757 results about "Service flow" patented technology

The invention provides a self-adaptive network topology dynamic reconstruction method and system based on deep reinforcement learning, and relates to the technical field of deep reinforcement learning, and the method comprises the steps: obtaining the topology state information, service flow distribution information and historical reconstruction records of a current network; extracting topological correlation characteristics among nodes through graph convolution operation, and generating fusion state representation in combination with service flow information; inputting the fusion state representation into a deep reinforcement learning model to identify bottleneck nodes and redundant links, and outputting a reconstruction action candidate set; searching and evaluating the long-term cumulative income of the candidate actions through a Monte Carlo tree, and screening an optimal reconstruction action sequence; a graph coloring algorithm is utilized to allocate time slots and process resource conflicts, and a resource-feasible topology adjustment scheme is generated; and extracting a network evolution rule through tensor decomposition, and constructing a topological optimization association mapping graph. According to the method, the network bottleneck can be intelligently identified, the network topology structure is dynamically optimized, and the network performance and the resource utilization rate are effectively improved.

The invention provides a multi-level service priority dynamic scheduling simulation method and device, a medium and a product. The method comprises the following steps: constructing a priority label system; establishing a dynamic binding relationship between the service flow and the priority label; when a service layer generates a data packet, embedding a priority label for the data packet based on the dynamic binding relationship; extracting a priority label carried by the data packet on a protocol stack MAC layer, and ensuring that the priority label is unvarnished to a lower layer protocol in a lossless manner; and based on the priority labels carried by the extracted data packets, classifying the data packets into logic queues with corresponding priorities, and executing a differentiated scheduling strategy. The method can adapt to diversified requirements of data services of different types and priorities for network resources, effectively improves the simulation model accuracy, improves the simulation experiment efficiency and simulation real-time performance and reliability in a multi-service priority 5G communication network simulation scene, more accurately reflects the performance of a real network, and improves the simulation experience of the 5G communication network. And meanwhile, the simulation platform has higher expansibility and flexibility.

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.

A routing method for supporting differential service requirements in a satellite internet comprises the following steps: step 1, constructing multi-dimensional network state perception as a base layer which is responsible for collecting and quantifying physical states and logic states of a satellite network in real time, and obtaining objective network states and subjective QoS (Quality of Service) requirements of services; 2, generating a nonlinear adaptive weight driven by a service as a strategy layer, mapping an objective network state and a subjective QoS (Quality of Service) demand of the service, dynamically adjusting the value orientation of routing judgment, and generating a dynamic weight; and step 3, taking the dynamic cost routing decision as an execution layer, calculating the comprehensive cost based on the dynamic weight, and executing next hop selection and path maintenance, and through cooperative work of the dynamic cost routing decision, the comprehensive cost and the next hop selection and path maintenance, realizing intelligent path selection and high-reliability transmission for different service flows in a high-dynamic and resource-limited environment of the low-orbit satellite. According to the invention, while the routing computation overhead is effectively reduced, multiple requirements of differentiated services on low time delay and high reliability can be considered.

Disclosed in the present application are a service flow scheduling method, apparatus and device based on deep reinforcement learning, and a medium. The method comprises: acquiring target data, wherein the target data comprises a current target topology state, current target service flow information and current target link information of a time-sensitive network; and inputting the target data into a deep reinforcement learning model to obtain a scheduling scheme, so as to implement scheduling of service flows on the basis of the scheduling scheme, wherein the deep reinforcement learning model comprises an agent and an environment, the agent is configured to determine gate control orchestration of the scheduling scheme, and the environment is configured to determine slot orchestration of the scheduling scheme on the basis of the gate control orchestration.

The invention relates to the field of low-altitude communication network planning methods, in particular to a 5G three-dimensional coverage and capacity planning design method for low-altitude economy, which comprises the following steps: performing airspace range limitation and application scene division on a target airspace, establishing a mobile model of a low-altitude terminal, and providing dynamic input for simulation; the method comprises the following steps: establishing a dual-frequency heterogeneous network, and determining base station addresses covering targets at different heights and meeting different signal station spacing; performing three-dimensional coverage and quality simulation on the established dual-frequency heterogeneous network, performing network KPI evaluation on the simulation until the standard is reached, and outputting a network deployment planning scheme; deploying according to a network deployment planning scheme, predicting low-altitude service flow, and adjusting a beam direction and a PRB reservation ratio to realize on-demand allocation of resources; and carrying out actual measurement on the deployed network, collecting an air measurement index, comparing a comparison deviation between the air measurement index and a simulation result, and carrying out fine adjustment on the network according to the comparison deviation. According to the invention, diversified communication requirements are met, and the success rate of terminal access is improved.

