435 results about "Computer network technology" patented technology

The invention relates to the technical field of computer networks, in particular to a monitoring method and system based on industrial computer network fault data, and the method comprises the steps: collecting the heterogeneous fault data of each layer of equipment in an industrial control network in real time through distributed probe nodes; performing multi-modal normalization processing on the original fault data; constructing a fault knowledge graph, and dynamically associating an equipment topological relation, a historical fault mode and a current production task context; fault root cause analysis is carried out by adopting a hybrid inference engine, and a potential fault propagation path is predicted in combination with a rule-based expert system and an LSTM-GNN joint model; generating a grading alarm strategy, triggering a self-adaptive fault-tolerant mechanism, and dynamically adjusting network bandwidth allocation or starting redundant equipment switching according to the fault grade; according to the invention, by constructing the industrial knowledge graph and the adaptive fault-tolerant mechanism, efficient, accurate and interpretable fault diagnosis and prediction are realized, and the reliability and operation and maintenance efficiency of an industrial network are improved.

The invention provides a private domain live broadcast bandwidth resource allocation and routing method and system based on reinforcement learning, and relates to the technical field of computer networks, and the method comprises the steps: collecting real-time data such as the number of users, geographical distribution, terminal types, content types, network delay, packet loss rate, bandwidth utilization rate and the like in a live broadcast room, and inputting the real-time data into a pre-trained reinforcement learning model; the model is based on a state space, features are extracted by using a deep neural network, bandwidth resource constraints are combined, and a bandwidth allocation and routing strategy is generated by adopting a strategy gradient algorithm; and according to the strategy, the software defined network controller adjusts bandwidth allocation parameters and routing table configuration in real time to realize differentiated bandwidth allocation and path optimization, establishes nearby access edge nodes based on user geographical distribution, and dynamically adjusts the path during congestion.

The invention relates to a distributed large two-layer network intelligent routing method and system based on edge cloud nodes, and belongs to the technical field of computer networks. Aiming at the problems of slow routing decision response and low fault recovery efficiency of the existing network in a dynamic environment, the invention provides a method for periodically collecting link bandwidth utilization rate, transmission delay and other state information through an edge cloud node, uploading the state information to a central cloud platform to generate a global routing strategy and issuing the global routing strategy to the edge node, and triggering fault switching in combination with local dynamic threshold monitoring. According to the technical scheme, bidirectional communication between edge nodes and a central platform, a neural network model of spatial-temporal feature fusion and a path priority generation mechanism of multi-objective optimization are included. The method and the system are suitable for a large-scale distributed network environment, and network resource utilization rate and service continuity can be improved.

The invention discloses a network data intelligent tool system and method based on a model context protocol MCP, and relates to the technical field of computer networks. The system comprises an AI analysis main body, an MCP Pcap tool engine, context management, a Pcap data source, various MCP Pcap tools, a Pcap tool gateway interface, a Pcap tool interface and a data packet interface. The invention provides an interaction mechanism of direct embedding and bypass data forwarding in tool calling. According to the method, direct embedded transmission of small-size data in tool calling is supported, separation of data transmission and instruction calling is achieved, the technical bottleneck that large-size Pcap data cannot be efficiently exchanged through a text channel is effectively overcome, efficient processing of the AI model on network packet capture data is achieved, and the data transmission efficiency is improved. And the efficiency and the automation degree of large-scale network traffic analysis are improved.

The invention discloses a scheduling system of a content distribution network based on edge computing, and relates to the technical field of computer networks. An edge resource sensing module; an NLP semantic analysis module; reinforcing a learning scheduling engine; a semantic and resource linkage module; and a federation collaboration module. According to the scheduling system of the content distribution network based on edge computing, semantic understanding is carried out on a request of a user to analyze a deep intention of the user, edge node multi-dimensional state sensing data and a semantic label vector are integrated, a scheduling action is generated based on a node state and the user intention, and the scheduling effect is improved. Therefore, each edge node is fully utilized while user requirements are met, the edge nodes have caching, computing and scheduling capabilities, the limitation of surface feature matching of a traditional CDN is broken through, technical upgrading from traditional file type recognition to intention understanding and from a fixed rule to dynamic intelligence is realized, and finally, the resource efficiency and service quality of the CDN are improved.

