63 results about "Topology management" patented technology

The invention proposes a smart park energy consumption management system and method based on artificial intelligence, and relates to the technical field of smart park energy consumption management, and the system comprises a data collection module which collects original time sequence energy consumption data and equipment state information; the data preprocessing module is used for performing data quality processing on the original time sequence energy consumption data to obtain preprocessed time sequence energy consumption data; the topology management module is used for constructing an energy consumption relation graph and generating node topology representation characteristics; the feature engineering module is used for obtaining a space-time-business joint feature tensor; the anomaly monitoring module is used for obtaining an anomaly score and outputting anomaly positioning information based on an interpretable analysis method; and the visual display module is used for generating an alarm report and performing visual display. According to the invention, accurate anomaly identification and intelligent positioning analysis of multi-level and multi-energy-type energy consumption data of the park can be realized, and the automation level and the operation and maintenance efficiency of park energy management are improved.

The invention discloses a power distribution network line fault positioning system based on multi-source information fusion, which relates to the technical field of power system operation and maintenance and comprises a data acquisition module, a data preprocessing module, an electric network topology management module, a fault prediction module, a fault judgment module and a man-machine interaction and alarm module. The method comprises the following steps: acquiring running state information from a power distribution network in real time, generating a structured multi-dimensional information database according to the running state information acquired by a data acquisition module, and performing time alignment, format standardization and feature vector construction on the acquired running state information to generate the structured multi-dimensional information database; according to the method, a fault section is preliminarily judged according to fault features, a fault state prediction model is constructed, a multi-dimensional information database is used for estimating state variables of the model, and the method aims at overcoming the defects that in the prior art, fault positioning fuzziness and reliability are insufficient due to the fact that a single information source is relied on.

According to the multi-chip link management method and device in the multi-chip verification environment, the global link mapping relation library is maintained through the programmable topology management module, then the link mapping pairs representing the links are added to the global link mapping relation library, and when data transmission between the chips needs to be carried out, the link mapping pairs representing the links are added to the global link mapping relation library; and a receiving end chip identifier of the target link is determined through the global link mapping relation library, and then verification data of the data transmission request is routed to a receiving end chip through the target link. The configuration of the link mapping pair is realized through the global link mapping relation library, and then the connection relation of the chip and hardware are decoupled, so that the dynamic management of topological connection and the connection of links are completed, the steps of manual configuration are reduced, the risk of manual errors is reduced, the verification cost is reduced, and the verification efficiency is improved.

The invention discloses a method for realizing point-to-point communication between nodes in a mobile cellular network. The method specifically comprises the following steps of: creating a virtual network card on each terminal device, distributing a virtual IP (Internet Protocol) address, and establishing a service gateway for grid topology management and data forwarding. Each node is connected with the service gateway through a network to form a grid topological structure, the nodes send data packets to the service gateway through the virtual network card, the service gateway searches the corresponding node connection according to the target virtual IP address of the data packets and forwards the data packets, and the target node receives the data packets and transmits the data packets to the local network protocol stack for processing through the virtual network card. The invention further provides an identity authentication mechanism based on the secret key and the certificate, and communication safety is guaranteed. The virtual private network constructed by the scheme of the invention breaks through the limitation that nodes in a cellular network only have dynamic virtual IPs and do not have public network IPs, improves the communication efficiency, reduces the energy consumption, and enhances the network topology adaptability.

The invention discloses a computer vision processing system based on machine learning, and the system comprises a dynamic topology management module which constructs and maintains a dynamic knowledge graph of a camera network in real time through a graph neural network technology, and carries out the topology self-adaption; the intelligent search module is used for dynamically selecting an optimal monitoring node for query based on a reinforcement learning technology; the multi-modal detection center is used for integrating multi-modal data, carrying out flame / smoke detection by combining an OfficientDet-D7 model with an optical flow method, integrating living body detection in a face recognition model trained in an MS1M-ArcFace data set based on an ArcFace framework to resist attacks, and carrying out multi-target tracking and cross-camera re-recognition by utilizing a DeepSORT algorithm; the distributed early warning system is used for triggering graded early warning through a dynamic threshold engine and carrying out context-aware false alarm suppression and key alarm priority response; the data persistence layer is used for storing structured data by adopting MongoDB fragmentation clusters and storing original video streams by adopting MinIO object storage; and the edge calculation node is used for locally executing lightweight calculation.

