74 results about "Network automation" patented technology

An artificial intelligence assistant analyzes network observations to generate regular expressions using an artificial intelligence model for network automation management pipelines that identify and resolve network issues. A method includes obtaining at least one instruction and information about a plurality of enterprise network assets and configuration of an enterprise network that includes the plurality of enterprise network assets and generating at least one regular expression using an artificial intelligence model based on context description of the at least one instruction and the information about the plurality of enterprise network assets and the configuration of the enterprise network. The method further includes generating at least one solution for configuring at least one network asset of the plurality of enterprise network assets based on the at least one regular expression and providing the at least one solution to cause a configuration change in the at least one network asset.

Embodiments here in disclose a method and system for network configuration generation using a network digital twin (NDT) comprising a spatio-temporal graph neural network (STGNN) for performance-based simulation in a communication network system is disclosed. A simulation request is received from a management service (MnS) consumer, including network parameters related to live network nodes. Performance data is retrieved from a management server, and performance is assessed against a performance threshold. Multi-domain telecom data is processed using a spatio-temporal graph neural network (STGNN) by a feature fusion attention mechanism, trained via a hybrid feedback loop with real and synthetic data. Upon meeting performance thresholds, a configuration recommendation is generated by a configuration recommendation engine, including an explanation and confidence value. The configuration recommendation is transmitted to the MnS consumer, enabling network automation without altering the live network directly.

The invention discloses a dynamic optimization system and method for a heterogeneous network communication protocol, and particularly relates to the technical field of communication network automation, and the system comprises a unified time base and multi-source state modeling module, a quick change detection and shadow section risk assessment module, a risk gating and hierarchical low-disturbance execution module and a closed-loop feedback and evolution management module. According to the method, a standard recording unit is constructed through unified time base and observation delay compensation, and multi-source communication state alignment is realized; a shadow section joint risk index is calculated based on online filtering and geographical priori, hierarchical low-disturbance strategy arrangement is implemented under the constraint of risk gating and comprehensive cost, and closed-loop feedback and anti-fact evaluation are utilized to drive parameter evolution governance. According to the method, the problems that short-time fading is smoothly masked in a high-speed or strong-shielding environment and unified risk assessment and low-disturbance execution are lacked are solved, the tail time delay, the disorder rate and the packet loss rate are reduced, the communication reliability is improved, and interpretable tradeoff between energy consumption and tariff is achieved.

In one embodiment, a device obtains data regarding routing decisions made by a machine learning-based predictive routing engine for a network. The device determines, based on the data regarding the routing decisions, a behavior of the machine learning-based predictive routing engine. The device compares the behavior of the machine learning-based predictive routing engine to a behavioral policy for the machine learning-based predictive routing engine. The device adjusts operation of the machine learning-based predictive routing engine, when the behavior of the machine learning-based predictive routing engine violates the behavioral policy.

Systems and methods are described for automated anomaly detection in computer networks using a dynamic network graph. Network data describing communications among computing entities are received, and a dynamic graph is constructed and maintained whose nodes represent the entities and whose edges represent observed communications. Behavior characteristics are computed for the nodes, and the nodes are clustered using a clustering algorithm to obtain cluster assignments. Anomalies are detected by identifying nodes whose behavior characteristics deviate from those of their assigned clusters, and alerts or security actions are generated in response. The system supports incremental updates to graph structure and cluster assignments as network conditions evolve, improving detection latency and accuracy.

This disclosure describes systems, methods, and devices related to automating and testing communication network topologies. A method may include identifying templates of respective communication network topologies defining network devices, connections between the network devices, roles for the network devices, and performance tests for the communication network topologies; selecting a first template; instantiating an instance to generate a first communication network topology by establishing first connections between first network devices based on the first communication network topology and first roles of first network devices of the first communication network topology; generating performance test results for the first communication network topology based on performance of first performance tests defined by the first template, wherein first test thresholds of the first performance tests are based on a machine learning model trained based on the communication network topologies and the performance tests; and modifying the first test thresholds based on the performance test results.

There is provided an apparatus arranged to: receive, from a configuration controller, a request for feedback on a network configuration in a communications network; request feedback on the network configuration from a plurality of network critic functions; aggregate feedback received from at least part of the plurality of network critic functions in response to the request; and provide the aggregated feedback to the configuration controller.

