECMP and priority scheduling control is carried out according to the final flow distribution prediction value. The device comprises a memory, a processor and a running computer program. According to the invention, flow prediction and dynamic scheduling driven by multi-dimensional data are realized, load balancing and priority guarantee are both considered, and the precision and efficiency of network flow control are improved.

Systems and methods are disclosed herein method for controlling traffic of a network at an application layer. A controller detects that an application is initiating transmission of a message from a sender host to a receiver host. The controller records one or more application layer sender timestamps corresponding to the transmission of the message, and records one or more application layer receiver timestamps based on detecting receipt of at least a portion of the message at the receiver host. Responsive to detecting that the message has been completely received by the receiver host, the controller determines a message duration spanning a length of time between a first one of the application layer sender timestamps and a last one of the application layer receiver timestamps. The controller performs a network traffic control function based on the message duration.

The present application relates to the technical field of network communication, and particularly relates to a RoCE network flow control method and system, the method comprising: performing static code analysis on source code of a RoCE protocol stack, identifying key function points on a data processing path, and generating a probe point set; processing historical monitoring data corresponding to the probe point set, calculating an utility value for each probe point; screening the probe points based on the utility values; deploying probes at the screened probe points, collecting network layer monitoring data and host layer monitoring data, and controlling network flow based on the network layer monitoring data and the host layer monitoring data.

Embodiments of the present disclosure provide a network traffic flow control method and apparatus based on a distributed storage system, an electrical device, and a storage medium. The method includes: acquiring a transmission link for transmitting target data in response to a first data server in the distributed storage system receiving a transmission request for the target data; configuring a first priority parameter for the transmission link by the first data server according to the priority information of the business type to which the target data belongs; and in response to transmitting the target data through the transmission link, configuring a second priority parameter for the target data by the first data server according to the first priority parameter of the transmission link, so as to enable a data transmission device to allocate a network bandwidth to the target data according to the second priority parameter.

The invention relates to a network communication method and device, computer equipment, a readable storage medium and a program product. The method comprises the following steps: determining a target receiving position of network traffic, redirecting the network traffic to a first target port in a virtual switch through a network traffic control program, redirecting the network traffic to a network card through a second target port in the virtual switch and the network traffic control program, and determining target network traffic from the network traffic by the network card. And sending the target network traffic to the target receiving position. Compared with a traditional communication mode that address migration is carried out on the network card after the network card is connected to the virtual switch, according to the scheme, the network flow control program is arranged at the port of the network card and the port of the virtual switch, and redirection of the network flow is achieved through the network flow control program; therefore, the network communication of the virtual machine is realized through the original setting of the network card, and the stability of the network communication is improved.

The application relates to a network traffic control method and device, a chip, a network interface card, computer equipment, a computer readable storage medium and a computer program product. The method is applied to a chip comprising a RISC-V architecture processor core and comprises the following steps: determining a to-be-updated token quantity corresponding to a token bucket; reading a number of overdraft tokens corresponding to the token bucket in a rate limiting configuration table based on a hardware characteristic of a RISC-V design, and reading a current token quantity; updating the current token quantity in the rate limiting configuration table based on the to-be-updated token quantity, the number of overdraft tokens and the current token quantity; reading the rate limiting configuration table, and marking a to-be-sent packet based on the current token quantity, the number of overdraft tokens in the rate limiting configuration table and a length of the to-be-sent packet; and processing traffic corresponding to the to-be-sent packet based on actions corresponding to each mark in the rate limiting configuration table. The method can improve processing efficiency.

This invention provides a network traffic control method, apparatus, and readable storage medium. The method includes: acquiring target information of a target router within a first AS and resource pool computing power information transmitted by a third AS, wherein the resource pool computing power information includes computing power information of at least one computing service node, and the target information includes the segment routing identifier (SID) of the target router; determining a target computing service node that meets the computing power requirements based on the target router's target information and the resource pool computing power information; identifying routers in the third AS connected to the target computing service node as last-hop egress routers, and generating a list of segment identifiers (SIDs) corresponding to packet forwarding paths based on the last-hop egress routers; and sending the SID list to the ingress router of the first AS.