The invention relates to the technical field of intelligent learning planning, and discloses an intelligent learning planning system based on multi-dimensional learning data driving. Comprising a main control module, a multi-modal data acquisition module, a data quality enhancement module, a multi-modal feature fusion module, a dynamic strategy planning module, a man-machine intention alignment module, a knowledge topology management module, an evaluation and federal optimization module and an auxiliary visualization module, and the main control module is used for coordinating operation of each module and data scheduling; the multi-modal data acquisition module acquires HRV, EDA and other physiological signals through a wearable device, records a fixation track and an alpha wave proportion through an eye tracker / electroencephalograph, and receives a user instruction in real time through a voice interaction device. According to the method, the dynamic adaptability is higher, full-process dynamic adjustment of stage division-parameter fine adjustment-load balance is achieved through hierarchical reinforcement learning and NSGA-III optimization, and a learning path can be flexibly adapted according to the real-time state (such as sudden fatigue and rapid knowledge point mastering) of a user.

This invention discloses a two-end reliability assessment method and system for SDN based on OBDD. Leveraging the centralized control and easy programming characteristics of SDN, this method establishes an SDN two-end reliability assessment model. By designing the topology management module and path calculation module within the network model, a two-end minimum path set that meets bandwidth and latency constraints is obtained. A minimum path set-breadth-first search algorithm is used to determine the variable ordering of the BDD. The corresponding OBDD is constructed using the Shannon formula in the OBDD construction module. Finally, the reliability assessment module recursively calculates network reliability from the bottom up, completing the SDN two-end reliability assessment. This method combines methods such as the constrained adjacency endpoint matrix algorithm, the minimum path set-breadth-first search algorithm, and the ordered binary decision diagram (OBDD) to assess connectivity reliability in SDN, demonstrating good scalability.

Since IP network topology often has a clear hierarchical structure, using community detection algorithm in graph theory can divide the topology into several regions with high cohesion and low coupling, and selectively spread the routing update in the region to other regions, which can effectively avoid the calculation amount of full routing simulation, and realize fast and accurate IP network routing simulation reasoning. The application proposes an IP network routing simulation reasoning method based on community detection, which first divides the whole network into multiple cluster structures based on the community detection algorithm, and the shortest path between the nodes in the cluster does not pass through other clusters, and uses this division result as the basis for calculating the routing update. Then, the change operation of the network topology is accurately identified, and according to the network elements involved in the change point and the cluster information to which they belong, the network element node pairs that need to be recalculated are further arranged, and the SPT tree of the node pairs is recalculated and the routing update is performed. At the same time, an IP network routing simulation reasoning device based on community detection is proposed, which includes a topology management module, a network configuration module, a network segmentation module, a change analysis module and a routing calculation module, to realize the topology segmentation and routing simulation reasoning process of the IP network.

The application discloses a product service network simulation platform based on multiple agents, and belongs to the field of service computing and simulation platform. The simulation platform comprises an agent template library, a digital twin interface, a topology manager and a simulation controller. The agent template library provides agents for representing roles in the product service network, and configures a predefined element attribute template for each agent. Each agent further comprises an agent memory set, which is divided into a short-term working memory, a long-term fact memory, a situational memory and a reflective memory. The digital twin interface acquires and records external simulation environment data in real time or periodically, ensures that the historical data is auditable, and inputs the data into the agents. The topology manager is used for mapping the interaction relationship of the roles in the product service network into the interaction relationship between the agents. The simulation controller is used for simulating each agent. The application breaks through the bottleneck of computational efficiency and scalability, and reduces the technical threshold of complex simulation construction and analysis.

