109 results about "Differentiated service" patented technology

The invention discloses an intelligent flow arrangement method based on fusion expert network and deep reinforcement learning, which comprises the following steps: collecting network node and link state data in real time, and constructing a time sequence input vector and a topological graph structure; a time sequence neural network and a graph neural network are used for extracting traffic spatial-temporal features and node topological features respectively, future traffic is predicted through a classification network after fusion, and coarse-grained arrangement of network slices of different service levels is completed; modeling resource scheduling into a multi-agent Markov decision process, and designing a state space, an action space and a reward function; a deep reinforcement learning agent is initialized, and training is carried out through interaction experience; fusing a pre-trained expert strategy network, and constructing a total loss function to optimize network parameters; and finally generating an intelligent strategy capable of dynamically optimizing the flow path and resource allocation according to the real-time state. According to the invention, efficient resource scheduling under multi-service differentiation service quality requirements can be realized.

An intention-driven low-orbit satellite network SRv6 routing management and control method comprises the following steps: step 1, receiving and analyzing a user service demand from an application layer, and generating a corresponding intention label according to a service type; step 2, collecting state information of a satellite network in real time, tracking and recording satellite node position change and link state conversion, and establishing a complete network state database; 3, calculating a routing path meeting the service quality requirement by adopting an improved breadth-first search algorithm; 4, monitoring the state change of the inter-satellite link in real time; step 5, continuously monitoring fault events in the network, immediately starting a pre-calculated standby path when a fault is detected, updating a corresponding SRv6SID list, and performing rapid path switching; and step 6, dynamically adjusting the network flow. The method not only can adapt to the dynamic characteristics of the low earth orbit satellite network, but also can effectively meet the differentiated service requirements, and has the rapid fault recovery and load balancing capability.

The invention discloses a low earth orbit satellite network digital twin drive switching optimization method and system, and relates to the technical field of inter-satellite communication, and the method comprises the steps: building a digital twin system which is synchronously evolved with a physical LEO satellite network; predicting the link quality between each candidate satellite and the user terminal in a future time window based on a digital twin system; dividing a time window into a plurality of continuous time slices, constructing a directed weighted dynamic graph model which takes a satellite-time slice as a node and takes link comprehensive utility cost as an edge weight, and searching an optimal path in the directed weighted dynamic graph model by utilizing a shortest path algorithm so as to determine an optimal switching opportunity and a target satellite sequence; the optimal switching strategy is issued to a user terminal to be executed, and a link quality prediction result is corrected in real time through a feedback mechanism of the digital twin system to form closed-loop optimization; the method can effectively meet differentiated service quality requirements in a multi-service scene, and is suitable for a high-dynamic LEO satellite communication system.

The invention relates to the technical field of voice recognition, in particular to a voice interaction system and method for customer service based on artificial intelligence, and the system comprises a voice input processing module, an intention classification and routing module, a context dynamic adjustment module, a user behavior learning module, a multi-level intention fusion module and a final result module. According to the method, a multi-dimensional feature system is constructed by extracting tone intensity, speech speed frequency and emotional fluctuation amplitude, intention categories, priority weights and confidence scores are generated to realize accurate acquisition of appeals, and dialogue history, context and emotional change dynamic reconstruction path nodes, switching rules and response time sequences are tracked during interaction. Historical behavior mining preference features, habit fusion intention relevance, emergency calculation of an optimal strategy, construction of service steps, resource allocation schemes and execution timelines, adjustment of an interactive interface, a service process and a feedback mechanism according to multi-dimensional analysis, guarantee of differentiated service experience, and improvement of response accuracy and user satisfaction.

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.

