40 results about "Dynamic network topology" patented technology

The invention discloses a distribution network dynamic topology identification and self-healing control method and device, and the method comprises the steps: collecting operation data of a distribution network, carrying out the time synchronization processing, data quality evaluation and data restoration, and obtaining a high-quality network state data set; based on the data set, performing dynamic topology identification by adopting a path improved by a relaxation method and a forest enhancement algorithm to obtain a dynamic network topology model; constructing a backpack network model by adopting a cyclic data generation method, and evaluating distributed photovoltaic output and load conditions; network abnormity is monitored in real time, and a machine learning algorithm is adopted to assist in judging fault types, positions and influence ranges; power supply reliability and economy are comprehensively considered, and a multi-objective optimization algorithm is adopted to generate a switch operation sequence; switching operation is executed, a temporary micro-grid is formed or a power supply path is adjusted, and the execution effect is monitored and evaluated in real time. According to the method, the dynamic topology of the high-proportion distributed photovoltaic power distribution network can be accurately identified, and fault positioning and efficient self-healing control are realized.

The invention relates to the technical field of network communication, in particular to a network resource entry method and system based on a topology self-discovery technology, and the method comprises the following steps: a detection source device generates a detection data packet containing a device identifier, a TTL value and an accessed device list, and sends the detection data packet to an adjacent device hop by hop; after the intermediate equipment receives the probe packet, if the intermediate equipment does not exist in the accessed list, adding equipment information and a connection relationship and continuing forwarding until the TTL value is exhausted or no available port exists; the method has the beneficial effects that hop-by-hop collection of network equipment information is realized by designing an intelligent detection data packet, a dynamic network topology is constructed in combination with a graph theory algorithm, deep resource attributes are extracted by utilizing a machine learning technology, and finally automatic input and real-time updating of network resources are realized. According to the method, through detection-construction-extraction-entry-visualization five-dimensional architecture, the problems of low efficiency and poor real-time performance of traditional manual entry are solved.

The invention discloses an industrial internet attack and defense situation and risk early warning and sensing method, and particularly relates to the field of internet risk early warning and sensing, which comprises the following steps of: acquiring multi-source heterogeneous data, constructing a basic data set covering an attack, service and equipment ternary space, including attack characteristics, service influence and equipment control vectors, and solving the problems of data heterogeneity and dispersion; constructing a triple function based on the data set, respectively quantifying the attack comprehensive threat degree, the influence degree of the attack on the service and the malicious control risk of the equipment, and retaining the characteristics of each dimension; a dynamic network topology model is constructed, nodes, edges and edge weights are defined, an attack propagation path and influence intensity are described, and node state dynamic updating is achieved; and finally, a risk prediction model is constructed by fusing quantitative indexes and topological information, a global risk value is calculated, graded early warning is realized through triple dimensions, a corresponding response mechanism is matched, and the timeliness and effectiveness of industrial internet security protection are improved.

The invention discloses a method, a system, equipment and a medium for improving reliability of high-frequency data acquisition in a multi-element load scene, and relates to the technical field of power system communication and data acquisition, comprising the following steps: broadcasting beacons to a station area and receiving terminal response, constructing dynamic network topology and channel state information, executing dynamic channel allocation based on the received information, and sending the dynamic network topology and channel state information to the station area. The method comprises the following steps: acquiring minute-level data packets, performing fragment coding on the acquired minute-level data packets, selecting an optimal path for each terminal for transmission in combination with a network state, collecting fragments at a receiving side, checking integrity, decoding and restoring when conditions are met, and otherwise, starting a local retransmission mechanism until the data packets are successfully recovered. According to the method, the reliability guarantee system is constructed by dynamically sensing the network state, cooperatively optimizing channel allocation and transmission paths and combining fountain code coding and a precise retransmission mechanism, and the success rate and the integrity of high-frequency data acquisition are remarkably improved in a multi-element load scene.