A communication method includes a first device that receives first indication information and a service flow identifier of a protocol data unit (PDU) session from a session management network element, where the first indication information indicates the first device to determine a transmission link for a service flow of the PDU session. The first device selects the transmission link for the service flow of the PDU session based on the service flow identifier and the first indication information.

The invention relates to the technical field of power internet of things, in particular to a broadband / narrowband self-adaptive switching power internet of things communication system and a control method, which intelligently identify the priority and quality of service (QoS) requirements of different services by collecting network states, terminal states and service flow data in real time. And an optimal communication mode switching strategy is dynamically generated based on a pre-trained machine learning model, seamless switching of broadband and narrowband communication links is realized, and the decision accuracy is continuously improved through a feedback optimization mechanism. According to the method, the problems that a traditional electric power Internet of Things communication mode is fixed and single and cannot intelligently adapt to services and network states are effectively solved, the system communication reliability is remarkably improved, the transmission time delay and energy consumption are reduced, and high-adaptability and high-reliability intelligent communication guarantee in a complex electric power scene is achieved.

The invention provides a service flow processing method and device, electronic equipment and a storage medium, and the method comprises the steps: determining a plurality of network feature dimensions associated with a service target according to the service target corresponding to the service type of the service flow; extracting a plurality of pieces of network data information associated with message header data from the service flow according to the plurality of network feature dimensions; wherein the plurality of pieces of network data information correspond to the plurality of network feature dimensions; and predicting field change characteristics of a plurality of header fields in the message header data according to the plurality of pieces of network data information, and generating a compression strategy matched with the field change characteristics. According to the method, different compression strategies can be dynamically adapted according to the service types of the service flows, so that the pertinence and effectiveness of the compression strategies are improved.

The invention relates to the technical field of power system network and information security, and discloses a power system transverse isolation and secure data transmission method and system.The method comprises the steps that a production control security domain and a management information security domain are determined, and cross-domain service flow information is configured; when transmission between a production control security domain and a management information security domain is needed, cross-domain service flow information to which service data belongs is collected and packaged into a security self-description data unit; on the transverse isolation path, acquiring header information to generate a session token; when the secure self-description data unit is forwarded, feature data are obtained and compared with the associated session token, and forwarding is carried out when limiting conditions are met; and maintaining a sliding time window, carrying out statistics on the forwarded security self-description data unit, and identifying an abnormal behavior. According to the invention, semantic-level access control and dynamic protection of cross-domain services between a production control security domain and a management information security domain are realized.

The invention discloses a customer service information generation method and system based on multi-modal intention recognition, and the method comprises the steps: obtaining customer service session data, and carrying out the heterogeneous data classification operation of the session data; performing feature extraction operation on each piece of parting modal information; establishing a semantic bridging matrix among the modal features, performing hierarchical attention routing, and outputting an intention label; a knowledge graph is injected, the knowledge graph comprises a static knowledge base, a real-time service flow and a user historical portrait, and three-source dynamic knowledge is output; constructing a decision tree based on the intention label, the three-source dynamic knowledge and the space-time identifier; and executing a corresponding text generation operation, a visual mark generation operation or a voice synthesis operation based on a response action corresponding to the leaf node of the decision tree, and generating customer service information. According to the method and the system, the buyer intention recognition accuracy of the multi-modal session data can be greatly improved, and the response delay time of generating the customer service information is shortened.

The invention provides a cross-equipment circulation and collaborative operation and maintenance method for a gap atomization service, relates to the technical field of computer system operation and maintenance, is applied to complex scenes such as a smart park, and aims to solve the problems that services among different gap terminals cannot be seamlessly coordinated and the operation and maintenance efficiency is low. According to the method, granularity self-adaptive splitting and standardized packaging are carried out on atomization services by constructing a swan gap terminal cluster; a cross-device circulation scheduling center is established based on the Gawan distributed soft bus, and dynamic migration of the service sub-modules among the terminals is realized through a circulation decision algorithm; meanwhile, a collaborative operation and maintenance system is constructed, operation and maintenance data are integrated, and intelligent early warning and batch operation and maintenance are achieved through a fault prediction model; and the data consistency before and after service circulation is guaranteed by combining a distributed incremental synchronization mechanism. According to the method, through deep fusion of seamless circulation of atomization services and collaborative operation and maintenance, the multi-terminal service collaborative efficiency in a complex scene is improved, the resource utilization rate is optimized, and the operation and maintenance cost is reduced.

