38 results about "Network traffic management" patented technology

The invention provides an aggregate communication server node sorting method and device, equipment, a medium and a product, and relates to the technical field of network flow management. Comprising the following steps: acquiring a to-be-sorted server node original list participating in set communication; according to a topology database, querying to obtain topology information of each server node in the server node original list; according to the topological information of each server node, reordering each server node in the server node original list, and generating a topological affinity node list; a list of topological affinity nodes is output for a collective communication operation. According to the method provided by the invention, by ensuring that the adjacent server nodes are at the same level or adjacent levels in the physical topology, the cross-level flow of set communication can be minimized, so that the set communication efficiency is improved, and the time consumption of a training task is reduced.

The invention relates to the technical field of network traffic management, in particular to a traffic management and control method and system fusing TSim and eSIM card data, and the method comprises the steps: receiving a traffic management and control instruction initiated by an ith terminal through an interactive gateway, recording the receiving time of the traffic management and control instruction, and if the data interaction amount is greater than or equal to a preset interaction amount threshold value, executing the step 1; and generating a to-be-transmitted data instruction for suggesting to use the eSIM card to send the to-be-transmitted data by using the interactive gateway, returning the to-be-transmitted data instruction to the ith terminal, when the to-be-transmitted data returned by the ith terminal is received, forwarding the to-be-transmitted data to the low-power-consumption network, and if the data interaction amount is smaller than the interaction amount threshold value, sending the to-be-transmitted data to the ith terminal. And generating a to-be-transmitted data instruction for suggesting to use the TSim card to send the to-be-transmitted data by using the interactive gateway, and transmitting the to-be-transmitted data to a target terminal of the ith terminal by using the first service RPL instance or the second service RPL instance. According to the invention, the flexibility and stability of TSim and eSIM card data traffic control can be improved.

The present disclosure is directed to network traffic management and load balancing at a cloud-based secure access service accessible to remotely connected user devices. In one example, a cloud-based secure service system includes a network controller configured to receive network traffic from one or more user devices remotely connected to the controller; parse the network traffic into flow data and contextual information associated with the network traffic; determine that the network traffic is to be serviced by a target firewall service at the cloud-based secure service system based on the flow data and the contextual information; and direct the network traffic to the target firewall service to be serviced.

The present disclosure provides a deep reinforcement learning (DRL) based dynamic network traffic management system including a LAN router, a plurality of WAN routers, a network switch, and a GNAT controller configured to measure one or more traffic states of a plurality of data flows, obtain an expected reward at the current time point, obtain the one or more traffic states to input to a DRL model to provide an expected reward of each data flow estimated for a next time point, obtain a target reward at the current time point, adjust parameters of the DRL model, predict a plurality of long-term rewards using the trained DRL model, select one of the plurality of long-term rewards, and adjust the bandwidth assigned to each data flow based on the selected long-term reward.

The application relates to the technical field of network security and discloses a network traffic threat detection and early warning method based on decoupling representation learning, which comprises the following steps: S1, detecting and identifying network traffic data in a network traffic management device to construct a data set containing a threat traffic data set and a normal traffic data set; S2, obtaining potential representation of the threat traffic data set according to a pre-trained Glow generation model; S3, constructing a learning strategy based on traffic changes in a potential space of the Glow generation model according to the potential representation to obtain a threat interpretable direction of a candidate traversal; S4, designing a comparison module through contrastive learning and extracting decoupling representation according to the threat interpretable direction; S5, constructing a threat detection model based on the decoupling representation and setting an early warning mechanism through a result of the threat detection model. The two can be obviously distinguished through decoupling, so that the efficiency of the detection process is improved. The method can well cope with detection and analysis of massive network traffic data.

The application discloses an edge network traffic prediction method based on redundancy reserve pool calculation, comprising the following steps: collecting traffic data of an edge base station, and constructing a training set and a test set according to the traffic data; inputting the constructed training set into an ESN model and training, and collecting a reserve pool state matrix; performing high-dimensional mapping on the reserve pool state matrix by using a ordinal pattern conversion network modeling method, calculating the ordinal complexity of reserve pool neurons according to a complex network measurement index, and determining key and non-key neurons of the reserve pool; balancing migrating the input weight and the internal weight of the key neurons of the reserve pool to the non-key neurons of the reserve pool in a redundant manner to form a new ESN model, retraining the new ESN model, and obtaining an optimal output weight matrix; deploying the trained new ESN model on an edge side network traffic management device, collecting traffic data of the edge base station in real time as input of the model, and obtaining a prediction value of future network traffic as output of the model.