1. The name of the design product: topology management graphical user interface of electronic device. 2. The use of the design product: for an electronic device. 3. The design points of the design product: the graphical user interface displayed on the electronic device. 4. The picture or photo that best shows the design points: front view. 5. The use of the graphical user interface: the graphical user interface is used for topology management; the front view is a topology management display page, and the user can jump to the interface change state diagram by clicking the save button in the upper right corner of the front view interface to view and manage related information. 6. Other circumstances that need to be explained: "XX" in the interface represents replaceable text and / or numbers and / or letters and / or symbols.

Provided are a communication method and a communication device, the method comprising: a first IAB node receiving a BAP address set, the BAP address set comprising M BAP addresses of the first IAB node, each of the M BAP addresses being associated with one of N host nodes, M being an integer greater than 1; the first IAB node manages a connection relationship with the N host nodes according to the BAP address set, and configures a plurality of BAP addresses for a single IAB node, and each BAP address corresponds to one host node, so that the IAB node can adopt one or more BAP addresses as required, and is connected to a correct host node through a corresponding path, and thus, the efficiency of the IAB node is improved. And the effectiveness of topology management is improved.

This invention provides a satellite network topology management method and system based on feeder link switching. The method includes: constructing a continuously time-varying network topology model, and storing the availability sequence, available bandwidth sequence, and propagation delay of each link; responding to new service requests and obtaining the source satellite node and the target ground station; selecting the target feeder link and its effective connection period based on link status information; screening inter-satellite links that are continuously connected within the time period to form a candidate set, and calculating the average propagation delay and minimum available bandwidth of each link to construct a temporary topology; calculating the transmission path from the source satellite node through inter-satellite links and the target feeder link to the target ground station on the temporary topology; and locally updating the available bandwidth sequence of each link on the path according to the path and bandwidth requirements. This invention achieves efficient management of highly dynamic satellite-ground networks through feeder link event-driven and continuously time-varying modeling, improving service continuity and reducing management overhead.

The invention discloses a distributed computing system based on a fungal hypha network topology structure. The distributed computing system comprises a topology management module which generates a dynamic connection signal by simulating biological behaviors of fungal hypha growth and fusion; the signal diffusion module receives the dynamic connection signal and generates a routing diffusion signal, and the routing diffusion signal asynchronously propagates a state and an instruction between nodes by simulating a chemical signal transduction mode in a hypha network; the resource scheduling module receives the route diffusion signal and generates a task scheduling signal; the node collaboration module receives the task scheduling signal and generates a collaboration computing signal, and the collaboration computing signal is used for coordinating a plurality of computing nodes to jointly execute a single distributed task; the topology management module also receives a node state feedback signal from the node cooperation module. According to the distributed computing system based on the fungal hypha network topology structure, the problem that a distributed system lacks self-adaption, high robustness and low-energy-consumption consensus can be solved.

The invention discloses a smart home ad hoc network system and method based on sound wave communication and dynamic topology. The system comprises smart home equipment nodes, a sound wave communication module, an environment sensing sensor, an environment modeling engine module, a dynamic topology manager, a security encryption module and a topology discovery protocol module. A sound wave / radio frequency transmitting module is arranged in the smart home equipment node; the intelligent household equipment node is connected with the sound wave communication module, the environment perception sensor and the security encryption module. According to the system, network construction can be automatically completed after the equipment is powered on, the manual operation error rate is reduced, self-adaptive routing and topological optimization of a smart home equipment network can be achieved, the network stability and performance are improved, the labor cost and time consumption are reduced, high-safety communication can be achieved by combining the sound wave communication technology and the voiceprint encryption technology, and the communication efficiency is improved. And the password leakage risk is reduced.

The application provides a multi-chip link management method and device in a multi-chip verification environment. A programmable topology management module is used to maintain a global link mapping relationship database, and then a link mapping pair representing a link is added to the global link mapping relationship database. When data transmission between chips is required, the receiving end chip identifier of the target link is determined through the global link mapping relationship database, and then the verification data of the data transmission request is routed to the receiving end chip through the target link. Since the link mapping pair is configured through the global link mapping relationship database, the connection relationship of the chips is decoupled from the hardware, thereby achieving dynamic management of the topology connection and the connection of the link, reducing the step of manual configuration, reducing the risk of human error, thereby reducing the verification cost and improving the verification efficiency.