The application discloses a kind of based on GNSS's dam vertical displacement monitoring reference network automation observation method.It includes the following steps, step one: point site reconnaissance, instrument and observation pier selection;Step two: GNSS data preprocessing and scheme optimization;In GNSS vertical displacement automation monitoring, determine the optimal observation period, repair frequent small cycle jump;Step three: baseline solution and network adjustment method;In GNSS vertical displacement automation monitoring, troposphere delay correction, thermal expansion effect correction these models are applied to baseline solution, introduce prior height difference information in network adjustment, improve the accuracy and reliability of baseline solution.The application has the advantages of improving the vertical direction of GNSS baseline solution precision.The application also discloses a kind of based on GNSS's dam vertical displacement monitoring reference network automation observation platform.

It is an object of the present invention to provide an electricity distribution network comprising an automation system which, following the occurrence of a fault on the electrical network, allows the electrical network to be re-powered net of the portion of the electrical network affected by the fault, without the need for intervention by the operator and without the need to be integrated into a central system. This excellent result is achieved by virtue of a network automation unit, connected to the high voltage to medium voltage electrical transformation station and to the medium voltage to low voltage electrical transformation substations, configured to transmit automation logic instructions and / or automation parameters to the high voltage to medium voltage electrical transformation station and to the medium voltage to low voltage electrical transformation substations. A method is further disclosed of controlling such electricity distribution network, implementable by through a related software.

In one embodiment, a device obtains data regarding routing decisions made by a machine learning-based predictive routing engine for a network. The device determines, based on the data regarding the routing decisions, a behavior of the machine learning-based predictive routing engine. The device compares the behavior of the machine learning-based predictive routing engine to a behavioral policy for the machine learning-based predictive routing engine. The device adjusts operation of the machine learning-based predictive routing engine, when the behavior of the machine learning-based predictive routing engine violates the behavioral policy.

The application relates to the field of data processing, and discloses a network automatic management system based on dynamic network security, which comprises a behavior characteristic fingerprint acquisition module, a security threat identification identification module, a security policy instruction generation module, a protection verification result acquisition module and a deployment target node module. The original communication characteristic set is matched with a preset behavior characteristic library in real time to obtain a behavior characteristic fingerprint. The behavior characteristic fingerprint is subjected to abnormal communication identification to obtain a security threat identification. The strategy constraint of the security threat identification is extracted, and a security policy instruction of the communication network is generated based on the strategy constraint. The communication network is synchronously adjusted, and the feedback data of the synchronously adjusted communication network is compared with an expected security threshold to obtain a protection verification result. When the protection verification result is passed, the protection verification result is deployed to a target node of the communication network. The application can improve the efficiency of network automatic management.

Systems and methods are described for automated anomaly detection in computer networks using a dynamic network graph. Network data describing communications among computing entities are received, and a dynamic graph is constructed and maintained whose nodes represent the entities and whose edges represent observed communications. Behavior characteristics are computed for the nodes, and the nodes are clustered using a clustering algorithm to obtain cluster assignments. Anomalies are detected by identifying nodes whose behavior characteristics deviate from those of their assigned clusters, and alerts or security actions are generated in response. The system supports incremental updates to graph structure and cluster assignments as network conditions evolve, improving detection latency and accuracy.

Described herein is a computer-implemented method for constructing a customized ear device in a virtual environment in the form of a design through a network automation process utilizing trained nerves. The described computer-implemented method is configured to allow for altering output from a neural network to create a change to an automatically generated custom ear device design. Further, a system is described herein that utilizes a processor running the methods described herein to automatically generate a virtual-constructed custom ear device that may be modified to adjust for any incorrect output generated by a neural network.

The invention relates to the field of data processing, and discloses an automatic network management system based on dynamic network security, which comprises a behavior characteristic fingerprint acquisition module, a security threat identifier identification module, a security policy instruction generation module, a protection verification result acquisition module and a target node deployment module, matching the original communication feature set with a preset behavior feature library in real time to obtain a behavior feature fingerprint; performing abnormal communication identification on the behavior characteristic fingerprint to obtain a security threat identifier; extracting a policy constraint of a security threat identifier, and generating a security policy instruction of the communication network based on the policy constraint; synchronously adjusting the communication network, and comparing feedback data of the synchronously adjusted communication network with an expected security threshold to obtain a protection verification result; when the protection verification result is successful, deploying the protection verification result to a target node of the communication network; according to the invention, the efficiency of network automation management can be improved.