The invention discloses an AI dynamic game virtualization resource scheduling system and method for a 5G low-delay service, and aims to solve the problems of insufficient QoS guarantee and low resource utilization rate caused by insufficient static rule adaptability, lack of service differentiation scheduling and low fusion degree of a game model and AI. A service feature extraction module is used for distinguishing a low-delay service (T = 0) and a common service (T = 1), constructing an AI dynamic game model taking the two types of services as participants, defining a payment function comprising a QoS satisfaction function and a resource consumption cost function, solving Nash equilibrium by adopting a deep reinforcement learning algorithm, outputting an optimal resource demand strategy, and realizing the optimal resource demand strategy. And the bandwidth and CPU allocation are dynamically adjusted through the virtualized resource management module. According to the invention, the delay compliance rate of the low-delay service can be improved by 20%-30%, the resource utilization rate of the common service can be improved by 15%-25%, the strategy iteration period is shortened to millisecond level, and differential fine scheduling and dynamic optimization in a 5G mixed service scene are realized.

The invention provides an end-network cooperative transmission system and method for a multi-mode network. The system comprises a terminal service demand layer which is used for identifying the service type of a terminal in a multi-mode network, generating structured service demand information and transmitting the service demand information to a network collaborative decision-making layer; the network cooperation decision-making layer is used for fusing the service demand information and the link state information, generating a transmission optimization strategy including path selection, priority mapping, bandwidth allocation and rate control, and transmitting the transmission optimization strategy to the transmission optimization strategy execution layer; and the transmission optimization strategy execution layer is used for executing a transmission optimization strategy, collecting link state information in the multi-mode network in real time through INT, and transmitting the link state information to the network cooperation decision layer. According to the method, efficient scheduling of heterogeneous network resources and high-reliability transmission guarantee of differentiated services are achieved, and the method is suitable for key service scenes sensitive to time delay and reliability, such as Internet of Vehicles and ultra-high-definition video transmission.

The invention relates to the technical field of large language models, in particular to a high-concurrency large language model high-speed reasoning deployment method, which comprises the following steps of: extracting a weight coefficient corresponding to a user identity identifier, an emergency degree numerical value mapped by a request type and a resource occupation value converted by an estimated calculation amount according to the user identity, the request type and the estimated calculation amount; according to the method, the dynamic priority is generated by performing comprehensive operation on the user identity, the request type and the estimated calculation amount, so that differentiated services for reasoning tasks are realized, interactive requests with high urgency degree can bypass batch processing tasks with long time consumption, the response delay and delay jitter of key services are reduced, and the user experience is improved. Meanwhile, according to the complexity of the request text and the geographic coordinates of the user, the task is intelligently routed to the model node with the most suitable scale in the distributed network, so that the wide area network transmission delay is greatly reduced through edge processing, and the computing power waste caused by using a super-large-scale model to process the simple task is also avoided.

The invention discloses a dynamic optimization method and system for a service function chain of a 5G core network, and relates to the technical field related to mobile communication, and the method comprises the steps: collecting network service data in real time through a three-dimensional perception module; decomposing a service function chain optimization problem into a multi-stage decision model; decomposing into a long-term UPF deployment main problem and a short-term traffic scheduling sub-problem, and solving to obtain a global optimal solution; dynamically determining UPF deployment positions and number; dynamically selecting a traffic forwarding path meeting the service level; and constructing a dual-node deployment framework at the core layer and the edge layer, and executing a differentiated service function link control strategy. The technical problems of low resource utilization rate, high energy consumption and poor service adaptability caused by lack of dynamic collaborative optimization and service function chain static optimization of UPF deployment and traffic scheduling in the prior art are solved, and the technical effects of improving the resource utilization rate of the edge server, reducing the network energy consumption, optimizing the service quality and guaranteeing the user experience are achieved.