Methods and apparatuses for network traffic control are disclosed. According to an embodiment, a first network function (NF) receives, from a second NF, control information for controlling non-access stratum (NAS) traffic that is to be processed by the first NF. The control information instructs the first NF to perform a predetermined action on the NAS traffic when the NAS traffic satisfies a predetermined condition. The first NF sends, to the second NF, a response to the control information.

The invention discloses a micro-service dynamic network flow control method based on multi-factor authentication, and belongs to the field of containerized network security management. Comprising the following steps of: prohibiting flow forwarding among all pods except a multi-factor authentication service pod; the multi-factor authentication service pod receives and verifies the access request; the authentication result is converted into a NetworkPolicy rule, and the NetworkPolicy rule is obtained; calling a kube-api-server to update the NetworkPolicy rule, and calling a Kube-api-server to update the NetworkPolicy rule; the method comprises the following steps of: automatically calling a kube-api-server to remove a Network Policy rule after a timer expires; and finally, automatically calling the kube-api-server to remove the Network Policy rule. According to the method, an attacker can be effectively prevented from breaking through container isolation and transversely moving to diffuse threats by using kernel vulnerabilities, and the security of the whole cloud environment is improved.

The invention relates to the technical field of computers, in particular to a rate control method and device for a Docker container virtual network. The method comprises the following steps: acquiring event data corresponding to a Docker internal event, and extracting network event characteristics in the event data; judging whether the Docker internal event is a virtual network creation event or a virtual network abnormal event based on the network event characteristics; if the Docker internal event is a virtual network creation event or a virtual network abnormal event, obtaining a network flow control parameter corresponding to the virtual network creation event or the virtual network abnormal event; and performing traffic control on the Docker internal event in a preset mode according to the network traffic control parameter. According to the invention, fairness and flow distribution of the container in the same network environment can be ensured, and an individual task container is prevented from occupying excessive bandwidth resources.

The invention relates to a network flow control method and device, computer equipment, a storage medium and a program product. The method comprises the following steps: generating a classification program; the classification program is an eBPF program running in a kernel mode; controlling the network flow through the classification program; wherein the classification program is configured to classify the network traffic, and if the network traffic belongs to a first category, the network traffic is sent to an auxiliary container; and if the network traffic belongs to the second category, sending the network traffic to a service container. By adopting the method, the communication efficiency can be improved.

The application discloses a special network data security detection method based on big data, belongs to the safety detection field, and comprises the following steps: acquiring real-time data packets from special network traffic, encoding the data packets through a forward error correction code technology, generating redundant check information, and obtaining encoded data packets; if bit errors are detected in the encoded data packets during transmission, requesting the sender to retransmit the damaged data packets through an automatic repeat request mechanism to obtain retransmitted data packets; according to adaptive error correction parameters, adjusting the redundancy of the forward error correction code and the trigger threshold of the automatic repeat request, generating an optimized error correction scheme, and obtaining repaired data packets; for an alarm processing instruction, automatically adjusting a network traffic control strategy, limiting the transmission bandwidth of an abnormal destination, updating a sensitive data fingerprint library, and obtaining an optimized protection configuration.

The present invention discloses a low-resource flow control method based on an FPGA, which is applied to a network flow control system. The system includes: a descriptor management module, a token flow control module, and a rate calculation module. The method comprises: the descriptor management module parses the descriptor corresponding to a data packet to be sent, obtains a first queue number and the length of the data packet to be sent, and then sends a flow control query request to the token flow control module; the token flow control module queries the number of first tokens in the corresponding sending queue based on the first queue number and generates a flow control decision result; the token flow control module periodically sends a token injection request to the rate calculation module, the token injection request including the second queue number of any sending queue; and the rate calculation module calculates the number of second tokens to be injected into the token flow control module based on the sending rate corresponding to the second queue number. The present invention eliminates the need to track the sending rate status of each sending queue in real time, thereby reducing hardware resource consumption on the FPGA.

