3038 results about "Network service" patented technology

The invention belongs to the technical field of data transmission, and particularly relates to an SD-WAN low-delay data transmission method and system based on edge computing, a plurality of edge computing nodes are deployed in an SD-WAN architecture, and the edge computing nodes are distributed on a network edge side, close to terminal equipment or a branch mechanism and have data preprocessing and local computing capabilities; monitoring network state parameters of each link in the SD-WAN in real time, wherein the network state parameters comprise delay, bandwidth, packet loss rate and computing resource utilization rate of edge nodes; routing to-be-transmitted data to the target edge node, and if the node has local processing capability, executing data preprocessing or caching operation; otherwise, forwarding the data to an adjacent edge node or a cloud data center; a distributed cache strategy is adopted, when network congestion is detected according to data access frequency and timeliness requirements, non-real-time data is temporarily stored in a local cache, and asynchronous transmission is executed after a link is recovered, so that the method has the effect of providing higher-quality and more reliable network service for a user.

The invention provides a large-scale network node scene construction method and system based on a network target range, and relates to the technical field of network security, and the method comprises the steps: dividing network nodes into a plurality of attack and defense levels through calculating the vulnerability association degree between the nodes, and screening a target network node template based on a vulnerability chain-type propagation coefficient. Secondly, optimizing a network topology structure by adopting a graph theory clustering algorithm, and constructing a connection relation between nodes based on service affinity; and finally, according to the resource utilization rate index, constructing a node operation environment, deploying network services, implanting a vulnerability program and carrying out anomaly detection and repair, and finally generating a large-scale network node scene meeting resource optimization scheme constraints. According to the method, the large-scale network target range with a complex topological structure and a real vulnerability environment can be automatically constructed, and the efficiency and authenticity of network security attack and defense drilling are improved.

The invention relates to the field of computing power network services, and provides a computing power network ecological digital simulator based on multi-agent self-organizing interaction. Comprising a multi-agent self-organizing interaction module, a resource modeling and dynamic allocation module, a service scheduling and collaborative optimization module, a risk management and emergency response module and a strategy evaluation and optimization regulation module. The digital simulator constructs a refined and virtualized computing network model through multi-agent self-organization interaction, can dynamically reproduce resource interaction behaviors in a complex environment, assesses the effectiveness of a scheduling strategy, and optimizes the adaptive capacity of a system in a high-dynamic environment, thereby providing a scientific basis for intelligent decision-making of computing network ecological operation.

The invention relates to the technical field of communication data analysis, and discloses a communication network service health degree analysis method, system and device and a medium, and the method comprises the steps: obtaining real-time link state data, carrying out the quantitative analysis, and judging whether the link jitter exceeds a preset threshold value or not; when abnormality is detected, abnormal points can be positioned and the influence range of the abnormal points can be analyzed, so that the influence degree of nodes on the abnormal diffusion path can be identified; calculating a service quality index change value, and determining a starting point and a diffusion direction of chain degradation; by analyzing historical traffic data of the key nodes, a service traffic change trend and traffic dense area distribution characteristics are obtained. According to the method, the bandwidth allocation strategy is dynamically optimized, the bandwidth resources at the junction are reconfigured, and the regional service health degree is evaluated. And if the degradation is not effectively controlled, monitoring and detection mechanism parameters can be adaptively adjusted, and continuous analysis and control of link abnormity are realized, so that the network performance and the service quality are effectively improved.

A generative artificial intelligence (AI) system includes a generative AI model configured to generate outputs based on a training data set. The AI system additionally includes a secure data vault system. The secure data vault system additionally includes a sandbox system storing the generative AI model and operatively coupled to the generative AI model to send inputs to generate the outputs from the generative AI model, wherein the sandbox system comprises an execution environment configured to restrict execution of the generative AI model to a predefined memory address range. The secure data vault system further includes a secure network service communicatively coupled to the sandbox system and configured to authenticate a connection to an external system and to download from the external system an update package for the generative AI model when the connection is authenticated.

