Intelligent agent domain name resource registration method and device, intelligent agent domain name resource query method and device, equipment and medium

Abstract

The invention relates to an agent domain name resource registration method and device, an agent domain name resource query method and device, equipment and a medium. The method comprises the steps of obtaining basic attribute information and initial state information of an intelligent agent in response to a first starting signal of the intelligent agent in an agent end; performing data structure conversion on the basic attribute information and the initial state information to obtain agent resource information under a target data structure; sending an agent registration request to a domain name server, the agent registration request including agent resource information under the target data structure, so that the domain name server stores the agent resource information based on the intelligent registration request; by adopting the method, the automatic registration of the agent domain name can be realized, and the agent resource information comprises the attribute and state of the agent, so that the efficient query of the subsequent agent can be realized.

Description

Technical Field

[0001] This application relates to the field of Internet technology, and in particular to a method, query method, apparatus, device, and medium for registering domain name resources for intelligent agents. Background Technology

[0002] With the rapid development of artificial intelligence and the Internet of Things (IoT) technologies, intelligent agents, as software entities capable of perceiving the environment, making autonomous decisions, and executing tasks, are becoming a core element of the next-generation Internet (the Internet of Intelligent Agents). Achieving efficient and reliable service discovery and collaboration among intelligent agents is the cornerstone of building the Internet of Intelligent Agents.

[0003] Traditional DNS (Domain Name Server) resource records resolve hostnames to IP addresses (Internet Protocol Addresses). However, for intelligent agents, the highly dynamic nature of intelligent agents means that traditional DNS resource records cannot meet the query needs of intelligent agents. Therefore, there is an urgent need for an intelligent agent domain name resource registration method to solve the above problems. Summary of the Invention

[0004] Therefore, it is necessary to provide a method, query method, device, equipment, and medium for registering and querying intelligent agent domain name resources that can improve the efficiency of intelligent agent domain name resource query, in order to address the above-mentioned technical problems.

[0005] Firstly, this application provides a method for registering intelligent agent domain name resources, including:

[0006] In response to the first start signal of the agent in the agent, the basic attribute information and initial state information of the agent are obtained;

[0007] The basic attribute information and the initial state information are transformed into a data structure to obtain the agent resource information under the target data structure.

[0008] A smart agent registration request is sent to the domain name server. The smart agent registration request contains smart agent resource information under the target data structure, so that the domain name server can save the smart agent resource information based on the smart registration request.

[0009] In one embodiment, the basic attribute information includes multiple fields, and the initial state information includes multiple fields; the step of performing data structure transformation on the basic attribute information and the initial state information to obtain agent resource information under the target data structure includes:

[0010] For each field in the basic attribute information and the initial state information, the field information is obtained by combining the field type, the content length corresponding to the field, and the field content of the field.

[0011] Based on the field information of each field, the agent resource information under the target data structure is obtained.

[0012] In one embodiment, the basic attribute information includes multiple fields such as an identifier field, a version number field, and a function description field; the initial state information includes multiple fields such as a resource status field, an access path field, a time-to-live field, and a security verification field.

[0013] In one embodiment, the method further includes: periodically collecting the latest state information of the agent based on a preset update frequency, and sending a first update request to the domain name server based on the latest state information, so that the domain name server updates the corresponding field in the stored agent resource information according to the latest state information contained in the first update request.

[0014] In one embodiment, the method further includes: upon receiving upgrade information of the agent, collecting the latest attribute information of the agent, and sending a second update request to the domain name server based on the latest attribute information, so that the domain name server updates the corresponding field in the stored agent resource information according to the latest attribute information contained in the second update request.

[0015] Secondly, this application also provides a method for querying domain name resources of intelligent agents, including:

[0016] Receive an agent query request initiated by the client; wherein the agent query request includes agent filtering parameters;

[0017] The query request from the intelligent agent is parsed to obtain the parsing result;

[0018] Based on the resolution result, query the agent resource information of the target data structure pre-stored in the domain name system; the agent resource information of the target data structure includes the basic attribute information and state information of the agent;

[0019] A corresponding response is generated based on the query results; wherein, the response results include target agent resource information that matches the parsing results;

[0020] Return the request response result to the client.

[0021] In one embodiment, querying the agent resource information of the target data structure pre-stored in the domain name system based on the resolution result includes:

[0022] Based on the parsing result, the local cache is queried. If the local cache does not contain target agent resource information that matches the parsing result, a resource query request is initiated to at least one domain name server in the domain name system. The at least one domain name server has pre-stored the target data structure agent resource information.

[0023] Thirdly, this application also provides an intelligent agent domain name resource registration device, comprising:

[0024] The acquisition module is used to acquire the basic attribute information and initial state information of the agent in response to the first start signal of the agent in the agent terminal;

[0025] The processing module is used to perform data structure transformation on the basic attribute information and the initial state information to obtain the agent resource information under the target data structure;

[0026] The registration module is used to send an agent registration request to the domain name server. The agent registration request contains agent resource information under the target data structure, so that the domain name server can save the agent resource information based on the agent registration request.

