513 results about "Service component" patented technology

The invention discloses a hardware basic service component test system, which comprises a test management module, a hardware simulation module, an automatic test module, a data acquisition module, a data analysis module, a report generation module and a feedback adjustment module, the hardware simulation module is used for simulating hardware environments under different load conditions; the automatic test module is used for executing predetermined test tasks; the data acquisition module is used for monitoring hardware states and performance data in real time; the data analysis module is used for analyzing the acquired data; abnormal behaviors are identified and performance is evaluated, a report generation module generates a test report, and a feedback adjustment module dynamically adjusts test parameters and resource allocation according to an analysis result. The hardware basic service component testing efficiency, accuracy and comprehensiveness are improved, and the method can be applied to the technical field of hardware testing.

The invention relates to the technical field of distributed computing and cloud computing, in particular to a multi-service and multi-tenant-oriented micro-service method and system, and the method comprises the steps: constructing a dynamic modular service framework based on a pluggable service component, a cross-tenant service module based on resource sharing, and a multi-service and multi-tenant service module based on resource sharing; modeling the calling relationship between the micro-services and calculating each resource demand weight coefficient of the micro-services; and scheduling the resource-shared cross-tenant service module by using the dynamic resource allocator. According to the method, the dynamic modular service framework based on the pluggable service component is constructed, so that accurate loading and unloading of each service module of the micro-service can be completed within hundreds of milliseconds, and the agility of the system is remarkably improved. According to the method, calling relation modeling is carried out on the cross-tenant service module, the resource demand weight coefficient is calculated, basic data is provided for resource scheduling, load changes are considered, optimal configuration of resources is achieved, and the overall performance and the response speed of the system are improved.

The invention provides a method for realizing agent development MCP service through computing power of an intelligent computing center, and relates to the technical field of intelligent computing centers, intelligent computing centers and computing power infrastructure, the method comprises the following steps: S1, determining interface information of a target application programming interface API, the target API being an interface of a target platform; s2, generating a first coding task based on the interface information through an intelligent agent of the intelligent computing center; s3, generating a first MCP service component corresponding to the first coding task through the intelligent agent; and S4, registering the first MCP service component to the intelligent computing center. According to the invention, the development efficiency of the MCP service of the intelligent computing center can be greatly improved.

The invention provides an intelligent computing center model development method and device oriented to the Plevatory computing power, and relates to the technical field of computing power infrastructure, the method comprises the following steps: S1, receiving first mirror image data of a to-be-developed model; s2, a first node is obtained, the first node is a node occupying graphics processing unit (GPU) resources of the intelligent computing center, and the first node comprises a debugging service component; s3, adjusting the first mirror image data based on the debugging service component; and S4, after the adjustment of the first mirror image data is completed, closing the first node, and releasing GPU resources occupied by the first node. According to the method, GPU resources can be prevented from being continuously occupied, the load of the intelligent computing center is reduced, the intelligent computing center can provide computing power service for more users, and the general application of computing power is realized.

The invention relates to an inference system and method for a large model. The system comprises a routing component, a pre-fill component, a decoding service component deployed independently of the pre-fill component, and a communication component between the pre-fill component and the decoding service component. The routing component routes the data processing request before long to the pre-filling component for pre-filling processing based on the token information of the current data processing request, and routes the data processing request before short to the decoding service component for decoding processing; and performing load balancing routing based on the load states of the plurality of reasoning forces in the prefill component or the decode service component.

The invention relates to a concurrent task processing method and device based on an event-driven architecture, computer equipment, a storage medium and a program product. The method comprises the following steps: receiving concurrent service events which are fed back by an event generation service component and respectively correspond to different service operations, publishing the plurality of concurrent service events to a message queue, and respectively carrying out event classification processing on the plurality of concurrent service events in the message queue according to a trained event classification model, and obtaining an event type corresponding to each concurrent service event, and determining the event type as a service theme corresponding to the concurrent service event. And in response to subscription requests triggered by different event consumption service components for the business theme, asynchronously feeding back at least one concurrent business event associated with the business theme to the event consumption service components, and asynchronously executing task operations corresponding to the concurrent business events through the different event consumption service components to obtain task execution results. By adopting the method, the concurrent task processing efficiency can be improved.

