237 results about "Network link" patented technology

The invention relates to the technical field of audio and video emergency transmission, and discloses an audio and video low-delay return method and system in an extreme environment. The method comprises the following steps: acquiring original multi-modal data of audio and video acquisition equipment in a target area, and analyzing a data state of the original multi-modal data; and meanwhile, available network transmission links are monitored, and the quality is evaluated. Self-adaptive coding parameters are generated in combination with the link quality and the data state, dynamic coding is executed on original data, and a coding stream suitable for redundant transmission is formed. And carrying out cooperative distribution transmission based on the network link set and the coded stream to generate return data. According to the generation process, a device and energy management instruction is formed and issued to the acquisition and relay device. According to the method, the network state and the content characteristics are optimized in a dynamic coding link in a collaborative manner, and the audio and video quality, the real-time performance and the system energy efficiency which are transmitted back in an extreme environment are improved through a feedback closed loop for transmitting a result to equipment management.

The present disclosure provides a search engine optimization (SEO) system comprising a remote server. The remote server comprises a memory with a set of executable routines and a search engine database with multiple fields of applications, each associated with multiple URLs indexed with a user engagement matrix, written data, and a search engine ranking. A processor acquires a web link from a computing device, extracts textual content, analyzes relevancy, and retrieves relevant URLs. The processor evaluates a thematic score, a readability score, and an emotional tone data using NLP techniques, analyzes written data of each URL to determine a topic weight, a legibility weight, and a sentiment tone data, develops a machine learning model, applies the model to recommend content alterations, and renders the alterations at the computing device.

The invention relates to an intelligent ship network optimization method, system and device based on multi-link convergence and a medium. The method comprises the following steps: firstly, acquiring multi-network link connection parameters of the intelligent ship, constructing an adaptive environment, modifying a protocol stack, and integrating a physical link into a virtual link to realize resource convergence; and based on the real-time parameters of the virtual link and the physical link, dynamically distributing traffic by adopting an improved aggregation protocol, and generating a load balancing scheme. And then, regularly sending a detection packet quality index, and predicting a link quality trend in combination with historical data and navigation longitude and latitude. And finally, dynamically adjusting flow distribution according to a prediction result, an application real-time demand, a bandwidth demand and a current position tariff characteristic, and generating a ship-shore communication scheme considering both efficiency and cost. By adopting the method, the stability, reliability and economy of ship-shore communication of the intelligent ship can be effectively enhanced, and the method is suitable for multi-scene network monitoring optimization.

The invention relates to a robot control technology, and discloses a robot cluster control method and system and a storage medium, and the method comprises the steps: receiving motion state data, network link state data and service type information of each robot; predicting a motion track of each robot in a future preset time period based on the motion state data in combination with a digital map, and predicting a communication quality change trend of a current network link of each robot in the future preset time period based on the network link state data; determining a target network link of each robot based on the motion trail, the communication quality change trend, the digital map, the service type information and the received node operation state information of each edge relay node, and generating a network switching instruction containing the target network link and the switching opportunity, and the corresponding robot executes network link switching according to the network switching instruction. According to the invention, global prediction and active switching of robot cluster communication can be realized.

The invention discloses a multi-network integration intelligent route selection method and system based on multi-dimensional dynamic evaluation, and the method comprises the following steps: S1, network communication hardware of equipment collects the signal intensity and signal quality parameters of GEO, LEO, Beidou short messages and 4G / 5G network links in real time, and transmits the parameters to an intelligent route selection decision engine module; by introducing the multi-dimensional dynamic weight evaluation model and the intelligent route selection decision engine, parameters such as signal strength and signal quality of multiple network links such as GEO, LEO, Beidou short messages and 4G / 5G can be monitored in real time, the optimal network link is automatically selected as an internet access channel in combination with data size and tariff standards, and the network access efficiency is improved. Therefore, optimal configuration of network resources is realized, the quality and efficiency of network connection are improved, and the use cost of a user is reduced.

The invention provides a network intrusion detection method and system based on artificial intelligence, and relates to the technical field of network intrusion detection, and the method comprises the steps: obtaining multi-dimensional behavior data of a terminal domain, a network link domain and an application layer domain, and employing a high-density or hierarchical collection strategy according to a network type; preprocessing the data through a standardization priority or coding priority scheme according to feature types; constructing a CNN-LSTM fusion model adaptive to network dynamics, and extracting space and time sequence correlation features; based on the sample condition, adopting full or incremental training to obtain a convergence model; a result is output through a high-precision or high-speed detection strategy in combination with scene requirements; and continuously iteratively optimizing the model based on the environmental change. The system correspondingly comprises a multi-domain data acquisition module, a data preprocessing module and the like. The method breaks through the limitation of single-domain detection, accurately recognizes cross-domain cooperative attacks, adapts to different network scenes, reduces the false alarm and missing alarm rate, improves the detection real-time performance and stability, and is suitable for various network environments such as enterprise intranets and hybrid clouds.