The invention discloses an electroencephalogram auditory attention recognition incremental learning method, device and equipment and a medium, and the method comprises the steps: carrying out the preprocessing and time-frequency feature extraction of a multi-channel electroencephalogram signal, and obtaining a global time sequence context feature through a convolutional attention network; a dynamic self-organizing incremental neural network module is constructed, and similarity matching and topology management are carried out through a prototype node set; wasserstein distance is introduced to measure data distribution difference, and when a threshold value is exceeded, an adaptive expansion mechanism is triggered; key parameters are restrained by combining an elastic weight solidification mechanism, and catastrophic forgetting is prevented. According to the method, continuous online learning in a non-stationary electroencephalogram signal environment is realized, self-adaptive distribution drifting can be realized without retraining the whole network, the accuracy, robustness and long-term stability of auditory attention recognition are remarkably improved, and the method can be widely applied to the fields of brain-computer interfaces, intelligent hearing-aid equipment, neural rehabilitation and the like.

One example method includes receiving network topology information delivered by a topology manager, where the data center includes a plurality of servers, a plurality of electrical switches, and at least one optical cross-connect device. A data flow can be obtained. A routing policy can be configured for the data flow based on the network topology information, where the routing policy includes any one or a combination of the following routing policies: a first routing policy, where the first routing policy indicates to forward the data flow through an optical channel in the at least one optical cross-connect device; a second routing policy, where the second routing policy indicates to split the data flow into at least two sub-data flows for forwarding; or a third routing policy, where the third routing policy indicates to forward the data flow through an electrical switch of the plurality of electrical switches.

The present invention discloses a planning method and system for a power distribution communication access network, which specifically relates to the technical field of dynamic topology management of power distribution communication networks, and is used to solve the problems of fault misjudgment and inaccurate positioning caused by topology update delays in the prior art. The method generates a dynamic topology data set by dynamically monitoring the operating status of each optical fiber node and the link transmission signal, generates a real-time topology view with a dynamic version identifier based on a preset topology planning strategy, quickly locks the network change area by combining the topology difference recognition technology of the alarm moment and the historical view, and screens the candidate fault links by the conflict relationship between the link switching frequency and the service priority, further utilizes distributed acoustic sensor data to analyze the vibration characteristics of construction machinery and eliminate external force damage and interference, and finally confirms the optical cable break fault through optical power interruption verification, heartbeat signal loss detection and redundant optical fiber phase mirror symmetry verification, and realizes multi-dimensional and precise positioning of the root cause of the topology data fault.

The invention discloses a self-organizing topology management method for a distributed wireless communication link of an urban power distribution network, and belongs to the technical field of power grid communication control. The method comprises the following steps: dividing frequency domain channels to obtain a channel division set; identifying interference among nodes in the high-density area to obtain an interference graph and dividing same-frequency neighborhoods; performing path mapping and node association modeling to obtain a node association weight matrix; performing path selection configuration to obtain a distributed path tree; quantifying a node communication state to obtain a switching threshold control table; and replacing the link maintenance logic to obtain a dynamic topology evolution result. According to the method, based on an interference adjacency graph construction mechanism of a channel division structure and a neighborhood decomposition strategy under multi-dimensional interference constraint, an interference action boundary between nodes is accurately identified under a high-density deployment condition, and a same-frequency communication neighborhood region with a physical isolation effect is extracted; a stable and reliable topological basic structure is provided for path selection configuration and state quantification, and the self-organizing evolution capability of a distributed wireless communication link in a complex interference environment is improved.

The invention relates to the crossing field of multi-agent control and space exploration technologies, and provides a multi-agent reinforcement learning formation control method and system for a rarefied Mars atmosphere in order to overcome the applicability defect of an existing multi-agent formation control method in an extreme Mars environment. The method comprises the following steps: firstly, sensing and accurately estimating a mars rarefied atmosphere state in real time, and providing reliable environment input for a control decision; secondly, an optimal control instruction is generated for each unmanned aerial vehicle through a multi-agent reinforcement learning framework; state information asynchronization caused by communication time delay and packet loss is processed through a communication and time delay compensation strategy, and real-time performance and stability of formation control are guaranteed; and finally, formation topology dynamic adjustment in a fault scene is realized through formation topology management and an adaptive reconstruction strategy, so that the fault-tolerant capability of the system to member faults is improved, and continuous execution of a Mars exploration task is ensured. The method can be widely applied to deep space exploration tasks such as Mars surface exploration, topographic mapping and resource exploration.