The invention provides a graphical construction and edge deployment method for configuration software development for a micro-service architecture, which comprises the following steps of: constructing an interface and logic of configuration software by adopting a graphical interface through operations such as drag-drop, connection and the like; establishing a graphical component library comprising a plurality of predefined micro-service components, wherein the predefined micro-service components comprise data acquisition, processing, storage, display and the like; the predefined micro-service component supports conversion of the graphical component into an executable micro-service code, and configuration software is constructed; deploying the micro-service of the configuration software at a position close to a data source in combination with an edge computing node deployment strategy; the edge deployment framework automatically completes deployment and starting of the micro-service according to the configuration file and supports automatic deployment, monitoring and upgrading of the micro-service; the states of the edge computing nodes are monitored through a graphical interface, and remote configuration and management are carried out; and performing real-time viewing, log analysis, troubleshooting and the like on the node state. The development efficiency is improved.

Embodiments are directed to a virtual microcontroller for device authentication in a confidential computing environment. An embodiment includes a processor to implement a service trust domain (TD) as a virtual microcontroller (VMC) trust domain (VMC-TD) for a device, where the VMC-TD is to support protocols for device authentication, device measurement, and device management; and receive a VMC certificate chain that is endorsed by a startup service component comprising at least one of a trusted module of the confidential computing environment, the VMC certificate chain comprising a root certificate of the startup service component, a startup services module signing certificate, and a full VMC certificate comprising the initial VMC certificate and a TD report comprising a measurement of the device.

The invention is suitable for the technical field of software development, and provides a bidirectional interaction method and system based on a low-code front-end rendering engine, and the method comprises the steps: a product side adds a dynamic component in a component library, uses the dynamic component and a plurality of low-code components to package the rendering engine, and issues the rendering engine through an intranet warehouse, the business side selects a low-code integration scheme by using a low-code system based on business requirements so as to complete low-code page development, takes a page code pageId or DSL of the low-code page and all customized development business components as input parameters and injects the input parameters into a rendering engine; the business component developed in a customized mode controls low-code content by obtaining a context when a rendering engine runs; and the rendering engine binds the service component which is developed in a customized manner by analyzing the JS code injected by the low-code component configuration item and controlling the context during operation of the low-code component configuration item. Therefore, two-way communication and mutual control between the low-code rendering engine and the customized development content are achieved, and the flexibility and practicability of a low-code platform are remarkably improved.

The invention relates to the technical field of private domain knowledge updating, and discloses an MCP protocol-oriented private domain knowledge dynamic updating method and system, which monitor the change of a private domain knowledge source in real time through an updating agent component, and calculate a hierarchical hash abstract to efficiently detect a change event. Once the change is found, the change is compared with the root hash which is successfully notified last time, and if the change is different from the root hash which is successfully notified last time, an update notification is sent to a knowledge update service component through an MCP protocol. And after confirming the root hash difference, the receiving end requests the increment message to obtain the specific change content. And then, the updating agent component accurately locates the changed knowledge unit, extracts an incremental data packet and transmits the incremental data packet to the knowledge updating service component for application through an MCP protocol. Therefore, not only are unnecessary network bandwidth and computing resource consumption greatly reduced, but also the real-time performance and accuracy of data updating are remarkably improved, and powerful support is provided for efficient decision making of enterprises.

