265 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 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 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 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 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 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 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, 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 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.

The invention discloses a network protocol integrated development environment system based on a model context protocol MCP, and relates to the technical field of computer networks. The system comprises an IDE plug-in structure, a protocol analysis engine interface, a context awareness editing module, a user interaction interface and a collaborative view module. According to the method, a development tool is embedded through an IDE plug-in structure, a protocol analysis interface is called to carry out protocol structure identification and semantic modeling, and intelligent suggestions and semantic verification are provided in combination with context information in the protocol editing process. A user can carry out protocol structure editing and visual control through the interactive interface, and different roles can collaboratively carry out protocol design and verification tasks through the collaboration view module. The whole process forms a closed-loop mechanism from protocol modeling and semantic editing to context awareness suggestion, and high-intelligence and high-integration protocol development experience is achieved. The system significantly improves the efficiency and accuracy of protocol development, and is especially suitable for rapid prototype design and standardized development of complex network protocols.

The invention provides an intelligent prediction and dynamic optimization distribution method for computer network traffic, which relates to the technical field of computer networks and comprises the following steps of: acquiring and preprocessing network traffic data; constructing a multi-model fusion network traffic prediction model; generating a dynamic optimization distribution strategy based on a prediction result; and allocation strategy execution and dynamic feedback adjustment: executing the allocation strategy through the SDN controller, monitoring the network state in real time and feeding back the network state. A multi-model fusion strategy is adopted, the time sequence capturing capability of the improved LSTM, the feature fitting capability of the XGBoost and the long dependence processing capability of the time sequence attention Transform are combined, and the weight is optimized through PSO, so that compared with a single model, the prediction error is reduced, the burst flow and periodic flow features can be accurately captured, and the problem that in the flow distribution link, the flow distribution efficiency is greatly improved is solved. Most methods only aim at maximizing the bandwidth utilization rate, and ignore the problem of QoS demand difference of different services.

The invention provides an application proxy routing forwarding method and system in a cluster environment, and relates to the technical field of computer networks, and the method comprises the steps: obtaining an available resource manager list through employing a double-layer adaptive filtering detection mechanism, and carrying out the routing forwarding of an application program based on an application program identifier and a target sub-cluster identifier; and constructing a multi-layer tree index structure, selecting an optimal resource manager by applying a dynamic path planning algorithm, and generating a redirection URL through annular hash space mapping and virtual node positioning. According to the invention, the system response speed is improved, the routing forwarding efficiency is enhanced, the load balancing capability is optimized, and the stability and reliability of application access in a cluster environment are improved.

The invention belongs to the technical field of computer networks, and discloses a resource-constrained network equipment-oriented double-layer GRU lightweight real-time network anomaly detection method, which comprises the following steps of: constructing an anomaly detection model and training, deploying the trained model to resource-constrained network equipment, the method comprises the following steps: acquiring a system log generated when network flow generated by each application server node flows through in real time, performing data preprocessing on the acquired system log to obtain log semantic vectors, and forming a window sequence by the continuous log semantic vectors to obtain an abnormal probability value; and comparing the abnormal probability value with a set threshold value, and directly outputting an output detection result at an equipment end. According to the method, complexity of entity information is eliminated, time dependence in a time sequence is enhanced, simplification is carried out, a high anomaly detection recall rate is achieved under the condition that low calculation overhead is kept, the risk of missing detection is reduced, and cascade faults caused by the fact that anomalies are not found in time are avoided.

The invention relates to the technical field of computer networks, in particular to a data security access method based on a service side. A primary access request sent by a client is converted into a secondary access request through a public network server, the secondary access request is sent to a message queue module, the message queue module sends the secondary access request to a sandbox module for compliance inspection, and if the compliance inspection is passed, the sandbox module sends the secondary access request to the message queue module; if yes, the sandbox module sends the second-level access request to the mirror image server, the mirror image server generates a feedback response according to the received second-level access request and sends the feedback response to the message queue module, and the message queue module sends the received feedback response to the public network server; the public network server sends the received feedback response back to the client; according to the invention, the problems of poor security, large resource consumption and the like in the prior art can be effectively solved.

The invention relates to a deterministic resource management method in a hierarchical computing power network architecture, and belongs to the technical field of computer networks. According to the invention, a hierarchical and domain-divided deterministic computing power network architecture based on threshold alarm and a deterministic resource management method thereof are constructed; the whole network is provided with a first-level network controller and is divided into different second-level network domains, each second-level domain is provided with a second-level network controller, and each second-level domain provides deterministic service; reinforcement learning agents are arranged in the first-level network controller and the second-level network controller, and the first-level agent obtains routing resource utilization rates, alarm states and current service information under all service flow categories in current second-level domains and decides to refuse to accept the service or select an optimal deterministic routing path for the service; and the secondary intelligent agent adjusts the service resource configuration proportion of the secondary intelligent agent and feeds back whether the service is successfully accepted or not. According to the invention, the utilization rate of network resources and the service acceptance rate are improved, and the occupation of computing resources and transmission resources during service acceptance is reduced.

The invention relates to the technical field of computer networks, and discloses a distributed model training-oriented congestion control method and device, and a medium. The method comprises the following steps: when a cooperative switch receives a local gradient data packet, updating the total communication traffic required to be transmitted by each training task in a task total communication traffic table according to a corresponding field; when the cooperative switch receives the global gradient data packet, the residual communication traffic of each training task in the task total communication traffic table is updated according to the corresponding field, and the residual communication traffic is broadcasted to each working node, so that the working node updates the residual communication traffic of each training task in the residual communication traffic table; when network congestion is detected, calculating a real-time proportion, and dynamically adjusting a sending rate of a working node corresponding to each training task through an increasing function; a working node senses the existence of other training tasks, the residual communication traffic of the other training tasks in the communication stage of the current iteration round is obtained, and the training task with less residual communication traffic obtains a larger bandwidth, so that the communication stage staggering is realized, and the link utilization rate is improved.

