56 results about "Local domain" patented technology

The invention discloses a Linux container-based Android and open source gap dual-system collaborative operation method, relates to the technical field of operation system collaboration, and aims to reduce resource occupation and improve collaboration and switching coherence, and the method comprises the following steps: step 1, by taking an Android as a host, creating a container isolation running domain, starting a namespace and managing resources by a control group; the method comprises the following steps: presetting a binder virtualization and three-state template; 2, deploying an open source gap in a container, mounting a shared directory in a directory binding manner, configuring bridging or address translation, and establishing copy-on-write and snapshot identifiers; and step 3, establishing a cross-system binder channel, and setting a service registration agent in a service manager and completing mapping of a handle and an authority domain by combining a shared memory and a local socket. And step 4, executing system switching without restarting, enabling one foreground and the other background through a foreground interface and continuous quota assignment, freezing a background session, limiting the speed of background heartbeat, and returning according to a snapshot when an exception occurs.

The invention relates to the technical field of artificial intelligence, in particular to a field adaptive large model fine tuning method and system based on enterprise private data, and the method comprises the steps: extracting the feature representation of local data by each participating client through a unified pre-training model, generating a prototype set representing local region category features by adopting a mean value, clustering or random sampling method; gaussian random noise is added to the prototype set, differential privacy protection is achieved, and then the prototype set is uploaded to a server; the server summarizes prototypes of all the clients, constructs a global prototype training set, performs global training of a single communication round on the adapter module by using supervised learning classification loss under the condition that similar prototypes of different clients are not averaged, obtains a global adapter model and issues the global adapter model to the clients; and the client initializes a local model based on the global adapter model, performs fine tuning by using a small amount of data with labels, and meanwhile, prevents catastrophic forgetting through knowledge distillation constraint by taking the global model as a teacher, so that balance between global knowledge retention and local performance improvement is realized. According to the method, the problem that the expression of the model in a cross-domain reasoning task is remarkably reduced due to the fact that domain characteristics of different enterprises cannot be effectively aligned in the prior art can be solved.

The invention discloses a biomedical multi-mode signal anomaly detection and prediction method and system, and the method comprises the steps: modeling a biomedical multi-mode signal into a time-varying non-local dynamic system, capturing the long-time-history dependence characteristic of the signal through a memory mechanism of a Caputo fractional derivative, and introducing a time-varying input item to process interference; the method comprises the following steps of: carrying out high-precision numerical integration by adopting an Adams-Bashform-Module solver; optimizing model parameters in combination with a local domain normalization pre-training strategy and a fusion loss function; abnormal detection is realized by calculating comparison between signal reconstruction deviation and a self-adaptive threshold value; a future anomaly probability is generated based on the trajectory prediction. According to the method, the problems of insufficient non-local dependence capture, poor time-varying interference robustness, high false positive rate and the like in the prior art are effectively solved, the accuracy and real-time performance of abnormal detection and prediction of biomedical signals such as electroencephalogram and electrocardiogram are remarkably improved, and the method is suitable for wearable medical equipment and clinical monitoring systems.

The invention belongs to the technical field of computer man-machine interaction and automatic control, and particularly relates to an RPA mouse and keyboard control method and system for a Wayland desktop. The method comprises the following steps: S1, creating and registering a virtual input device supporting mouse and keyboard functions in a user space by accessing a virtual input device interface provided by an operating system kernel; s2, current activity display output is detected, and screen resolution information is obtained; s3, the server program monitors a preset local Unix domain socket path for receiving a control instruction from the client; s4, the client sends a control request to the local Unix domain socket path in a structured format, and the server receives and analyzes the control request; s5, the server side maps the analyzed control request into a corresponding kernel input event sequence according to the operation type; meanwhile, by writing event data into the virtual input device, an input event is injected into the system so as to simulate a control operation on the graphic desktop.

An improved computing system is arranged for cross-origin network communications on a single computing device. The system includes a processor, a networking module, and memory with software instructions arranged to operate a local computing server resource on a first local domain, instantiate a relay mechanism that has an iFrame and an invisible window, instantiate a local web server on a second local domain, install a service worker on the invisible window, receive a request for information at the local web server, verify a presence of the local computing server resource on the first local domain, communicatively connect the second local domain to the iFrame, and directly communicate, via the at least one networking module, at least one message between the local computing server resource on the first local domain and the local web server on the second local domain using the relay mechanism.

