47 results about "Network size" patented technology

The invention provides a power distribution network communication network fault diagnosis and self-adaptive reconstruction method, which comprises the steps of formulating corresponding layering and partitioning strategies aiming at different network scales and service types, including modular management of a large-scale multi-layer network and centralized response of a small-scale network; the faults of various networks can be effectively positioned and isolated; recognizing a reconstruction object after the fault positioning is completed, and formulating a network reconstruction scheme according to the recognized reconstruction object and the current state of the network, including but not limited to replacing a fault node, reconstructing a connection or modifying a route by starting a standby resource; after the reconstruction scheme is executed, the data collection and analysis period is adjusted according to the fault frequency, and the reconstruction interval is controlled to reduce redundant network structure adjustment and potential network fluctuation, including active detection and passive monitoring of the power distribution network and bidirectional monitoring of the network condition.

A fast code generation device supporting the generation of fusion operators, belonging to the technical field of deep learning. The present invention includes: an LDM area division module for functionally partitioning the local storage space according to the network size parameters input by the upper-layer framework; a fusion operator address configuration module for defining the addresses of the input, output, and intermediate result data in the operator in the functional partition according to the type of fusion operator input by the upper-layer framework; a fusion operator data interaction module providing function interfaces for asynchronous memory access between the local and the main memory, and between the local and the local; a SIMD fusion operator calculation module for fusing the operator according to the addresses generated by the fusion operator address configuration module; and a systolic array instruction configuration module for configuring the instructions for driving the systolic array to perform calculations. The present invention can effectively reduce the code error rate, improve the code generation efficiency, and simplify the debugging process.

This application provides a distributed wireless resource scheduling method and electronic device, relating to the field of wireless communication network technology. In this method, the coordinator and computing nodes only need one round of information exchange, avoiding the huge signaling overhead and accumulated latency caused by multiple rounds of iterative negotiation. Time-consuming optimization calculations are offloaded to multiple computing units for parallel execution, achieving a linear reduction in overall computation time. Furthermore, it leverages the approximate achievable rate to provide theoretical feasibility for distributed solutions, while global coordination by edge devices ensures the performance of critical users, allowing the performance of the distributed solution to approach that of centralized algorithms, which serve as the performance ceiling. Because the coordination overhead is constant and minimal, and the computational load is effectively distributed, the system performance is far less affected by network size growth than centralized solutions. This makes it highly suitable for deployment in future network scenarios such as ultra-dense networking and large-scale carrier aggregation, enabling high-performance, low-overhead, and scalable distributed resource allocation under an O-RAN architecture.

The application discloses a scalable network security risk checking method, and relates to the technical field of network security, and comprises the following steps: establishing a network information collection mechanism to collect network information from each node of a target network; establishing a risk feature library, initializing the feature library, storing feature information of common network security threats in the risk feature library in a classified manner, and establishing indexes and classification labels; extracting a network topology graph from network topology information, calculating a network scale evaluation value according to the network topology graph; and generating a checking strategy according to the network scale evaluation value. The application flexibly generates a checking strategy according to a network scale evaluation value, is suitable for networks of different scales and architectures, can timely adjust the checking strategy when the network scale changes, ensures the effectiveness of risk checking, and effectively overcomes the limitations of traditional methods designed for specific network architectures.

The invention relates to a self-adaptive planning method for an aircraft data link network, and the method comprises the steps: obtaining the number of micro time slots contained in all types of time slots in a communication network based on an aircraft communication link model and an aircraft motion model; based on the aircraft motion model and the micro time slot duration, obtaining a micro time slot number required by a network management information updating period of the communication network; based on the aircraft clock model and the micro time slot duration, obtaining the number of micro time slots required by a clock synchronization update period of the communication network; based on the time slot table, the number of micro time slots included in each type of time slots, the network scale of the aircraft data link network and protocol requirements, obtaining the total number of micro time slots required by each type of time slots in the communication network; arranging various types of time slots in a time slot table based on the total number of micro time slots required by various types of time slots in the communication network and the number of micro time slots required by a network management information updating period and a clock synchronization updating period; and executing the corresponding time slot task according to the time slot table. The problem that network planning is not practical and not comprehensive is effectively solved.