The invention discloses a novel AI (artificial intelligence) cognitive fusion network (Cogntive Fusion Network) architecture and a realization method of the novel AI (artificial intelligence) cognitive fusion network architecture. The architecture comprises a dynamic attention mechanism, double seven-layer cognitive fusion processing units (perception, understanding, reasoning, decision making, execution, reflection and meta-cognition), a memory-calculation separation engine, and a dynamic network topology management and multi-time sequence parallel processing engine. Through the functions of a dynamic attention mechanism, multi-level cognitive processing, knowledge and calculation separation, dynamic network adjustment, parallel time sequence processing and the like, the advanced cognitive ability exceeding the traditional Transform architecture is realized. Compared with the prior art, the cognitive understanding accuracy is improved by 90%, the reasoning speed is improved by 182%, the concurrent processing capacity is improved by 450%, and the multi-time sequence processing efficiency is prompted by 8 times. The method can be widely applied to a plurality of cross-industry fields such as frontier scientific research, precise medical diagnosis, enterprise intelligent decision making, government public management, personal intelligent assistants and the like.

The invention discloses an unmanned aerial vehicle ad hoc network identification and multi-hop relay method and system based on dynamic optimization of an HCAR. According to the method, a dynamic network topology is constructed and maintained through periodic beacon interaction between nodes; after a target unmanned aerial vehicle identification signal is received, evaluating the direct link quality with a ground control center, and if the direct link quality is lower than a threshold value, starting a multi-hop relay; the optimal next-hop node and the communication channel are jointly selected according to the real-time topology and the channel state through the HCAR algorithm, and data are forwarded to a ground control center hop by hop. According to the invention, through the dynamic collaborative optimization of the routing and the channel, the transmission stability and the spectrum efficiency in a high-density scene are improved; link interruption rapid detection and self-healing capabilities are provided, and data transmission continuity is guaranteed; energy state monitoring and dynamic deployment are combined, and outdoor long-term reliable operation is supported.

This application provides a wireless ad hoc network transmission method and system for VOCs monitoring data from oil storage tanks, relating to the field of wireless transmission technology. The method includes: deploying monitoring nodes in the tank area to collect VOCs monitoring data and meteorological data, and deploying relay nodes to collect wind speed and direction data; correcting the VOCs monitoring data based on the meteorological data to generate a data packet to be transmitted, and simultaneously generating link state parameters based on the wind speed and direction data; then determining the stability parameters of the wireless link based on the link state parameters and constructing a dynamic network topology; selecting a first transmission path for the data packet to be transmitted; and finally updating the stability parameters when the number of consecutive wind direction data changes exceeds a preset threshold, selecting a second transmission path, and switching the data packet to be transmitted to the second transmission path, thus completing the wireless ad hoc network transmission of VOCs monitoring data. This application improves the continuity and reliability of data transmission under complex meteorological conditions.

According to the content caching method considering the dynamic network topology in the satellite edge calculation, when modeling is conducted on the content caching problem in the satellite edge calculation, the dynamic nature of the satellite network topology is considered, and dual optimization of transmission time delay and transmission energy consumption is achieved under the constraint condition of the satellite caching capacity and the repeated caching number; according to the method, the content caching problem is solved by utilizing multi-agent graph attention reinforcement learning, and the purpose of solving a caching strategy in a dynamic environment is achieved. And the low-orbit satellite selects to cache the content to the local, so that the transmission delay and transmission energy consumption of the user for acquiring the content are reduced, the increase of the transmission delay and the transmission energy consumption caused by the topology change of the satellite network is avoided, and the cache resources of the satellite are effectively utilized.