This invention discloses a method and system for generating real-time content in a specific domain based on AI technology, belonging to the field of artificial intelligence technology. The method includes the following steps: 1. Constructing a local material knowledge base RAG_src in the form of word vector storage using AI technology, whose materials include multimodal materials such as text, voice, audio / video, or H5; 2. Constructing a local domain knowledge classification knowledge base RAG_policy in the form of file storage using AI technology, whose content includes domain specification documents and technical classification documents categorized by domain knowledge and information; 3. Constructing PageIndex by combining a Large Language Model (LLM) with RAG_policy; 4. Receiving content generation requests from real-time software, calling RAG_src and PageIndex through LLM to generate real-time content that meets the requirements of the corresponding scenario; 5. Checking the generated content and outputting compliant content. This invention solves the problems of non-standard content generation, disconnection from relevant standards, low reuse rate of proprietary materials, and low retrieval efficiency in existing technologies, achieving accurate, efficient, and real-time content generation. It is adaptable to various scenarios such as real-time content generation, content compliance checking, and real-time domain assistance in specific domains. Application scenarios include, but are not limited to, oral practice and oral examinations according to teaching syllabi.

The invention relates to the technical field of data query, in particular to a bank data query intelligent question and answer interaction system based on a large model. Comprising a question and answer interaction end, a bank database, a data retrieval module, a local domain extraction module, a cross-domain extraction module and a reply integration module, in order to solve the technical problems of tedious cross-domain extraction, dependence on manual authorization and limited question and answer range caused by data dispersion, the invention constructs a large-scale model driving system fusing natural language understanding, intelligent permission routing and collaborative workflow. Inherent data islands in banks are converted into logically associated data networks and efficient intelligent collaboration, so that non-technical personnel can accurately obtain cross-system complex business data in a dialogue mode, automation and refinement of data security management and control and cross-department collaboration process reconstruction are realized at a bottom layer, and the data security management and control efficiency is improved. Therefore, on the premise that financial compliance and data security requirements are strictly met, fundamental improvement of data query efficiency, depth and a cooperation mode is realized.

The invention discloses a redundancy optimization-based power grid data consistency method, which comprises the following steps of: dividing a whole network into a plurality of local domains by utilizing reputation data and topological information of nodes, electing a global committee, further performing dynamic influence evaluation on a transaction request based on a network domain division graph, and according to an evaluation result, determining the consistency of the transaction request. High-frequency local transactions are limited in a local consensus domain for closed-loop processing, and only transactions related to global influences are submitted to a global committee. Through the mode, the communication redundancy of the whole network is remarkably reduced, so that the concurrent processing capability and expansibility of the system are greatly improved while the data consistency is guaranteed.

This invention discloses a generalized identification method and system for slope rock mass structural surfaces based on multi-level domain adaptation. This invention relates to the field of slope rock mass identification technology. By constructing four levels—global domain adaptation, regional domain adaptation, local domain adaptation, and sample-level adaptive adaptation—this invention achieves hierarchical and progressive evolution of model capabilities. A variational autoencoder is used to explicitly decouple features into domain-invariant and domain-specific parts, enabling the model to distinguish between the essential geometric features of rock mass structural surfaces and the weathering and unloading features of specific regions. Through regional meta-learning training, it can quickly adapt to new regions with only a small number of labeled samples.

The invention discloses a network access method and device in a DNS hijacked scene and a related product, and relates to the technical field of network security. The method comprises the following steps: firstly, checking a local domain name resolution cache of a client, preferentially multiplexing a valid IP address cache, if the valid IP address cache is invalid, acquiring an IP address list corresponding to a target domain name through an IP direct connection trusted service interface, and bypassing a DNS resolution link; an IP address set with timeliness is generated and stored persistently, and address validity is guaranteed through regular refreshing of a double-judgment mechanism; a main domain name, a standby domain name and a local cache IP address are obtained based on the set, and a domain name-first progressive failover access strategy is generated in combination with multi-network configuration; and when the access of the main domain name and the standby domain name fails, automatically switching to the local cache IP address to initiate the access. According to the method and the device, stable network access in a DNS hijacking scene is realized, and reliable network access guarantee is provided for various software which depends on domain name access.