The application belongs to the field of FPGA-based hardware accelerator design, and proposes a point cloud target detection neural network accelerator and an acceleration method based on FPGA. The convolution accelerator comprises an instruction decoding module, a convolution module, an accumulation module, a truncation module and an activation function. The intermediate value cache only temporarily stores the channels of one feature map, consumes less BRAM, and is suitable for accelerating the point cloud target detection neural network with large feature map size, large number of channels and large network size. The application has flexible configurability and excellent reusability, so the application can accelerate different convolution layers of the point cloud target detection neural network, and is suitable for being integrated as an IP into a large design, reducing FPGA resource consumption and improving resource utilization. Moreover, the weight and the input feature map share one data input channel, and the convolution intermediate value is temporarily stored on-chip BRAM, reducing the feature map carrying frequency and saving the FPGA interface bandwidth.

Devices, systems, methods, and processes for facilitating a disaster recovery within a workload protection solution. As segmented networks increase in size, the probability of disasters or other events occurring increases. To allow for disaster recovery facilitation, network devices subject to disaster recover can be configured with similar or identical security identifications (or certificates). This can allow agents to easily travel and operate between various network devices. Target network devices are determined as subject to a disaster event and corresponding source network devices are sourced. Depending on the network devices affected, one or more of a variety of configurations can be replicated from the source network device(s) to the target network device(s). This replication can occur in response to a user prompt, a timed interval, a warning signal, or other connection issue that is determined. This disaster recovery replication can occur in series or in parallel between various network devices.

The invention discloses a TDMA (Time Division Multiple Access) ad hoc network access method based on a dynamic time slot frame structure, which comprises the following steps: on the basis of networking in a fixed TDMA mode, interacting an on-line node mapping table and an off-line node mapping table through signaling to obtain the number of on-line nodes and node IDs (Identity) of the whole network so as to adjust the design of an on-network time slot frame structure, reduce the occupation of useless time slot resources and improve the access efficiency of the whole network. The frame efficiency is effectively improved, and the service transmission quality is improved. According to the method, the time slot frame structure can be adjusted according to the number of online nodes, the node information is notified to the whole network in a mapping table mode, the signaling overhead is reduced, the method adapts to different network scale scenes through the access mode of the dynamic time slot frame structure, and the service transmission quality is effectively improved.

The invention provides a Torus network scale expansion method based on an optical switch, a medium and equipment, and belongs to the field of data center networks. According to the method, a k * k Torus structure serves as super nodes, the super nodes are connected through an optical switch, and the method is mainly divided into three parts of task placement, logical topology mapping and flow forwarding. The tasks are classified according to sizes and then placed, and communication requirements between super nodes are guaranteed as much as possible; two principles are provided for logical topology mapping, that is, reconfiguration in an optical switch cannot affect a running task and connectivity between tasks placed in different super nodes needs to be considered during reconfiguration. And when the cluster fragments are more or the load is higher, the nodes cannot directly reach each other, so that the flow forwarding is started. According to the invention, flexible scale expansion of a large-scale Toruss network can be effectively realized, and connectivity and performance requirements of each task are ensured.

The embodiment of the invention provides a network reliability analysis method based on a mixed K / Q-cascade model. The network reliability analysis method is based on a mixed K / Q-cascade model, and comprises the following steps: 1, initializing model parameters; step 2, generating an initial random network and extracting a node initial degree; step 3, first-round failure detection is carried out, and the first-round failure detection is carried out only for k-cascade nodes; 4, recording the initial change of the network scale; step 5, cascade failure iteration judgment and network updating: carrying out loop iteration until no node fails; and step 6, visualizing network scale evolution. According to the hybrid K / Q cascade model provided by the invention, the local dependence and heterogeneity of network nodes are considered, and the node difference is also considered. Analysis is carried out according to a mixed K / Q cascade model, and besides information rapid propagation and information rapid stop, information propagation also has a third state, namely a metastable state. When the complex network is in the state, information spreading almost stops for a long period of time in the earlier stage until sudden collapse occurs at a certain moment in the middle. The phase change phenomenon is more suitable for some actual scenes.