The invention discloses a low earth orbit satellite network deterministic multicast routing method based on a time expansion graph, which relates to satellite and communication technologies, and comprises the following steps: constructing a time expansion graph to represent time slot characteristics, dynamic network topology and time-varying network resources of a low earth orbit satellite network; pruning the original time expansion graph according to the working characteristics of the CSQF mechanism and multicast service transmission requirements, and providing a solution space for deterministic multicast routing calculation; and by taking the pruned and enhanced time extension graph as input, calculating a deterministic multicast route from a source node, and selecting a transmission edge with sufficient capacity and a storage edge conforming to a CSQF mechanism hop by hop until all virtual nodes are reached, so that the obtained route has the maximum bottleneck capacity on the premise of meeting the multicast service time delay upper limit requirement. According to the method, a low-complexity algorithm is designed, the link with the optimal resource and the transmission time slot with the time delay guarantee are selected hop by hop in the graph, and the multicast tree with the time attribute is constructed, so that end-to-multi-end deterministic guarantee is provided.

The invention relates to the technical field of wireless communication testing, and discloses an automatic testing method for a wireless ad hoc network, which comprises the following steps of: initializing a testing system, establishing connection between automatic testing software and a plurality of communication agent modules, and respectively controlling a tested ad hoc network module by the communication agent modules; through the communication agent module, the test network topology is constructed by adopting at least one of the following modes: 1, based on a preset path loss model, calculating and setting the minimum transmitting power capable of establishing a preset link for each tested module; 2, controlling a moving trolley bearing the tested module, and driving the moving trolley to a physical position capable of forming a preset link; and after the target network topology is constructed, executing an automatic test and collecting a test result. According to the method, high-precision, high-efficiency and high-reproducibility construction of the complex dynamic network topology is realized, and the automation level and reliability of the test are remarkably improved.

The invention relates to a network situation display and auxiliary decision-making system, and belongs to the field of communication networks and cloud computing. According to the invention, the situation display module realizes the comprehensive visualization of network resources, security and protection situations and target monitoring in a unified Web portal by fusing three kinds of data of network resources, network security and protection and target monitoring; the intelligent network resource allocation module generates an optimal resource allocation scheme through a multi-stage decision process based on the acquired network resource situation data, and ensures that network resource fragments are minimized; and the network security and protection intelligent analysis module provides potential attack path visualization and defense key points for the user by performing dynamic labeling in the dynamic network topology. According to the method, the minimization of network resource fragments is ensured, the situation elements are converted into executable strategies, and the effect of providing auxiliary decisions for users through situations is achieved.

The invention discloses an intelligent AI combined unmanned aerial vehicle air-ground integrated communication method, relates to the technical field of unmanned aerial vehicle communication, and is used for solving the problem of cooperative disorder in unmanned aerial vehicle cluster communication. According to the invention, the real-time position, speed, attitude and signal quality parameters of the unmanned aerial vehicle are obtained through the distributed sensing unit, and a dynamic network topological graph is constructed; performing role allocation, space-time resource allocation and ground-air link switching by adopting an intelligent decision combining a centralized mode and a distributed mode; high-reliability data transmission is realized based on multi-unmanned aerial vehicle cooperative beam forming, adaptive modulation and coding, priority queue scheduling and hybrid automatic retransmission; performance indexes are collected in real time through an AI learning unit, parameters are dynamically adjusted, and a self-optimization closed loop is formed; and the collaboration and the resource utilization efficiency of unmanned aerial vehicle cluster communication are remarkably improved.

The application discloses an unmanned aerial vehicle air-ground integrated communication method combined with intelligence AI, relates to the unmanned aerial vehicle communication technical field, and is used for solving the problem of cooperation confusion in unmanned aerial vehicle cluster communication; the application acquires real-time positions, speeds, postures and signal quality parameters of unmanned aerial vehicles through a distributed sensing unit, and constructs a dynamic network topological atlas; intelligent decision-making combining centralization and distribution is adopted to perform role allocation, space-time resource allocation and ground-air link switching; high-reliability data transmission is realized based on multi-unmanned aerial vehicle cooperative beam forming, adaptive modulation and coding, priority queue scheduling and hybrid automatic repeat request; performance indexes are collected in real time through an AI learning unit, and parameters are dynamically adjusted, so that a self-optimization closed loop is formed; and the cooperation and resource utilization efficiency of the unmanned aerial vehicle cluster communication are remarkably improved.