The invention discloses a multi-tenant resource demand prediction method based on an LSTM-XGBoost fusion model. The multi-tenant resource demand prediction method comprises the following steps: constructing multi-dimensional input characteristics including a tenant historical resource usage amount, a task priority, an SLA constraint coefficient and a time period load mode; respectively inputting the input features into an LSTM (Long Short Term Memory) time sequence channel and an XGBoost attribute channel for feature extraction; splicing the feature vectors output by the two channels, and inputting the spliced feature vectors to a fusion layer for joint modeling; and outputting the resource demand prediction vector in the future time period through a regression device. By introducing a dual-channel modeling structure, structured information such as historical resource usage sequences and task priorities of tenants, SLA constraint coefficients and load modes is processed respectively, and accurate prediction of multi-dimensional virtual resource demands is realized. By combining a fusion layer and a regression output mechanism, the prediction precision before resource scheduling is improved, efficient utilization and fair distribution of platform resources are realized, and differentiated service guarantee requirements in a multi-tenant environment are met.

The invention relates to the technical field of computers, and discloses a process scheduling method based on a tenant isolation strategy, and the method comprises the steps: receiving a process scheduling request of a tenant, and carrying out the standardization processing and legality verification; querying a predefined tenant mapping table, and determining an internal unified tenant identifier corresponding to the flow scheduling request and associated single-tenant concurrent quota, tenant resource weight, isolation level and strategy rule; obtaining a single-tenant concurrent quota and a tenant resource weight, generating a tenant isolation strategy in combination with the calculated rate limiting parameter and the tenant correction priority, and performing admission judgment; and based on the judgment result, distributing the flow scheduling request to the corresponding tenant scheduling unit according to the local priority, selecting a target tenant scheduling unit according to the scheduling qualification value and the global scheduling priority, generating an execution instance and triggering the execution instance. Through differentiated services, resource monopoly is prevented, task hunger is eliminated, system overload is avoided, multi-dimensional mutual restriction is carried out, and isolation between tenants is achieved.

The invention discloses an urban public facility layout optimization method and system based on multi-source space-time big data, and relates to the technical field of urban planning. Comprising the following steps: firstly, acquiring and fusing multi-source space-time big data such as mobile equipment signaling data and point-of-interest data; identifying and delimiting an urban public service three-level center system based on the fusion data through a spatial clustering and network analysis algorithm, and determining each center level and a spatial influence range; constructing a differentiated service demand quantification model for each level of service center; constructing a multi-stage collaborative layout optimization model, and completing facility hierarchical assignment and site selection optimization; evaluating the layout scheme in the simulation environment and outputting a grading evaluation report; through dynamic analysis and multi-level collaborative optimization driven by multi-source space-time big data, accurate matching of public facility layout and service requirements is achieved, and meanwhile the service coverage rate and cross-level connection efficiency are improved.

The embodiment of the invention provides an intelligent customer service response method and device, electronic equipment and a medium, belongs to the technical field of artificial intelligence, and is suitable for financial scenes and medical scenes. The method comprises the following steps: performing service period prediction by combining user portrait features and behavior features extracted from service interaction data to obtain a user service period state; performing product demand prediction according to dialogue features, behavior features, user portrait features and user service period states extracted from the service interaction data to obtain a product service demand degree; and sending a target service response scheme generated based on the product service demand degree and the user service cycle state to the user. According to the embodiment of the invention, the target service response scheme is generated by combining the product service demand degree and the user service period state generated by the dialogue features, the behavior features and the portrait features of the user, differentiated service strategies can be adopted for clients with different demand degrees in a proper service stage, and the intelligent customer service response effect is improved.

The invention provides a smart campus task collaboration method and system oriented to multi-group service optimization, and relates to the technical field of campus service management. According to the method, historical service logs are called, and storage nodes are distributed according to a service process to generate data sets before and after collaboration; determining a group cooperation state based on the data set, and constructing an exclusive task measurement set and a group behavior feature set; quantifying a cross-group task cooperation priority through a double-evaluation mode mark; generating a group-task collaborative set in combination with iterative operation, and screening and optimizing by using a segmentation coefficient (cohesion + separation degree); the system correspondingly comprises a data acquisition and storage module, a task and feature construction module, a collaborative priority quantification module and a collaborative adaptation analysis and optimization module. According to the method, the problems of lack of precise adaptation, fuzzy priority quantization and the like in multi-group coordination in the prior art are solved, directional optimal configuration of service resources is realized, task coordination efficiency and group satisfaction are improved, and an efficient solution is provided for multi-group differentiated services of the smart campus.

