34 results about "Link weight" patented technology

The invention relates to the technical field of network security, in particular to a distributed network attack tracing method and system, and the method comprises the following steps: carrying out the statistics of flow transmission time delay, bandwidth occupancy rate and data packet quantity among distributed network nodes, carrying out the clustering division of each node flow feature value, and generating a node flow feature clustering value; and on the basis of the node traffic feature clustering value, constructing an inter-node traffic transmission relation graph, and calculating an inter-node link weight and an association degree. According to the method, clustering division is carried out on the flow characteristic values among the distributed network nodes, the flow transmission relation graph among the nodes is constructed, the link weight and the correlation degree are calculated, a complex network structure is converted into a topological correlation matrix capable of being quantitatively analyzed, and basic data support is provided for follow-up attack traceability. Data packet identifiers and timestamp information are extracted based on a time series data analysis method, and abnormal traffic transmission characteristics are identified and statistically analyzed, so that the attack behavior detection accuracy is improved.

The invention discloses a multi-link switching method based on a heterogeneous network, relates to the technical field of multi-link switching, and is used for solving the problems of low link state detection and switching efficiency and link state misjudgment caused by a single address in the prior art. According to the method, the number of heterogeneous networks is determined, link dynamic binding and priority configuration are carried out on each heterogeneous network, the link weight and the link switching threshold value of each heterogeneous network are self-defined to serve as switching judgment logic, a dynamic routing protocol is constructed, and an optimal routing table of a link corresponding to each heterogeneous network is generated in real time; and executing routing control through the optimal routing table, performing multi-thread independent detection, binocular address detection and IP state monitoring on the link of each heterogeneous network, obtaining the link state of each link based on detection and monitoring results, and switching the link according to the link state of the link to which the heterogeneous network belongs and switching judgment logic. And a corresponding switching strategy is formulated for synchronous execution, so that efficient and accurate multi-link switching is realized.

The invention discloses a data-driven unmanned aerial vehicle cluster digital twin network binding routing method. According to the method, a tight coupling dependency relationship between data transmission and link control is relieved, and a management plane-control plane-data plane decoupling unmanned aerial vehicle cluster network architecture is constructed. The management plane decides a link weight with the help of a depth deterministic strategy gradient learning method by taking minimization of time delay and packet loss probability as optimization targets. And the control plane formulates a forwarding strategy according to the Floyd shortest path algorithm and the weighted topological graph and issues the forwarding strategy to the data plane. And the unmanned aerial vehicle nodes in the data plane concentrate on data forwarding to realize execution of binding routing. A simulation result shows that the link weight is adaptively adjusted by adopting the method, and compared with a traditional routing algorithm with a fixed link weight, the average end-to-end time delay and the packet loss rate can be effectively reduced, and the network service quality is improved.

The invention belongs to the technical field of communication, and discloses a link planning method and device, equipment, a storage medium and a product. According to the invention, a link weight matrix is constructed according to communication information between each layer of constellation and each gateway station, then a link matrix between each layer of constellation and each gateway station is constructed, and each element in the link matrix is used for representing a link connection relationship between each layer of constellation and each gateway station. And the value of each element in the link matrix is solved based on the link weight matrix, and the optimal connection gateway station of each layer of constellation is determined according to the value of each element in the link matrix. According to the method and the device, the value of each element in the link matrix is solved based on the link weight matrix, and each layer of constellation is limited to establish a link with only one gateway station, so that the link communication relationship between each layer of constellation and each gateway station can be obtained, and the optimal connection gateway station for establishing a satellite-ground link with each layer of constellation can be obtained; and the data of the whole multi-layer constellation system is ensured to be transmitted back through the optimal connection gateway station.