The invention belongs to the technical field of software system optimization and intelligent operation and maintenance, and discloses a shared platform autonomous upgrading method based on a graph neural network, and the method comprises the following specific steps: S1, component state perception and feature coding; s2, constructing a heterogeneous dynamic evolution diagram; s3, dynamic graph neural network embedding modeling; s4, state prediction and conflict evaluation; s5, constructing an upgrade game diagram and strategy reasoning; s6, executing an upgrading plan and real-time feedback acquisition; and S7, graph structure reconstruction and strategy closed-loop optimization. According to the method, the heterogeneous dynamic evolution diagram is constructed, the time sequence label and the state quantification model are introduced, real-time sensing and standardized modeling can be carried out on the running state of each service component in the sharing platform, and compared with a traditional upgrading method depending on static configuration and a predefined template, the upgrading efficiency is greatly improved. According to the mechanism, inductive expression of multi-dimensional features such as node resource occupation, access frequency and response fluctuation is completed in the stage before upgrading.

The invention provides an intelligent intelligent supervision system for civil aviation VoIP communication equipment, relates to the basic field of civil aviation air traffic control equipment, and solves the limitation problems of non-centralized supervision, imperfect supervision, non-autonomous supervision and the like existing in an existing supervision mode. The system comprises a system architecture module which adopts a layered modular design to construct a double-layer system comprising a top layer management architecture and a bottom layer operation architecture; the function service module comprises an equipment state monitoring unit, a risk assessment engine and an operation and maintenance management unit; the data processing architecture forms a multi-stage processing channel by a data acquisition layer, a data transmission layer, a data storage layer, a data calculation layer and a data application layer which are connected in sequence; the technical support system comprises a micro-service component group, a continuous integration platform and a security authentication module. The intelligent supervision network architecture of the VoIP communication equipment is subjected to brand-new autonomous design, transformation from passive response to active management is completed, and the supervision efficiency and the treatment efficiency are improved.

The invention provides an interaction method and device, equipment, a medium and a program product. A specific embodiment of the interaction method in the application comprises the steps of generating a question message based on a question operation; inputting the question message into the large model to obtain streaming response data returned by an interface of the large model; and converting the streaming response data into a text content type, and performing streaming rendering by using a service component in the large model interaction system to generate an answer message corresponding to the question message. According to the implementation mode, interaction with the business system can be easily realized in a large model interaction system in a mode of injecting the business component, so that all business systems can be supported by one set of system.

The invention discloses a data query method, device and equipment. The method comprises the following steps: firstly, obtaining a data query request proposed by a user; then, combining the data query request with a prompt instruction prompt, and inputting the data query request into a preset large language model for identification of user intention and preliminary screening of data query service components MCP to obtain N MCPs; wherein N is a positive integer greater than zero; collecting parameter information required by N MCPs through a large language model; calling a corresponding MCP service instance according to the parameter information required by the N MCPs and a preset calling mode; and data query can be carried out by using the MCP service instance to obtain a data query result. Therefore, the accuracy of the data query result and the availability of the system can be effectively improved.

The invention relates to the technical field of embedded system testing, in particular to a method for testing functionality and stability of a core board service component, which comprises the following steps of: initializing a core board testing environment, ensuring that software and hardware parameters are consistent in a testing process, and aiming at the service component on a core board, testing the service component on the core board; the method comprises the following steps of: analyzing and generating a dependency relationship graph among components by utilizing a dependency graph model, optimizing a key dependency relationship through a deep learning model, performing functional testing on the components according to a priority based on the optimized dependency relationship graph, and testing the stability of a core board during high-concurrency and multi-task operation through multi-thread scheduling and concurrent task simulation. Abnormal, resource competition and deadlock problems are detected; and finally, in combination with an actual application scene, carrying out component hot plug, network abnormity, power-off recovery and other scene tests, and analyzing test data to generate a comprehensive test report. According to the method, the test coverage rate and efficiency are improved, and stable operation of the system under complex conditions is ensured.