The invention provides a network service acceleration method and system applied to a security transaction service platform, and the method comprises the steps: firstly obtaining a security transaction request set sent by a user terminal in a transaction period, enabling each transaction request unit to comprise a request type identifier, a timestamp and content data, and then carrying out the classification according to the request type identifier to generate a priority queue, the method comprises the following steps: determining a queue ordering rule according to a timestamp, dynamically screening a proper service node group from a pre-established distributed service node cluster, mapping and binding the proper service node group with a priority queue, distributing request units to corresponding service node groups in batches according to the ordering rule to execute transaction operation, generating a response data packet, and returning the response data packet to a user terminal. And when the service node group executes the operation, the load state parameters are updated in real time and synchronized to the global load monitoring module, so that the network service acceleration performance of the security transaction service platform is effectively improved, and efficient transaction is ensured.

This disclosure describes systems, methods, and devices related to optimized resource technologies. A device may create a Managed Object Instance (MOI) representing actions executed based on artificial intelligence or machine learning (AI / ML) inference function. The device may notify a management and network service (MnS) consumer about the creation of the MOI. The device may execute actions by a network or management function acting as the consumer of the inference output. The device may manage performance of the AI / ML inference function.

Techniques are provided for enabling on-demand positioning reference signals (PRS) with a user equipment (UE). An example method for determining a location of a mobile device includes sending a request for downlink positioning reference signals to a network server, where the request includes positioning reference signal configuration information, receiving assistance data based on the positioning reference signal configuration information, measuring one or more downlink positioning reference signals based at least in part on the positioning reference signal configuration information, and determining a location of the mobile device based at least on part on the measurements obtained from the one or more downlink positioning reference signals and the assistance data.

Systems and methods for managing resources across a global and / or cloud network. In particular, systems and methods for mitigating issues related to providing services while resources are offline (or may potentially go offline). For example, the systems and methods may mitigate issues related to providing services while resources are offline (or may potentially go offline) by monitoring network services at an aggregate level.

The invention discloses a power business scheduling method and system based on 5G communication grading and classification, and relates to the technical field of 5G slicing. According to the method, the prediction model and the real-time monitoring data are utilized to effectively predict the network flow and dynamically adjust the network resources according to different levels of power business requirements, so that the power business with high priority can quickly obtain necessary network support, the quality of the overall network service and the operation efficiency of the power business are improved, and the network flow is effectively predicted. And network resource allocation is optimized through the graph neural network, accurate analysis and response to power service grading are realized, predictability and stability of the network are enhanced, and more complex power service application is supported.

The invention relates to the technical field of network service testing, in particular to a testing method and system based on optical fiber characteristics. The method comprises the following steps: acquiring multi-dimensional optical fiber characteristic data of an optical fiber link through optical fiber characteristic acquisition equipment; performing characteristic data hierarchical integration on the multi-dimensional optical fiber characteristic data to obtain an optical link characteristic vector group; performing temperature-error code wavelet transform association according to the optical link feature vector group to obtain a temperature-error code wavelet feature set; constructing an association prediction matrix according to the temperature-error code wavelet feature set; performing a service delay exception test according to the association prediction matrix to obtain a delay tail exception event set; and performing micro-bend three-dimensional feature recognition according to the delayed tail abnormal event set to obtain micro-bend mode features. According to the invention, the operation and maintenance efficiency, reliability and toughness of the optical fiber network of the data center are improved through full-link test analysis from optical fiber physical characteristics to storage service delay.

The WTRU may determine that it has a need to request a NAS network service and may generate an application layer NAS message that comprises the request. The WTRU may determine, based on configuration information, one or more network nodes configured to provide NAS network services. The WTRU may determine, based on analytics data and policy data, a first network node in the one or more network nodes to which the application layer NAS message may be sent. The WTRU may determine, based on the policy data, one or more parameters for sending the application layer NAS message to the first network node. The WTRU may determine an endpoint address associated with the first network node. The WTRU may send the application layer NAS message to the first network node using the endpoint address and the one or more parameters.

Various embodiments herein provide techniques to enable communication between a user equipment (UE) microservice and a microservice of a wireless cellular network via service mesh. A first solution is described, in which the service mesh is in the network, and the network includes a service mesh proxy to communicate with the UE. A second solution is also described, in which the UE is part of the cellular network service mesh and includes a service mesh proxy in the UE. Other embodiments may be described and claimed.