[0027] Fourthly, this application also provides an intelligent agent domain name resource query device, comprising:

[0028] A receiving module is used to receive an agent query request initiated by a client; wherein the agent query request includes agent filtering parameters;

[0029] The parsing module is used to parse the query request from the intelligent agent and obtain the parsing result;

[0030] The query module is used to query the agent resource information of the target data structure pre-stored in the domain name system based on the resolution result; the agent resource information of the target data structure includes the basic attribute information and state information of the agent;

[0031] A response module is used to generate a corresponding response result based on the query result; wherein, the response result includes target intelligent agent resource information that matches the parsing result;

[0032] The transmission module is used to return the request response result to the client.

[0033] Fifthly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the above-described method.

[0034] Sixthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-described method.

[0035] In a seventh aspect, this application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the above-described method.

[0036] The aforementioned intelligent agent domain name resource registration method, query method, device, equipment, and medium collect basic attribute information and initial state information of intelligent agents, integrate them into standardized resource records based on a unified target data structure, and store them in a domain name server to obtain intelligent agent resource information. Since the intelligent agent resource information stored in the domain name server can simultaneously contain information about the intelligent agent across multiple dimensions, refined filtering of intelligent agents can be achieved through information from multiple dimensions during intelligent agent queries, improving query efficiency and accuracy. Simultaneously, the intelligent agent resource information stored in the domain name server shares the same target data structure, achieving standardization of intelligent agent resource information. This allows for targeted information updates, efficient information queries, and information transmission based on the standardized target data structure, improving the interactivity of intelligent agent resource information in the domain name server, enabling dynamic updates of intelligent agent resource information in the domain name server, and further improving the real-time performance and accuracy of intelligent agent queries. Attached Figure Description

[0037] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0038] Figure 1 This is a flowchart illustrating a method for registering domain name resources for an intelligent agent in one embodiment;

[0039] Figure 2 This is a flowchart illustrating a method for querying domain name resources of an intelligent agent in one embodiment;

[0040] Figure 3 This is a system architecture block diagram of an intelligent agent query system involved in one embodiment;

[0041] Figure 4Provided in one embodiment Figure 3 Interaction flowchart for agent registration in China;

[0042] Figure 5 Provided in one embodiment Figure 3 Interaction flowchart for intelligent agent query;

[0043] Figure 6 This is a schematic diagram of an intelligent agent domain name resource registration device in one embodiment;

[0044] Figure 7 This is a schematic diagram of an intelligent agent domain name resource query device in one embodiment;

[0045] Figure 8 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0046] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0047] It should be noted that the terms "first," "second," etc., used in this application can be used to describe various elements, but these elements are not limited by these terms. These terms are only used to distinguish the first element from the second element. The terms "comprising" and "having," and any variations thereof, used in this application, are intended to cover non-exclusive inclusion. The term "multiple" used in this application refers to two or more. The term "and / or" used in this application refers to one of the embodiments, or any combination of multiple embodiments.

[0048] The intelligent agent domain name resource registration method provided in this application embodiment can be applied to the application environments described below. The agent communicates with a domain name server via a network. The domain name server can be equipped with a data storage system to store the intelligent agent resource information that the domain name server needs to retain. The data storage system can be integrated into the domain name server or located in the cloud or on other network servers.

[0049] The agent can respond to the agent's initial start signal, obtain the agent's basic attribute information and initial state information; and perform data structure transformation on the basic attribute information and initial state information to obtain the agent resource information under the target data structure; then, send an agent registration request to the domain name server, which contains the agent resource information under the target data structure, so that the domain name server can save the agent resource information based on the agent registration request.

[0050] The proxy terminal can be, but is not limited to, various personal computers, laptops, smartphones, tablets, drones, low-altitude aircraft, IoT devices, and portable wearable devices. IoT devices can include smart speakers, smart TVs, smart air conditioners, smart in-vehicle devices, and projection devices. Portable wearable devices can include smartwatches, smart bracelets, and head-mounted displays. Head-mounted displays can be virtual reality (VR) devices, augmented reality (AR) devices, and smart glasses. The domain name server can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services.

[0051] In one exemplary embodiment, such as Figure 1 As shown, a method for registering domain name resources for intelligent agents is provided. Taking the application of this method to the device where the agent is located as an example, the method includes the following steps 202 to 206. Wherein:

[0052] Step 202: In response to the first start signal of the agent in the agent, obtain the basic attribute information and initial state information of the agent.

[0053] Intelligent agents refer to software entities that can perceive the environment, make decisions, and take actions to achieve specific goals; for example, chatbots and recommendation service robots.

[0054] An agent is a carrier that carries the core functions of an intelligent agent. It can serve as a bridge connecting the logic of the intelligent agent with the physical or virtual environment. Furthermore, an agent can be a software component, such as a mobile application or desktop software; it can also be a physical component, such as an IoT device or a robot; or it can be a hardware and software component system, such as cloud collaboration.