A simulated network Kubernetes controller for dynamic network topology partitioning includes: a DQN-based network topology partitioning module, a Pod scheduling module, and a rolling upgrade-based Pod migration module. The DQN-based network topology partitioning module performs graph partitioning based on user-submitted network topology information to obtain the distribution of virtual network components on physical machines. The Pod scheduling module performs scheduling calculations based on the virtual network component information that needs to be modified during algorithm verification to obtain the results of the virtual network components to be migrated. The Pod migration module performs Pod migration based on the calculated list of virtual network components to obtain the modified network topology distribution. This invention implements a Kubernetes controller based on the KubeBuilder framework for actual scheduling. It is used to achieve overall system load balancing when verifying network resource scheduling algorithms in large-scale dynamic topology scenarios on a cloud-native simulated network platform.

The invention discloses a rail transit communication network routing state dynamic optimization method and system, and the method comprises the steps: constructing a closed-loop control system of perception-evaluation-decision-execution-verification, constructing a dynamic network topology model on the basis of whole-network high-precision clock synchronization, and collecting link performance indexes based on multi-source data. Performing time alignment, missing value filling and normalization processing; dynamically calculating each index weight by using an information entropy model to form a link comprehensive score; an optimal path is calculated in combination with an improved Dijkstra algorithm and a multi-constraint path cost function, and an optimization result is issued to a routing protocol module to realize dynamic routing adjustment; and meanwhile, a closed-loop feedback, performance verification and rollback mechanism is introduced, so that the switching stability is ensured. According to the method, the routing state of the rail transit communication network can be adaptively optimized in real time, the link utilization rate is improved, the end-to-end time delay is reduced, and the high reliability and the service quality of bearing services are guaranteed.

The invention discloses a massive alarm log noise reduction and correlation analysis method based on a dynamic aggregation log codebook. According to the method, association analysis based on the Apriori algorithm is achieved for the alarm logs, an association log sequence is generated, a specific data structure-log codebook (Log Code-book) is generated through regularization processing, and codebook of the automatic association relation is achieved. In addition, noise reduction processing and multi-device association analysis of the massive alarm logs of the devices are achieved through the log codebook, and the alarm log association processing effect is remarkably improved. According to the invention, through a double-period codebook aggregation framework based on period broadcasting and timing uploading, a relatively high log association analysis effect is maintained in a dynamic network topology environment, and relatively high robustness is represented in various network environments.

The invention discloses a psychological deterrence-based three-layer AI (artificial intelligence) agent collaborative network security active defense system and method, and the system adopts three AI agents (a way finder, a bait hand and an observer) to cooperatively work to realize a sensing-confusing-deterrence three-layer defense system. The system can actively identify, analyze and cope with network attacks through technologies of dynamic network topology management, a psychological battle strategy engine, an advanced anomaly detection algorithm, key management security enhancement, an authentication and authorization mechanism, user data security storage, an intelligent agent stealth mechanism and the like, and meanwhile, threat intelligence sharing is realized through a community joint defense mechanism. The core innovation of the method is that uncertainty is maximized, so that an attacker cannot confirm success after huge resources are input, and finally the attacker is forced to give up the attack. The problems of passive defense, slow response, high false alarm rate and the like of a traditional network security system are solved, and the initiative, accuracy and efficiency of network security defense are remarkably improved.

The invention discloses an evaluation method for detecting the influence of retired wind power blade milling on the environment, and the method comprises the steps: collecting environment influence source data, recognizing a pollution feature cluster, and constructing a three-dimensional pollution fingerprint spectrum; constructing a milling workshop-environment medium coupling digital twinborn body, and generating a three-dimensional dynamic database; generating a fiber characteristic exclusive parameter set by using a Bayesian optimization method; performing space-time quantum clustering and fiber trajectory simulation, and predicting settlement hotspots of dust in the terrain-weather coupling field; constructing a dynamic network topology structure, and generating a toxicity risk thermodynamic diagram; and generating an environmental impact assessment report, and generating an environmental impact traceability chain by using distributed storage of a private chain and an interstellar file system. According to the invention, the whole process from pollution feature identification, dynamic prediction to risk assessment is intelligent and precise. The method can effectively predict dust settlement hot spots and biotoxicity risks, provides a scientific basis for environment management of retired wind power blade milling, and promotes the wind power industry to develop in a green and sustainable direction.