The invention discloses a cross-network domain HTTP proxy method and device based on a message queue and a storage medium, and the method comprises the steps: serializing an HTTP request of a client into a request message in a ProtoBuf format through a local proxy server, and transmitting the request message to a message queue system, so that the message queue system forwards the request message to a remote proxy server; the remote proxy server deserializes a request message into an HTTP request and sends the HTTP request to the server, and then serializes an HTTP response returned by the server into a response message in a ProtoBuf format and sends the response message to the message queue system, so that the message queue system forwards the response message to the local proxy server; and deserializing the response message into an HTTP response through the local proxy service and returning the HTTP response to the client. The method improves the efficiency and reliability of cross-network domain communication, and can be widely applied to the technical field of computer networks.

The invention relates to the technical field of computer networks, and discloses a DPDK-based high-speed data isolation method, which comprises the following steps of: S1, directly taking over a data packet transceiving function of a network card through a DPDK driver, bypassing a kernel protocol stack of an operating system, and establishing a user mode data channel; s2, based on a multi-core CPU architecture, distributing the received data packets to independent processing cores according to a preset rule, and binding each processing core to an exclusive memory pool to realize physical-level data isolation; and S3, directly transmitting the isolated data to a target application module through a zero copy technology in the user mode, and verifying the data integrity in real time through a hardware verification module. According to the method, the network card is directly taken over through the DPDK driver, the user state data channel is established, an operating system kernel protocol stack is bypassed, the zero copy technology is combined, data does not need to be copied in the whole process from receiving, processing to transmission, the end-to-end delay is reduced to 50 microseconds or below, and the method is suitable for a high throughput scene.

The invention discloses a distributed node communication transmission system based on a local area network, which relates to the technical field of computer networks and comprises a monitoring center connected with a node management module, a security verification module, a data transmission module and a load balancing module. The method comprises the steps of registering node equipment through an MAC address and an IP address, constructing a node equipment fingerprint parameter database and a node topological graph, evaluating the credibility of the node equipment, selecting whether to issue a digital certificate according to a credibility evaluation result, constructing a communication delay matrix and a communication path weight matrix for the node equipment, and calculating an optimal communication path. According to the method, the optimal communication path is automatically kept, the balance degree of the whole network is calculated in real time through the node load index, the dynamic adjustment of the communication delay matrix is triggered, and the load balance of the whole network is maintained. And the transmission efficiency and stability of the local area network are effectively improved.

The present invention relates to a distributed large-scale Layer 2 network intelligent routing method and system based on edge cloud nodes, and belongs to the field of computer network technology. In view of the problems of slow response to routing decisions and low fault recovery efficiency in existing networks under dynamic environments, it is proposed to periodically collect link bandwidth utilization, transmission delay and other status information through edge cloud nodes, upload them to the central cloud platform to generate a global routing strategy and send it down to the edge nodes, and trigger fault switching in combination with local dynamic threshold monitoring. The technical solution includes two-way communication between edge nodes and the central platform, a neural network model for spatiotemporal feature fusion, and a multi-objective optimized path priority generation mechanism. The present method and system are suitable for large-scale distributed network environments and can improve network resource utilization and business continuity.

The invention relates to the technical field of computer networks, in particular to a wireless terminal roaming method and device based on a PON network, computer equipment and a storage medium. In addition, the wireless terminal roaming method based on the PON network can also be applied to fiber to room (FTTR), enterprise level fiber to room (FTTR-B) and broadband fusion terminal products. The method comprises the following steps: performing received signal strength scanning in response to a received signal strength scanning request from a current access point to obtain a scanning received signal strength indication value of the access point, obtaining a first actual received signal strength indication value for data transmission with the current access point, and determining a scanning compensation value according to the difference between the two values. Further correcting the scanning received signal strength indication values of other access points; the first actual received signal strength indication value and the scanning received signal strength indication correction values of the other access points are used for the current access point to determine a target access point to which the wireless terminal needs to be switched.

This application provides a session persistence method and related apparatus, relating to the field of computer network technology. It includes: after determining that the session request sent by the client carries a gateway session identifier and that the target service gateway caches a session mapping table, determining the target service node in the monolithic application cluster to handle the session request through a gateway node scheduling strategy; determining the session credentials corresponding to the target service node through the gateway session identifier and the session mapping table; updating the session request based on the target session credentials to generate a target session request; forwarding the target session request to the target service node for processing to generate a service response; and sending the service response carrying the gateway session identifier to the client. This application, based on the pre-built and cached correspondence between the gateway session identifier and the session credentials of each service node, and relying on the gateway node scheduling strategy to achieve high-availability random load forwarding, effectively ensures the session persistence function of the monolithic application.

The invention discloses a mixed domain AI high-performance network flow congestion suppression control method, which relates to the technical field of computer networks, and comprises the following steps: a congestion detection step: introducing data packet transmission round-trip time and a switch queue length as congestion detection signals, and a switch queue length management coefficient lambda and a data packet transmission round-trip time management coefficient theta are set. The method comprises the following specific steps: acquiring the current queue length Q of the switch, the data packet round-trip time RTT and the reference round-trip time baseRTT; and when the switch queue length Q is less than the queue length lower limit Kmin or greater than the queue length upper limit Kmax, calculating the data packet congestion marking probability P according to a formula. According to the invention, on the basis of the ECN, RTT indexes which can be collected without special support of network equipment are introduced as congestion detection signals together, and Q and RTT management coefficients are set, so that the response sensitivity of the network to congestion is further improved.