The present application relates to the technical field of artificial intelligence, in particular to a domain self-adaptive large model fine-tuning method and system based on enterprise private data, the method comprising: each participating client extracts the feature representation of local data using a unified pre-training model, and generates a prototype set representing the category features of the local domain by using mean, clustering or random sampling methods; uploading the prototype set to the server after adding Gaussian random noise to realize differential privacy protection; the server aggregates all client prototypes to construct a global prototype training set, and performs global training of the adapter module in a single communication round using supervised learning classification loss without averaging the same prototypes of different clients, obtains a global adapter model and distributes it to the client; the client initializes the local model based on the global adapter model, fine-tunes it using a small amount of labeled data, and uses the global model as a teacher to prevent catastrophic forgetting through knowledge distillation, achieving a balance between global knowledge retention and local performance improvement. The present application can solve the problem that the existing technology cannot effectively align the domain features of different enterprises, resulting in a significant decline in the performance of the model in cross-domain reasoning tasks.

This application provides a data security sharing method, apparatus, and system based on a usable but invisible mechanism, applied in the field of cross-domain data sharing security technology. It constructs a secure sharing mechanism based on a three-dimensional collaborative approach of "spatiotemporal-object-rights," deeply integrating a spatiotemporal grid coding system with a digital object identification system to generate unique identifiers with spatiotemporal semantics. This is combined with a rights root mechanism to complete data ownership registration. During data circulation, relying on data network infrastructure and digital contract mechanisms, usage requests are routed to the data provider side, and a trusted execution environment bound to the contract is scheduled. This ensures that the original data completes secure computation without leaving the local domain. Simultaneously, traceable evidence information and measurable encrypted credentials are automatically generated along with the computation results. Ultimately, this achieves trusted sharing throughout the entire lifecycle of data—data that remains within the domain, usable but invisible, controllable, and measurable—providing fundamental support for a data-driven society.

A UMR auto-discovery mechanism which allows a gateway EVPN router to advertise a UMR route and to suppress redistribution of remote domain MAC-IP routes. In one embodiment, upon joining a local EVPN domain of a network, a network device (an EVPN router) advertises its UMR capability, which may include UMR installer capability or UMR originator capability. The UMR-capable devices in the network are also advertised to the newly added network device. A UMR originator (e.g., gateway) with knowledge of the UMR capabilities of the devices in the network then generates and sends a route list to the devices, where the route list includes a UMR route, or MAC / IP routes, or both, depending upon whether all of the network devices are all UMR-capable, none are UMR-capable, or the devices include both UMR-capable and non-UMR-capable devices, respectively.

The invention discloses an intelligent comparative analysis method and system for a network security situation, and relates to the technical field of network security, and the method comprises the steps: constructing a multi-source coupling index E and a disturbance anomaly index Ycz on the basis of obtaining a standard environment perception data set and a standard communication perception data set; quantitative judgment on whether environmental disturbance can reasonably explain communication abnormity or not is achieved. When the disturbance anomaly index Ycz is higher than a set threshold value, a node transverse behavior structure analysis mechanism is further triggered, the sensing node is divided into a local domain Dm based on physical adjacency and topological adjacency, and a behavior structure offset function Mm is calculated based on the disturbance anomaly index of each node in the local domain. According to the structural analysis mode, abnormal outliers, synchronous abnormal groups or potential attack source nodes in a local structure can be effectively recognized, the linkage recognition capability of a system on local explosive attacks or node out-of-control phenomena is improved, and comprehensive perception upgrading from single-point behavior abnormity to structure-level situation migration is achieved.

The application discloses a multi-working-condition industrial process fault diagnosis method based on a dynamic adaptive domain adversarial network, and comprises the following steps: standardizing process data and taking a sliding window to obtain dynamic data; training a dynamic adaptive domain adversarial network by using labeled dynamic data of a source working condition and unlabeled dynamic data of a target working condition; the dynamic adaptive domain adversarial network comprises a feature extractor, a label classifier, a global domain discriminator and a local domain discriminator; the global domain discriminator aligns the marginal distribution of the source working condition and the target working condition; the local domain discriminator aligns the conditional distribution of the source working condition and the target working condition; a kind of learnable parameter is proposed to adaptively evaluate the relative importance of the marginal distribution and the conditional distribution, so as to better extract domain-invariant features; a kind of common center loss is proposed to improve the inter-class separability and intra-class compactness of data, and further improve the fault diagnosis precision; and the label classifier is used to predict the fault category of a sample. The application establishes an accurate fault diagnosis model for the target working condition.