[0055] It should be noted that a single agent can support multiple agents; for example, a mobile phone can have multiple applications installed, and each application can correspond to an agent. Conversely, an agent is usually managed by one agent, but it can also be managed by multiple agents. For example, a high-load AI model can be deployed on multiple nodes, and each node can be regarded as an agent of the model. In this way, the AI ​​model can utilize the resources of multiple nodes to meet the high-load requirements.

[0056] Basic attribute information of an intelligent agent refers to information describing the inherent or static attributes of the intelligent agent; among them, static attributes refer to attributes that change very infrequently; for example, basic attribute information of an intelligent agent may include the intelligent agent's identifier, the intelligent agent's capability description, the intelligent agent's structure, the intelligent agent's protocol version, security verification protocol, access path, etc.

[0057] The initial state information of an agent refers to the information used to describe its dynamic attributes after the agent is started. For example, the initial state information of an agent may include the agent's initial load, initial memory, initial latency, etc.

[0058] In some embodiments, an information collection instruction may be generated in response to the first start signal of the agent in the agent, and the agent may collect the basic attribute information and initial state information of the agent according to the information collection instruction.

[0059] In other embodiments, the agent may automatically report basic attribute information and initial state information to the agent in response to the agent's first start signal.

[0060] Step 204: Perform data structure transformation on the basic attribute information and initial state information to obtain the agent resource information under the target data structure.

[0061] In some embodiments, before performing data structure transformation on the basic attribute information and initial state information, data preprocessing can be performed on the basic attribute information and initial state information, such as data filtering, integrity checks, outlier detection, etc.

[0062] For example, information can be filtered from basic attribute information and initial state information based on preset fields; or, if there is missing or abnormal data in the basic attribute information and initial state information, a supplementary data collection request can be initiated for the missing or abnormal data to ensure that accurate basic attribute information and initial state information are obtained.

[0063] Here, data structure refers to the way data is organized; further, the target data structure is predefined; for example, the target data structure can be a key-value (KV) structure or a key-length-value (KLV) structure, which can be selected according to actual needs.

[0064] Step 206: Send an agent registration request to the domain name server. The agent registration request contains agent resource information under the target data structure, so that the domain name server can save the agent resource information based on the agent registration request.

[0065] The agent registration request is an encapsulation of agent resource information under the target data structure. The agent registration request may also include timestamps, agent information, security signatures, etc.

[0066] In some embodiments, the domain name server may pre-configure a security interface for registration. In this case, the agent registration request may also include security credentials, such as an access token, for security verification. Only after passing the security verification is the domain name server allowed to save the agent resource information based on the agent registration request, thereby ensuring the security and legality of agent registration.

[0067] The aforementioned agent domain name resource registration method collects basic attribute information and initial state information of agents, integrates them into standardized resource records based on a unified target data structure, and stores them in a domain name server to obtain agent resource information. Since the agent resource information stored in the domain name server can simultaneously contain information about the agent across multiple dimensions, fine-grained filtering of agents can be achieved through information from multiple dimensions during agent queries, improving query efficiency and accuracy. Simultaneously, the agent resource information stored in the domain name server shares the same target data structure, achieving standardization of agent resource information. This allows for targeted information updates, efficient information queries, and information transmission based on the standardized target data structure, improving the interactivity of agent resource information in the domain name server, enabling dynamic updates of agent resource information in the domain name server, and further improving the real-time performance and accuracy of agent queries.

[0068] In an exemplary embodiment, the basic attribute information includes multiple fields, and the initial state information includes multiple fields; step 204 includes steps 302 to 304. Wherein:

[0069] Step 302: For each field in the basic attribute information and initial state information, combine the field type, the corresponding content length, and the field content to obtain the field information.

[0070] The field type is based on the function of the field. Fields with different functions correspond to different types. Fields with the same function are identified as fields of the same type. For example, the first type of field is the identifier field, and the second type of field is the version number field, etc.

[0071] The content length of a field refers to the number of bytes occupied by the field's content. By knowing the content length of a field, we can clearly define the boundaries of the field content, thus knowing where the current field content ends and where the next field begins. In this way, when parsing data, we can clearly define the specific content to be parsed for a field and avoid incorrect parsing.

[0072] The content of a field is the actual data content included in the field; for example, for an identifier field, its content can be an identifier label; for a version number field, its content can be a version number, etc.

[0073] Step 304: Based on the field information of each field, obtain the agent resource information under the target data structure.

[0074] In some embodiments, the field information of each field can be concatenated to obtain the agent resource information under the target data structure; alternatively, an information set can be constructed based on the field information of each field, and this information set can be used as the agent resource information under the target data structure.

[0075] Furthermore, in the process of splicing the field information of each field or constructing an information set based on the field information of each field, the splicing order of each field information or the arrangement order in the set can be preset in advance, thereby realizing the standardization of intelligent agent resource information.