The invention relates to an application test method and device, electronic equipment and a storage medium, and relates to the technical field of computers, and the method comprises the steps: obtaining an application service relation graph and test range indication information under the condition that an application test instruction is received; determining a plurality of to-be-tested services and service link diagrams based on the application service relation diagram; performing link weight analysis on each to-be-tested sub-link based on the edge weight information or the node weight information in each to-be-tested sub-link to obtain sub-link weight information; based on the sub-link weight information and the service link diagram, performing a flow distribution test on the plurality of to-be-tested sub-links to obtain a link calling test result; obtaining service test codes corresponding to a plurality of to-be-tested services; based on the service test code, performing a service execution test on each service to be tested in the plurality of services to be tested to obtain a service execution test result; and generating an application test result based on the link call test result and the service execution test result.

The present application relates to the field of communication technology, and in particular to a method and device for optimizing the timeliness of data streams. The method comprises: for any data type to be transmitted, determining the link weight corresponding to the data type to be transmitted on each link according to the transmission rate of each link, the link comprising an adjacent first network node and a second network node; determining the target data type from each data type to be transmitted according to the link weight corresponding to each data type to be transmitted on each link; determining the target scheduling link from each link according to the link weight corresponding to the target data type on each link, and the transmission rate of each link, and transmitting the data stream corresponding to the target data type on the target scheduling link. The use of this method can improve the timeliness of the data stream, which is conducive to maintaining the stability of the network and the freshness of information.

The application provides a signaling communication network topology determination method and device, electronic equipment and a storage medium. The method comprises: obtaining an original optical network topology; determining the original carrying traffic, original security attribute value and original link weight of each link; deleting a first target link with the lowest original link weight to obtain a first updated network topology, and determining whether the first updated network topology meets the connectivity requirement; if the first updated network topology meets the connectivity requirement, determining the first updated carrying traffic and first updated security attribute value of each link; determining whether the first updated carrying traffic is not greater than the maximum carrying traffic of the link, and whether the first updated security attribute value reaches a preset security attribute value; if the first updated carrying traffic is greater than the maximum carrying traffic of the link, and / or the first updated security attribute value does not reach the preset security attribute value, adding the first target link to the first updated network topology to determine a target network topology.

This application discloses a transmission path determination method, comprising: determining the predicted performance value of each network node in a predetermined time period using a preset model based on a historical network graph of a historical time period, wherein the historical network graph includes: adjacency weight values ​​between network nodes and historical performance values ​​of each network node in the historical time period, wherein the historical time period corresponds to the predetermined time period; determining the link weight of each link between network nodes in the predetermined time period based at least on the predicted performance values ​​of each network node, wherein the link weight is used to characterize the transmission performance of the link; and determining the transmission path used for transmitting service data in the predetermined time period based on the link weights of each link, wherein the transmission path includes at least one link. This application also discloses a transmission path determination apparatus, an electronic device, and a storage medium.

The invention relates to a traffic distribution method and device, electronic equipment and a computer program product, and belongs to the technical field of computers. The method comprises the following steps: acquiring an initial weight corresponding to each link between a multi-path route and a next-hop route in a network architecture; obtaining a weight upper limit value of the network architecture, and adjusting the initial weight according to the weight upper limit value to obtain an adjusted link weight; and carrying out flow distribution between the multi-path route and the next-hop route according to the adjusted link weight. According to the invention, the link weight of the multipath routing is adjusted according to the weight upper limit value, the traffic can be distributed more reasonably, the risk of service packet loss is reduced, and the stability of the network is ensured.

The application provides a production management method based on artificial intelligence, comprising the following steps: constructing a space-time correlation traceability graph based on a production network topology and taking time sequence characteristic values of micro-variable mark sequences as node and link weights according to the micro-variable mark sequences, determining a congestion diffusion conduction direction and a network topology boundary coordinate; obtaining a real-time delay of a production task transmission path, performing space-time dimension feature correlation on the congestion diffusion conduction direction, the network topology boundary coordinate and the real-time delay of the corresponding production task transmission path, and determining a congestion risk; and monitoring a path utilization rate in real time, if the path utilization rate breaks through a preset critical buffer threshold, switching a new task to a next available path in order, and obtaining a final task bearing scheme that adapts to production load demand.