The invention discloses an open set domain adaptive blast furnace fault diagnosis method based on reciprocity point learning, and belongs to the field of industrial process monitoring and intelligent diagnosis. According to the method, an open set domain adaptation framework is provided for the problems of fault sample scarcity, data distribution drift and unknown fault category occurrence in the blast furnace production process. The method comprises the following steps: firstly, constructing a mixed CNN-ViT feature extractor, and fusing local and global features to capture the slow time-varying feature of a blast furnace fault; and secondly, designing a prototype-reciprocity double classifier, constraining the open space risk through reciprocity point learning, and realizing effective distinguishing of known and unknown faults. And an entropy-based adaptive threshold mechanism is further introduced to dynamically identify an unknown fault. And finally, domain invariant feature learning and cross-working-condition knowledge migration of known faults are realized through local domain adaptation and joint distribution alignment. The method has excellent fault diagnosis precision and robustness in multi-working-condition and multi-source-domain data of the blast furnace, and the recognition capability of unknown faults is remarkably improved.

The invention provides a GSM-R (Global System for Mobile Communications-Railway) cross-domain coordinated multipoint cluster wireless network simulation method and system, and the method comprises the steps: receiving a call request from at least one vehicle-mounted device for each domain, determining the call request as a circuit domain request or a packet domain request based on the call request, the calling request carries address information and identification information of the vehicle-mounted equipment, local domain address information and identification information of called target ground control equipment, or carries request content and address information of the vehicle-mounted equipment and a target domain name; if the call request is determined to be a circuit domain request, determining whether the call request is cross-domain communication based on identification information of the called target ground control equipment and address identification information stored in the domain; and after the address information of the local domain is reconstructed and the address information of the target ground control equipment of the target domain is determined through the central server, the reconstructed call request is forwarded to the target ground control equipment based on the address information of the target ground control equipment.

This invention provides a network traffic anomaly detection method adapted to multi-domain IoT federated domains. The method involves acquiring network traffic data from multi-domain IoT and processing it to generate a unified feature vector; establishing a multi-task labeling system for the IoT network traffic data based on attributes; deploying a shared backbone network and a local domain adapter on each federated client and performing local training; calculating a multi-task loss based on the multi-task labeling system; aggregating the parameter differences of the multi-domain IoT clients on the server side based on the multi-task loss and updating the global model; distributing the updated global model to each client of the multi-domain IoT and adjusting sampling, loss weights, and threshold calibration; performing multiple rounds of federated iterations until a termination condition is met, freezing the shared backbone network while retaining the local domain adapter; and performing anomaly detection and output on the real-time acquired multi-domain IoT network traffic data using the acquired shared backbone network and local domain adapter.

Disclosed are a cross-domain access method, apparatus, device and medium, which relate to the technical field of communications, comprising: a first terminal device configured with a non-transparent bridge in a source domain obtains a target data packet routed by other devices in the source domain in the domain through a local virtual function, determining a target domain index corresponding to the source domain address field of the first terminal device from the source domain address mapping table; different virtual functions correspond to different virtual machines; and packaging the target data packet based on the domain information including the target domain index and the routing information including the routing type, and transmitting the packaged data packet to a second terminal device configured with a non-transparent bridge in a target domain corresponding to the target domain index in a cross-domain manner, so that the second terminal device triggers a routing operation corresponding to the routing type, and routing the target data packet in the target domain by using the target identity determined from the target domain mapping table. According to the method, the mapping table is adopted, so that the terminal equipment serving as a cross-domain access initiator can perform cross-domain operation through the local domain identity.

The application discloses an intelligent diagnosis method and system for mechanical equipment faults in an open set, which comprises the following steps: a new FCformer encoder based on Fourier and convolution embedding is used to construct long-distance dependency in the frequency domain and extract more representative local domain invariant fault features; a dynamic sub-domain adaptive module based on DLMMD is designed to align the conditional feature distribution of known classes by masking potential unknown classes; in order to reduce the influence of experience threshold setting on unknown class detection, an adaptive threshold learning method is used to establish the decision boundary of known classes and unknown classes. The shared feature extractor and fault classifier in the model are trained by a min-max entropy game training strategy to suppress the overconfidence problem of the model when the entropy value is minimized. The application can solve the problems of cross-domain knowledge transfer and intelligent detection of unknown faults of mechanical equipment in an open set, and has a wide application prospect.