[0076] In this embodiment, when both the basic attribute information and the initial state information contain multiple fields, a data structure transformation is performed on each field. By splitting each field, fine-grained processing of the information is achieved. In this way, when information updates or queries are needed later, fine-grained precise queries or fine-grained local updates can be performed, thereby improving query accuracy and update efficiency.

[0077] In one exemplary embodiment, the basic attribute information includes multiple fields such as an identifier field, a version number field, and a function description field; the initial state information includes multiple fields such as a resource state field, an access path field, a time-to-live field, and a security verification field.

[0078] The identifier field contains a globally unique and immutable identifier (ID) for the agent. Furthermore, this identifier can be decoupled from a specific hostname or IP address, thereby avoiding the unique binding of the agent to the agent.

[0079] In some embodiments, a decentralized identifier (DID) format can be used to generate the identity identifier of an agent, such as DID:example:123456. The decentralized identifier is a self-generated, globally unique identifier that does not rely on any centralized registration authority and is stored on a decentralized network. In this way, the persistence of the identity identifier and cross-system interoperability can be determined.

[0080] The version number field can include the version number of the current agent resource information, which identifies the data structure version of the agent resource information itself and defines the format, meaning, and parsing rules of each field in the record. In this way, when the data structure of the agent resource information changes, the parsing rules of the current agent resource information can be determined by the version number. It can also include the agent's protocol version number, such as 0x01. In this way, when the agent is upgraded or updated, the protocol version number can be used to distinguish between the agent before the update and the agent after the update, and then determine whether the agent resource information matches the current agent.

[0081] The functional description field includes metadata about the agent's inherent capabilities and functions; for example, the agent's task type is image recognition, the framework is PyTorch, and the data precision used is 16-bit floating-point numbers.

[0082] In some embodiments, a CBOR (Concise Binary Object Representation) encoded mapping structure can be used to represent the field content of the functional description field, thereby achieving efficient serialization and parsing. The content is a machine-readable collection of key-value pairs. For example, for the above field content "task type is image recognition, framework is PyTorch, and data precision is 16-bit floating-point", the field content obtained by using CBOR encoded mapping can be: {"task-type": "image-processing", "framework": "pytorch", "precision": "fp16"}.

[0083] The resource status field contains metadata describing the agent's real-time dynamic status, such as CPU load, available memory, latency, video memory utilization, remaining video memory, throughput, bandwidth, request queue length, requests per second, error rate, current session count, and service quality level.

[0084] In some embodiments, a CBOR-encoded mapping structure can also be used to represent the field content of the resource status field. For example, the field content of the resource status field "CPU load is 0.3; available memory is 1024; latency is 50" can be represented as: {"CPU-load": 0.3, "mem-avail": 1024, "latency": 50}.

[0085] The access path field specifies how to access the agent service. It can be a Uniform Resource Identifier (URI) representing the service access point; or it can be a traditional network socket address or a higher-level application endpoint.

[0086] The Time to Live (TTL) field indicates the lifespan of the information, and its value can be the TTL value in related technologies. It's understandable that, to ensure the real-time nature of the agent's domain name information, the TTL value is actually determined by the most frequently changing fields in the basic attribute information and initial state information.

[0087] The security verification field stores information related to agent security authentication and authorization.

[0088] In some embodiments, the content of the security verification field can be one of the following two forms: a digital certificate fingerprint, for example, the SHA-256 hash value (fixed 32 bytes) of the agent's X.509 certificate; or a credential pointer, a DID URL pointing to a verifiable credential through which the parser can obtain complete credential information.

[0089] In this embodiment, the agent can be comprehensively described from multiple dimensions by using multiple fields included in the basic attribute information and multiple fields included in the initial state information, which enriches the agent resource information and facilitates subsequent agent query based on the agent resource information.

[0090] In an exemplary embodiment, the intelligent agent domain name resource registration method may further include step 402. Wherein:

[0091] Step 402: Periodically collect the latest status information of the agent based on a preset update frequency, and send a first update request to the domain name server based on the latest status information, so that the domain name server updates the corresponding fields in the stored agent resource information according to the latest status information contained in the first update request.

[0092] Understandably, since the state information of an agent is dynamically changing, if the agent's resource information is not updated in a timely manner, the state of the agent recorded in the resource information may not match the actual state of the agent, thus affecting the agent's query. Therefore, by periodically collecting the latest state information of the agent through a preset update frequency, the latest state data collected can be used to realize the dynamic updating of the agent's resource information and ensure the real-time nature of the agent's resource information.

[0093] In some embodiments, the status information may include multiple fields. Different fields in the status information may have different preset update frequencies. The latest status information of each field may be collected according to the preset update frequency of each field. Based on the status information of the field, a first update request for the field may be sent to the domain name server, thereby updating the content corresponding to the field in the domain name server.