The application discloses a routing method, medium, equipment and product of a low-orbit satellite constellation, relates to the technical field of satellite routing, and comprises the following steps: according to a quality of service parameter, performing snapshot freezing on a current network topology to construct a static topology graph structure; constructing a basic quality of service parameter cost function for each link; performing an offline ant colony optimization algorithm to globally evaluate a satellite topology library constructed in advance, constructing a heuristic function according to a link basic quality of service parameter cost; initializing a pheromone value for each link, and updating the pheromone in an iteration process according to the heuristic function; adjusting the cost function based on the pheromone; taking the cost of the discounted pheromone as the final link weight of the satellite network, constructing a weighted graph structure, and adopting a shortest path search algorithm to calculate a routing path between a source node and a target node, so that an optimal routing path is obtained. The application solves the problems of high-speed time-varying satellite link state adaptability and poor quality of service.

The application discloses a substation communication network fragile structure evaluation method based on a complex network theory, which comprises the following steps: constructing a substation communication network model, generating link weights based on attack paths of the substation communication network model, combining the complex network theory with the link weights, and calculating a plurality of node vulnerability values; based on the node vulnerability values, comprehensively considering local information and global information of the links, and calculating a plurality of link vulnerability values; and based on the node vulnerability values and the link vulnerability values, respectively evaluating the fragile structure of the substation communication network. The application can solve the problems of fast network attack updating speed and difficulty in quantification and subjectivity of expert evaluation in the prior art.

The invention discloses a bridge acceleration acquisition method and acquisition system based on an improved Dijkstra algorithm, and the method comprises the steps: S1, enabling a bridge acceleration measurement device, network transmission equipment and a data processing center to serve as nodes, enabling communication links between the equipment to serve as edges, enabling w to represent the weight of each link, and enabling w to serve as the weight of each link; abstracting a data transmission network from the bridge acceleration measurement device to the data processing center into a network topology structure diagram; s2, taking the data processing center as a source node, and calculating a shortest path from the bridge acceleration measurement device to the data processing center based on an improved Dijkstra algorithm; s3, transmitting data measured by the bridge acceleration measuring device to a data processing center based on the shortest path obtained in S2; the invention discloses a bridge acceleration acquisition method and acquisition system based on an improved Dijkstra algorithm, the link weight is adjusted according to the change of the network state, a Dijkstra algorithm optimization module can dynamically adjust the data transmission path, and the real-time performance and reliability of data transmission are ensured.

The present application relates to a microservice scheduling method, apparatus, device, and storage medium under a k8s cluster. The method includes: collecting node data of each node under the k8s cluster and service traffic data of each microservice instance; constructing a dynamic microservice topology relationship graph according to the service traffic data; wherein, the dynamic microservice topology relationship graph includes: microservice nodes, call links, and link traffic information and link weight information; based on the dynamic microservice topology relationship graph and the node data, evaluating candidate nodes from multiple dimensions, and screening to obtain target nodes; scheduling microservice pods to the target nodes. Thus, it is possible to comprehensively consider the resource utilization rate of the server and the network topology structure between microservices, greatly optimize the microservice scheduling strategy, and obtain a scheduling scheme that not only conforms to the node resource load balancing but also minimizes the communication cost between microservices and has the best communication performance.

The invention relates to a routing method and device based on fuzzy logic and logarithm accumulation, equipment and a medium. The method comprises the following steps: acquiring preprocessed node state parameters; inputting the node state parameters into a preset fuzzy logic system, and respectively generating corresponding energy weight, queue weight and link weight through membership function mapping, fuzzy rule reasoning and defuzzification operation; performing weighted calculation on the node state parameters according to the energy weight, the queue weight and the link weight to obtain node reliability; performing logarithmic operation on the node reliability, and performing hop-by-hop accumulation on a logarithmic operation result based on a node sequence to generate path logarithmic reliability; calculating the path logarithm reliability according to a preset path hop count calculation mode, and determining a corresponding path comprehensive routing degree; and comparing the candidate paths according to the path comprehensive routing degree, and determining a corresponding optimal path as a target route. The method has the effect of improving the routing reliability.