The invention discloses a pre-request optimization method for an embedded H5 page of a mobile terminal application program and a storage medium. The invention relates to the technical field of computer networks. And carrying out system environment detection, and determining whether a network state, equipment resources, a storage space and the like meet preloading conditions or not. If yes, a preloading strategy configuration file is loaded, and the file comprises the preloading resource list, the priority, the cache rule and the timeout time. And constructing a preloading task queue according to the configuration strategy. In the task queue, the resources with high priorities are loaded preferentially. According to the method, key resources are loaded in advance, so that the waiting time of a user is shortened, and particularly, the first screen content is quickly displayed, so that the application feels smoother and responds immediately. Even under the condition that the network is unstable, instant availability of the basic content can be guaranteed by means of the local cache, and the bad experience of white screen or long-time loading is avoided.

The invention relates to the technical field of integrated circuits and computer networks, and particularly discloses a transmission control and intelligent scheduling system for an integrated chip, and the system sets a dual-mode decision and dynamic switching mechanism for each routing node. Calculating dynamic characteristic parameters including an instantaneous value, a first-order trend and a second-order acceleration; when the parameter is matched with a pre-stored abnormal feature set and the load exceeds a threshold value, the node is immediately atomized and switched to a predefined security scheduling strategy loaded from a shared storage area, and otherwise, the node generates a scheduling decision according to self-adaptive decision logic continuously optimized based on historical performance feedback; all the nodes carry out data packet forwarding control according to the current execution strategy; and the system also periodically realizes federated global knowledge evolution according to the quality evaluation result of the self-adaptive decision of each node.

The invention relates to the technical field of computer networks, and discloses a method for locating reasons for network dial test quality index abnormity, which comprises the following steps of: multi-source data acquisition and network topology modeling: generating state information of network equipment and links by acquiring performance data of each equipment and flow data of the links in a network, and establishing a network topology model; establishing a network topological graph model; shortest path calculation and abnormal path identification based on the graph theory: calculating a shortest path from source equipment to target equipment by using a shortest path algorithm in the graph theory, and identifying abnormal links and equipment in the path; and load evaluation and bottleneck analysis based on an information theory. Through combination of multi-source data acquisition, graph theory optimization, information theory evaluation, game theory resource allocation, deep reinforcement learning and multi-target optimization, network paths and loads are dynamically adjusted, abnormal sources are accurately positioned, and network performance, stability and adaptive capacity are improved.

The invention discloses a website map crawler method and device based on browser rendering, and relates to the computer network technology. The method comprises the steps that a current page of a target website is rendered through a browser rendering engine; after the page rendering is finished, simulating an interactive behavior of a user on the page, monitoring a DOM change event occurring in the page, and capturing a page dynamic path triggered by the interactive behavior of the user; constructing all captured page dynamic paths into an extensible path set of the current page, performing comprehensive priority scoring on each path to be accessed in the extensible path set, performing dynamic sorting on the path priorities according to a scoring result, and taking the path with the high priority as an access entry of next page rendering; and repeating the steps until a task termination condition is met. According to the invention, a set of website subpath capturing system with high coverage rate, high precision and high controllability is constructed.

The invention discloses a network data integration analysis system and method based on a model context protocol MCP, and relates to the technical field of computer networks. The system comprises an MCP-LSP adaptation layer, a network analysis language server, an IDE plug-in, a remote cooperation management module, an MCP analysis engine, an LSP client and an IDE UI component. According to the invention, deep fusion of the network protocol analysis capability and the integrated development environment is realized; by constructing an MCP-LSP adaptation layer, a network analysis language server can convert a semantic analysis result of an MCP analysis engine into an LSP standard message format, and standardized services of functions such as protocol analysis, session state and anomaly detection are realized; the working efficiency of a developer is improved by the IDE plug-in; the remote cooperation management module realizes synchronization and sharing of session states, improves integration, expandability and cooperation efficiency of network analysis, and is suitable for diversified requirements of modern software development teams.