[0094] In other embodiments, when different fields in the status information correspond to different preset update frequencies, the highest preset update frequency among all fields can be determined as the preset update frequency of the status information. Based on the preset update frequency of the status information, the latest status information of each field under the status information is collected, and based on the status information of each field, a first update request for the status information is sent to the domain name server, thereby updating the content corresponding to each field in the status information in the domain name server.

[0095] In some embodiments, the state of the agent can be detected in real time. When a change in the state of the agent is detected, the latest state information can be obtained, and the agent resource information can be updated through a first updated request.

[0096] In this embodiment, in the face of highly dynamic state information, the latest state information is collected periodically to realize the dynamic updating of state information in the agent resource information, ensuring the real-time performance and accuracy of state information in the agent resource information; at the same time, highly dynamic state information is allowed to be updated at a high frequency, without the need to frequently update relatively static basic attribute information, thereby effectively reducing system overhead and network traffic while ensuring information real-time performance.

[0097] In an exemplary embodiment, the intelligent agent domain name resource registration method may further include step 502. Wherein:

[0098] Step 502: Upon receiving upgrade information from the agent, collect the latest attribute information of the agent and, based on the latest attribute information, send a second update request to the domain name server so that the domain name server updates the corresponding fields in the stored agent resource information according to the latest attribute information contained in the second update request.

[0099] The upgrade information of the agent can be generated when the agent undergoes software upgrades or functional changes. It can be understood that receiving the upgrade information of the agent means that the agent's own attributes or functions have changed. Therefore, the latest attribute information of the agent can be collected when the upgrade information of the agent is received.

[0100] In some embodiments, considering that there may be multiple fields in the attribute information, and not all fields will change due to the upgrade of the agent, for example, the agent's identifier usually remains unchanged throughout its life cycle, it is also possible to determine the fields in the attribute information that need to be collected, and collect the latest attribute information of the corresponding fields in a targeted manner, thereby reducing unnecessary network overhead.

[0101] In this embodiment, the second update request ensures that the attribute information in the agent resource information can be updated in a timely manner when the agent is upgraded, thus ensuring the real-time nature of the agent resource information with a low update frequency.

[0102] In one exemplary embodiment, such as Figure 2 As shown in the illustration, this application also provides a method for querying domain name resources of an intelligent agent. Taking the application of this method to the domain name resolver corresponding to the client as an example, the domain name resolver can be deployed on the gateway device, local server, or cloud platform corresponding to the client, etc., including steps 602 to 610. Wherein:

[0103] Step 602: Receive an agent query request initiated by the client; wherein the agent query request includes agent filtering parameters.

[0104] Among them, the client's agent query request is initiated when the client needs to call the agent service; for example, when the client needs to call the image recognition service, it initiates an agent query request for image recognition.

[0105] Among them, the agent filtering parameters are parameters used to describe the agents that need to be queried; furthermore, the agent filtering parameters are determined based on the agent requirements of the client.

[0106] For example, the agent filtering parameter can be "&Capability.task-type=image-processing &max-latency=100", which means that you need to query agents that can provide image recognition services and whose maximum latency does not exceed 100ms.

[0107] In some embodiments, the agent filtering parameters included in the agent query request can be of multiple types, and different types of agent filtering parameters can have different priorities. In this way, if the corresponding agent cannot be found based on all the agent filtering parameters, it means that the agent restriction conditions are too strict. In this case, some low-priority agent filtering parameters can be abandoned, thereby relaxing the restrictions on the agent and ensuring a successful response to the agent query request.

[0108] Step 604: Parse the agent's query request to obtain the parsing result.

[0109] The parsing rules are predefined based on the data structure of the agent's query request. By parsing the agent's query request, interference from irrelevant information in the request can be removed, thereby improving the efficiency of subsequent request processing.

[0110] The parsing results should include at least agent filtering parameters; they may also include client identification information, session timestamp information, etc.

[0111] Step 606: Based on the resolution result, query the agent resource information of the target data structure pre-stored in the domain name system; the agent resource information of the target data structure includes the basic attribute information and state information of the agent.

[0112] Specifically, the agent filtering parameters contained in the parsing results are matched with the agent resource information of the pre-saved target data structure, and the agent indicated by the agent resource information that meets the agent filtering parameters is identified as the agent requested by the agent query request.

[0113] Step 608: Generate a corresponding response result based on the query result; wherein the response result includes target intelligent agent resource information that matches the parsing result.

[0114] Specifically, the queried target intelligent agent resource information is encapsulated to obtain the response result.

[0115] It should be noted that the target agent resource information that matches the parsing result can be one or more. When there are multiple target agent resource information, one can be selected and encapsulated to obtain the response result, or multiple target agent resource information can be encapsulated together to obtain the response result.

[0116] Of course, if no target agent resource information matching the parsing result exists, the restrictions on the agent can be relaxed by modifying some parameters in the agent filtering parameters, and then the query can be performed again based on the modified agent filtering parameters.

[0117] Step 610: Return the request response result to the client.