The invention provides a cross-domain identification method for FeO content of sintered ore, which comprises the following steps of: acquiring cross-sectional images of a sintering machine tail under different working conditions, and dividing an image sample into a source domain data set and a target domain data set; converting the source domain image and the target domain image into a Token sequence through a patch embedding module, and mixing the source domain Token and the target domain Token at the same spatial position in a linear interpolation mode to obtain an intermediate domain Token sequence; a local domain adaptation module is arranged in the feature extractor, fine-grained feature alignment is carried out on a source domain Token, a target domain Token and a middle domain Token, and disturbance is added to a Token sequence in a randomly selected Transform Block hidden layer; a game strategy is adopted, coarse-grained feature alignment is executed through a domain mixing module, and a self-refining strategy is adopted to carry out iterative optimization on pseudo tags; and inputting a label-free target domain sample into the trained model, and outputting the FeO content category of the sintered ore. The method can effectively solve the common problems of inconsistent data distribution, label data scarcity and the like in actual industrial process working condition identification.

The present application relates to the technical field of communications. Disclosed are communication methods, a satellite system, an electronic device and a storage medium. In a communication method disclosed in the present application, when a first server has received a domain name resolution request sent by a terminal device, if the first server stores a first IP address corresponding to a first domain name in the domain name resolution request, the first IP address can be directly returned to the terminal device; and when the first server does not store the first IP address corresponding to the first domain name, the domain name resolution request is forwarded to a local domain name server by means of a second server deployed in a geostationary earth orbit satellite, and the first IP address is acquired from the local domain name server by means of the second server. In this way, satellite communication resources can be effectively saved, and the situation of network access failure of a terminal device can be effectively reduced, thereby improving the user experience.

The application relates to a dynamic configuration VPN server multi-domain name distribution method and device, computer equipment and medium, the method comprises the following steps: receiving the flow of a VPN client, identifying whether the flow is DNS query flow or non-DNS query flow; when the flow is DNS query flow, forwarding to a local DNS query server, obtaining DNS response information returned by the DNS query server, extracting IP address and domain name information from the DNS response information, and updating the local IP domain name mapping table; when the flow is non-DNS query flow, performing domain name resolution; when the resolution is successful, performing a domain name distribution operation according to the domain name information obtained by resolution, updating the target IP address of the flow and the domain name information obtained by resolution to the local IP domain name mapping table; when the resolution fails, querying the local IP domain name mapping table according to the target IP address of the flow, and performing a domain name distribution operation according to the domain name information found. The method can accurately, timely and safely distribute the domain name of encrypted flow.

The application provides a sinter FeO content cross-domain recognition method, comprising the following steps: collecting sinter machine tail cross-section images under different working conditions, and dividing the image samples into source domain data sets and target domain data sets; converting the source domain and target domain images into Token sequences through a patch embedding module, and mixing the source domain Token and the target domain Token at the same spatial position in a linear interpolation manner to obtain an intermediate domain Token sequence; setting a local domain adaptation module in a feature extractor, performing fine-grained feature alignment on the source domain Token, the target domain Token and the intermediate domain Token, and adding disturbance to the Token sequence in the randomly selected Transformer Block hidden layer; adopting a game strategy, performing coarse-grained feature alignment through a domain mixing module, and iteratively optimizing the pseudo label by adopting a self-refinement strategy; inputting the unlabeled target domain sample into the trained model, and outputting the sinter FeO content category. The application can effectively solve the problems of inconsistent data distribution and label data scarcity commonly encountered in actual industrial process working condition recognition.

The embodiment of the invention provides a file system access method and device, equipment and a storage medium, and the method comprises the steps: obtaining a shared name and an Internet protocol address of a file system, the file system comprising a target file system; registering a local domain name for the file system according to the shared name; determining a mapping relation between a local domain name of the file system and an internet protocol address; and controlling the terminal node to access the target file system based on the local domain name according to the target internet protocol address corresponding to the target file system and the mapping relation. According to the embodiment of the invention, under the constraint condition that the terminal node is only allowed to access the file system through the domain name and the file system only supports the access mode based on the IP address, the terminal node can still effectively access the file system by using the access mechanism based on the Internet protocol address, so that the convenience and experience of user use are improved, and the user experience is improved. And the function application range of the file system is expanded.