The invention relates to the technical field of signal switching control, in particular to a multi-network signal switching control system and method based on big data, and the system comprises a user track prediction module, a network coverage analysis module, a signal load evaluation module, a signal switching decision module and a switching execution monitoring module. According to the invention, accurate prediction of a user moving track is provided by integrating user positioning and moving speed data, a potential network switching point is effectively predicted, and a system is allowed to dynamically adjust a network switching strategy by analyzing user behaviors in real time, so that the continuity and the stability of network services are improved, and the user experience is improved. The system can predict the future network demand before the user state is stable by calculating the trajectory trend change rate of the user, the prediction mode combines the current data and the historical trend, the prediction accuracy is improved, the signal switching opportunity and the target network selection are optimized by analyzing the signal coverage and the real-time load of each base station, and the user experience is improved. And data packet loss and time delay are reduced.

Systems and methods for managing resources across a global and / or cloud network. In particular, systems and methods for mitigating issues related to providing services while resources are offline (or may potentially go offline). For example, the systems and methods may mitigate issues related to providing services while resources are offline (or may potentially go offline) by monitoring network services at an aggregate level.

A method for fetching a content from a web server to a client device is disclosed, using tunnel devices serving as intermediate devices. The tunnel device is selected based on an attribute, such as IP Geolocation. A tunnel bank server stores a list of available tunnels that may be used, associated with values of various attribute types. The tunnel devices initiate communication with the tunnel bank server, and stays connected to it, for allowing a communication session initiated by the tunnel bank server. Upon receiving a request from a client to a content and for specific attribute types and values, a tunnel is selected by the tunnel bank server, and is used as a tunnel for retrieving the required content from the web server, using standard protocol such as SOCKS, WebSocket or HTTP Proxy. The client only communicates with a super proxy server that manages the content fetching scheme.

Technologies for configuring flexible hardware-accelerated rules in a Service Function Chaining (SFC) architecture are described. A DPU includes an acceleration hardware engine to provide a single accelerated data plane, and a processing device that generates a first virtual bridge and a second virtual bridge. The first virtual bridge is controlled by a first network service hosted on the DPU and has a first set of one or more network rules. The second virtual bridge has a second set of one or more user-defined network rules. The processing device generates a combined set of network rules based on the first set of one or more network rules and the second set of one or more user-defined network rules. The acceleration hardware engine processes network traffic data in the single accelerated data plane using the combined set of network rules.

A system and method for implementing a non-interactive and automatic way of facilitating user authentication with a proxy server is disclosed. At least, the technique disclosed includes determining a request to access a web server by a Hypertext Transfer Protocol (HTTP) agent on a client device, retrieving a proxy configuration file from a Uniform Resource Locator (URL) assigned to the client device, determining, using the proxy configuration file, a host name and a port number of a proxy server corresponding to the request, and routing, from the HTTP agent to the proxy server, the request using the host name and the port number of the proxy server, the proxy server configured to look up a user mapping table using a set of proxy connection information and uniquely identify a user of the client device based on the look up, the set of proxy connection information including a combination of a public Internet Protocol (IP) address of the client device, the host name of the proxy server, and the port number of the proxy server.

The invention provides a business data sharing fusion system and method based on a trusted data space, and relates to the technical field of data sharing. According to the method, sharing and fusion of service data are realized by constructing a trusted data space infrastructure. The method comprises the following steps: firstly, establishing a node path planning model for priority evaluation and data matching; then forming a model collaborative deployment scheme to distribute tasks to edge nodes; then perception scoring and resource scheduling are carried out on the tasks, and a multi-task concurrent transmission scheme is generated; constructing a multi-domain network service level protocol evaluation model to perform service decomposition and business collaborative management; and finally carrying out heterogeneous processing and data fusion on the business data. According to the method, the problems of information islands, multi-source heterogeneous data fusion and cross-domain business collaboration among regional mechanisms are solved, and the system performance and the user experience are improved.