[0118] In some embodiments, when the request response result contains only one target agent resource information, the client can establish a connection with the agent indicated by the target agent resource information and initiate a service request based on the agent access path contained in the target agent resource information.

[0119] In other embodiments, when the request response contains multiple target agent resource information, the client can select one from the multiple target agent resource information according to preset conditions, establish a connection with the agent indicated by the selected target agent resource information according to the agent access path contained in the selected target agent resource information, and initiate a service request; for example, the preset conditions may be to select the one with the lowest current load, or to select the one with the lowest latency, etc.

[0120] Using the above-described intelligent agent domain name resource query method, when intelligent agent resource information of the target data structure is pre-stored in the domain name system, the intelligent agent can be accurately queried according to the intelligent agent query request. Then, a connection between the client and the intelligent agent can be established based on the queried intelligent agent resource information, so as to realize the client's access control over the intelligent agent.

[0121] In an exemplary embodiment, step 606 may further include step 702. Wherein:

[0122] Step 702: Based on the parsing result, query the local cache. If the target agent resource information that matches the parsing result is not found in the local cache, initiate a resource query request to at least one domain name server in the domain name system. At least one domain name server has pre-stored the target data structure agent resource information.

[0123] On the other hand, if the target agent resource information that matches the parsing result exists in the local cache, a request-response result can be generated and returned to the client based on the target agent resource information that matches in the local cache.

[0124] The local cache refers to the cache of the domain name resolver, which is generated by the domain name resolver based on historical agent query requests and their response results. For example, if the request vector result of historical agent query request a includes agent resource information b, it can be written into the local cache according to the agent filtering parameters of historical agent query request a and agent resource information b. If another agent query request with the same agent filtering parameters is received, the agent resource information b in the local cache can be used as the target agent resource information, and a request response result can be generated and returned to the client.

[0125] Furthermore, considering that the agent resource information in the domain name system is constantly being updated, a cache time for the local cache can be set. When the cached agent resource information reaches the cache time, it will be deleted from the local cache, thereby avoiding a mismatch between the agent resource information queried through the local cache and the agent resource information in the current domain name system.

[0126] In the above embodiments, the agent query request is initially queried through local caching. If no target agent resource information matching the parsing result is found in the local cache, the query is then performed through the domain name server, which further improves the response efficiency of the agent query request.

[0127] In one embodiment, please refer to Figure 3 , Figure 3An architectural block diagram of an intelligent agent query system according to an embodiment of this application is shown. In this architecture, a domain name query system from related technologies is reused, and the processing capability of intelligent agent queries is added to the existing domain name query system, as detailed below:

[0128] The intelligent agent query system includes an intelligent agent agent, an extended DNS server, an extended DNS resolver, and a client.

[0129] The agent agent is responsible for the agent itself. When the agent is first started, the agent agent collects the agent's basic attribute information and initial state information, and requests the extended DNS server to register the agent through a secure API (Application Programming Interface). After successful registration, the agent agent is also responsible for updating the agent's resource information through the secure API to ensure the real-time nature of the agent's resource information in the extended DNS server.

[0130] The extended server includes a secure update API, an Agent Resource Record (RR) storage area, and a traditional RR storage area (traditional domain name information storage area). The secure API is a secure channel (such as a RESTful API based on OAuth 2.0 or JWT tokens) reserved for agent registration and update requests from agent agents. The secure API is responsible for strict authentication and authorization, ensuring that only legitimate agents can modify their records. The agent resource information storage area stores the agent resource information registered by each agent agent agent. The traditional domain name information storage area stores the traditional domain name-IP mapping relationship.

[0131] The client runs an application that can provide various agent services. When the application needs to provide a certain type of agent service, it can send an agent query request to the extended DNS resolver for that agent service.

[0132] The extended DNS resolver includes an agent query request processing module (i.e., Agent RR query processing in the diagram) and a traditional domain name query request processing module (i.e., traditional RR query processing in the diagram). Specifically, the agent query request processing module can identify and process agent query requests. This module understands the structure of agent resource information and can perform preliminary matching and filtering based on the filtering parameters carried in the query request. The traditional domain name query request processing module is used to process regular domain name query requests.

[0133] In the agent query architecture shown above, compared to the domain name records in related technologies that only define service priority, weight, port, and hostname and cannot describe rich metadata such as service capabilities and status, this embodiment defines standardized, structured, and machine-readable agent resource information, specifically used to carry the complete capabilities and status of the agent. Moreover, it directly reuses and extends the globally ubiquitous DNS system, requiring no additional infrastructure deployment, and the agent can be discovered by any client in any corner of the world. In addition, the agent resource information adopts a structure that separates status and capabilities and allows for independent incremental updates, which can balance query efficiency and information dynamism.