The application provides a network scheduling method and device, a network orchestrator, a communication system and a storage medium, and relates to the technical field of communication. The method comprises the following steps: constructing an optoelectronic fusion topology based on a packet layer, a time division multiplexing layer and an optical layer; after receiving a service request, modifying the corresponding link weight in the optoelectronic fusion topology based on the service type carried in the service request; performing multi-layer joint path selection based on the modified optoelectronic fusion topology to obtain a candidate path set; for each candidate path in the candidate path set, performing multi-dimensional service quality quantifiable and promised network scheduling on the candidate path; and deploying the service according to the network scheduling result and updating the optoelectronic fusion topology and the link weight. The application can construct an optoelectronic fusion topology, design a multi-layer joint path selection and multi-dimensional service quality quantifiable and promised network scheduling strategy, promote the deep integration of the packet domain and the transmission domain, and meet the core requirements of service customization.

This invention discloses a method, medium, device, and product for dynamic OSPF link weight optimization, relating to the field of OSPF link weight optimization technology. The method includes: acquiring OSPF link bandwidth, link latency, maximum utilization, and link error rate in real time via the SNMP protocol to construct a state vector; using the state vector as input and the weight adjustment values ​​of each link as output to construct a deep reinforcement learning model; calculating new link weights based on the weight adjustment values ​​output by the model; writing the new weight values ​​into the interface configuration of the OSPF router to trigger OSPF to recalculate routes. This invention directly applies deep reinforcement learning technology to OSPF link weight optimization, achieving intelligent and automated dynamic OSPF link weight optimization.

The application discloses an unmanned ship cluster cooperative communication method and system, and particularly relates to the technical field of unmanned ship cluster communication, and is used for solving the problem of poor unmanned ship cluster cooperative communication; the application constructs a cooperative communication mechanism with real-time sensing and self-adaptive capability, collects the spatial position, speed and heading information of the unmanned ship, constructs a standardized state vector, generates and dynamically maintains a communication topology graph, and screens out effective links meeting the communication distance and link weight conditions; the link load is monitored in real time, a node congestion sensing factor is calculated, an optimal path is selected based on the distance and the load after path optimization is triggered, and the forwarding rate is adjusted; a scheduling factor is constructed in combination with a task time limit, an active node range and a delay sensitivity level, a priority score is generated, communication tasks are scheduled to the optimal link and period according to the task priority, and the spatiotemporal cooperative scheduling optimization of the unmanned ship cluster according to the task level is realized.

The present application relates to the field of mobile communication technology, especially to a kind of software defined wireless Mesh network adaptive networking method based on multi-link cooperation, comprising the following steps: each node discovers neighbor node, is connected by three different frequency band links to form Mesh network;Introduce SDN controller, real-time collection node state information, combine network topology change and service demand, according to different message type and link characteristic on-demand selection optimal route;When node fails or off-line, combine node mobility management mechanism, routing protocol converges quickly, simultaneously adjusts transmission path.The present application adopts software defined routing, is uniformly distributed by controller route and link selection, can be realized on-demand routing according to service type;By collecting network state information, adaptively change link weight, according to link condition and service type selection suitable route and link;Adopt E-Dijkstra algorithm, can realize the fast decision of route and link selection, reduces processing delay.

The invention discloses a giant constellation network routing method and device based on containment control, and belongs to the technical field of satellite network routing control, and the method comprises the steps: selecting a controller node and an associated node thereof in a giant constellation network; each controller node obtains the link weight and the flow information of the associated node of the controller node; taking one or more associated nodes with the maximum flow of each controller node as driving nodes; each controller node updates the weight of a link connected with a driving node of the controller node; and calculating path weights of all nodes in the giant constellation network, and selecting the path with the minimum weight to update the routing table. According to the method, the burden of routing state interaction in the giant constellation can be greatly reduced, the routing convergence time is shortened, and the requirements of large scale and high dynamic of the giant constellation network space on the routing method are met. Meanwhile, the method can be widely applied to various giant constellation networks.