A topology management method, device, equipment and network are disclosed. The method is applied to the field of communication. A first device and a second device are connected through a port. The first device is located in a first network, and the second device is located in a second network. The first network and the second network are independent. The method comprises the following steps: sending a topology query request message to the second device, and receiving a topology query response message from the second device. The two newly connected devices send topology query request messages to each other, discover the topology structure of the network where the opposite end device is located, and perform a merging operation with the local topology graph to obtain a merged topology graph. That is, topology discovery can be completed through one topology query request. The topology graph of the network where the device is located is updated in real time, and the topology convergence speed is significantly improved.

The invention provides an electronic cam editor developed based on a Qt interface. Comprising an interface interaction module used for converting pixel coordinates into main axis and slave axis engineering coordinates in real time; the topology management module is used for maintaining a reference point set and updating the curve segment topology according to an adjacent relation when receiving a reference point insertion, deletion or movement instruction; the curve calculation module is used for calling a corresponding algorithm in a preset curve algorithm library to generate a curve segment coefficient and outputting a curve sampling sequence according to the reference point and the curve type identifier output by the topology management module; the extreme value analysis module is used for performing first-order, second-order and third-order derivation on the curve sampling sequence; the curve cache module is used for receiving the curve sampling sequence and the extreme value data and writing the curve sampling sequence and the extreme value data into curve cache; and the linkage rendering module is used for synchronously rendering the position and speed related multi-dimensional curve in the Qt interface and refreshing and displaying. According to the method, real-time linkage display of the multi-dimensional curve, rapid inert curve editing and synchronous export of the chart table can be realized.

The application discloses a peripheral dynamic loading and bus interconnection modeling method based on QEMUProxyAPI and belongs to the field of hardware modeling.The peripheral dynamic loading and bus interconnection modeling method based on QEMUProxyAPI comprises the following steps: establishing a ProxyAPI interface layer;constructing a device loading and topology management layer;creating and realizing devices in sequence according to a dependency relationship;automatically constructing a system topology and address mapping;realizing master-slave device interconnection;and realizing automatic signal connection.The application solves the problems that the prior art is prone to causing incompatible plug-ins, is difficult to realize module reuse, seriously affects maintenance and transplantation, and lacks rapid iteration capability.The application realizes cross-platform peripheral modeling interface standardization, guarantees that devices are connected on correct buses, enables IRQ / GPIO to be directly bound through names, improves the readability and maintainability of a system, and realizes cross-platform compatibility.

The invention relates to a vehicle network topology management method and related equipment. The method is applied to a vehicle, and a network topology structure of the vehicle comprises a main node and a first-level node connected with the main node. When it is detected that the vehicle is powered on, the main node sends a first topological node detection message to all first-level nodes in communication connection with the main node; and in response to the received first topological node detection message, the first-level node determines whether the first-level node itself is a newly added first-level node. And if the first-level node determines that the first-level node is the newly-added first-level node, replying a first newly-added node message to the main node. And the main node updates first-level network information corresponding to the network topology structure of the vehicle according to the first newly-added node message. According to the invention, the main node can update the first-level network information of the network topology structure according to the first newly-added node message, so that the network topology structure of the vehicle can be updated, and the vehicle can obtain the network topology structure belonging to the vehicle.

The present disclosure relates to techniques for determining optimal routing paths for computing devices in a network, including selecting an optimal gateway among a number of available gateways. The techniques include gathering data regarding characteristics of a network, including gateways and network access nodes (NANs) in at least one access network. The characteristics can include, e.g., supported frequency bands, communication protocols, signal-to-noise ratio, power, signal noise and quality, slicing information, and whether a network vender is a standalone network vendor or a non-standalone network vendor. In one aspect, the characteristics are obtained using the Mobile Broadband Interface Model (MBIM). The characteristics can be used by devices in determining routing paths based on requirements of individual flows and / or workflows of individual application instances.