The invention discloses a dynamic resource optimal configuration method for an electric power communication network, and belongs to the technical field of electric power system communication. The problems of low communication resource utilization rate and poor real-time response in the existing electric power communication are solved, the communication resources of physical network equipment are acquired through a network management system, and network operation state data and traffic flow characteristics are acquired in real time by utilizing a network probe or NETCONF / YANG; the method comprises the following steps: identifying service flows flowing into a communication network by adopting a deep packet inspection technology, classifying the service flows according to security partitions of power services, and mapping different types of service flows to different service levels; a quantitative QoS demand template is established for each type of services; and on the basis of the network operation state data, the service flow characteristics and the QoS demand template, constructing a multi-objective optimization model which takes guarantee of the service quality of key services as a highest priority objective, and solving by adopting an optimization algorithm to obtain an optimal resource allocation strategy. The method is suitable for optimal configuration of dynamic resources of the power communication network.

The disclosure relates to a communication method and device for an extended reality (XR) service in a wireless communication system. A method performed by an application server for the XR service in the wireless communication system includes allocating, to at least one UE, identification information for identifying the at least one UE using a same XR service or identifying at least one service flow for transferring XR data to each of the at least one UE and providing XR service-related information including the identification information and information about a delay time allowable for the XR service to the wireless communication system accessed by the at least one UE.

The invention discloses an AI large model-oriented financial private network optimization method and system, and relates to the technical field of communication networks. According to the method, an exclusive path strategy is generated for AI training, reasoning and sensitive data traffic by collecting AI service requirements and network states and utilizing the SID programming capability of SRv6; the load of the computing power node is monitored in real time, the computing power state is linked with network scheduling, and network-computing power collaborative optimization is realized; a hop-by-hop path authentication mechanism based on a dynamic authentication segment identifier Auth-SID is introduced, so that the security of a data transmission path is enhanced; and end-to-end visual operation and maintenance and closed-loop feedback of the service flow are realized by adopting a flow-following detection technology. According to the invention, the problems of mismatching of flow scheduling and AI service requirements, insufficient network and computing power collaboration, lack of path security guarantee and weak operation and maintenance visualization capability in the prior art are solved, deep adaptation of network resources and the AI service requirements is realized, and the computing power collaboration efficiency, the path security and the operation and maintenance intelligence level are improved.

The invention relates to the technical field of computers, in particular to a flow limiting method and system based on an AI gateway and a micro-service gateway, a medium and equipment, and the method comprises the steps: receiving service flow data corresponding to the micro-service gateway, AI flow data corresponding to the AI gateway, and a system resource utilization rate, building a quota negotiation channel between the micro-service gateway and the AI gateway, and transmitting the quota negotiation channel to the micro-service gateway; constructing a data set; calculating the flow quota of the micro-service gateway and the AI gateway through a dynamic quota algorithm based on the data set; receiving and identifying a service scene priority corresponding to the target request, and reserving an elastic burst quota for the target request based on the service scene priority; and judging the relationship between the total number of the current effective requests and the traffic quota of the corresponding gateway, and triggering a corresponding process. By establishing a dynamic quota mechanism and constructing a double-gateway cooperation mode of an AI gateway and a micro-service gateway, insufficient overall resource utilization efficiency caused by local current limiting is avoided, optimal global resource allocation is realized, and system stability is improved through cascade backoff.

A service flow scheduling method and apparatus, and a system. When transmission quality of a service flow with a higher priority does not meet a service level requirement corresponding to the service flow, a first network device adjusts, to a first threshold, a transmission rate threshold of an HQoS model for a service flow with a lower priority, where the first threshold is less than a current data transmission rate of the service flow with a lower priority. By performing traffic shaping on the service flow with a lower priority, a bandwidth resource of a downlink port of the first network device may give way to the service flow with a higher priority, to ensure that the service flow with a higher priority meets the service level requirement of the service flow with a higher priority.