The embodiment of the invention provides a cooperative task complexity analysis method and system based on task network characteristics, and the method comprises the steps: carrying out the hierarchical decomposition of a command and control task into atomic tasks according to four dimensions, constructing a task network model, traversing the task network model, extracting network scale characteristics, structural relation characteristics and uncertainty characteristics, and carrying out the calculation of the complexity of the atomic tasks. Complexity calculation is carried out on the network scale feature, the structural relationship feature and the uncertainty feature, a corresponding complexity quantification result is determined, and optimization adjustment is carried out on the task network model according to the complexity quantification result, so that the task network complexity of the task network model is reduced, and the task network complexity of the task network model is improved. The accuracy and efficiency of command and control task complexity measurement can be improved.

The invention provides a hybrid access control method and an unmanned flexible ad hoc network system based on a multi-channel access structure. The method comprises the following steps: in an initialization stage, configuring a plurality of service queues and cache spaces thereof; performing synchronous network access processing on each subnetwork accessed to the network; taking a time period and a time slot as units, and performing multi-service queue scheduling by combining a whole-network broadcast time period, a multi-user polling time period and a multi-user competition time period; according to the system, the method is implemented in the layered and clustered elastic ad hoc network through an established multi-channel access structure. According to the invention, a layered and clustered networking architecture and a multi-channel access structure are adopted to realize each cluster frequency packet networking and flexible networking control, and a hybrid access control method is adopted to realize service classification scheduling, so that the problems of limited network scale and capacity bottleneck in the existing ad hoc network are solved, and the service performance of the ad hoc network is improved. And the requirements of large-scale networking, flexible clustering and partition service exchange of unmanned trunking communication are met.

The invention provides a network segment planning method based on an industrial internet platform and related equipment, and the method comprises the steps: carrying out the network planning of the industrial internet platform according to a network scale, and obtaining an address space of the industrial internet platform; performing subnet planning on the address space, and determining a plurality of subnets and an independent network segment corresponding to any subnet; determining a network address of any network access device based on the address space, the subnets, the corresponding independent network segments and the number of the network access devices; configuring a corresponding routing strategy for any subnet, and binding the routing strategy and any independent network segment; configuring a firewall of the industrial internet platform, and determining an access control strategy of the network access equipment; and outputting pre-stored network segment early warning information according to the network state of the Internet platform. According to the invention, the efficiency of carrying out network segment planning on the industrial internet platform can be improved.

The present application relates to the technical field of network security, and particularly relates to a multi-step attack trapping method and system enabled by dynamic deception defense, different types of honeypots are generated according to the resources required by microservices and the relevance between microservices to perceive network attack behaviors by using the honeypots; a security game model for describing the attack and defense confrontation process of the honeynet is constructed according to the network scale and defense requirements, the security game model is represented by using attack and defense participants, the current state of the network environment, the attack and defense action set, the discount factor, the network state transition probability and the attack and defense payoff function; the security game model is optimized and solved by using a reinforcement learning algorithm to obtain the optimal number and position of the honeypots in the spatial dimension, the honeypots are deployed into the network according to the optimal number and position, and the state and position of the honeypots in the network are dynamically adjusted according to a hopping strategy. The present application can effectively induce the attacker to enter a preset line diameter, realize the timely discovery of attack behaviors and improve the network security protection performance.

According to the routing type CGRA fault-tolerant simulation platform, when the simulation platform runs, the instruction register sends an operation code to the PE for configuration, the PE loads a data packet from the data register, and the PE completes corresponding operation and outputs an operation result to the local router or the data register; the local router sends the data to the target PE node through a multi-hop route to complete calculation and output a result; wherein the data packet contains operands and address information. The platform realizes a routing type CGRA interconnection structure model, a user can flexibly configure all PE, network scale, routing algorithm and other parameters, and can read a data packet from any specified PE node and forward the data packet to a target PE through multi-hop routing so as to simulate time delays under different conditions.