The present invention belongs to the field related to energy storage technology, and discloses a lithium battery energy storage system and its liquid cooling pipe network automatic design method, which includes: obtaining the number of battery packs of the energy storage system and performing thermal and flow simulation of the single battery pack and the water-cooled plate to determine the minimum refrigerant flow, flow difference and water-cooled plate flow resistance coefficient S1; outputting the liquid cooling pipe network parameters that can meet the temperature uniformity conditions and have the best economic performance according to the design method; and building the actual liquid cooling pipe network of the energy storage system according to the liquid cooling pipe network parameters. The present invention can obtain a high-average temperature and high-reliability energy storage system liquid cooling pipe network module, which can effectively solve the technical problems such as capacity loss and life reduction caused by uneven temperature distribution of the current energy storage system compared with the prior art.

The invention discloses an automatic deployment method for a long safety chain network based on Kubernetes Operator, and the core scheme of the method is to define double-layer custom resources (CRD): ChainMakerNetwork is used for declaring chain-level global configuration, ChainMakerNode is used for declaring node-level configuration, through the cooperative work of a node controller and a network controller, the network controller is used for declaring the global configuration of the chain-level, and the network controller is used for declaring the global configuration of the chain-level and the node-level configuration of the chain-level. A node controller generates an identity for each node and reports the identity to a resource state field in advance, and a network controller aggregates information to generate a global chain configuration file after monitoring that all dependencies are ready, so that the mechanism of the scheme breaks the circular dependency that node starting depends on network configuration, and network configuration generation depends on node identity; according to the invention, one-key and declarative deployment and full-life-cycle management of the long safety chain network in the Kubernetes environment are realized, and the deployment efficiency, reliability and operation and maintenance automation level are greatly improved.

The embodiment of the invention provides a network testing method, device, equipment and system and a storage medium, and relates to the technical field of computers, the embodiment of the invention can be applied to various scenes such as cloud technology, artificial intelligence, intelligent traffic and auxiliary driving, and the method comprises the following steps: receiving a sandbox cloud host creation request sent by a client, creating a first sandbox cloud host, and creating a second sandbox cloud host; the method comprises the following steps: sending a first sandbox cloud host to a first physical server to enable the first sandbox cloud host to be carried on the first physical server, sending an instance identifier of the first sandbox cloud host to a client, receiving a request for accessing the first sandbox cloud host sent by the client, and forwarding the request for accessing the first sandbox cloud host to the first physical server, and the first physical server is used for establishing communication connection between the client and the first sandbox cloud host and carrying out network function testing in the first sandbox cloud host according to the communication connection. Therefore, the efficiency of the network automatic test is improved, and the cost of the network automatic test is reduced.

The invention provides a distribution network automatic monitoring method and device, electronic equipment and a storage medium. The method comprises the following steps: determining each automatic switch equipment on a fault line and an initial switch state of the automatic switch equipment before a fault occurs based on a real-time operation mode of a fault event; taking an automatic switch device of any power failure simulation operation in the power failure simulation operation sequence associated with the fault event as a target switch device, and based on the operation instruction type and the initial switch state, determining a final expected switch state after executing the target power failure simulation operation; determining an abnormal action judgment result based on the final expected switch state of each automatic switch device in the power failure simulation operation and the actual action information of the automatic switch device in the fault event time window; and updating a power supply path connection relation based on the final expected switch state to obtain a post-operation power supply influence range and an action abnormity judgment result, and generating a fault handling logic process. According to the invention, the traceability and logic self-consistency of the fault handling process are improved.

Automation system, apparatus and method for coupling a device network and a communication network, wherein the system verifies addressing of components in an automation system having a hyper-convergent infrastructure, where a gateway extends data telegrams to include a device-specific signature if such a signature cannot be implemented by the automation device of the automation system itself.

The invention discloses an automatic network testing method for a novel reliable transmission protocol of a multi-modal network, which relates to the technical field of network testing and comprises the following steps of: S1, building a testing environment: building an automatic testing platform, configuring hardware, software and a network environment required by testing by using the platform, and setting up the testing environment; the platform is logically divided into an adaptation layer, a function layer, an interface layer and an application layer. S2, designing a test case; s3, executing a test process; and S4, analyzing a test result. According to the automatic network testing method for the novel reliable transmission protocol of the multi-modal network, a set of complete testing system is established and matched with an established automatic testing platform, so that full-process automation from testing environment establishment, testing case design, testing process execution to testing result analysis can be executed; the test consistency and repeatability are ensured, manual intervention is reduced, manual operation errors are effectively reduced, and meanwhile the test efficiency is remarkably improved.