The invention relates to the technical field of communication network maintenance, and discloses a communication network operation quality monitoring and closed-loop operation and maintenance scheduling management system, which comprises an acquisition unit for acquiring network element telemetry data; the observation module extracts a flow fingerprint, converts a link into a transfer function model, and generates a consistency gradient vector according to singular point offset; the echo prediction module converts the scheduling instruction into an expected gradient offset vector; the module calculates the scheduling residual error of the actually measured offset and the expected offset; the decision-making unit generates a path reconstruction instruction, and the scheduling residual error is utilized to check the execution efficiency and update the operation reference; according to the invention, the flow conduction consistency constraint is anchored, the link degradation characteristic and random fluctuation decoupling is realized, and the transient interference generated by the scheduling action is eliminated.

A computer program product, system, and computer implemented method for adaptive throttling of storage service traffic within a client application. The approaches provided herein allow a client or user of a storage service to dynamically and adaptively determine the capability of a storage service to service requests even when the client is not provided with a fixed reserved capacity and when other user may cause the unused capacity to vary. For instance, the approach may include maintaining a computing cluster that accesses a storage service, wherein the remote storage service has limited capacity to service requests, the limited capacity is share among a plurality of clients that access the storage service. Repeatedly determining, at the computing cluster, an available capacity of the storage service based on success or failure of requests, and adaptively throttling requests to the storage service based on at least a then current available capacity.

The embodiment of the invention discloses a message forwarding method, electronic equipment, a storage medium and a program product. The message forwarding method comprises the following steps: receiving a virtual routing forwarding message sent by private network equipment; the virtual routing forwarding message carries first target address information; determining a first service flow corresponding to the virtual routing forwarding message according to the first target address information; determining a first network tunnel corresponding to the virtual routing forwarding message according to the first service flow and a preset association relationship; the preset association relationship is a corresponding relationship between the identification information of the service flow and the network tunnel; the identification information of the service flow comprises first identification information of the first service flow; and forwarding the virtual routing forwarding message to a target network device corresponding to the first target address information through the first network tunnel. According to the invention, the configuration efficiency and the configuration flexibility of the message forwarding path can be improved.

A message processing method for in-situ flow detection and network device relate to the field of communication technology. The method includes: receiving a first service message; sending a second service message to a second network device, wherein the second service message includes a first in-situ flow detection option and the first service message, wherein the first in-situ flow detection option includes first additional information, the first additional information includes first reverse service flow characteristics, and the first reverse service flow characteristics are used by a head node of a first reverse path for generating a first service flow identification rule for in-situ flow detection; wherein, the head node is a tail node of a first forward path, and the first network device and the second network device are both on the first forward path and the first reverse path. The configuration workload can be reduced.

The invention relates to the technical field of video communication, and discloses a video conference system network inspection method and device based on multiple protocols. The method comprises the following steps: constructing a network topology structure reflecting the health state of a video conference transmission link based on multi-protocol state data and equipment connection information; mapping the screened service flow data to a network topology structure to obtain a service transmission path; threshold judgment is carried out on the service detection data and the multi-protocol state data, and a network stability mode of the video conference system is determined; when the network stability mode is an unstable network, respectively determining an affected service transmission path and an unstable network cause, and obtaining change management data related to the affected service transmission path; and generating a network stability result of the video conference system based on the unstable network cause, the affected service transmission path and the change management data. The evaluation accuracy of the network fault of the video conference system can be 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.

The technology discloses a method for training a model tailored to a service through the service Application Programming Interface (API) traffic. The system provides a microservice architecture application with a plurality of services, where one or more of the services have existing API traffic. An API gateway intercepts the API traffic being received by or sent from the service. The API gateway then identifies the training data from the existing API traffic, and uses the identified training data to generate a specialized model. The specialized model captures patterns or behaviors observed within the API traffic.

The invention provides a bandwidth allocation method and device, electronic equipment and a storage medium. The method comprises the following steps: monitoring network state indexes of a plurality of private line links in real time; carrying out heat analysis on service flows transmitted on the plurality of private line links based on the network state indexes, and identifying a heat flow meeting a preset condition; selecting a target link from the plurality of private line links according to the flow characteristics of the heat flow and the network state index; establishing a hardware direct connection forwarding channel on the target link for the heat flow, and synchronizing configuration information of the hardware direct connection forwarding channel to a control component; and receiving a global bandwidth allocation strategy issued by the control component based on the configuration information, and calling the hardware direct connection forwarding channel to execute local flow scheduling for the heat flow according to the global bandwidth allocation strategy and the network state index. Therefore, the forwarding performance and the resource utilization rate of the private line gateway are remarkably improved.