The embodiment of the invention provides a reserved resource configuration method and device, equipment, a storage medium and a program product, and relates to the field of cloud computing. The method comprises the following steps: detecting a first state of a node server in a Kubernetes cluster, wherein the first state is a hardware resource which can be allocated to a container by the node server; determining a target action in actions corresponding to the first state by a pre-trained reinforcement learning model according to the first state, the actions including increasing or decreasing hardware resources reserved for a core process of an operating system of the node server and increasing or decreasing hardware resources reserved for a core service component of the Kubernetes system; and controlling the node server to execute the target action. According to the method provided by the invention, the hardware resources reserved by the node server for the core process of the operating system and the core service component of the Kubernetes system are dynamically adjusted according to the hardware resources which can be allocated to the container by the node server through the pre-trained reinforcement learning model.

The present application belongs to the technical field of computer applications. Disclosed are a detection method and device for an abnormal dependency, and a storage medium. In the present application, component dependency topology information corresponding to a component library is acquired, wherein the component dependency topology information comprises component description information, a component dependency relationship and a component architecture level that correspond to each micro-service component in the component library, the component dependency relationship is used for representing other micro-service components on which the running of the micro-service component needs to depend, and the component architecture level is used for representing an architecture level to which the micro-service component belongs in a service architecture; and on the basis of the component dependency topology information, whether there is an abnormal dependency between the micro-service components in the component library is detected.

The invention belongs to the technical field of computer application, and discloses an abnormal dependency detection method and device and a storage medium. According to the method, the component dependency topology information corresponding to the component library is obtained, the component dependency topology information comprises the component description information, the component dependency relationship and the component architecture hierarchy corresponding to each micro-service component in the component library, and the component dependency relationship is used for representing other micro-service components which the micro-service components need to depend on during operation; the component architecture hierarchy is used for representing an architecture hierarchy to which the micro-service component belongs in the service architecture; and detecting whether the micro-service component in the component library has abnormal dependency based on the component dependency topology information. As the component dependency topology information corresponding to the component library can be obtained, and various types of abnormal dependencies are detected by adopting different modes according to the information contained in the component dependency topology information, the abnormal dependency detection of the micro-service component in the component library is quickly realized by utilizing automatic detection.

The invention relates to the field of software deployment scheme optimization, and discloses a quick application system deployment method based on a two-stage resource allocation mechanism, which comprises the following steps of: performing complete set service modeling, performing modeling on deployment resource requirements of an application system in a layered manner, and performing resource allocation; the method comprises the following steps: modeling and describing deployment requirements of four service components, namely a basic platform service component, a platform component service component, an application service component and an application component, according to an application system architecture layer; deploying a basic management service, wherein the basic management service comprises a management node module and an agent node module; the system generates a to-be-deployed background service list according to an application requirement of a user and a strategy; the system automatically plans and deploys basic platform services according to a first-level resource allocation method; the basic platform service automatically plans and deploys platform component service and application service according to a secondary resource allocation algorithm; and the user downloads and uses the application system according to requirements. The automation of the deployment process is enhanced, the deployment difficulty and working time of deployment personnel are reduced, and certain universality is achieved.

The invention particularly relates to a spatial analysis method based on large model agent driving. According to the spatial analysis method based on large model agent driving, syntactic analysis and intention recognition are carried out on a spatial problem described by a natural language through a large model, and spatial-temporal clustering, network analysis and a field simulation algorithm module are dynamically matched; packaging a heterogeneous algorithm into a standardized service component based on a model context protocol (MCP), and automatically constructing an analysis process chain; and integrating a GIS engine and a visual template library, generating a dynamic thematic map according to the processed spatio-temporal data through the visual engine, and superposing multi-dimensional analysis annotations. According to the spatial analysis method based on large model agent driving, the full-chain intelligent capability from data processing to decision support is constructed, the efficiency and precision of spatio-temporal evolution modeling are remarkably improved, meanwhile, the system integration and maintenance cost is reduced, the method is suitable for high-complexity scenes needing real-time spatio-temporal data analysis, and the method is suitable for popularization and application. And the method has remarkable technical innovation and industrial application value.