[0134] In one embodiment, please refer to Figure 4 , Figure 4 It shows Figure 3 The interaction flowchart for agent registration is as follows:

[0135] When the agent starts up, the agent agent collects the agent's capabilities and state data, which is the basic attribute information and initial state information of this application. Then, the agent agent constructs Agent RR records (agent resource information) based on the collected information. Specifically, it performs data structure transformation on the basic attribute information and initial state information to obtain the agent resource information under the target data structure. Finally, it sends a registration request to the extended DNS server.

[0136] In the extended DNS server, the security API performs security verification based on the token included in the registration request. If the verification is successful, the Agent RR record is written to the Agent RR storage area.

[0137] Afterwards, the state is updated using a heartbeat mechanism, or periodically. The process of updating the request is similar to that of the registration request, and will not be described in detail here.

[0138] In one embodiment, please refer to Figure 5 , Figure 5 It shows Figure 3 The interaction flowchart for client-side queries is as follows:

[0139] When a client application needs to invoke the agent service, the client initiates an Agent query request (agent query request) to the extended DNS resolver; and establishes a connection with the agent based on the request response result.

[0140] After receiving a query request from an Agent, the extended DNS resolver parses the query request and queries the local cache based on the resolution result. If the local cache contains target agent resource information that matches the resolution result, it directly responds to the client based on the retrieved target agent resource information.

[0141] If no target agent resource information matching the resolution result is found in the local cache, an iterative query is initiated to the extended DNS server. After the extended DNS server finds the target agent resource information matching the resolution result, it returns the retrieved target agent resource information to the extended DNS resolver. If there are multiple returned target agent resource information entries, the extended DNS resolver can sort and filter the multiple target agent resource information entries, and finally return the response information generated by one or more target agent resource information entries to the client.

[0142] It should be understood that although the steps in the flowcharts of the above embodiments are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages in other steps. It is understood that the steps in different embodiments can be freely combined as needed, and all non-contradictory solutions formed by such combinations are within the scope of protection of this application.

[0143] Based on the same inventive concept, this application also provides an intelligent agent domain name resource registration device for implementing the aforementioned intelligent agent domain name resource registration method. The solution provided by this device is similar to the implementation described in the above method; therefore, the specific limitations in one or more embodiments of the intelligent agent domain name resource registration device provided below can be found in the limitations of the intelligent agent domain name resource registration method described above, and will not be repeated here.

[0144] In one exemplary embodiment, such as Figure 6 As shown, a schematic diagram of an intelligent agent domain name resource registration device is provided. The intelligent agent domain name resource registration device 800 includes:

[0145] The acquisition module 802 is used to acquire the basic attribute information and initial state information of the agent in response to the first start signal of the agent in the agent.

[0146] The processing module 804 is used to perform data structure transformation on the basic attribute information and initial state information to obtain the agent resource information under the target data structure.

[0147] The registration module 806 is used to send an agent registration request to the domain name server. The agent registration request contains agent resource information under the target data structure, so that the domain name server can save the agent resource information based on the agent registration request.

[0148] In one embodiment, the basic attribute information includes multiple fields, and the initial state information includes multiple fields; the processing module 804 is specifically used to combine each field in the basic attribute information and the initial state information based on the field type, the content length corresponding to the field, and the field content of the field to obtain the field information of the field; and based on the field information of each field, obtain the agent resource information under the target data structure.

[0149] In one embodiment, the basic attribute information includes multiple fields such as an identifier field, a version number field, and a function description field; the initial state information includes multiple fields such as a resource state field, an access path field, a time-to-live field, and a security verification field.

[0150] In one embodiment, the intelligent agent domain name resource registration device 800 further includes a first update module, which is used to periodically collect the latest status information of the intelligent agent based on a preset update frequency, and send a first update request to the domain name server based on the latest status information, so that the domain name server updates the corresponding fields in the stored intelligent agent resource information according to the latest status information contained in the first update request.

[0151] In one embodiment, the intelligent agent domain name resource registration device 800 further includes a second update module, which is used to collect the latest attribute information of the intelligent agent when receiving upgrade information of the intelligent agent, and send a second update request to the domain name server based on the latest attribute information, so that the domain name server updates the corresponding fields in the stored intelligent agent resource information according to the latest attribute information contained in the second update request.

[0152] Each module in the aforementioned intelligent agent domain name resource registration device 800 can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0153] Based on the same inventive concept, this application also provides an intelligent agent domain name resource query device for implementing the intelligent agent domain name resource query method described above. The solution provided by this device is similar to the implementation described in the above method; therefore, the specific limitations in one or more embodiments of the intelligent agent domain name resource query device provided below can be found in the limitations of the intelligent agent domain name resource query method described above, and will not be repeated here.

[0154] In one exemplary embodiment, such as Figure 7 As shown, a schematic diagram of an intelligent agent domain name resource query device is provided. The intelligent agent domain name resource query device 900 includes:

[0155] The receiving module 902 is used to receive an agent query request initiated by the client; wherein the agent query request includes agent filtering parameters.

[0156] The parsing module 904 is used to parse the agent's query request and obtain the parsing result.