The invention provides a pressure measurement method and device, electronic equipment and a storage medium. The method comprises the following steps: dynamically sampling online service traffic to obtain sampled traffic data; constructing a user behavior model based on the sampling flow data; according to the user behavior model, dynamically mixing real playback traffic and simulated enhanced traffic, and generating target pressure measurement traffic; and injecting the target pressure measurement flow into a test system to execute a pressure test. According to the invention, real service flow data is obtained through dynamic sampling, so that the distortion problem of fixed scripts and random sampling is solved; constructing a user behavior model based on the sampling data to restore user operation path features; the real playback flow and the simulated enhanced flow are dynamically mixed according to the model, so that the authenticity of the service logic is maintained, and directional pressurization can be performed for a key path; and finally, through injection of the target pressure measurement flow, performance verification in a specific service scene is realized. Therefore, the problem that a traditional method cannot give consideration to both test authenticity and target pressure verification is solved.

The invention belongs to the technical field of software testing, is suitable for the medical field and the financial field, and discloses a service flow chart-based test path generation method, device and equipment and a medium, and the method comprises the steps: obtaining a service flow chart of a service scene, and extracting nodes of the service flow chart and path topology information between the nodes; on the basis of the service importance weight and the historical execution probability of each node, key test paths in the path topology information are identified, and priorities of the key test paths are sorted; constructing a path coverage rate prediction model based on the dynamically adjusted priority of the key path and the historical execution probability of the key path, and predicting the coverage rate of each key path in the business flow chart based on the constructed path coverage rate prediction model; and configuring a test case set based on the predicted coverage rate of each key path in the business flow chart, and dynamically adjusting the configured test case set based on a multi-objective optimization algorithm. According to the invention, the test efficiency of the business scene is improved.

The invention discloses a cable television network multi-mode fault root cause positioning method and system, and mainly relates to the technical field of cable television networks. Comprising the steps of collecting multi-source operation and maintenance data and triggering a diagnosis event; screening topological nodes based on a service flow path, and constructing a multi-modal data unit; cross-modal features are extracted, a topological weight matrix is introduced, and a joint causal feature vector is constructed; initial root cause inference is carried out in combination with topology level constraints; correcting the root cause probability based on the fault propagation consistency; and outputting a diagnosis result and updating the model based on feedback. The method has the beneficial effects that structural fusion of multi-modal data is realized, topological constraint and propagation consistency verification are introduced, the positioning accuracy and interpretability of a complex chain fault are remarkably improved, and the method has a self-evolution capability.

The invention discloses a high-concurrency virtual service transfer scheduling method and system based on a cloud edge collaborative architecture, and relates to the technical field of cloud computing and edge computing collaboration, and the method comprises the steps: constructing a service gene analysis model at an edge node, responding to a virtual service access request, extracting the resource consumption characteristics of a service flow in real time, and calculating a service separation potential energy index. The virtual business is dynamically decoupled into a connection anchoring phase and a computing power free phase based on the index; establishing a load inertia monitoring mechanism, modeling resource consumption of edge nodes into a kinematics system, collecting speed and acceleration of load change in real time, calculating system pressure momentum, and generating a graded unloading instruction when the momentum exceeds a preset critical collapse threshold value; starting a convergent differential injection mechanism, pre-constructing a logic shadow at a cloud end, and calculating a convergence ratio of a memory dirty page generation rate to a network transmission rate in real time; the method has the advantages of being high in practicability, having the pre-judgment capacity and being capable of achieving lossless switching.

A user equipment (UE) route selection policy (URSP) detection method including obtaining first policy section identifier (PSI) information corresponding to a first URSP rule corresponding to a target user equipment, the first URSP rule being matched with a target service flow corresponding to the target user equipment, generating a first packet detection rule based on the first URSP rule that corresponds to the first PSI information, configuring the first packet detection rule to a user plane function (UPF) network element of a first protocol data unit (PDU) session, the first PDU session corresponding to the first URSP rule, and receiving, from the UPF network elements, a first detection result based on the first packet detection rule and indicating whether the target service flow associated with the first PDU session matches the first packet detection rule.