The invention discloses an oil field equipment fault early warning method based on a block chain, and relates to the technical field of oil field equipment fault early warning. The problem of key data delay or congestion discarding caused by traditional fixed-rate transmission in a complex edge-block chain collaborative environment is fundamentally solved. Compared with a'one-cut 'transmission strategy in the prior art, the method intelligently adjusts the transmission rate of each structured data packet in combination with the real-time bearing state of a network link according to the fault risk level and the aging attenuation characteristic of the data and the current oil field operation stage, and improves the data transmission efficiency. And high-risk and high-emergency equipment state data can be preferentially and quickly sent to the target parallel chain. The optimization directly ensures that the structured data written into the block chain has higher time freshness and stronger business relevance, so that the accuracy, sensitivity and early warning capability of a fault prediction result are remarkably improved.

The application discloses a kind of power industrial control terminal network isolation method and system based on process security label binding;Belong to the technical field of power system network security, its operating steps include: decoupling physical network resources into independent partitions and mapping to independent user-mode network protocol stack instances;Through the bottom flow direction rule, the in-bound traffic is accurately delivered to the corresponding partition;Identify process security label at the application layer, establish the forced mapping of process and specific protocol stack instance and link;Through the controlled shared memory channel, realize the safe data interaction between partitions.The application realizes strong logical isolation on unified hardware, through the forced binding of process identity and network link, reduces the privilege promotion and horizontal penetration risk caused by traditional protocol stack sharing, while limiting the scope of failure impact, without relying on external physical isolation equipment, significantly improves the endogenous security protection capability of industrial control system network boundary.

Systems and methods are provided for “on the fly” routing of data transmissions in the presence of errors. Switches can establish flow channels corresponding to flows in the network. In response to encountering a critical error on a network link along a transmission path, a switch can generate an error acknowledgement. The switch can transmit the error acknowledgements to ingress ports upstream from the network link via the plurality of flow channels. By transmitting the error acknowledgement, it indicates that the network link where the critical error was encountered is a failed link to ingress ports upstream from the failed link. Subsequently, each ingress port upstream from the failed link can dynamically update the path of the plurality of flows that are upstream from the failed link such that the plurality of flows that are upstream from the failed link are routed in a manner that avoids the failed link.

The invention discloses a network security protection method based on artificial intelligence and computer equipment. The method comprises the following steps: acquiring multi-dimensional data in a network link; performing clustering analysis on the multi-dimensional data to generate threat candidate regions; according to the threat candidate region, generating a threat risk assessment result by using an adversarial game learning algorithm driven by a graph neural network; based on the threat risk assessment result, adopting an optimal transfer entropy analysis method based on a multi-hop path to obtain a causal relationship and an evolution law of a risk event; analyzing a causal relationship and an evolution rule of the risk event to generate a safety control strategy suggestion; and generating and executing a protection response instruction according to the safety control strategy suggestion. The method has the advantages that the real-time response speed of network protection is increased, and the method has certain self-adaptive protection capability on a novel network attack mode.

The invention relates to the technical field of financial data intelligence, and discloses a financial personalized management classification system based on digital economy. According to the system, a dynamic mapping network is formed through weaving by constructing a user composite intention profile. And injecting a probe into a network node, performing compliance deconstruction and verification on a response sequence, driving behavior partition structure recombination, and performing re-calibration on the network according to the behavior partition structure recombination. And capturing an intention drift trajectory through a real-time data stream, dynamically and elastically telescoping network link weight, and finally fusing a strategy to complete management classification. According to the system, online driving optimization of data partitions in a compliance state and real-time dynamic shaping of a decision network by intention drift are realized, a closed-loop adaptive mechanism from bottom data to upper rules is formed, and classification accuracy, timeliness and compliance adaptability of financial personalized management in a dynamic environment are improved.