The invention provides a mine underground ventilation parameter transmission method and device, and relates to the technical field of data transmission in a mine scenario, and the method comprises the steps: initializing the network scale of a mine underground segmented lane according to a preset time period, so as to determine a data transmission node in the current network scale; calculating the residual energy in the current network scale, the energy consumed by the last round of network transmission and the survival time; determining a cluster head of the current network scale according to the residual energy in the current network scale, the energy consumed by the last round of network transmission and the survival time; according to the current network scale, cluster members corresponding to the cluster heads are selected from the conventional transmission nodes, the ventilation parameters are transmitted to the main roadway under the mine, and the problems that for ultra-large mines and large mines, the existing ventilation system parameter real-time sampling efficiency and updating rate are low, and the sampling space density is insufficient are solved.

The invention discloses a time division multiple access multiplexing method for mesh networking and a wireless ad hoc network communication system, in the method, a network works in a time division mode, the network comprises N nodes, only one or i nodes are appointed for receiving in a certain time slot, and other nodes are appointed for transmitting, each node has the capability of directionally transmitting i beams and directionally receiving j beams, (1) when the network scale is relatively small, that is, N is less than or equal to 8, i is equal to 1, j is equal to N-1, and each node receives simultaneous pilot frequency signals from other N-1 nodes in turn according to time slots; (2) the network scale is medium, namely 8lt; when N is smaller than or equal to 32, i = 1, j = (N-1) / M is taken, M is the number of groups of transmitting nodes, at the moment, a node is designated as a receiving node, other nodes are divided into M groups to serve as the transmitting nodes, each group occupies one time slot, all the nodes in the groups transmit pilot frequency signals to the receiving node at the same time, transmission of the whole network to the first receiving node is completed through M time slots, then the second receiving node is replaced, and the first receiving node and the second receiving node are connected in sequence. And so on, a network sending period is completed through M * N time slots; (3) the network scale is large, namely 32lt; when N is smaller than or equal to 128, i is larger than or equal to 2, j is equal to (N / i-1) / M, the network is divided into i sub-networks, time domain synchronization and frequency domain orthogonality are kept between the sub-networks, and work is carried out in the sub-networks according to the mode in the step (2).

The invention provides a network flexible slicing and dynamic optimization method, system, device and medium, and relates to the field of network function virtualization, and the method comprises the steps: obtaining a resource utilization rate and an energy consumption level of a network in an NFV environment as a resource-energy efficiency parameter, and taking resource-energy efficiency maximization as a target function, carrying out VNF deployment problem modeling to obtain a VNF deployment model; constructing a preference list of VNFs and nodes in a network flexible slice according to the VNF deployment model; a preset matching algorithm is adopted, matching is carried out according to the preference list of the nodes and the VNFs, and each VNF is deployed on the optimal node; and monitoring the load change of the network flexible slice in real time, and dynamically scaling the network scale according to the load change. According to the method, the change of the network load is dynamically sensed, the network scale is flexibly scaled according to the real-time load condition, and meanwhile, the deployment position of the VNF is reasonably arranged, so that efficient utilization of network resources and optimization of energy consumption are realized.

The invention discloses an SDN (Software Defined Network) intelligent delay monitoring system and method, belongs to the technical field of network monitoring, and aims to solve the technical problem that control plane overhead and delay monitoring precision in a delay monitoring method cannot be balanced along with increase of a network scale. Comprising a delay measurement module which is used for obtaining a detection interval from a data storage module, carrying out delay monitoring on a switch and each link of a data plane based on the detection interval, and sending switch time delay, link time delay of each link and CPU overhead in a network to a data conversion module; the data conversion module is used for converting CPU overhead generated by current delay monitoring, switch delay in a network and a ratio of link delay of m links with the highest delay to a detection interval into a state required by the agent module, and sending the state to the data storage module for storage; an action set and two initialized Q tables are arranged in the agent module, and the agent module is used for executing decision learning and state updating.

The system allows real time collection and processing of massive data from many network elements. It has an elastic architecture that scales horizontally to support different network sizes. The system in a uniform data format for downstream consumption. It employs a pub / sub data distribution mechanism that supports multiple concurrent downstream subscribers efficiently in real-time.