A network flow control method includes: a first network device receives a target packet from a second network device, where the target packet carries packet flow control information, and the packet flow control information includes identification information of the second network device, information about a port from which the target packet flows into the second network device, information about a queue in which the target packet is located in the second network device, and / or priority information of the target packet. The first network device determines that the second network device needs to perform a flow control operation, then generates a first flow control notification based on the packet flow control information. The first network device sends the first flow control notification to the second network device, where the first flow control notification indicates the second network device to perform the flow control operation.

The invention belongs to the technical field of digital communication and network flow control, and particularly relates to an electric power communication resource elastic allocation method and system based on multi-objective optimization, and the method comprises the steps: extracting a spatial distribution difference according to real-time flow state data, and calculating a flow space-time evolution gradient in combination with a historical flow rate surge state; a physical cache boundary is extracted according to node attribute features, and information physical vulnerability is calculated by fusing with a flow spatio-temporal evolution gradient; according to the physical vulnerability of the information and the service priority, carrying out self-adaptive privilege lifting processing, and generating an elastic distribution factor; and allocating the actual available bandwidth quota according to the elastic allocation factor, and refreshing the rate configuration parameter. According to the invention, the key communication node which is endangered to the congestion limit can be identified and the physical bandwidth compensation is carried out, so that the key signaling is ensured to obtain the priority forwarding resource and the network communication robustness is improved.

Facilitating dynamic network traffic steering using artificial intelligence in advanced communication networks is provided. A method includes determining respective results of application of a utility function to respective combinations of potential handovers of a specified user equipment from a source cell to respective target cells of a group of target cells. The method also includes, based on the respective results of the application of the utility function, determining that a first combination of the respective combinations increases a value of the utility function as compared to other combinations of the respective combinations, other than the first combination. Further, the method includes, during a defined interval associated with a traffic steering process, facilitating the handover of the specified user equipment from the source cell to the first target cell. Other user equipment other than the specified user equipment within the communication network are not handed over during the defined interval.

The present invention discloses a method, product, device and medium for cluster network traffic control, which relates to the field of computer technology, and includes: collecting current subnet information, current access control rule files and current malicious network traffic characteristics in a container cluster; dividing the subnet addresses in the current subnet information into each subnet address set, classifying the current access control rule files to obtain each rule address set, and obtaining the container addresses corresponding to the current malicious network traffic characteristics; respectively generating each new access control rule based on each subnet address set, each rule address set and the container addresses, and determining the priority of each new access control rule; and sending each new access control rule to the kernel of each virtual switch in the container cluster according to the priority, so that each virtual switch controls the network traffic according to each new access control rule. The access control rules are adjusted more reasonably, thereby improving the control reliability of the cluster network traffic.

This disclosure provides a method, apparatus, electronic device, and storage medium for intelligent computing network traffic control, relating to the field of intelligent computing network technology. The method includes: generating work queue elements within a first preset time period; matching each work queue element with a corresponding first token; sequentially sending each work queue element carrying a first token in the first work queue to a receiving network interface card (NIC), wherein the receiving NIC receives each work queue element when it determines that the first token carried by each work queue element is valid; and when the current time enters a second preset time period, if the first work queue contains unsent work queue elements, placing the unsent work queue elements into the second work queue. This disclosure stores data in a work queue, thereby controlling the transmission of work queue elements through tokens and preset time periods, avoiding network traffic congestion, packet loss, and other problems, and improving the effectiveness and reliability of network traffic control.