The invention provides a time service precision evaluation method and system for a network time server, and relates to the technical field of computer networks, and the method comprises the steps: 1, collecting the operation data of the network time server in a dynamic network environment in real time, including core index data and auxiliary index data, carrying out the normalization of the core index data, and carrying out the calculation of the auxiliary index data; generating a standardized core index data set; step 2, dynamically integrating the standardized core index data set according to the fluctuation characteristics and relevance of each core index to generate a comprehensive core index characterization value; and step 3, in combination with auxiliary index data, carrying out dynamic compensation correction on the comprehensive core index representation value, and generating a comprehensive time service precision evaluation value. According to the invention, comprehensive, accurate and dynamic evaluation and abnormity diagnosis of the time service precision of the network time server are realized, and the network time service quality and the operation and maintenance efficiency are effectively improved.

The invention relates to the technical field of computer networks, in particular to a network risk processing method and system based on a graph. The method comprises the following steps: performing network entity model construction on a target network to obtain a target network entity model; performing network entity graph modeling on the target network based on the target network entity model to obtain a network entity relationship graph; performing dynamic graph updating on the network entity relation graph to obtain an updated network entity relation graph; carrying out risk propagation source node determination on the updated network entity relation graph to obtain a risk propagation source node set; and performing global risk assessment on the target network according to the risk propagation source node set based on the updated network entity relationship graph to obtain a network global risk assessment result. According to the invention, the efficiency and accuracy of network risk assessment are improved.

The invention relates to a comprehensive management process design system and method based on AI code interpretation, and belongs to the technical field of computer networks. The system comprises a process design console, an AI code interpreter and a business logic execution framework, the flow design console is used for providing a Web interface, so that a user can design and manage a flow in an interactive form, including interactive natural language programming, real-time feedback and preview, flow deployment and management, and historical record and version control; the AI code interpreter is used for converting business requirements and processes expressed by a user in a natural language form into executable codes, and comprises a natural language understanding sub-module, a code generation sub-module and a security verification sub-module; the business logic execution framework comprises a code execution sub-module, a data access sub-module and an exception handling sub-module. According to the method, the technical threshold of process design is lowered, personnel can easily master, and organic combination of intelligence and humanization is achieved.

The invention provides a user attribution method and system capable of meeting various configurations and conversions, and belongs to the technical field of computer networks, and the method comprises the following steps: according to a unified identity mapping table, ordering behavior records on each device according to a time sequence, integrating the behavior records into a continuous behavior path data set, and determining a full-link view of a user conversion path; carrying out fragmentation storage and parallel analysis by adopting a distributed computing framework through the behavior path data set, and optimizing resource allocation to obtain a real-time processed user conversion path result set; according to a user conversion path result set processed in real time, a cache mechanism is constructed to store high-frequency access path data, and if a new query request is received, data is extracted from a cache preferentially, and a quick-response path analysis result is determined; through a path analysis result, an encryption technology is applied to protect a user identity identifier and behavior data, and in combination with an access control strategy, a safe and compliant attribution analysis data set is obtained. According to the method, the problem of cross-device user behavior tracking is solved, a full-link user conversion path view is provided, the path analysis requirement can be quickly responded, and data support is provided for precise marketing decision making.

The invention relates to the technical field of computer networks, in particular to a bamboo-based composite material environment monitoring unmanned aerial vehicle and a networking method thereof, and the method comprises the following steps: each unmanned aerial vehicle obtains a residual electric quantity value and a three-dimensional coordinate position, actively broadcasts an identity beacon to the surrounding, and simultaneously monitors beacon signals from other unmanned aerial vehicles; for each received beacon signal, a transmitting node identity is extracted and a received signal power value is recorded, and an average signal strength indication value is calculated by continuously receiving a plurality of signal samples. According to the invention, the unmanned aerial vehicle actively broadcasts identity beacons and monitors surrounding beacon signals, masters neighbor node positions, energy levels and communication quality, and further completes comprehensive evaluation of initial network topology and node states; based on intelligent analysis of environmental data, pollution diffusion boundary data with high information value are distinguished, important information is ensured to be transmitted preferentially, and energy consumption of nodes is effectively balanced by calculating the relationship between the information value and energy consumption.