[0157] The query module 906 is used to query the agent resource information of the target data structure pre-stored in the domain name system based on the resolution result; the agent resource information of the target data structure includes the basic attribute information and state information of the agent.

[0158] The response module 908 is used to generate corresponding response results based on the query results; the response results include target agent resource information that matches the parsing results.

[0159] The transmission module 910 is used to return the request response result to the client.

[0160] In one embodiment, the query module 906 is specifically used to query the local cache based on the parsing result. If the target agent resource information that matches the parsing result is not found in the local cache, a resource query request is initiated to at least one domain name server in the domain name system. At least one domain name server has pre-stored the agent resource information of the target data structure.

[0161] Each module in the aforementioned intelligent agent domain name resource query device 900 can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0162] In one exemplary embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 8As shown, this computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The database stores intelligent agent resource information data. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communicating with external terminals via a network connection. When executed by the processor, the computer program implements an intelligent agent domain name resource registration and query method.

[0163] Those skilled in the art will understand that Figure 8 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0164] In one exemplary embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the method described above.

[0165] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-described method.

[0166] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps of the method described above.

[0167] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0168] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0169] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0170] The above embodiments are merely illustrative of several implementation methods of this application, and their descriptions are relatively specific and detailed. However, they should not be construed as limiting the scope of this application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for registering domain name resources for intelligent agents, characterized in that, The method includes: In response to the first startup signal of the agent in the agent, the basic attribute information and initial state information of the agent are obtained; The basic attribute information and the initial state information are transformed into a data structure to obtain the agent resource information under the target data structure. A smart agent registration request is sent to the domain name server. The smart agent registration request contains smart agent resource information under the target data structure, so that the domain name server can save the smart agent resource information based on the smart registration request.

2. The method according to claim 1, characterized in that, The basic attribute information includes multiple fields, and the initial state information includes multiple fields; The process of transforming the basic attribute information and the initial state information into a data structure to obtain agent resource information under the target data structure includes: For each field in the basic attribute information and the initial state information, the field information is obtained by combining the field type, the content length corresponding to the field, and the field content of the field. Based on the field information of each field, the agent resource information under the target data structure is obtained.

3. The method according to claim 2, characterized in that, The basic attribute information includes multiple fields such as an identifier field, a version number field, and a function description field; the initial state information includes multiple fields such as a resource status field, an access path field, a time-to-live field, and a security verification field.

4. The method according to any one of claims 1-3, characterized in that, The method further includes: The latest status information of the agent is periodically collected based on a preset update frequency, and a first update request is sent to the domain name server based on the latest status information, so that the domain name server updates the corresponding fields in the stored agent resource information according to the latest status information contained in the first update request.

5. The method according to any one of claims 1-3, characterized in that, The method further includes: Upon receiving the upgrade information of the agent, the latest attribute information of the agent is collected, and based on the latest attribute information, a second update request is sent to the domain name server, so that the domain name server updates the corresponding fields in the stored agent resource information according to the latest attribute information contained in the second update request.

6. A method for querying domain name resources of an intelligent agent, characterized in that, include: Receive an agent query request initiated by the client; wherein the agent query request includes agent filtering parameters; The query request from the intelligent agent is parsed to obtain the parsing result; Based on the resolution result, query the agent resource information of the target data structure pre-stored in the domain name system; the agent resource information of the target data structure includes the basic attribute information and state information of the agent; A corresponding response is generated based on the query results; wherein, the response results include target agent resource information that matches the parsing results; Return the request response result to the client.

7. The method according to claim 6, characterized in that, The process of querying the agent resource information of the target data structure pre-stored in the domain name system based on the resolution result includes: Based on the parsing result, the local cache is queried. If the local cache does not contain target agent resource information that matches the parsing result, a resource query request is initiated to at least one domain name server in the domain name system. The at least one domain name server has pre-stored the target data structure agent resource information.

8. A smart agent domain name resource registration device, characterized in that, The device includes: The acquisition module is used to acquire the basic attribute information and initial state information of the agent in response to the first start signal of the agent in the agent terminal; The processing module is used to perform data structure transformation on the basic attribute information and the initial state information to obtain the agent resource information under the target data structure; The registration module is used to send an agent registration request to the domain name server. The agent registration request contains agent resource information under the target data structure, so that the domain name server can save the agent resource information based on the agent registration request.

9. A smart agent domain name resource query device, characterized in that, The device includes: A receiving module is used to receive an agent query request initiated by a client; wherein the agent query request includes agent filtering parameters; The parsing module is used to parse the query request from the intelligent agent and obtain the parsing result; The query module is used to query the agent resource information of the target data structure pre-stored in the domain name system based on the resolution result; the agent resource information of the target data structure includes the basic attribute information and state information of the agent; A response module is used to generate a corresponding response result based on the query result; wherein, the response result includes target intelligent agent resource information that matches the parsing result; The transmission module is used to return the request response result to the client.

10. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 7.

11. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

12. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

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