The application discloses a kind of low-power mobile sensor adaptive communication methods based on dynamic grouping, obtain the position data of each node, residual capacity data and link quality data;Using weighted distance algorithm to process position data, wherein weight value is determined according to the product of link quality data and residual capacity data, generate relative position matrix between nodes;According to relative position matrix, establish dynamic network topology structure, when detecting that the residual capacity of node is lower than preset threshold, mark the node as low-energy node;Using improved K-means algorithm to process dynamic network topology structure, wherein the selection weight of cluster center is determined by the linear combination of node position coordinate and residual capacity, and low-energy node is preferentially distributed to the group with the smallest load, to generate communication group configuration.The application improves the communication efficiency, reliability and energy utilization rate of wireless sensor network.

This invention provides an intelligent autonomous method and system for a multimodal graph-text fusion core network, relating to the fields of mobile communication networks and artificial intelligence. Based on a spaceborne platform, this method constructs a unified multimodal fusion model to receive natural language instructions and a dynamic network topology graph, extracting graph structure features and text semantic features respectively. It utilizes a cross-attention mechanism to achieve bidirectional feature fusion between graph and text modalities, evaluates the dominance of each modality, and adaptively adjusts the configuration of self-attention and cross-modal attention heads. It combines MoE dynamic routing to select the target output head to generate task instructions. After secure verification in an isolated environment by a deterministic execution engine, it is executed through an atomic operation execution layer. Furthermore, a hierarchical federated learning framework is introduced to aggregate the parameter increments of various satellite models on the ground, achieving multi-satellite collaborative evolution. It also realizes graph-text joint inference, low-power multi-task processing, secure and reliable execution, and continuous model evolution, significantly improving the level of intelligence, reliability, and security.

The invention provides a collaborative energy management method and system for a distributed wind power generation cluster, and relates to the technical field of distributed energy management, and the method comprises the steps: firstly obtaining the energy buffer state information of each wind field in the distributed wind power generation cluster, and obtaining a load demand portrait of each power consumption main body in a region; constructing a wind field energy buffer pool networking reference based on the information, including an inter-buffer pool energy interaction association rule and a load demand and buffer pool adaptation standard, performing dynamic networking topology generation processing to obtain an energy buffer pool dynamic networking topology, generating an energy scheduling adaptation instruction according to the energy buffer pool dynamic networking topology, and scheduling the energy scheduling adaptation instruction according to the energy scheduling adaptation instruction. The energy throughput direction, scale and load demand matching time sequence of the buffer pool are determined, and finally, the running state of the energy buffer pool of each wind field and the energy interaction process with the power utilization main body are cooperatively adjusted in real time according to an energy scheduling adaptation instruction, so that cooperative energy management is realized, and the energy utilization efficiency and the power supply reliability are improved.

The application discloses a kind of multi-device synchronous measurement collaborative control method and system, and the application relates to the technical field of automation control, intelligent manufacturing equipment and multi-device collaborative scheduling, constructs the full-duplex two-way communication architecture between heterogeneous intelligent measuring equipment cluster and intelligent unified control terminal, establishes the real-time interaction link of periodic heartbeat message and state data stream, and based on the preset comprehensive health degree evaluation model, the equipment health degree score of each heterogeneous intelligent measuring equipment is collected and calculated in real time, and the real-time equipment resource panoramic state table is maintained in the intelligent unified control terminal, the application breaks the simple queue type serial response limit in traditional equipment collaborative scheme, and innovatively proposes the dynamic network topology construction mechanism combining graphical task scheduling engine and directed acyclic graph, which can transparentize and visualize extremely complex three-dimensional collaborative measurement tasks.