The invention discloses a network resource loading method and system, electronic equipment and a storage medium. The method relates to the technical field of computer networks, is applied to a server, and can comprise the steps that a page access request of a client side is obtained, and the page access request is used for requesting the server to access a page; in response to the page access request, identification information is identified from the page access request, and the identification information is used for representing the access authority of the client to the content distribution network; at least one target page matched with the identification information and network resources matched with the identification information are determined, the page type of the target page corresponds to the permission corresponding to the identification information, and the source of the network resources corresponds to the permission corresponding to the identification information; and returning the target page to the client, and loading the network resources to the target page. The technical problem of low loading efficiency of network resources is solved.

The invention provides a network transmission method and device based on non-perceptual computing, a storage medium and electronic equipment, and relates to the technical field of computer networks, the method comprises the following steps: receiving a transmission request sent by user equipment, and predicting a network resource demand of the user equipment according to a network bandwidth demand and a state parameter of the user equipment; based on the load and delay of the node server, screening out a target server meeting the network resource requirement from the server cluster, and establishing a target transmission channel between the user equipment and the target server; and in the transmission process, the transmission rate is adjusted based on the trigger type transmission control strategy until the data transmission is completed. According to the network transmission method and device based on non-perceptual calculation, the storage medium and the electronic equipment provided by the invention, efficient and reliable data transmission can be realized on the premise of not depending on a user to know the state of an underlying server, and the method and the device have important significance for improving the network service quality and the user experience.

The invention discloses a network protocol analysis system based on a model context protocol MCP, and relates to the technical field of computer networks. The system comprises an MCP module, a network analysis module, a data source module, a context module, an MCP interface, a data source interface and a network analysis interface. An MCP module, a network analysis module, a data source module and a context module. All the modules work cooperatively through standardized interfaces to form a unified network protocol analysis platform. The system supports a context-driven tool calling process and a double-channel execution structure, control logic and data transmission are decoupled, and efficiency and expandability in a large-size Pcap data processing scene are improved. Through a unified semantic modeling and context state tracking mechanism, through analysis of a multi-layer protocol, multi-round traceable execution of a task and structured expression of an analysis result are realized, and infrastructure support is provided for a modularized, pluggable and reusable intelligent network protocol analysis platform.

The invention provides a large-scale concurrent network request management method based on a computing power host management platform, belongs to the technical field of computer networks, and aims to reduce the request pressure on a rear-end host through technologies such as merging same or similar requests, allocating priorities for the requests, maintaining request queues and controlling the request sending frequency. The utilization efficiency of resources is improved, so that the system performance and the user experience are improved.

The invention relates to the technical field of computer networks, and discloses a bandwidth allocation method and device, computer equipment, a storage medium and a program product, and the method comprises the steps: determining the priority of a to-be-transmitted data packet based on the type of the to-be-transmitted data packet; based on the priority of the to-be-transmitted data packet, determining the priority of the flow formed by the to-be-transmitted data packet; pre-allocating bandwidths for the flows with different priorities; for the flow of any priority, dividing a first shared bandwidth from the bandwidths pre-allocated for the flow of the priority, dividing a second shared bandwidth from the bandwidths pre-allocated for the flow of the priority lower than the priority, and generating a shared bandwidth based on the first shared bandwidth and the second shared bandwidth; and if the bandwidth occupied by the flow of the priority reaches a first bandwidth threshold value, allocating the shared bandwidth to the flow of the priority, and performing flow transmission by utilizing the bandwidth pre-allocated for the flow of the priority and the shared bandwidth. According to the invention, the data transmission reliability of the service system is improved.