Methods, non-transitory computer readable media, network traffic management apparatuses, central management devices, and network traffic management systems that control access to configuration data in a distributed system are illustrated. With this technology, a set of configuration data is stored in a first data structure and a corresponding set of configuration data is stored in a second data structure along with an encrypted digest value that was encrypted using a private key associated with a particular administrator role. The stored configuration data and / or newly received modifications to stored configuration data can be authenticated via a comparison of a digest value calculated using the configuration data compared to the stored encrypted digest value, which is decrypted with a stored public key corresponding to the administrator role. Accordingly, configuration data can be securely controlled by authenticating it as valid in accordance with authorized administrator roles prior to being updated or loaded.

The invention relates to the field of cloud native network traffic management, and provides a traffic scheduling method, a traffic scheduling device, a computer readable storage medium and electronic equipment, and the traffic scheduling method comprises the steps: receiving service endpoint change information and traffic scheduling configuration for an upstream service cluster; the change information is used for indicating a newly added service end point; the traffic scheduling configuration is obtained by analyzing annotation information of an application access entry resource associated with the upstream service cluster, and the traffic scheduling configuration is used for indicating to start a slow start strategy for a newly added service endpoint; and based on the traffic scheduling configuration, applying the slow start strategy to the newly added service end point to realize progressive traffic scheduling. According to the method and the device, the problems of performance jitter, request failure or cascade failure and the like caused by the fact that the new online service instance immediately bears full traffic can be effectively solved.

Methods, non-transitory computer readable media, network traffic management devices and network traffic management systems that provide protection of core networks are illustrated. With this technology, the method includes configuring a service communication proxy among a plurality of service communication proxies to receive a request from a network function. In some examples, the network function is one of the plurality of network functions. Next, the service communication proxy can be configured to determine whether a profile of the network function is stored in a common cache and, in response to determining the profile is in the common cache, retrieve the profile to respond to the request. Then, service communication proxy can be configured to select a destination NF based on based on the stored profile of the network function retrieved from the common cache.

The present disclosure relates to a packet transmission method applied to a network device. This method includes obtaining a priority bucket value for a packet. The priority bucket value represents consumable priority values for transmitting the packet across various paths. The packet is scheduled and transmitted based on the priority bucket value and the distance to a destination of each path, with updating the priority bucket value updated after each scheduling. This approach enables consistent end-to- end Quality of Service (QoS) across different network paths, enhancing the efficiency and reliability of network traffic management.

Methods, network traffic management apparatuses, non-transitory computer readable media, and systems that optimize transport of unknown and changing unstructured log data in a network environment. The method includes retrieving one or more entries associated with target unstructured log data; structuring the one or more entries into sorted structured batches comprising structured data and sorted unstructured batches without structured data, based on a current configuration and producing current batch metadata; converting the sorted structured batches into columnar-oriented representation; compressing the columnar-oriented batches; evaluating the compressed columnar-oriented batches by comparing a compression ratio of compressed sizes of the sorted structured batches and the sorted unstructured batches using the current batch metadata thereby producing a compression rate; receiving the compression rate and the current batch metadata; and determining an optimized configuration for the retrieved one or more entries; and repeating the above steps using the optimized configuration.

A network traffic management system prepares a map showing network delays updated through the transmission of regularly time-stamped messages. This map is then employed to prioritize packets, address quality of service requirements, or drop expired / expiring packets.

The application discloses a network flow management method and device of a cloud platform, equipment and a storage medium, relates to the technical field of cloud computing, and comprises the following steps: monitoring message flow data on a virtual switch bridge by using a virtual switch in the cloud platform; determining the number of polling central processing units according to the message flow data in a preset time period; and adjusting the number of polling central processing units in a data plane development kit network of the virtual switch according to the number of polling central processing units; by determining the number of polling CPUs according to the message flow data in the preset time period, the number of polling CPUs of the dynamically adjusted OVS-DPDK network can be determined by using the monitored network flow on the virtual switch bridge, so that the dynamic adjustment of the polling CPUs is realized, the number of polling CPUs can be reduced when the network flow is small, the message forwarding energy consumption of the cloud platform is reduced, and the network forwarding performance of the cloud platform is not obviously reduced.

The invention discloses a traffic management method, device and equipment and a storage medium, and relates to the technical field of computer network traffic management and optimization, and the method comprises the steps: obtaining a switch configuration address, a switch configuration path and a to-be-sent data packet; locking a mapping relation between each switch port and corresponding target equipment based on the switch configuration address, and determining a static address table; setting a routing path and a priority corresponding to each data flow based on the switch configuration path, and determining a static routing table; switching a network label corresponding to the to-be-sent data packet based on the static address table and the static routing table, and determining label switching information; and forwarding the to-be-sent data packet along the forwarding path identified by the label switching information to complete routing flow management. According to the invention, the static address table and the static routing table are utilized to accurately control the data flow and select the optimization path, network label switching is carried out to realize rapid and efficient forwarding, and the flow optimization efficiency is improved.