The invention provides an industrial wireless sensor network topology control method for data collection, which comprises the following steps of: uniformly dividing a task period into a plurality of continuous time periods, and calculating an initial network topology sequence according to whether each industrial sensor node is active or not in each time period and dynamic position information, constructing a space-time diagram according to the initial network topology sequence; calculating an energy consumption index and a reliability index of each link in the space-time diagram, and fusing the energy consumption index and the reliability index into a comprehensive link weight; and searching an optimal space-time path from each industrial sensor node to a control node by using an improved shortest path algorithm according to the space-time diagram and the comprehensive link weight, and combining link sets of all the shortest space-time paths to form a final network topology of the IWSNs. According to the method, the energy consumption and reliability of data transmission in a dynamic network are balanced while the influence of node mobility on industrial wireless communication is considered.

The present invention discloses a link weight prediction method and system based on network reconstruction and weight perturbation, comprising the following steps: Step S1, randomly dividing the weight set W in the weighted network to generate a training set W T With the test set W V Two parts; Step S2, from the training set W T A small part is randomly selected as the perturbation set ΔW, and the rest is W r ; Step S3, W r Perform eigenvalue decomposition to obtain the perturbed weight matrix W1; Step S4, reconstruct the weighted network weights and obtain the weight matrix W2; Step S5, combine the matrices W1 and W2 using linear fusion to obtain the link weight prediction matrix; Step S6, combine the test set W V The corresponding weight values ​​are compared with the predicted weight values ​​to determine the effectiveness of the algorithm. This method cleverly linearly integrates the two elements of network reconstruction and weight perturbation, effectively correcting the errors in the weight information and successfully revealing potential new weight information.

The present disclosure relates to a communication line determination method and device, electronic equipment and computer program product. The method comprises: in response to a service access request of a terminal, determining a starting node and a destination node matched with the service access request; obtaining a plurality of candidate communication lines between the starting node and the destination node, and determining links included in the plurality of candidate communication lines respectively; obtaining a node performance index of a node corresponding to the link, and determining a link weight corresponding to the link according to the node performance index; and determining a line weight corresponding to each of the plurality of candidate communication lines according to the corresponding link weight, and determining a target communication line from the plurality of candidate communication lines according to the line weight. The embodiments of the present disclosure can fully consider all communication lines between the starting node and the destination node, so that the communication line calculation is more accurate, and the optimal communication line can be obtained more accurately.

The invention belongs to the field of network management and traffic engineering, and discloses a routing optimization method based on traffic matrix completion prediction, which comprises the following steps: step 1, constructing a routing matrix A and collecting a link load vector at the current moment, and step 2, constructing a traffic matrix completion model and outputting a complete traffic matrix. 3, constructing a space-time traffic prediction model, and outputting a predicted traffic matrix at the next moment; 4, connecting the traffic matrix completion model and the space-time traffic prediction model in series, and defining a joint loss function to perform parameter updating on the whole end-to-end network; and step 5, pre-evaluating a pre-estimated load state, dynamically adjusting a link weight and generating an optimal routing strategy by utilizing the output predicted traffic matrix at the next moment and combining network topology information, and finally issuing configuration to a data level to realize routing optimization of traffic transmission. According to the method, the integrity of the traffic matrix is ensured, adaptive attention to the key link is realized, and the complemented data highly conforms to future trend prediction.

The application belongs to the technical field of communication, and discloses a link planning method, device, equipment, storage medium and product. According to the communication information between each layer constellation and each gateway station, a link weight matrix is constructed, then a link matrix between each layer constellation and each gateway station is constructed, wherein each element in the link matrix is used for representing the link connection relationship between each layer constellation and each gateway station, the value of each element in the link matrix is solved based on the link weight matrix, and the optimal connection gateway station of each layer constellation is determined according to the value of each element in the link matrix. Based on the link weight matrix, the value of each element in the link matrix is solved, and each layer constellation is limited to establish a link with only one gateway station, the link connection relationship between each layer constellation and each gateway station can be obtained, so that the optimal connection gateway station for establishing the space-ground link with each layer constellation can be obtained, and the data of the whole multi-layer constellation system is backhauled through the optimal connection gateway station.