The invention discloses an internet of things edge computing dynamic load prediction data processing method and system, and belongs to the technical field of edge computing. According to the method, edge node operation, network link quality and Internet of Things task characteristic parameters are collected, a time sequence prediction model is adopted to complete edge node load prediction, and related parameters are integrated to construct a task dynamic decision state space; computing task routing allocation is completed based on the state space, and a heterogeneous resource scheduling multi-objective optimization model is established and solved to obtain a scheduling scheme; according to the scheme, the original data of the Internet of Things is subjected to mixed compression, and a prefetching rule is constructed by combining compressed data access statistics and time-space association attributes, so that data prefetching and cache management are completed. According to the method, dynamic adaptation of the computing tasks and reasonable utilization of resources can be realized, data transmission bandwidth occupation is reduced, the cache hit rate of the edge nodes and the system operation stability are improved, and the real-time processing requirement of the edge computing scene of the Internet of Things is met.

The application discloses a kind of server fault diagnosis method and system for server group, it is related to server operation and maintenance technical field, present and propose the following scheme, including data acquisition unit, data preprocessing unit, data training unit, data diagnostic analysis unit, scheme generation unit, scheme verification trial unit, data storage unit and data early warning unit, each unit is connected by communication bus or network link and forms closed loop diagnosis system.The application constructs full-link fault diagnosis system, through multidimensional collection hardware, software, network data, improves data quality by scientific pretreatment, adopts rule matching+machine learning hybrid model, combined with self-learning mechanism, improve diagnostic accuracy and coverage, generate personalized repair scheme and be verified by simulation / real machine, avoid secondary failure, full-process data safety storage and double early warning mechanism, realize fault tracing and prevention and control in advance, greatly improve server group operation and maintenance efficiency, guarantee business continuity.

The application provides a computer network monitoring system and method. First, a network security risk graph integrating logical dependencies and vulnerability attributes is constructed, and potential attack chains are deduced and their dynamic risks are evaluated based on the network security risk graph; then, data request sequences of key nodes on the potential attack chains are monitored to identify suspicious behaviors based on dynamic behavior portraits. Then, the identified suspicious behaviors are combined with the dynamic risks of the corresponding attack chains to determine the attack stages of attack activities; finally, based on the determined attack stages, enhanced monitoring is started on related network links and decoy nodes are deployed, and hierarchical alarms are triggered according to attack interaction features captured by the decoy. The above scheme can realize dynamic evaluation and hierarchical response of potential attack chains based on a network security risk graph.

The invention discloses a stable video transmission method and system in a high-speed moving scene and electronic equipment, and relates to the technical field of video transmission and communication, and the method comprises the following steps: obtaining the moving state data of a video transmitting end, and judging whether the video transmitting end enters a high-speed moving transmission state or not; after entering a high-speed mobile transmission state, acquiring current network link state data, and determining a corresponding link risk interval; generating a corresponding transmission control instance according to the link risk interval; performing structured redundancy construction on the video data according to the transmission control instance and completing video transmission; according to the invention, through prospective motion determination and structured redundancy, the problem of unstable video transmission under high-speed movement is solved.

This invention discloses a novel intelligent sharing and optimization method and system for aesthetic education resources based on a cloud platform, belonging to the field of resource sharing technology. By deploying multiple types of sensors in the classroom to collect teaching environment data and construct a classroom environment feature vector, a resource environment demand vector is established, and the environmental adaptability between the classroom environment and various aesthetic education resources is calculated. The network link status between the classroom terminal and the cloud platform is detected in real time, and parameters such as bandwidth, latency, and packet loss rate are obtained. Resource network matching coefficients are calculated, and the environmental adaptability and network matching coefficients are further integrated to construct a comprehensive resource availability. A resource scheduling priority sequence is generated by combining course matching degree and concurrent call status. This achieves intelligent sharing and dynamic optimization scheduling of aesthetic education resources in multi-classroom scenarios, improving the environmental adaptability and transmission stability of resource sharing, and enhancing the utilization efficiency and teaching implementation reliability of aesthetic education resources on the cloud platform.

Disclosed are a network traffic load balancing method and apparatus for a data center, which are applied to the data center including a switch, a host, and a server. The method includes the following steps: collecting connection information between the switch, the host, and the server, and constructing a network topology structure of the data center according to the connection information; monitoring working information about each network link under the network topology structure, and correspondingly determining a congestion condition of each network link according to the working information about each network link; and allocating pre-transmitted data traffic packets to each network link according to the congestion condition to balance data traffic on each network link.