Methods, network traffic manager apparatuses, non-transitory computer readable media, and systems that optimize resource usage of an application running in a network traffic management system are disclosed. The method monitors a usage of execution resource by one of a plurality of application functions of the application during the running of the application to obtain resource usage data of the application function, the plurality of application functions being separately allocated resource for executing the plurality of application functions. The method stores the resource usage data and detects a restart of the application. In response to the detection of the restart of the application, the method further retrieves the stored resource usage data of the application function and adjusts resources to be allocated to the application function at the restart of the application based on the resource usage data.

A network switch includes an input port configured to receive a first data packet comprising a header of metadata and a payload of a plurality of cells. The network switch includes a controller configured to determine, using at least the metadata, an eligibility of directing the first data packet to a first path or otherwise directing the first data packet to a second path. The first path is characterized by a first latency. The second path is characterized by a second latency. The first latency is lower than the second latency. The network switch is configured to start storing the first data packet from the first path into a queue upon receiving a first cell of the payload, to manage the packet in the queue, to retrieve the cells from the queue to prepare a second data packet; and to transmit the second data packet upon identification of a destination port.

A computer can monitor network traffic on a blockchain computing network. The computer can determine a current level of network congestion on the blockchain computing network. The computer can execute a first machine learning model that predicts a timeseries of future transaction costs based on historical data and the current level network congestion level of the blockchain computing network. The computer can also execute a second machine learning model to predict a timeseries of future transaction sizes and UTXO types for the distributed ledger-based account based on historical transaction data. The computer can select one or more UTXOs to use to complete the transaction of the transaction request. The computer can append a block instance containing an identification of the selected one or more UTXOs to the blockchain to complete the transaction.

A system to manage network traffic is described. The system can include a data processing system that receives a request to execute a data analysis process to measure an effectiveness of a first content item on a plurality of end user computing devices. Client data, for each end user computing device, can be accessed, which includes interaction data representing interactions with the first content item. A data processing model can be executed in a secure environment using the client data to obtain (i) transformed client data structured in accordance with a predefined format and (ii) a data mapping of one or more data fields from the client data to input data. A performance score representing the effectiveness can be received from the external computing device based on (i) the transformed client data and (ii) the data mapping. A second content item can be selected based on the performance score.

A system to manage network traffic is described. The system can include a data processing system that receives a request to execute a data analysis process to measure an effectiveness of a first content item on a plurality of end user computing devices. Client data, for each end user computing device, can be accessed, which includes interaction data representing interactions with the first content item. A data processing model can be executed in a secure environment using the client data to obtain (i) transformed client data structured in accordance with a predefined format and (ii) a data mapping of one or more data fields from the client data to input data. A performance score representing the effectiveness can be received from the external computing device based on (i) the transformed client data and (ii) the data mapping. A second content item can be selected based on the performance score.

A system for optimizing network traffic management is provided. The system includes a plurality of data processing units (DPUs), each assigned an identifier and configured to process network traffic for associated virtual network interface cards (vNICs). The system also includes a vNIC placement handler configured to receive media access control (MAC) address information from the plurality of DPUs and execute a relocation of at least two vNICs to be directly associated with one of the plurality of DPUs without through an inter-DPU physical network based on mapping the MAC address information to the identifier. The system further includes a communication framework integrated with the vNIC placement handler to enable transmission of MAC address information from the plurality of DPUs to the vNIC placement handler and offload network traffic from the vNICs to corresponding one or more of the plurality of DPUs.

Methods, non-transitory computer readable media, network traffic manager apparatuses, and systems that assist with generating insights with TLS parameters includes receiving a request from a client for establishing a TLS connection to a server. In some examples, the request comprises parameters for the TLS connection. Next, the network traffic manager apparatus determines an identity of the client based on the TLS parameters in the request unique to the client and executes an action based on the TLS parameters which alters a handling of the request.

The application provides an intrusion abnormal behavior detection method and system based on cloud cooperation, relates to the field of intrusion abnormal behavior detection, and comprises the following steps: receiving a data packet containing business data and internal running state information, performing abnormal identification on the meta information of the business data stream, and combining the internal running state information to perform situation awareness judgment, which can effectively distinguish internal interpretable abnormalities caused by internal difficulties of the edge computing node, such as memory usage, authentication connection state, business data processing mode, network traffic management state and the like, from real external attacks; the application can avoid misjudging internal difficulties as external attacks, thereby reducing the false alarm rate, improving the accuracy and reliability of detection, enabling the system to take targeted defense measures, avoiding resource waste and defense failure caused by misjudgment, and effectively improving the security protection capability in the industrial internet environment.