This application discloses a device time correction method, apparatus, device, storage medium, and program product, relating to the field of embedded technology. The method, applied to embedded devices, includes: starting a time correction service via a local configuration file when the device boots up, and setting it as a prerequisite service for business services to ensure that business services start subsequently; calling the time correction service to perform corresponding time correction operations: if the hardware detection information of the real-time clock module indicates a hardware fault or absence, then performing anomaly detection on the current system time; if the current system time is abnormal, correcting the system time using a target time generated and pre-configured based on device batch information. This time correction scheme does not rely on an external network, is automated and timing-controllable, and based on a local time source, enables embedded devices to achieve time self-correction in offline deployment environments, ensuring time consistency and the reliability of business functions even without a network.

The invention discloses an automatic training system and method for a neural network, and relates to the field of network model training, and the system comprises a parameter configuration module which is used for loading a configuration file, displaying the configuration file in a tree structure in a visual interaction interface, interactively editing the configuration file, and storing the edited configuration file; the data preparation module is used for extracting actual data based on the stored configuration file, interactively obtaining a data set and further integrating model training preparation data; the model training module is used for searching an optimal architecture and hyper-parameter combination of a neural network model by using a genetic algorithm; and the reasoning prediction module is used for loading the optimal architecture and hyper-parameter combination of the neural network model, inputting the received user data into the neural network model and further returning a prediction result. According to the invention, the training efficiency of the neural network model is effectively improved.

The application discloses a full-parameter feedback type intelligent heat room layered cooperative control system and method, relates to the technical field of centralized heating pipe network automation control, and comprises a multi-dimensional heterogeneous parameter sensing module, a layered cooperative calculation module, a dynamic decoupling execution module and a soft measurement self-recovery monitoring module. The sensing module collects hydraulic transient and thermal lag data in all directions; the cooperative calculation module constructs a dimensionless 'thermal-hydraulic coupling urgency index' based on heterogeneous data, realizes decoupling calculation of time scale and physical dimension and generates a cooperative regulation instruction; and the execution module executes anti-oscillation clamping regulation of the regulation valve according to the instruction and in combination with a dynamic penalty function. The application breaks the dimensional interference and regulation deadlock in traditional full-parameter control, completely eliminates feedback storm under the layered architecture, and innovatively converts building thermal inertia into a virtual energy storage pool of the pipe network, so that high decoupling of thermal and hydraulic forces and peak load cutting and valley filling without additional hardware are realized.

The invention relates to the field of box-type feeder terminals, in particular to an automatic feeder terminal of a box-type power distribution network, which comprises a supporting component, a box-type feeder terminal body, a bearing plate arranged on the box-type feeder terminal body, an air switch arranged on the side wall of the bearing plate, and a shifting piece arranged on the air switch, the shifting rod is arranged on the lower side of the shifting piece; the pushing part comprises a power assembly arranged on the bearing plate, a guide assembly arranged on the power assembly, an elastic assembly arranged on the power assembly and an anti-falling assembly arranged on the guide assembly; the device comprises a box-type feeder terminal body, an anti-drop assembly arranged on the box-type feeder terminal body, and a warning component which comprises an extrusion assembly arranged on the anti-drop assembly, a trigger assembly arranged on the extrusion assembly, and a signal transmission assembly arranged on the box-type feeder terminal body. And long interruption time of the box-type feeder terminal body is avoided.

The invention relates to the technical field of cloud, the scheme can be applied to the fields of finance and medical treatment, and the invention provides an automatic deployment method, device, equipment and medium of a test cloud, and the method comprises the steps: after creating a preset number of KVM cloud hosts, executing network automatic configuration on each KVM cloud host to obtain a configured KVM cloud host; performing NAS intelligent mounting operation on each configured KVM cloud host to obtain a mounted KVM cloud host; performing environmental health examination on all the mounted KVM cloud hosts to obtain an environmental health examination result; if the environmental health examination result is passed, obtaining temporary snapshots of different test stages; and after the test task is completed, closing and deleting all the mounted KVM cloud hosts, and synchronously triggering an NAS storage cleaning task so as to position and delete corresponding NAS data based on the test task identifier. According to the invention, high-frequency and multi-version agile test requirements can be met, and the labor cost is reduced.