The invention discloses a box-user relation automatic identification method and system based on an intelligent measurement switch, and the method comprises the steps: transmitting a feature signal through the intelligent measurement switch, receiving the response of an electric energy meter, and extracting a multi-dimensional feature comprising time domain, frequency domain and wavelet packet frequency band energy; the NTB zero-crossing detection technology of HPLC is utilized to identify the physical phase of the electric energy meter and perform ABC three-phase classification; the multi-dimensional features and the phase information are input into a pre-trained AI judgment model, the model adopts a CNN-RF mixed structure to perform feature screening, and a LightGBM classifier outputs a box household affiliation probability; based on the judgment result, three-phase fitting and abnormity elimination are carried out in combination with the impedance consistency principle of the loop in front of the meter, and a final box user topology is generated; and the identification result is actively reported to the marketing master station through the communication module. According to the invention, high-precision and full-automatic identification and dynamic maintenance of the box-user relationship are realized, and the intelligent level of topology management of the low-voltage power distribution network is remarkably improved.

The invention discloses a wireless Mesh network dynamic topology sensing method based on a distribution consistency protocol. The method comprises the following steps: initializing network nodes; judging whether the nodes can communicate or not based on the Euclidean distance between the nodes and a preset communication range, and establishing a neighbor relationship; each node periodically executes the Gossip protocol; the receiving node processes the Gossip message; and the node updates position information according to the own mobile model, recalculates the distance between the adjacent nodes, and updates the neighbor connection state. The method mainly solves the problems that network topology sensing is not timely and network connectivity is difficult to maintain in a node high-speed moving scene in the prior art. According to the method, the bottleneck of centralized control is avoided, the dynamic property, the stability and the adaptivity of wireless Mesh network topology management are remarkably improved while the overall connectivity of the network and the consistency of topology views are ensured, and the method is particularly suitable for a wireless self-organizing network environment in which nodes move frequently and the network state changes dynamically.

The present invention relates to the field of network management technology, and provides a network topology management method, device, system and storage medium, wherein the method comprises: upon receiving a topology discovery start instruction, sending a topology discovery request message to a switch, so that the switch broadcasts the topology discovery request message to a second device, the second device being a device other than the first device connected to the switch in a southbound network; receiving a topology discovery response message forwarded by the switch; parsing the topology discovery response message, and establishing a network connection with the second device based on the identification information of the second device obtained by the parsing and local identification information, to obtain the network topology information of the first device. The present invention can collect all the network topology information of the entire southbound network by having the first device send a topology discovery request message in the southbound network, thereby realizing the management and maintenance of the southbound network.

Provided in the present application are a communication method and a communication apparatus. The method comprises: a first IAB node receiving a BAP address set, wherein the BAP address set comprises M BAP addresses of the first IAB node, each of the M BAP addresses being associated with one of N host nodes, and M being an integer greater than 1; and on the basis of the BAP address set, the first IAB node managing connection relationships with the N host nodes. A plurality of BAP addresses are configured for a single IAB node, and each BAP address corresponds to a host node, such that the IAB node can use one or more BAP addresses according to requirements, and is connected to a correct host node by means of a corresponding path, thereby improving the effectiveness of topology management.

The invention belongs to the technical field of intelligent power grid dispatching, and particularly relates to a power grid dispatching adaptive cruise decision-making method based on a large model. Performing power grid state prediction through an improved Transform large model; generating a self-adaptive scheduling instruction based on model predictive control MPC and a fuzzy self-adaptive PID algorithm; on-line iterative optimization of a large model is realized through a closed-loop feedback mechanism, and the state sensing and anti-disturbance capability of the power grid is enhanced through digital twin modeling and dynamic topology management; through laser radar three-dimensional modeling and graph database topological mapping, a power grid equipment geometric model, electrical parameters and a dynamic mirror image of a connection relation are constructed. The graph database updates the on-off state of the switch in real time, the power grid topology is automatically reconstructed, and prediction deviation caused by topology change of a traditional static model is avoided.