The application provides a domain name resolution method and device, electronic equipment and readable medium. The method comprises: obtaining a domain name resolution request initiated by a client for a to-be-resolved domain name; searching for domain name resolution information of the to-be-resolved domain name in a local domain name cache according to the domain name resolution request, wherein the domain name resolution information in the local domain name cache is obtained from an online domain name resolution service according to historical domain name resolution requests; if the domain name resolution information of the to-be-resolved domain name is not found in the local domain name cache, sending the to-be-resolved domain name to the online domain name resolution service to obtain the domain name resolution information of the to-be-resolved domain name from the online domain name resolution service; and sending the domain name resolution information of the to-be-resolved domain name to the client and updating the domain name resolution information of the to-be-resolved domain name in the local domain name cache. The method can avoid the service of the client being unable to be normally used due to the return result of the domain name resolution being empty, prevent domain name hijacking, and improve the stability and availability of the domain name resolution service.

The application discloses a kind of multimodal feature fusion and global local domain alignment UDA SAR ATR method and equipment, comprising: obtaining the full-aperture SAR image to be identified of actual measurement;The image is divided into a group of sub-aperture images;The scattering topological graph of the image is constructed;Using the trained deep recognition network, a group of sub-aperture images and scattering topological graph of the image are processed, to obtain the category of target contained in the image;The trained deep recognition network is obtained based on preset data set training;Multiple categories of simulation full-aperture SAR images and actual measurement full-aperture SAR images are contained in preset data set, each simulation full-aperture SAR image has real domain label and category label, each actual measurement full-aperture SAR image only has real domain label, domain label indicates whether image is simulation image or actual measurement image, and category label indicates the category of target in image.The application can improve cross-domain SAR target recognition performance.

The application belongs to the field of location tracing in wireless communication, and relates to a method and system for tracing the location of voice wireless network in public area wireless network, which comprises the following steps: S1: a user initiates the attachment of an evolved packet core network, a gateway extracts the local domain name, a port number and the physical address of a wireless access point of the user; S2: the user successfully passes the voice wireless network service authentication, the gateway and a fixed network AAA fixed network interact, and the local domain name and the port number are transmitted to the fixed network AAA system; S3: the fixed network AAA system extracts a service port in a line information, and queries the physical address and an installation address through the service port; and S4: the fixed network AAA system returns the physical address and the installation address to the gateway. The application realizes the high-precision positioning of the intelligent terminal user through the above technical scheme.

The application discloses a cross-domain authentication method for device anonymous traceability in a trusted execution environment, comprising the following steps: deploying a trusted execution environment (TEE) and completing generation of public and private keys of participants and registration of local domain devices; realizing cross-domain real identity permission through interaction of a challenge value set and an intermediate value set between the TEE local domain devices and target domain authentication nodes; realizing cross-domain anonymous identity permission through distributed key generation of the TEE local domain devices and the target domain authentication nodes; in the authentication stage, the local domain devices select real identities or pseudo identities to send cross-domain authentication requests to target domain devices, and the target domain devices query identities and corresponding public keys on a block chain to complete cross-domain authentication. TEEs are deployed on semi-trustworthy authentication nodes of each domain, and supervision of the authentication nodes is realized through interaction of the TEEs, the challenge value set and the intermediate value set, so that the authentication nodes replace traditional local domain trusted institutions to help devices to perform cross-domain authentication.

The embodiment of the invention provides a domain name resolution method, device and system, a storage medium and a program product. In the scheme, a private domain name resolution system is additionally arranged on the basis of a public domain name resolution system, a resolution data collection device can collect a domain name query result returned by a public domain name server and report the domain name query result to a centralized domain name server, and the centralized domain name server can maintain the domain name query result and a corresponding relation between the domain name query result and an available area. And the local domain name server can provide domain name recursive query for the application server according to the sequence of the local cache, the public domain name server and the centralized domain name server. Even if the link between the local domain name server and the public domain name server is unstable or the public domain name server is abnormal, the local domain name server can provide domain name recursive query for the application server of the available area to which the local domain name server belongs according to the corresponding relationship maintained by the centralized domain name server. Therefore, the problem of failure in querying the authoritative domain name server is solved, and the domain name resolution success rate is improved.