The invention provides a user service charging method, a network element and related equipment, and relates to the technical field of communication. The method comprises: receiving user traffic data sent by a user plane network element, the user traffic data being obtained by the user plane network element counting a first service message, the first service message comprising a first IPv6-based segment routing SRv6 segment list; when the charging triggering condition is met, a charging data request is sent to a charging network element through a charging triggering network element, the charging triggering network element is arranged in a session management network element, and the charging data request comprises user flow data. Through the technical means, the problem that the differentiated service based on the SRv6 path cannot be charged in the related technology is solved.

The invention belongs to the technical field of wireless communication, discloses a perception-assisted satellite-borne base station access method, device and equipment and a storage medium, and is applied to a non-ground network satellite access system. The method comprises the following steps: firstly, constructing a multi-dimensional information sensing model oriented to differentiated service requirements, fusing user requirement information, network state information and satellite-ground channel information, and monitoring the use condition of a resource block in real time; the method comprises the following steps: carrying out real-time estimation on the number of active users based on an active user number estimation method of a Bayesian criterion and multi-dimensional perception information, and then, carrying out self-adaptive allocation of time-frequency resources on the users by adopting a weighted dynamic resource allocation strategy according to service priorities and weights; and the access control parameters are dynamically adjusted according to the number of the active users and the resource allocation condition, so that efficient and reliable access in a high-dynamic and frequent switching scene is realized. According to the invention, the resource utilization rate and the access success rate of the satellite access system can be obviously improved, and the method adapts to differentiated service requirements in a high-dynamic scene.

A trigger to enable data traffic replication in a wireless network may be provided. A data packet comprising a Differentiated Service Code Point (DSCP) field in a header may be received. A determination may be made that the data packet comprises a candidate traffic for bi-casting. In response to determining that the data packet comprises the candidate traffic for bi-casting, a flag may be set in the DSCP field in the header of the data packet. The flag triggers bi-casting of the data packet. The data packet may be sent to a destination device.

The application relates to the field of mobile communication, and discloses a method and device for monitoring data packet disorder in a mobile network, a computer readable medium and an electronic device. The method is executed by a first user plane node in a user plane, and comprises the following steps: when the first user plane node receives a disorder statistics request sent by a target network element in a control plane, sending a notification message containing a differentiated service code point to a second user plane node in the user plane; receiving a plurality of echo messages sent by the second user plane node in sequence, wherein the echo messages comprise a message sequence number and the differentiated service code point; determining a disorder monitoring result according to the message sequence number in each received echo message and the normal order of the message sequence numbers in the plurality of echo messages; and reporting the disorder monitoring result to the control plane, so that the control plane determines the disorder condition of the data packet according to the disorder monitoring result. The method can realize monitoring of the disorder condition of the data packet, and provide data support for reliable transmission of the mobile network.

The application discloses an intelligent traffic arrangement method based on a fusion of an expert network and deep reinforcement learning, comprising the following steps: collecting network node and link state data in real time, and constructing a time sequence input vector and a topological graph structure; using a time sequence neural network and a graph neural network to respectively extract traffic space-time features and node topological features, fusing the features, predicting future traffic through a classification network, and completing coarse-grained arrangement to different service level network slices; modeling resource scheduling as a multi-agent Markov decision process, designing a state space, an action space and a reward function; initializing a deep reinforcement learning agent, and training the agent through interactive experience; fusing a pre-trained expert strategy network, constructing a total loss function to optimize network parameters; and finally generating an intelligent strategy capable of dynamically optimizing traffic paths and resource allocation according to real-time states; and the application can realize efficient resource scheduling under differentiated service quality requirements of multiple services.