The present invention relates to a device (100) for operation in a network (400), wherein the device (100) comprises a sensor, an actuator, a transmitter and / or receiver unit, or other electronic equipment, wherein the network is configured as a two-wire network with Power over Dataline (PoDL), comprising at least one first input-side interface (102), at least one second output-side interface (104), a power supply unit (110), a functional unit (180), and a data and electronic assembly (190), wherein the data and electronic assembly (190) comprises the following: a processor unit (170), an input-side PHY (172), an output-side PHY (174), an input-side coupling unit (176), and an output-side coupling unit (178). - wherein the first interface (102) is connected to the second interface (104) via a two-wire through-line (120) which has a first conductor (122) and a second conductor (124), - wherein the supply unit (110) is connected to the two-wire through line (120) via a first, input-side node pair (132, 134) and a line branch (140), and - wherein the data and electronic assembly (190) is arranged via a pair of nodes (136, 138) in the line branch (140) leading to the supply unit (110) and via an output-side line (150) and a second output-side pair of nodes (132, 134) parallel to the through line (120), characterized in that - in the line branch (140) between the node pair (136, 138) and the supply unit (110) at least one first differential-mode choke (160) is arranged as a low-pass filter and - in the through line (120) between the first input-side node pair (132, 134) and the second output-side node pair (132, 134) a second push-pull choke (130) is arranged as a low-pass filter.

The invention relates to the technical field of network communication, and discloses a software-defined multi-path network flow real-time dynamic optimization method, which comprises the following steps of: acquiring an initial application experience intention of a user on a service flow; collecting context information of the service flow, and performing multi-mode user experience quality perception on the service flow to obtain a current user experience quality evaluation result; under specific conditions, performing dynamic intention negotiation with a user or an agent application to obtain a negotiated user intention; generating or adjusting a multi-path network strategy according to the negotiated user intention, the current user experience quality evaluation result, the context information and the state information of each available path of the current network; controlling the transmission of the service flow on a plurality of paths according to a multi-path network strategy; according to the invention, the dynamic change experience requirement of the user can be more accurately met, and the user satisfaction and the network automation level are improved.

The invention belongs to the technical field of rail transit on-board networks, and provides an on-board network automatic single-vehicle debugging system and method based on a TRDP protocol. The debugging system comprises a debugging server, at least one interactive tool, a mobile terminal and a bicycle network cabinet. The debugging server is used for receiving and responding to a networking request of the mobile terminal, converting a pre-stored automatic debugging task script into a debugging instruction and sending the debugging instruction to the response bicycle network cabinet through the mobile terminal; the single vehicle network cabinet is used for converting the debugging instruction into a TRDP hexadecimal frame and sending the TRDP hexadecimal frame to the corresponding interactive tool through a TRDP protocol; the interactive tool is used for executing debugging operation on the to-be-debugged vehicle according to the received debugging instruction and returning a TRDP result frame to the single vehicle network cabinet; and the bicycle network cabinet is used for analyzing the TRDP result frame and pushing the TRDP result frame to the mobile terminal for display in real time. Universal debugging of vehicle debugging scripts of different vehicle types and different batches can be realized.

The invention provides an automatic communication method and system for a multi-service bearing type distribution network based on an EPON (Ethernet Passive Optical Network), and relates to the technical field of data processing, and the method comprises the following steps: grouping control service data and monitoring service data, counting the size and time interval of data packets in each group, calculating the bandwidth occupancy rate of each group in an EPON frame structure, and sending the bandwidth occupancy rate to the EPON frame structure; the method comprises the following steps: obtaining a frame occupation interference index, sorting grouped feature data sets, carrying out packet length cutting and packet segment rearrangement on the grouped feature data sets, detecting the position distribution of each packet segment in an EPON frame time slot, obtaining a cross-service coverage coefficient, adjusting the time slot distribution of a control segment data set, and inserting a delay compensation field at the adjusted position. And respectively mapping to a first data queue and a second data queue of an uplink channel of the EPON, and generating a multi-queue transport stream. According to the invention, the multi-service data flow can be efficiently managed and dispatched, and the safe data transmission of the distribution network automation communication system is ensured.

A network automation system platform is described herein for carrying out a method for automated multi-node performance validation testing on a communications network. The method includes acquiring a test configuration for executing a multi-node performance validation test, wherein the test configuration identifies: a multi-node network performance test, carried out by an application layer, that specifies a technology-independent test script that is generic to particular technologies for providing performance validation-related services, and a node group upon which the multi-node network performance test is to be performed. The method further includes executing the multi-node network performance validation test by the application layer issuing requests to a core layer comprising a set of technology-specific services that issue, in accordance with the application layer requests, technology-specific commands to external services during performance validation of nodes within the node group.