The application is a neural network-based traffic control method, and relates to the technical field of network traffic control.The application collects network traffic metadata, constructs a standardized feature dataset, classifies and predicts traffic data based on a hybrid neural network, generates differentiated traffic control strategies, and implements strategy optimization and dynamic adjustment.Statistical features are extracted from traffic metadata collected in multiple environments, convolutional neural networks and long short-term memory networks are combined for spatiotemporal feature fusion and attention weighting, network state recognition and traffic trend analysis are realized, control strategies adapted to different network environments are generated based on analysis results, and strategy optimization and real-time adjustment are realized through reinforcement learning.The application effectively solves the problems of accurate traffic control and dynamic strategy adjustment in complex network environments, and improves the accuracy, adaptability and system stability of traffic control.

One or more multi-service network traffic controllers are established for a distributed system. The controllers are connected to traffic control implementation units at a first service and a second service. Based at least in part on data collected from a traffic control implementation unit deployed at the second service, a modification to be made to a parameter of a traffic control implementation unit deployed at the first service is determined at the controllers. The modification is applied at the first service, and results in a change to a traffic flow of the second service.

The invention discloses a private instant messaging system based on a virtual network and an implementation method thereof. The implementation method of the private instant messaging system based on the virtual network comprises the following steps: step S1, constructing an intelligent box; s2, accessing a user to a system by adopting a two-dimensional code mechanism; s3, designing an IM application running on the mobile terminal equipment of the user; s4, performing application-level network flow control of virtual network access; and S5, establishing a public network registration service. According to the private instant messaging system based on the virtual network and the implementation method of the private instant messaging system based on the virtual network, through deep integration of pre-configuration hardware, the virtual network technology and a simplified user access mechanism, complete control over communication data of a user is achieved, and convenient and safe user experience is provided.

Control of network traffic in a network is provided, including classifying a network request from a network source address using request classifiers selected from a plurality of request classifiers based on the network request satisfying classification conditions of the selected request classifiers, associating the network request with each classifier metric corresponding to the selected request classifiers, aggregating the classifier metrics associated with the network request to determine an aggregate request control metric of the network request, and instructing a network traffic controller to operate on the network request based on whether the aggregate request control metric satisfies a request control condition. Each of the plurality of request classifiers is associated in memory with a corresponding classifier metric.

Facilitating dynamic network traffic steering using graph neural networks in advanced communication networks is provided. A method includes determining respective results of application of a utility function to all combinations of potential handovers of the specified user equipment from a source cell to respective target cells of a group of target cells. A communication network can include the source cell and the group of target cells. The operations can also include, based on the respective results of the application of the utility function, implementing a network traffic steering process that moves connectivity of the user equipment from the source cell to a single target cell of the group of target cells.

One or more embodiments of the present disclosure provide an access control method and apparatus for a container network, a device and a medium, the access control method for the container network is applied to a first computing node included in a first computing cluster, and the container network of the first computing cluster is a first type of container network. When network flow is transmitted in a first type container network, the network flow does not pass through a protocol stack of each computing node in a first computing cluster, and the method comprises the following steps: acquiring a plurality of network flow control rules associated with a first computing node; screening the plurality of network flow control rules according to the container group information of the first container group, and generating a first access control strategy of the first container group; and configuring the first access control policy in a protocol stack of the first container group. In the method, an access control strategy in a protocol stack in a container group is utilized to process network traffic, and access control of the network traffic is realized in a specific type (such as MacVlan) container network.

The invention discloses a flexible flow control method, a network node, electronic equipment and a storage medium. The flexible flow control method comprises the following steps: when a first network node is in network congestion, acquiring flexible flow control node information carried in a service message; the flexible flow control node information comprises node information of a flexible flow control enabling node located at the upstream of the first network node; determining a first flexible flow control node corresponding to the first network node based on the flexible flow control node information; the first flexible flow control node is at least one of upstream flexible flow control enabling nodes; generating a first flexible flow control protocol message according to the node information of the first flexible flow control node; the first flexible flow control protocol message is used for indicating the first flexible flow control node to perform network flow control; and sending the first flexible flow control protocol message to the first flexible flow control node. According to the invention, a flexible control mechanism for the network flow is realized, so that the network flow control is not limited to a hop-by-hop flow control mechanism or a source end flow control mechanism any more, and the network flow control effect is optimized.