The invention discloses a network layer ultralimit packet processing method and system based on first fragmentation and then encryption. The method comprises the following steps: deploying between a sending end encryption machine and a receiving end decryption machine, and carrying out fragmentation processing on a load of an original IP data packet by the sending end encryption machine to obtain a plurality of load fragments; respectively carrying out encryption and authentication processing on each load fragment; packaging a predefined header for each encrypted load fragment, including: predefining an outer layer packet header protocol number and packet header information including an IP protocol number to form an encrypted fragment data packet, and sending the encrypted fragment data packet to a network link layer; the receiving end decryption machine receives the encrypted fragmented data packet on the network link layer; after identifying a predefined outer layer packet header protocol number, decrypting to obtain a decrypted load fragment; and forwarding the load fragments to a receiving end host according to the IP protocol number, and completing fragment recombination by the receiving end host. The method can meet the urgent requirements of a modern high-speed network on high performance, low delay and high robustness of encryption equipment.

The invention discloses a dynamic network link prediction method based on node importance and edge feature learning, and aims to improve prediction precision and time-dependent modeling capability of missing links in a complex dynamic network. According to the method, the influence of node centrality and attribute characteristics on network evolution is comprehensively considered by constructing time-aware node importance measurement; meanwhile, multi-dimensional feature modeling is carried out on the edges, the features comprise topological structures, node similarity and time evolution features, different features are fused through a self-adaptive weighting mechanism, and the expression capacity of the node relation is improved. On the basis, deep dynamic embedding of node representation is realized by combining a graph neural network and a time sequence modeling technology, so that an evolution rule of a node structure along with time change is captured. The method is suitable for practical scenes with remarkable dynamic evolution characteristics, such as social networks, citation networks and recommendation systems, and has good expandability and interpretability. Experimental results show that the method is superior to an existing link prediction method on various dynamic network data sets, and has remarkable advantages in the aspects of prediction accuracy, time sensitivity and generalization ability.

The technology enables efficient and effective real-time sharing of contact information, for instance email addresses, with other people. A machine-readable code, such as a QR code, is associated with a specific email address, which may be an alias of an actual email address of a person. The aliased email address and machine-readable code may be associated with selected contact information, which can automatically be presented to another person who scans the machine-readable code with their device. For example, capture of the machine-readable code may enable an email template to be presented that is prepopulated with at least the aliased email address and / or the selected contact information, or the capture may enable a web link to be presented to the person, so that that person can view the selected contact information.

The invention relates to addressing predicted unhealthy conditions for network links. In some examples, a system monitors health indicators associated with a plurality of edge links connecting a set of switches to an electronic device. The system predicts an unhealthy condition of a first edge link of the plurality of edge links based on the pattern of health indicators. Based on the prediction, a workload manager triggers a maintenance mode of an electronic device connected to the first edge link to address a predicted unhealthy condition, where the workload manager avoids scheduling any further workload on the electronic device when the electronic device is in the maintenance mode.

Methods, systems and computer program products for implementing high-availability file services in a clustered computing environment. Two or more clusters are interconnected to carry out operations for replication of file content between file servers. The file servers and their respective network links are registered with a file server witness. The file servers operate in synchrony, where each file I / O is replicated from one file server to another file server over a first set of network paths. A file server witness communicates with each file server using a second set of two or more network paths interfaced with respective file servers. The file server witness monitors the file servers to determine operational health of the file servers. Upon receipt of a file I / O request, the file I / O request is directed to one of the two file servers based at least in part on the determined operational health.

The invention provides a multi-rate network intelligent route planning method based on minimum media occupancy time, and belongs to the field of multi-rate networks and route planning. According to the method, firstly, an ant colony algorithm is adopted, the mobility of nodes is introduced, a stable and optimal MPR set is selected, and whole network topology information is obtained; then giving a network link weight based on media occupancy time; and finally, selecting an optimal route based on a simulated annealing algorithm of multi-agent optimization. According to the method, the traditional method of selecting the routing based on the minimum hop count is abandoned, the media occupation time is defined to comprehensively evaluate the network link weight, the time delay of the network is reduced, and the throughput of the network is increased; and secondly, routing is selected by adopting a simulated annealing algorithm based on multi-agent optimization, so that the optimization capacity is improved, the network dynamics is adapted, and the robustness of the network is enhanced.

Various embodiments of the present disclosure provide a network linking technique that improves the functionality of a computer in various aspects. The techniques comprise receiving a member-specific assertion request encapsulating an assertion request from a user of the first member platform; determining a local construct of a cross-platform data object; determining, using the local construct of the cross-platform data object, a second member platform; providing an internal member-specific assertion request to an internal service associated with the second member platform; providing, via the internal service, an incoming member-specific assertion request to the second member platform; responsive to receiving a user input at the second member platform, receiving an assertion response at the internal service and from the second member platform; and providing the assertion response to the first member platform.