The invention discloses an expandable network security risk checking method, which relates to the technical field of network security, and comprises the following steps: establishing a network information collection mechanism, and collecting network information from each node of a target network; establishing a risk feature library, establishing an initialized feature library, storing feature information of common network security threats in the risk feature library in a classified manner, and establishing indexes and classification tags; extracting a network topological graph from the network topological information, and calculating a network scale evaluation value according to the network topological graph; and generating a troubleshooting strategy according to the network scale evaluation value. According to the method, the troubleshooting strategy is flexibly generated according to the network scale evaluation value, the method is suitable for networks of different scales and architectures, when the network scale changes, the troubleshooting strategy can be adjusted in time, the effectiveness of risk troubleshooting is ensured, and the limitation of a traditional method for specific network architecture design is effectively overcome.

The invention provides an asynchronous network search method, system and device for a frequency hopping ad hoc network and a medium. The method comprises the following steps: determining a network scale M of the frequency hopping ad hoc network and a time error N between network nodes; determining a corresponding synchronous frequency point Ftod in combination with the original data key PK and a preset operation rule, and returning to the first N-1 minutes to obtain N synchronous frequency points; uniformly setting N + 1 synchronous time slots in each subframe through the time error N, and selecting a continuous time slot between two synchronous time slots as an asynchronous network detection time slot; and based on the asynchronous network detection time slot, sending and receiving of broadcast messages are carried out by using the synchronous frequency point, and asynchronous network discovery and time synchronization are completed. According to the method, through time error and synchronization frequency point design, efficient network discovery and time synchronization are realized, different scene requirements can be adapted, time delay fluctuation is reduced through a detection and backspacing mechanism, and network real-time performance and stability are improved.

The application provides a model embedding-based radiation source identification method, different modal data are jointly input, an end-to-end multi-modal identification framework is trained, parameter sharing between different modal models is realized, compared with multiple modal corresponding to multiple network identifications, the network scale is obviously reduced, the convergence speed is improved, and in the process of sharing parameters of multiple modes, the network obtains more common information between modes. Meanwhile, after the end-to-end identification framework, a fusion algorithm based on the Bayes theory is provided, compared with using a single mode as the network output, since the output after fusion comes from different modes, the confidence of the result is higher, therefore, the fused output is used as the decision of the radiation source individual identification, the iteration number required during network convergence is reduced, and the effect of optimizing the network performance is achieved.

The application discloses a FastFlood detection method and device based on a Flink stream processing engine, and the method comprises the following steps: collecting traffic data from various data sources in real time by the Flink stream processing engine, and distributing the traffic data to corresponding sliding time windows; the sliding time window allows the window to slide on a time axis, and the change of traffic is captured by setting the window size and the sliding step; in each sliding-out window, statistical analysis is performed on the traffic data; the statistical analysis result is compared with a preset threshold value, and it is judged whether the typical characteristics of the pulse type DDoS attack are presented; if the pulse type DDoS attack is identified, the corresponding protection mechanism is triggered. The method and device can not only cross the limit of the operator-level network scale, realize seamless coverage and efficient data collection, but also accurately extract attack characteristics in a complex and changeable network environment, and build a high-sensitivity real-time detection model.

The present application relates to the technical field of cloud native Kubernetes container, in particular to a method and system for realizing quick switching of calico network mode of multi-CPU architecture, comprising the following steps: parameter setting, configuring Calico to use BGP mode in the cluster, setting calico_network_mode=BGP parameter, Calico will automatically configure a series of parameters to realize efficient network routing distribution and communication; beneficial effects are that: the method and system for realizing quick switching of calico network mode of multi-CPU architecture based on calico network realize quick switching of BGP, BGP(RR), IPIP and CrossSubnet four network modes. Different network modes can be selected according to network scale and complexity, and network strategy can be flexibly selected. Because IPIP mode has one more layer of packet and unpack than BGP mode, network overhead and delay will be increased, therefore network transmission performance of IPIP mode is lower than that of pure BGP mode, in order to realize flexible switching of same subnet and cross subnet, the functions of BGP, BGP(RR), IPIP and CrossSubnet switching are increased.