The invention discloses a computing power network routing and online data processing joint optimization method and system based on deep reinforcement learning, and the method comprises the steps: S1, collecting the state information of a whole network, and constructing network state representation; s2, inputting the network state representation into a pre-configured decision model, wherein the decision model is used for extracting network features and outputting strategy distribution parameters; s3, based on the strategy distribution parameters, sampling from the strategy distribution to generate a joint action vector; s4, calculating a transmission path for the data stream based on the link weight parameter; s5, screening on the transmission path based on the processing probability parameter and determining a computing node for executing the on-network data processing task; and S6, issuing a routing table item and a calculation instruction, and executing data stream forwarding and online data processing operation. According to the method, a unified decision framework is created, and whether more computing resources are consumed to save communication resources or the communication resources are directly used for transmission can be determined according to the real-time network state.

The invention provides a portal frame quality detection method and system, and relates to the technical field of portal frame production, and the method comprises the steps: obtaining the process link data of each key part in the production process of a forklift portal frame, and the process link data comprises the welding link data and the assembly link data; performing anomaly detection on the link data of each process to obtain a link anomaly degree value; according to the link abnormal degree value and the link weight corresponding to the link abnormal degree value, stability analysis of different use modes is carried out to obtain a stability index; and according to the stability index, determining the qualification of the door frame quality so as to complete door frame quality detection. According to the detection method and system provided by the invention, the quality evaluation efficiency of the door frame after production can be effectively improved, and the reliability of a door frame quality qualification detection result is ensured.

The application provides a LEO mega-constellation flexible routing method based on graph reinforcement learning and related equipment, and relates to the technical field of satellite communication. The method comprises the following steps: dividing the constellation topology into multiple control domains, managing the multiple control domains by using master-slave controllers based on the SDN architecture; the master controller calculates the global shortest path from the source node to the destination node, and decomposes the cross-domain traffic request between the source-destination node pair into multiple intra-domain traffic requests according to the domain boundary nodes and inter-domain links passed by the global shortest path; the slave controller constructs a virtual traffic topology according to the total intra-domain traffic request and the fault link, selects the key link in the domain, extracts the link feature matrix of the virtual traffic topology by using the GNN, updates the weight of the key link by using the reinforcement learning algorithm, and then generates the intra-domain routing path based on the new link weight under the constraints of the path delay and the link bandwidth. The application can meet the high availability and low delay requirements of LEO mega-constellation data transmission.

The invention discloses a link weight prediction method and system based on network reconstruction and weight perturbation, and the method comprises the following steps: S1, carrying out the random division of a weight set W in a weighted network, and generating a training set WT and a test set WV; s2, randomly selecting a small part from the training set WT as a disturbance set delta W, and taking the rest part as Wr; s3, performing eigenvalue decomposition operation on the Wr to obtain a disturbed weight matrix W1; s4, reconstructing the weight of the weighted network, and obtaining a weight matrix W2; s5, combining the matrix W1 and the matrix W2 in a linear fusion mode to obtain a link weight prediction matrix; and S6, comparing the weight value corresponding to the test set WV with the predicted weight value, and judging the validity of the algorithm. According to the method, the two major elements of network reconstruction and weight perturbation are ingeniously and linearly integrated, errors in weight information are effectively corrected, and potential new weight information is successfully revealed.

The application belongs to the field of network management and traffic engineering, and discloses a routing optimization method based on traffic matrix completion prediction, which comprises the following steps: step 1, constructing a routing matrix A , collecting a link load vector at the current moment, step 2, constructing a traffic matrix completion model to output a complete traffic matrix; step 3, constructing a space-time traffic prediction model to output a predicted traffic matrix at the next moment, step 4, connecting the traffic matrix completion model and the space-time traffic prediction model in series, defining a joint loss function to update parameters of the entire end-to-end network; step 5, using the output predicted traffic matrix at the next moment, combining network topology information, pre-evaluating an estimated load state, dynamically adjusting link weights and generating an optimal routing strategy, and finally configuring and issuing to the data layer to realize routing optimization of traffic transmission. The application guarantees the integrity of the traffic matrix, realizes adaptive attention to key links, and makes the completed data highly consistent with future trend prediction.