Various embodiments of the present disclosure provide a network linking technique that improves the functionality of a computer in various aspects. The techniques comprise responsive to an exchange request, receiving, originating from a member platform within the member computing ecosystem, a linking code request comprising a member-specific identifier corresponding to the member platform; providing, to an internal service, the linking code request to generate an ephemeral transport object storing a linking code and a link reference corresponding to the member-specific identifier and the linking code; providing the linking code to the member platform; receiving, originating from the another member platform within the member computing ecosystem, a linking request comprising the linking code; and authorizing, using the second member platform, the exchange request based on the linking code.

The invention relates to the technical field of computing power networks, in particular to an intelligent scheduling method and system for a computing power network. The method comprises the following steps: collecting computing power node data, network link data and task demand data of each node in a computing power network, and generating a standardized data sample; inputting the standardized data sample into a demand analysis model to complete a task demand portrait; combining the task demand level with the real-time resource state of the computing power network, constructing a multi-target optimization scheduling model, and solving the model to obtain an optimal scheduling scheme adaptive to the task and the network state; according to the optimal scheduling scheme, computing power resource allocation and task issuing are completed; the system comprises a data acquisition module, a task demand analysis module, an intelligent scheduling decision module and an execution module. Through the above mode, systematic consideration of the computing power resource state, the task demand characteristics and the dynamic adaptation adjustment is realized, and accurate dynamic matching of the computing power resource and the task demand can be realized.

The application discloses a kind of network link dynamic monitoring method and system based on distributed network, belong to dynamic monitoring technical field;The historical transmission state parameter information and historical transmission state node time information of each network link in distributed network are acquired;Transmission state marker is carried out to historical transmission state node time information;Historical transmission state node time set is constructed, and transmission state transition case library is established;The equal transmission state stability of single network link is calculated;Based on the equal transmission state stability, the stable similarity between network links is calculated;Equal transmission state stability threshold and stable similarity threshold are preset, and dynamic monitoring is analyzed and carried out.The application improves the accuracy and real-time of network link monitoring by phased data processing, state marker, stability calculation and similarity analysis, guarantees stable communication under distributed network environment, and optimizes the allocation and management of network resources.

A method for scheduling edge nodes and a cloud scheduling platform are disclosed, relating to the field of computer technology. This method is applied to a cloud scheduling platform. After receiving a DNS request from a target user, the cloud scheduling platform determines the IP address of the first edge node corresponding to the target access information indicated in the DNS request, based on edge node scheduling information, and returns the IP address of the first edge node to the target user. Since the first edge node scheduled by the cloud scheduling platform has fewer ASs on its network link to the target AS indicated by the target access information than other edge nodes, when the target user accesses the first edge node corresponding to the target domain name through the target AS, the number of AS hops on the network link is reduced compared to accessing other edge nodes corresponding to the target domain name. This reduces access latency and improves network communication quality.

The application discloses an online singing and microphone passing interaction method and device and a medium, relates to the technical field of communication, and is applied to a lead singer client in an online singing room and comprises the following steps: if a currently sung song meets preset microphone passing conditions, a microphone passing button is displayed on a local preset screen area; if it is monitored that the microphone passing button is clicked, a chorus invitation request is sent to each audience client in the online singing room; a communication connection establishment request sent by a microphone receiving client is responded to, so that a point-to-point link is established with the microphone receiving client; a first audio stream uploaded by the microphone receiving client through the point-to-point link is acquired, and the first audio stream and a second audio stream locally acquired are merged to obtain a chorus audio stream; and the chorus audio stream is uploaded to a content distribution network, so that non-microphone receiving clients in the audience clients acquire the chorus audio stream from the content distribution network through a content distribution network link and play the chorus audio stream. The application can realize microphone passing interaction between singers and audiences in the online singing room.

This application discloses a method and system for dynamic mapping and scheduling of network resources based on identity resolution, relating to the field of computer network technology. The method includes: acquiring request information of the task to be scheduled, multi-source identity signals, resource node status, overall network load status, and service preference information; fusing and parsing the multi-source identity signals to construct a cross-domain unified identity identifier and generate an identity attribute vector; then, combining computing resource status, network link status, and service preferences, calculating the identity adaptability between the unified identity identifier and each resource node to generate a candidate resource node list; finally, making dynamic scheduling decisions based on overall network load and link status to determine the target resource node and its corresponding network path, and issuing network configuration rules and resource scheduling instructions. This achieves collaborative perception and dynamic matching of identity, network, and computing resources, improving the accuracy, real-time performance, and service adaptability of cross-domain resource scheduling.