The invention relates to a networking control method and device, equipment, a storage medium and a product. A current popularity threshold value, a target networking magnitude and a current actual networking magnitude corresponding to a live broadcast stream are obtained, the popularity threshold value is used for determining whether to perform networking on the live broadcast stream based on the popularity of the live broadcast stream, and the networking magnitude is used for representing the carrying capacity of a constructed network on the live broadcast stream. And further, under the condition that the target networking magnitude and the current actual networking magnitude meet a preset adjustment condition, the current heat threshold is adjusted, a target heat threshold is generated, and the target heat threshold is used for regulating and controlling the networking magnitude of the networking for processing the live broadcast stream. Compared with the prior art, the embodiment of the invention has the advantages that the heat threshold can be adjusted in real time, the networking structure can be optimized in real time, the situation that the networking magnitude is insufficient or excessive is reduced, the networking magnitude is kept stable, the cost income is not unbalanced, and the income is maximized.

This invention provides a method for dynamic resource allocation in heterogeneous networks based on graph attention. The method involves selecting several access points for each user in the heterogeneous network according to a first parameter; constructing a directed graph for parallel transmission in the heterogeneous network based on each user and all access points selected by each user, and defining the feature vector of each node in the directed graph; weighting and aggregating the feature vectors of each node in a single-layer graph attention layer of the graph attention network using a multi-head graph attention mechanism to obtain the first node feature; iteratively updating the first node feature in multiple layers of the graph attention network to obtain resource allocation coefficients; and dynamically allocating network resources based on these resource allocation coefficients. Compared to traditional optimization methods and conventional DNNs, this method achieves flexible adaptation to different network scales and user numbers, improving the service quality and resource utilization efficiency of parallel transmission in 6G multi-band heterogeneous networks.

The invention provides a strict priority queue scheduling method oriented to SD-WAN and differentiated services, and belongs to the technical field of differentiated services of software defined wide area networks, and the method comprises the steps: obtaining the time delay, throughput and related queue information of each service flow in a network based on a flow INT technology; based on a graph convolution deep reinforcement learning algorithm, reasonable priorities are automatically allocated to different services according to maximum time delay and minimum throughput requirements of various services so as to guide a scheduling process of a strict priority queue; a dynamic queue mapping adaptive algorithm is adopted, more priorities are flexibly mapped to less strict priority queues, and the priority space is expanded. According to the method, the high-priority service requirement is better ensured, and the priority configuration can be automatically generated based on the reinforcement learning technology only by giving out the visual service requirement; the communication overhead of the control plane is small, the exponential level is not increased along with the increase of the network scale, and a plurality of controllers can obtain the whole network information only by exchanging information of adjacent nodes.

The invention relates to a multi-level hierarchical networking method and device based on an openharmony soft bus. According to the embodiment of the invention, effective expansion of a network scale is realized through a multi-level hierarchical architecture; the limitation of the connection number of the original openharmony soft bus is applied to regional internal management, the first central node of each region still follows the limitation, but a plurality of regions can be supported through hierarchical management, and larger-scale network deployment can be realized by increasing the number of hierarchies; and a solution with good expansibility is provided for large-scale application of the Internet of Things. Moreover, the process of finding the other leaf node by any leaf node comprises the following steps: firstly, querying a local cache, if the local cache does not exist, querying the cache of the first central node of the corresponding network region, and if the other leaf node is still not found, the other leaf node may be a cross-region leaf node, and the other leaf node may be a cross-region leaf node. The overall stability of the network can be improved while the query response time is shortened.

The application discloses an implementation method and device for realizing localization of file transmission intelligent support, and relates to the technical field of artificial intelligence. The method comprises the following steps: determining the network scale of an AI model according to the hardware constraints of a to-be-deployed system; selecting an AI model smaller than the network scale, and preparing a specific data set related to file transmission; training the AI model by taking the specific data set related to file transmission as a data sample, to obtain a basic model; fine-tuning a discriminant model and a plurality of expert models from the basic model through fine-tuning technology, the discriminant model being used for matching an input question to a corresponding expert model, and the expert model being used for obtaining a result based on the input question; and publishing the discriminant model, the plurality of expert models and file transmission software to the to-be-deployed system. The embodiments provided by the application are applied to servers with hardware condition restrictions and network access restrictions, realize a faster reasoning speed, and improve the intelligence of file transmission.