A system may include a directory-based identity-related services component that authenticates and authorizes enterprise users and computers in a network and enforces security policies. A business intelligence, application development, and application connectivity component may implement business workflow products and exchange application authentication data with the directory-based identity-related services component. A database storage component may provide document management and storage of dashboard tables and lists associated with inventory data received from the business intelligence, application development, and application connectivity component. A cloud-based storage and data management engine may exchange secure authentication storage data with the business intelligence, application development, and application connectivity component. At least one governance or user application may then automatically determine enterprise site inventory information, and, responsive to the determined enterprise site inventory information, automatically determine enterprise site membership information. The dashboard tables and lists may be exchanged in support of a graphical user display.

The invention belongs to the technical field of micro-service scheduling, and discloses an APP micro-service intelligent arrangement and scheduling method and device based on a fast application, and a medium. The method comprises the following steps: firstly, performing feature extraction on equipment data to obtain feature data with high representativeness, secondly, creating an atomization service component and a service dependency relationship graph by splitting service instances, and then, on the basis of considering the dependency relationship among services, resource requirements, network bandwidth and service performance by adopting a multi-objective optimization algorithm, establishing an atomization service component and a service dependency relationship graph. And optimizing a scheduling decision, designing an alternative path and a service degradation scheme, establishing a service scheduling strategy, and finally realizing flexible scheduling of service instances based on the set service scheduling strategy. According to the method, the technical problems of insufficient resources, delay, service interruption and the like in a high-concurrency environment are effectively solved, and the performance and the reliability of the industrial APP in a complex environment are improved.

The invention provides an online interactive programming education system based on a micro-service architecture, and the system comprises an infrastructure layer which serves as a bottom layer computing power and provides an elastic computing power through a cross-cloud deployment technology and a dynamic resource scheduling technology; the platform core layer constructs a stateless micro-service cluster through a service registration discovery module, a load balancing module and a fusing mechanism module depending on elastic resources of the infrastructure layer, and the infrastructure layer provides physical resource guarantee for operation of the micro-service cluster of the platform core layer; the platform support layer is used for integrating an authority management component, a workflow engine component and a general service component based on a stateless micro-service cluster constructed on the platform core layer, and providing resource isolation and high-concurrency task scheduling support in a multi-tenant environment for the programming education system; the platform core layer is combined with distributed transaction management to provide stable service scheduling and communication capability for an authority management component, a workflow engine component and a general service component of the platform support layer; and the platform application layer combines service scheduling and communication capabilities, realizes teaching functions such as multi-language development, code debugging visualization, AI personalized suggestion and collaborative learning, and directly serves programming learning of students and teaching management requirements of teachers.

The software resource management method, device, storage medium and computer equipment provided by the present application first deploy a target Docker environment when performing software resource management, and build an image repository based on the environment to centrally manage software images of various types and versions; then, based on the image management strategy, pull the software image corresponding to the custom configuration file from the image repository to allocate software resources on demand to create containers, thereby improving the speed and flexibility of software management; then, use network communication components to establish network connections between containers, and manage data for each container through digital volumes, thereby promoting the collaborative work between different service components under the microservice architecture, and further enhancing the flexibility and security of software resource management; finally, the operating status of each container can be monitored in real time, and software resources can be dynamically adjusted according to the monitoring results to improve resource utilization, thereby improving the application efficiency of Docker technology in software resource management.

The invention discloses a data distribution method and system, and the method comprises the steps: dividing to-be-processed data into a plurality of data subsets, determining tasks and service components corresponding to the data subsets, determining the dependency relationship between the tasks, and the operation resource demands of the service components, and carrying out the processing of the to-be-processed data. Determining a calling relationship between the service components and a communication resource demand of the calling relationship between the components; on the premise that operation resource requirements of service components on a server are less than available computing resources of the server, and communication resource requirements of a calling relationship between the components are less than or equal to available communication resources between the servers where the components are located, data processing benefit maximization is taken as a target; and the tasks, the service components and the data subsets are distributed to the servers, so that reasonable distribution of the data is realized, and subsequent data processing benefits can be improved.