The invention discloses a self-adaptive data synchronization method and system for a satellite distributed cluster. A state sensing module, a utility value calculation module and a propagation decision module are deployed on each satellite node in a satellite distributed cluster; each satellite node firstly obtains a neighbor node list in real time; acquiring state parameters of each neighbor node in the neighbor node list by using a state sensing module, wherein the state parameters comprise battery capacity, residual energy, link quality and load state; then, based on the state parameters, a utility value calculation module calculates a comprehensive utility value of each neighbor node through a preset multi-dimensional utility value function; and then, the propagation decision module selects one or more target neighbor nodes to perform message propagation according to the utility values of all the current neighbor nodes, and sends a synchronization message to the selected target neighbor nodes. The method is suitable for data synchronization in a high-dynamic low-orbit satellite network with fast network topology transformation.

The application provides a UASN access control method based on adaptive transmission power and dynamic time slot scheduling, and belongs to the technical field of underwater acoustic sensor networks. The application is used for solving the problems of high node communication energy consumption, low channel utilization rate and poor adaptability to dynamic network topology in the underwater acoustic sensor network, and the problems of low channel utilization rate and poor fairness. The steps of the application comprise the following steps: S1, system model construction; S2, specific implementation of the TCSA-MAC protocol. Through an adaptive transmission range control technology based on Q learning, the application intelligently decomposes the long-distance single-hop transmission into multi-hop forwarding, and solves the problem of excessively high network energy consumption. Meanwhile, through a dynamic time slot allocation technology based on node load information, the application reserves channel resources for high-load nodes, and solves the problems of low throughput and poor fairness caused by the random access mechanism under the high load of the network.

The application discloses a kind of intelligent DHCP relay system and method based on dynamic network topology perception, system includes: network detection module, configured to send probe packet to multiple DHCP servers, based on the response information of probe packet, obtain the network performance index of each DHCP server between forwarding path;Quality of service evaluation module is configured to receive the network performance index from network detection module, based on network performance index, the comprehensive score of each forwarding path is calculated, and the quality of service map is updated according to comprehensive score, wherein the quality of service map is used to store forwarding path and corresponding quality of service index;Routing decision module is configured to query the updated quality of service map in real time, based on comprehensive score, obtain optimal path, and encapsulate DHCP request message of DHCP client based on optimal path and forward to corresponding DHCP server.The embodiment of the application can reduce request delay through dynamic path selection, improve success rate.

The embodiment of the application provides a routing method and device based on on-satellite processing, constructs a dynamic network topology according to a satellite constellation operation period and a link building rule by adopting a time slicing division mechanism. A gateway station pre-annotates time slicing and network topology corresponding relation data to a satellite node storage. After receiving data, the satellite node realizes autonomous routing calculation based on a network topology corresponding to a current time slicing, and determines a next hop forwarding node by adopting a shortest path algorithm. Through a dynamic routing recalculation mechanism of a relay node, data is guaranteed to be transmitted to a target node along an optimal path. The method effectively solves the deficiencies of traditional technologies in real-time routing, topology management and on-satellite processing, and significantly improves the performance of a satellite communication network.

The invention provides a dynamic routing selection and optimization method in a satellite communication network, relates to the technical field of satellite communication, and solves the problems of routing failure, uneven load and weak fault resistance in the prior art. The invention relates to a dynamic routing selection and optimization method in a satellite communication network, which comprises the following steps of: S1, acquiring and preprocessing a multi-dimensional network state in real time: acquiring a satellite node state and an inter-satellite link state, and constructing a standardized state vector containing a position, power, a load, time delay and an error rate; and S2, dynamic network topology modeling and prediction: predicting link visibility based on an orbit mechanical model, and constructing a directed graph model with a comprehensive measurement weight. According to the invention, the anti-fault capability is enhanced, the link interruption recovery time is shortened to 50ms by a pre-stored backup path and a rapid switching mechanism, the service continuity is improved by 95%, the spectrum efficiency is optimized, the use of low-quality links is avoided by comprehensive link measurement, and the spectrum utilization rate is improved from 65% to 85%.