The invention relates to a financial case fund flow traceability analysis method, and belongs to the technical field of computer networks. According to the method, the social network analysis technology and the graph neural network technology are combined, and the advantages of the social network analysis technology and the graph neural network technology are comprehensively utilized to analyze and track the fund flow direction in the financial transaction network. According to social network analysis, key nodes and group structures in a transaction network are identified by calculating node centrality and community discovery; the graph neural network analysis further extracts complex transaction features and modes through a deep learning model, and identifies abnormal transaction behaviors. Besides, advanced graph neural network models such as a graph convolutional network and a graph attention network are utilized, parallel computing and distributed training technologies are combined, the model training process is efficient and has good expansibility, and the method adapts to processing requirements of large-scale financial transaction data.

The invention relates to the technical field of computer network technologies, in particular to a network motion capture platform based on synchronization equipment, which comprises an external expansion equipment group and a network switch, and further comprises the synchronization equipment connected with the external expansion equipment group and the network switch, the external expansion device group comprises at least one external expansion device, and each external expansion device is connected with the synchronization device by adopting a corresponding synchronization signal; according to the scheme of the embodiment of the invention, different software synchronization interfaces can be adopted by the four devices, so that the collected information can be synchronized in respective subsystems, and the synchronization efficiency of the four devices is improved. Therefore, the requirement for information data synchronization of the network motion capture camera and other equipment such as audio and video equipment, an active mark point, a dynamometer and a myoelectric instrument is met, and the synchronization precision and the application range of the whole system are improved.

The invention relates to the technical field of computer networks, in particular to a shortest routing and deadlock avoiding method and device for a double-layer polygon topology, and the method comprises the steps: determining the routing type of the topology; xOR processing is carried out on the mark low bits of the source node and the target node, and a candidate node corresponding to the shortest path of the source node is determined; determining an available state of the anti-deadlock node, if the available state is idle, determining routing bypass information, and sending the routing bypass information to the source node; and determining an available state of the common node, and generating a route selection vector of the candidate node, so that the source node determines a next-hop node according to the route selection vector, sends the data packet to the next-hop node, and takes the next-hop node as a new source node. According to the method provided by the embodiment of the invention, the number of the shortest paths is expanded into all theoretical shortest paths, so that the number of the shortest paths among the nodes in the computer network topology structure is increased, the system transmission efficiency and the data throughput are improved, and meanwhile, deadlock is avoided.

The invention relates to the technical field of computer networks, in particular to an intelligent agent system and method based on the MCP technology, and the system comprises an MCP intermediate layer protocol engine, an intelligent scheduling module, a channel management system, a security enhancement mechanism and an edge node self-learning mechanism. The method has the beneficial effects that support for various communication protocols (such as HTTP, MQTT, gRPC and the like) is realized through the MCP technology. Through the protocol adapter module, the system can automatically identify and load different protocol adapters, and parallel work of multiple protocols can be supported without manual intervention. The multi-protocol support greatly improves the flexibility of the system, so that the system can be seamlessly connected with equipment of different manufacturers and standards, and the requirements of complex and diverse application scenes are met.

The invention relates to the technical field of computer networks, and discloses a link state sensing neural network model training flow path selection method, which comprises the following steps: collecting path information between each pair of hosts by sending a detection data packet carrying an in-band network telemetry field; calculating a priority index based on the number of sent bytes of the training task, wherein the priority index is determined by the proportion of the number of sent bytes of the training task to the total number of bytes needing to be sent and the number of sent bytes; a greedy algorithm is adopted, the training tasks serve as current training tasks according to priority indexes from high to low, paths with the lowest congestion degree are preferentially allocated to the current training tasks, and if the paths with the lowest congestion degree are occupied, suboptimal paths are allocated to the current training tasks; the congestion degree of the path is evaluated through the link utilization rate of each link in the path; according to the method, the link state and the task characteristics are monitored in real time, the path selection strategy is dynamically adjusted, and the communication efficiency of distributed neural network model training is remarkably improved.