The invention relates to the technical field of routers, in particular to a packet transmission optimization method based on intelligent traffic prediction, which comprises the following steps: S1, extracting traffic characteristics; s2, generating a flow prediction result; s3, dynamically generating a packet transmission optimization strategy for the preset time window in the future; and S4, performing active optimization on packet transmission. The invention relates to a packet transmission optimization method based on intelligent traffic prediction, which realizes the fundamental change of network traffic management, that is, a traditional passive and reactive management mode is upgraded to a prediction-based active and preventive optimization mode, and the network traffic is optimized through a closed loop of'acquisition-prediction-strategy generation-execution '. According to the invention, the router can pre-configure resources and adjust the strategy before traffic congestion or decline of service quality, so that network jitter is significantly reduced, transmission delay is reduced, sudden packet loss is avoided, and smoother, more reliable and predictable network experience is provided for users.

Methods, non-transitory computer readable media, network traffic manager apparatuses, and systems that assist with generating client-executable actions with TLS parameters includes receiving a request from a client for establishing a TLS connection to a server, wherein the request comprises TLS parameters for the TLS connection. An identity of the client is determined based on the TLS parameters in the request unique to the client. A recommended client-executable action is generated based on the TLS parameters. The recommended client-executable action is an adjustment of a characteristic of a system of the client. The recommended client-executable action is transmitted to the client.

Methods, non-transitory computer readable media, network traffic management devices and network traffic management systems that provide for efficient overload protection in 5G core networks are illustrated. With this technology, a load at a producer network function (NF) is monitored and in response to determining that the producer NF is overloaded, a plurality of types of network traffic flowing to the overloaded producer NF are monitored. An overloaded network traffic type is identified, which is a type of network traffic flowing to the producer NF that is of an amount that exceeds a first threshold amount above a first baseline amount of network traffic. An overloaded session is identified, which is a session having an amount of the overloaded network traffic type that exceeds a second threshold amount above a second baseline amount of network traffic. A mitigating action to reduce network traffic from the overloaded session is performed.

The invention discloses an Internet of Things card traffic consumption prediction method based on big data analysis, and relates to the technical field of network traffic management, and the method comprises the following steps: S1, collecting the traffic state data of an Internet of Things card; s2, preprocessing the traffic state data of the Internet of Things card; s3, generating a traffic consumption prediction value through a Mamba2 model; s4, generating an optimized flow management strategy based on a Mamba2 model and an improved Gibwei shark algorithm; s5, deploying an optimized flow management strategy; and S6, supplementing manual maintenance operation. The method overcomes the limitation that a traditional Internet of Things card traffic prediction method depends on artificial experience, is insufficient in precision and is delayed in real-time early warning, and provides an efficient and accurate solution for Internet of Things card traffic management.

Methods, non-transitory computer readable media, network traffic management devices and network traffic management systems that provide protection of 5G core networks are illustrated. With this technology, the user plane status can be received from a network repository function indicating whether a user plane restarted. Then the system can determine whether an amount of error messages flowing from the user plane to a gNodeB for a source exceeds a predetermined threshold. In response to determining the amount of error messages exceeds a predetermined threshold and determining that the user plane was not restarted, all messages flowing to the gNodeB for the source can be blocked. Lastly, in response to determining the amount of echo messages from the user plane to the gNodeB is below a second predetermined threshold and that the user plane did not restart, the source can be stored as a bad actor.

Methods, non-transitory computer readable media, network traffic manager apparatuses, and systems that assist with managing hardware security servers includes receiving a request from a client. The request can comprise of a unique numerical handle and a command for a hardware security server. The unique numerical handle can be generated as a response to a previous request from the client. It can further include searching for a key handle mapped to the unique numerical handle and hardware security server in memory. The method can also include sending the request to the hardware security server with the key handle when the key handle is retrieved from memory during the search and sending a response received from the hardware security server to the client. The response can be received as a result of sending the request to the hardware security server.

The invention relates to the field of network traffic management, and discloses a port traffic data processing method based on multi-modal parameter analysis, which comprises the following steps of: acquiring the bandwidth utilization rate, traffic component type probability distribution and IP path load coefficient of a port in real time; constructing a dynamic modal incidence matrix, quantifying self-stability coefficients of bandwidth, components and path modals through an improved Sigmoid function, and calculating cross-modal coupling strength by adopting a grey correlation analysis method of a dynamic resolution coefficient; analyzing the direction and the amplitude of the maximum feature vector of the matrix, and triggering service priority remarking according to the dominant state of the component mode, or generating a cross-device path reconstruction request based on the sensitivity of the path mode; and when it is detected that the modal stability coefficient is abnormal, variance attenuation is performed on the off-diagonal weight, and the parameter acquisition window is reset. According to the invention, self-optimization and robust control of the network traffic in a complex dynamic environment are realized.