The invention discloses a photographing method and device, and relates to the technical field of medical health and artificial intelligence. A specific embodiment of the method comprises the following steps: determining a target camera installed on a terminal; collecting a video stream by using the target camera, and rendering the collected video stream into a camera frame so as to display the collected video stream on a screen of the terminal; loading the video stream rendered in the camera frame to a canvas; and in response to a received photographing instruction, intercepting a target picture from the video stream loaded by the canvas. According to the embodiment, while a photographing function is realized, differential services can be provided for terminal applications, and the use experience of a user is improved.

The invention discloses a mobile terminal shopping platform donation and commission discount method and a sales system, and relates to the technical field of e-commerce, and the system comprises a user management module, a commodity management module, an order management module, a payment and settlement module, a donation and commission discount core module, a marketing and promotion module, and a data statistics and analysis module. Registration, authentication, information maintenance and authority and level management are achieved through the user management module, and authenticity and safety of user identities are ensured. A basis is provided for personalized services and rights, so that the user experience and loyalty are remarkably improved; the user management module is used for providing differentiated services for different levels of users by analyzing user behaviors and preferences, such as buying activities and preferential customer services exclusively shared by advanced users; according to the differentiated service strategy, the participation degree and loyalty of the user are effectively improved, and the problem of insufficient user stickiness is solved.

A communication method and related apparatus, in which a first communication device receives first information indicating N gateway stations and / or K feeder links on one or more transmission paths of data of a terminal device, and the first communication device can determine a first user plane function connected with the N gateway stations and / or the K feeder links according to the first information. The first communication device can subsequently send second information to the first user plane function, so that the first user plane function can perform data processing based on the N gateway stations and / or the K feeder links indicated by the second information. In this way, the first communication device can select a user plane function based on the gateway stations and / or feeder links indicated by the first information, so that the data of the terminal device can be transmitted through the user plane function and the gateway stations matching the first information, to provide differentiated services and improve the quality and reliability of the services.

The invention discloses an air-sea cross-domain communication network slice dynamic mapping and forwarding method based on an SRv6 Color-Mapping table, and belongs to the technical field of communication networks, and the method comprises the steps: constructing a cross-domain network intelligent management and control platform, defining a network slice service level according to a service demand, calculating an optimal SRv6 strategy path meeting a constraint condition, and transmitting the optimal SRv6 strategy path to the cross-domain network intelligent management and control platform; creating an SRv6 Color-Mapping table of an ordered SID list corresponding to a service grade, an SRv6 color value and an optimal strategy path; the network entry node identifies the service level of the service data packet and marks the corresponding color value of the service data packet, performs SRv6 packaging according to the SID list associated with the color value, and forwards the service data packet segment by segment according to the SID list to complete end-to-end cross-domain communication; and the management and control platform monitors the network state in real time, dynamically updates the mapping table and issues the mapping table, so that non-perception path switching of the service flow is realized. According to the invention, non-aware switching and automatic management of services are realized, and differentiated services and network reliability in a complex heterogeneous environment are effectively guaranteed.

The application provides a kind of star-ground fusion network differentiated service flow deterministic transmission scheduling method and system, belongs to communication network technical field, according to the total demand of service flow, based on the elastic transmission algorithm of cache utilization of genetic, calculate the complementary star-ground cross-domain peak cache resource reserved, and carry out the adaptive optimization of cache resource in domain, obtain the domain node resource allocation result;According to node resource allocation result, based on the transient routing and variable queue algorithm of deep reinforcement learning, the two-dimensional scheduling of routing-queue is carried out to service flow, and deterministic transmission scheduling is carried out to meet the differentiated cache capacity demand and time demand of service flow.The application makes up the defects of traditional STIN network architecture, such as lack of differentiated deterministic service concept and loose adaptation between protocol stack levels, significantly improves the deterministic communication guarantee capability of network in different scenarios, and provides strong support for efficient operation and reliable transmission of STIN.