The invention relates to the technical field of computer networks, in particular to an implementation method and system for an RDMA network card request queue, and the method comprises the steps: checking whether a residual space exists in an RDMA Cache module or not when a write request is received; if yes, writing the writing information of the writing request into an RDMA Cache module, updating a free bit, and recording a queue pair number and an unfinished pointer; if not, writing the writing information of the writing request into a host memory module; when a read request is received, checking whether the queue pair number and the unfinished pointer carried by the read request are matched with historical records in the RDMA Cache module or not; if yes, reading from the RDMA Cache module; and if not, reading from the host memory module. According to the invention, multiple QPs in the RDMA network card share the internal resources of the Cache, the resource consumption is reduced, and the utilization rate of the cache is improved.

The invention relates to the technical field of computer networks, and discloses a communication method and device for a computing node, equipment and a storage medium. The method is applied to a computing node, the computing node comprises a virtual switch and a physical network card, a plurality of virtual network interfaces are created in the virtual switch, the plurality of virtual network interfaces are in one-to-one correspondence with a plurality of service networks, and the physical network card is connected with at least one other node. The method comprises the following steps: receiving a target data message of a target service network through a target virtual network interface of a virtual switch; and sending the target data message to a corresponding node in the at least one other node through the physical network card. A plurality of virtual network interfaces are created in the virtual switch, and one virtual network interface corresponds to one service network, so that deployment of a plurality of service networks in the virtual switch is realized, network multiplexing in the virtual switch is realized, and the problem that physical network card resources of computing nodes are insufficient is solved. And a plurality of virtualized networks cannot be provided.

The invention discloses a data packet processing method and device, equipment, a storage medium and a product. The invention relates to the technical field of computer networks. The method comprises the steps of coding features of data packets through a pre-trained data packet classification model and determining priorities; coding the numerical characteristics and / or type characteristics of the network traffic through a pre-trained traffic prediction model, and predicting the trend of the network traffic; adjusting the priority and queue length of each data packet according to the prediction result; and in each scheduling, according to the queue length, the priorities of the data packets in the queue and the waiting time, selecting one data packet in the queue, and sending the selected data packet to the network card for processing. The artificial intelligence algorithm is applied to data packet classification and network flow trend prediction, and the data packets in the queue are scheduled according to the priorities based on the data packet classification result and the network flow trend prediction result, so that the network flow change trend can be flexibly adapted while the service processing efficiency of different priorities is ensured.

The invention belongs to the technical field of computer networks, and provides a method for finding lawyers online. In order to solve the problem that a traditional lawyer finding mode is inaccurate in matching, case description and files are received through a user input module, and preprocessing, semantic understanding and key information extraction are carried out; the dialogue interaction module obtains legal service demand information through multiple rounds of interaction; the law office-lawyer-judgment document database stores lawyer agent historical case information; the lawyer recommendation module combines various methods to calculate similarity scores, screens out judgment documents with good case results, recommends lawyers, and displays information such as lawyer agent fees; and the charging mode management module realizes the unified setting of the charging function. According to the method, various artificial intelligence technologies are comprehensively applied, efficient and accurate lawyer recommendation service is provided for the user, the matching efficiency is improved, and the transparency and reliability of the recommendation process are enhanced.

The invention discloses an HTTP (Hyper Text Transport Protocol) text restoration method based on DPDK (Data Platform Development Kit), which relates to the technical field of computer networks, and adopts a multi-process decoupling architecture to respectively run processes such as flow collection and protocol analysis, fragmentation recombination and text restoration, formatted message splicing, text restoration timeout waiting and the like in independent CPU (Central Processing Unit) cores; and efficient and lock-free data transmission is carried out by using a ring mechanism of the DPDK. Different from a traditional memory splicing scheme, the data offset is calculated based on the TCP serial number, the load content is directly written into the corresponding position of the file, the problems of message disorder, packet loss, retransmission and the like are effectively solved, an atomic renaming mechanism from the file ID1 (intermediate state) to the file ID2 (complete state) is adopted, and accurate migration of the file state is ensured. Besides, the invention innovatively provides a bidirectional asynchronous scheduling mechanism based on data export and text restoration state monitoring, so that the data export process can continuously keep high throughput, and the overall processing capacity of the system is ensured.