A system for detecting service interruptions in a cable broadband network using telemetry-based anomaly detection, wherein the system comprises the following: a telemetry acquisition unit configured to acquire multi-parameter telemetry data from heterogeneous broadband infrastructure elements, including cable modems, amplifiers, optical nodes and cable modem termination systems (CMTS), wherein the telemetry data includes the signal-to-noise ratio, modulation error ratio, forward error correction counter, power levels and latency statistics; a preprocessing and harmonization module that is operationally coupled with the telemetry acquisition unit, wherein the module is configured to normalize heterogeneous telemetry streams by adjusting sampling rates, synchronizing timestamps, interpolating missing data, and filtering out false outliers; an anomaly detection unit that is communicatively connected to the preprocessing and harmonization module, wherein the unit comprises a hybrid detection framework with statistical prediction models and machine learning models, wherein the statistical prediction models include ARIMA or Holt-Winters models to predict the expected telemetry behavior and the machine learning models include recurrent neural networks and autoencoders trained on historical telemetry; an ensemble evaluation subsystem within the anomaly detection unit, configured to combine the outputs of the statistical prediction models and the machine learning models to generate anomaly probability evaluations with adaptive confidence intervals; an interruption classification module configured to receive anomaly probability values ​​and correlate anomalies across multiple devices, geographic clusters, and time windows, wherein the interruption classification module differentiates between transient anomalies and service-impairing interruptions based on a multidimensional correlation; and an alerting interface configured to transmit outage alerts with severity, root cause metadata, and geolocation to a network management system so that the operator can intervene.

To provide a method, an apparatus, a system, an architecture, and an interface for a wireless transmit / receive unit (WTRU) to discover available edge network (EN) management (ENM) servers associated with either an edge network (EN) service and an EN application.SOLUTION: A method may include sending a first message to a core network entity including information indicating a request for discovery of an ENM server, receiving a second message from the core network entity responding to the request for discovery of an ENM server, the second message includes ENM server information indicating (1) any number of available ENM servers and (2) respective available ENM server endpoint information, and performs communication with one or more of the available ENM servers.SELECTED DRAWING: Figure 2

Technologies for creating an optimized and accelerated network pipeline using a network pipeline abstraction layer (NPAL) for policy-based routing (PBR) over Service Function Chaining (SFC) are described. A DPU includes acceleration hardware engine to provide a single accelerated data plane. A processing device can generate a first virtual bridge and a second virtual bridge, the first virtual bridge to be controlled by a first network service hosted on the DPU and having a set of one or more network rules, and the second virtual bridge having a policy-based routing policy (PBR policy). The processing device can add the virtual port between the first virtual bridge and the second virtual bridge. The acceleration hardware engine, in the single accelerated data plane, can route network traffic data using the PBR policy and process the network traffic data using the set of one or more network rules.

Methods and systems for adaptive spectrum allocation are provided. An example method includes receiving an input from a network consumer of a network, extracting a consumer intent from the input data and mapping the consumer intent with one or more predetermined QoS attributes, assigning a consumer priority indicator to the network consumer based on the QoS attributes, generating a network slice and assign the network slice to the network consumer, selecting a radio frequency band, assigning the band to the network slice, allocating a first allotment of the band to the network slice, provisioning network service to the network consumer for at least one UE connected to the network slice to use the allocated allotment of the band, monitoring continuously real-time bandwidth usage by the network slice, and adjusting, automatically and adaptively, a total bandwidth allocated to the network slice during network

The invention belongs to the technical field of wireless communication, and particularly relates to a channel state information acquisition method based on a conditional generative adversarial network. The method is based on CSI fusion and a conditional generative adversarial network (GAN), and serves a large-scale MIMO scene; according to the method, firstly, CSI based on an uplink reference signal (SRS) and CSI of a downlink feedback channel are fused, a generator generates predicted CSI of another frequency band after receiving the fused CSI, and a discriminator optimizes the performance of the generator by comparing the real CSI with the generated predicted CSI, so that the prediction accuracy is improved. Experimental results show that the acquisition precision of the channel state information in the FDD system can be effectively improved, and the fusion of the SRS and the downlink feedback and the conversion of the CSI between the frequency bands are realized. The method is suitable for wireless communication, a 5G / 6G MIMO system and other application scenes needing efficient CSI transmission.

The invention provides a smart power grid data communication optimization method based on edge calculation, and relates to the technical field of smart power grids, and the method comprises the steps: obtaining an inspection topology network of a target power grid; performing multi-angle communication analysis to obtain K power transmission equipment communication feature tuple sets and L inspection site communication feature tuples; carrying out edge step identification to obtain M edge topology sub-networks; performing balanced configuration of sub-network service resources to obtain M edge computing servers; performing routing inspection by using a routing inspection unmanned aerial vehicle and a routing inspection robot to obtain routing inspection video data of L sites; and distributing the data to M edge computing servers for data preprocessing, and uploading the data to a cloud computing center for routing inspection data analysis to obtain a routing inspection analysis result. According to the invention, the technical problem of low data processing efficiency caused by data transmission delay and overweight network load due to the fact that power grid monitoring generally depends on centralized data processing in the prior art is solved.