The application discloses a network conference traffic forwarding method and device, electronic equipment and storage medium, and relates to the technical field of big data, wherein the traffic forwarding method comprises the following steps: acquiring global conference information; based on the global conference information, generating conference interaction information of each network conference, wherein the conference guarantee priority contained in the conference interaction information is used for configuring a differentiated service code point (DSCP) value of traffic data packets transmitted between a conference terminal participating in the network conference and a conference management end, and traffic data packets with different DSCP values correspond to different forwarding strategies; and according to the forwarding strategy, the traffic data packets formed between the conference terminal participating in the network conference and the conference management end are forwarded. The application solves the technical problems in the prior art that the guarantee priority of the network conference cannot be flexibly defined, and different forwarding strategies cannot be formulated to flexibly forward the traffic data packets.

The application relates to the technical field of PNT service, and discloses a differentiated PNT service method and device based on a multi-dimensional SLA model and a storage medium, the method comprising the following steps: acquiring user information of all user terminals corresponding to a PNT service system; for each user terminal, determining an SLA level corresponding to the user terminal according to user information corresponding to the user terminal; constructing an SLA model corresponding to the PNT service system according to the SLA levels corresponding to all the user terminals; and determining resource configuration information of the PNT service system based on the SLA model. The application can divide PNT services into different levels, thereby providing a reasonable classification basis for the division of PNT resources; subsequently, according to the determined SLA model, the basic resources of the PNT service system are reasonably divided based on the total service level of the service indicators that can be promised by each SLA level represented by the SLA model, which is beneficial to providing targeted PNT services for different PNT service objects, thereby improving the operation efficiency of the PNT service system.

The invention discloses a communication optimization method. The method comprises the following steps: collecting physical layer information, link layer information and network layer information of a target communication system; the network layer information comprises the service type of the target communication service; performing fusion processing on the physical layer information, the link layer information and the network layer information according to the service type to obtain a network state of the target communication system; determining a modulation coding scheme value and a differential service code point value according to the network state and the service type; and setting a modulation and coding scheme according to the modulation and coding scheme value, and setting a differential service code point according to the differential service code point value so as to execute the target communication service. By applying the technical scheme provided by the invention, collaborative optimization of the MCS and the DSCP can be realized in the communication system, so that the communication performance is effectively improved, the waste of communication resources is avoided, and the service quality is ensured. The invention also discloses a communication optimization device, electronic equipment and a computer readable storage medium, which also have the above technical effects.

The invention relates to the technical field of medical data processing, and discloses an intelligent digital operating room data processing method and system based on the 5G Internet, and the method comprises the steps: building a URLLC slice and an eMBB slice, configuring differentiated service quality parameters, and completing the end-to-end deployment; executing real-time registration of the intraoperative image and the preoperative three-dimensional image on the edge computing node; the multi-channel physiological signals are analyzed in real time, and hierarchical control instructions are generated; privacy area detection is carried out on the operation view video, and a shielding mask is generated and synthesized in real time; transmitting the control instruction to a target terminal device through a URLLC slice, and transmitting the shielded video to a video receiving terminal through an eMBB slice; federal learning is realized by adopting homomorphic encryption and differential privacy technologies, and original medical data is ensured not to go out of an operating room boundary. Real-time processing and safe transmission of operating room data are achieved, and operation safety and teaching demonstration efficiency are remarkably improved.

Differentiated service in a federation-based access network is provided by receiving a set of credentials from a User Equipment (UE) for a wireless network offering a plurality of service levels. In response to determining that the set of credentials indicate a realm associated with a given service level, network access is provided to the UE according to the given service level. In response to determining that the given service level is not a highest service level in the wireless network, a list of one or more preferred realms is transmitted to the UE, where each realm of the list of one or more preferred realms is associated with one or more higher service levels than the given service level.