The invention discloses a distributed micro-service architecture service component efficient management and control method based on an intelligent learning model, and belongs to the field of intelligent operation and maintenance, and the method comprises the steps: S1, constructing a multi-granularity service component map, collecting service calling data, mapping the service calling data into a third-order tensor, eliminating non-service flow, and carrying out smooth processing; s2, performing parallel orthogonal subspace slice mapping on the tensor, and extracting an abnormal path subtensor set; s3, constructing a dynamic health assessment model based on the heterogeneous service dependency graph, and fusing indexes such as response time delay and overload frequency; s4, constructing a nested meta-learning model fusing support vector classification and graph convolution, and generating a strategy group; s5, expanding a service behavior response function in a disturbance environment, and improving the coverage rate of a strategy to a rare state; s6, based on an execution engine of a rescheduling factor, guiding the resources to be redirected to a high-aggregation-degree substructure; and S7, comparing the structure entropy change to judge whether to enter the next round of intervention or adjust the disturbance source. The beneficial effects are that abnormity is accurately detected, health is dynamically evaluated, and scheduling efficiency is improved.

A system and method for determining root causes of a failure in a virtual desktop system in real time is disclosed. The virtual remote desktop system has interconnected service components to make a virtual desktop available on a client device, and agents monitoring events from the components. An event collection module is coupled to the agents of the desktop system. The event collection module compiles events from the components relating to the failure. An aggregation module is coupled the event collection module. The aggregation module correlates events in a time-ordered stream relating to the fault. A diagnosis analysis system identifies one of the events of the time-ordered stream as the likely root cause of the fault.

The invention belongs to the technical field of cloud computing resource management, and provides a service elastic scaling system based on resource calling, which comprises a resource calling analysis module used for constructing a dynamic resource dependency graph by monitoring calling relations of service components in an application program, and analyzing the resource calling analysis module; analyzing historical calling data in the dynamic resource dependence graph by using a long-short-term memory network model, and predicting a future resource demand condition; the elastic scaling strategy generation module is used for dynamically generating a priority queue of resource calling and generating an elastic scaling strategy based on the topological structure and the real-time load data of each service component; and the elastic scaling implementation module is used for implementing service elastic scaling through resource buffering and fusing of resource calling abnormity according to the elastic scaling strategy. According to the method, the application program resource calling link is analyzed, the machine learning prediction and the security policy are combined to dynamically optimize the scaling decision, the calculation overhead caused by frequent starting and stopping of resources can be reduced, and the data security and the service stability are improved.

A disclosed method facilitates communications between an edge device and a cloud-based service component via an enterprise proxy without configuring the enterprise proxy to allow access to a service domain associated with the cloud-based service component. The method includes receiving, at a first proxy on the edge device, a service domain connection request from the service agent that specifies a service domain associated with the cloud-based service component. The first proxy responds to the first connection request by transmitting a sequence of nested connection requests including an inner connection request and an outer connection request. The inner connection request establishes a first communication channel between the first proxy and a cloud-based gateway. The outer connection request is transmitted along the first communication channel and establishes a second communication channel between the cloud-based gateway and the service domain requested by the service agent.

A system includes a memory configured to store a software application and a plurality of microservices including a set of independent software service components configured to be independently executed. The system includes processors operably coupled to the memory and configured to receive a request to initiate an execution of interactions with the software application for satisfying the request, and to identify, based on the request, one or more microservices to be executed to initiate the execution of the interactions with the software application. The processors further execute one or more generative machine-learning models trained to identify anomalous interservice interaction patterns between the one or more microservices. In response to identifying the anomalous interservice interaction patterns, the processors dynamically update operations processes associated with the one or more microservices, and further execute the one or more microservices to initiate the execution of the one or more interactions with the software application.