The invention discloses an Internet of Vehicles network selection and switching decision system supporting access of multiple operators. According to the method and the device, the timeliness and the continuity of network switching are remarkably improved through prediction and planning in advance. The module depends on a trajectory-network matching prediction sub-module, combines a vehicle navigation trajectory and a global digital twinborn model, identifies a base station coverage area in a future driving path and the network service quality of each operator in advance, and avoids the lag problem that switching is triggered only after signals are weakened in traditional passive switching. The pre-switching resource reservation sub-module further sends a resource request to a target operator base station and confirms reservation before the vehicle enters a new road section, ensures that resources such as bandwidth and time slot required during switching are in place, reduces switching failure or interruption caused by resource competition, avoids common communication interruption after signal sudden drop in traditional switching, and improves the switching efficiency. And continuous transmission of key businesses such as automatic driving control instructions and real-time road conditions is ensured.

Systems, methods, and instrumentalities are provided for a network control node for connecting a wireless transmit / receive unit (WTRU) to a network slice in a network. The network control node may receive service information associated with a service being requested by the WTRU, wherein the service information comprises one or more of a service class, a quality of service (QoS) requirement, or a mobility characteristic. The network control node may determine slice information associated with a plurality of network slices, wherein the slice information comprises one or more of an identifier of the network slice, priority of the network slice, a service class served by the network slice, a target device class, a QoS target, mobility support, security service, charging information, and / or performance information. The network control node may determine subscriber information for the WTRU. The network control node may select at least a first network slice of the plurality of network slices to serve the WTRU, wherein the network control node selects the first network slice based on the service information, the slice information associated with the first network slice, and the subscriber information for the WTRU. The network control node may determine whether the network control node or another network control node should service the WTRU for accessing the first network slice. On condition that the network control node determines that the network control node should service the WTRU for accessing the first network slice, the network control node may provide at least one network service associated with the first network slice to the WTRU. Or, on condition that the network control node determines that the another network control node should service the WTRU for accessing the first network slice, the network control node may send a request to the another network control node that indicates that the another network control node should service the WTRU for accessing the first network slice.

System and techniques for network flow-based hardware allocation are described herein. A workload for is obtained for execution. Here, the workload includes a flow that has a processing component and a network component. Then, during execution of the workload, the flow is repeatedly profiled and assigned a network service and a processing service during a next execution based on a network metric and a processing metric obtained from the profiling.

Systems and methods are disclosed for implementing cloud network service management. In certain embodiments, a method may comprise operating a cloud native application (CnApp) custom operator in a containerized software environment to dynamically manage cloud native network service on a target application pod via a persistent network interface to an external network. The method may include obtaining a first resource definition data, for a first custom resource, to define attributes for a bundle of resources used to implement the cloud native network service, and creating the first custom resource based on the first resource definition data, including initializing the target application pod. The method may include generating a second resource definition data, derived from the first resource definition data, to define attributes for a virtual network interface to associate with the target application pod, and applying the second resource definition data to initialize creation of a second custom resource.

The invention provides a refrigerating machine room control strategy optimization method and system and a network server. The refrigerating machine room control strategy optimization method comprises the following steps: acquiring operation data and environment data of each device and system of a refrigerating machine room to form a training set; the operation data comprises historical operation data and real-time operation data. Configuring equipment boundary conditions, and establishing a prediction model of the refrigerating machine room. And regularly updating the training set, and updating the prediction model according to the updated training set. And according to the updated prediction model, generating a plurality of optimized operation strategies of the refrigerating machine room, wherein the optimized operation strategies comprise the optimized operation strategy with the optimal energy efficiency, the optimized operation strategy without switching the startup equipment and the optimized operation strategy with the least operation equipment. And the operation strategy of the refrigerating machine room is adjusted according to the optimized operation strategy. According to the refrigerating machine room control strategy optimization method and system and the network server, the operation efficiency and the operation effect of the refrigerating machine room can be improved.