14 results about "Service choreography" patented technology

The invention relates to the field of edge computing, in particular to a primary and secondary fusion complete ring main unit energy efficiency optimization system based on cloud edge collaboration. The system comprises an edge device deployment and data acquisition module used for collecting operation electric parameters and device states and generating a service calling request; the service calling module is used for screening target control parameters under security constraints based on the energy efficiency optimization service package; the data synchronization module unloads the data to a cloud platform through a message queue protocol; the cloud service arrangement module aggregates the data updating service package and issues the data updating service package to the edge; and the real-time control module converts the parameters into instructions to drive equipment to act. A cloud training and edge reasoning collaborative architecture is adopted, the problems that local control lacks adaptivity, edge resources are limited and full-cloud control communication time delay exists are solved, and real-time energy efficiency optimization is achieved.

The invention provides a service orchestration method and device and related equipment, and the method comprises the steps: obtaining a first state space and a first action space of a to-be-orchestrated service, the first state space being used for representing the states of a server and an interface related to the to-be-orchestrated service, and the first action space being used for representing the states of the server and the interface related to the to-be-orchestrated service; the first action space is used for representing an interface function and a calling relation of an interface related to the to-be-arranged service; based on the first state space and the first action space, generating first calling information of an interface related to the to-be-arranged service; based on the first action space, M candidate interface calling sequences of the to-be-arranged service are generated, and M is a positive integer; selecting a target interface calling sequence matched with the first calling information from the M candidate interface calling sequences; and performing link configuration on the to-be-arranged service based on the target interface calling sequence.

Provided in the present disclosure are a digital twin service orchestration method, system and device, a storage medium and a product. The method comprises: receiving at least one twin task request sent by a demander, the twin task request carrying a first quality of service requirement of the demander for twin services; mapping the first quality of service requirement to a second quality of service requirement for twin service chains; on the basis of the second quality of service requirement, searching a plurality of registered twin models for corresponding target twin models; and requesting for the target twin models from corresponding twin model libraries, and performing parallel orchestration on the target twin models corresponding to the twin task request, so as to generate parallel twin service chains.

The present invention discloses a dedicated wireless protocol stack and service orchestration method for video streaming, wherein the dedicated wireless protocol stack is constructed as a cloud-edge-end system architecture, including a core network, a service-based RAN and a terminal device: the core network is deployed in the cloud and connected to a video application server; the service-based RAN is deployed at the edge of the network to provide wireless access services for the terminal device, and the service-based RAN includes a service management network element and a local AI service; the terminal device is wirelessly connected to the service-based RAN and uploads the video stream data collected by its camera through the service-based RAN using different processing strategies according to different resolutions: for 4K video stream: when the service-based RAN discovers the local AI service, the 4K video stream collected by the terminal device is diverted to the local AI service deployed at the edge of the network for processing; for 480P video stream: the service-based RAN directly transmits the 480P video stream uplink through the core network to the video application server deployed in the cloud for intelligent analysis and processing.

The present invention relates to the field of digital service technology, and the present invention discloses a service orchestration system and optimization method based on a rule engine, including a rule parsing module, a service registration center module, an orchestration engine module, an execution engine module, a monitoring feedback module, and a fault-tolerant module. The present invention introduces feature vectors to carry out fine-grained modeling of service attributes, which can comprehensively quantify the performance, resource consumption and dependencies of services, and provide a scientific basis for the precise disassembly of services. With the help of the optimal path search mechanism of reinforcement learning, the system can autonomously optimize the scheduling path in continuous exploration, dynamically balance service quality, resource consumption and risk control, and significantly improve the intelligent decision-making ability of the system. By establishing a fuse model, the fault-tolerant module can respond quickly and adopt corresponding strategies when facing instantaneous and persistent faults to ensure the continuity of services. It supports dual-channel input of natural language description and flowchart sketch, which lowers the threshold for system design.

The present application relates to the field of edge computing, and particularly to a primary and secondary fusion complete ring network box energy efficiency optimization system based on cloud edge cooperation. The system comprises: an edge device deployment and data acquisition module, which collects operating electrical parameters and device states, and generates a service call request; a service call module, which filters target control parameters under safety constraints based on an energy efficiency optimization service package; a data synchronization module, which unloads data to a cloud platform through a message queue protocol; a cloud service orchestration module, which aggregates data update service packages and distributes them to the edge; and a real-time control module, which converts parameters into instructions to drive device actions. The present application adopts a cloud training and edge reasoning cooperative architecture, solves the problems of lack of adaptability in local control, limited edge resources, and communication time delay in full cloud control, and realizes real-time energy efficiency optimization.

The embodiments of this specification disclose a task scheduling method, device and medium based on a language big model, which relate to the field of artificial intelligence technology. The method includes: obtaining task information to be scheduled and a pre-set service library of the task to be scheduled, the service library including multiple services and service information of each service; generating a task description text of the task to be scheduled based on the task information to be scheduled, the task description text including task input and output information; determining a service set description text corresponding to the service library based on the service information of each service in the service library, the service set description text including multiple service descriptions, each service description including service input and output information; determining a task scheduling result of the task to be scheduled based on the task description text of the task to be scheduled and the service set description text corresponding to the service library through the language big model, the task scheduling result including multiple required services and the service scheduling order between the multiple required services.

The invention provides a heterogeneous service dynamic arrangement method, application method and device, and the method comprises the steps: setting a basic protocol, and creating the service configuration of the basic protocol for services employing other protocols; dividing a service hierarchical structure and constructing a service connection component; defining parameters of the service as input parameters for arranging the initial service; logic calculation is carried out according to a condition judgment device in the service connection assembly and a preset rule engine, service arrangement is executed according to a judgment result, an unpacker, a packer, a combiner and a filter in the service connection assembly are utilized to carry out decomposition, combination, deletion and other processing on service data, and finally a new service is constructed and obtained. The orchestration method provided by the invention can improve the orchestration efficiency and the new service performance.

The invention provides a service orchestration execution method, device and equipment. The method comprises the following steps: constructing a CFS object of a service delivery task; setting execution attributes of each RFS object in the CFS objects; based on the order data and the resource instance data, instantiating the CFS object to obtain a CFS instantiation message, and based on the CFS instantiation message, generating a structured form of the RFS object of the manual execution category; and executing a service delivery task based on the CFS object and the received filling information of the structured form. All automatic or manual service delivery links are incorporated into a unified CFS / RFS object for management, so that unified modeling of service delivery tasks is realized. And the received structured form filling information is used as a basis for driving subsequent tasks to be executed, so that a manual processing link and an automatic flow control execution process are realized, and the execution efficiency of the whole service delivery task is improved.

The invention relates to the technical field of industrial software and system integration, in particular to a flexible pluggable production line digital service integration framework system, comprising an access layer comprising a data acquisition gateway for acquiring original data of equipment and a protocol adapter cluster for converting the original data of the equipment into structured data; the middle layer comprises a data integration engine used for processing the structured data into a standardized data object, a service orchestration engine used for performing service orchestration on the standardized data object to generate business data, and a message bus and communication module used for transmitting the business data to a target system; the application layer comprises an open API gateway used for providing an API interface for the message bus and the communication module; and packaging the function module into an independent Docker container, deploying an OSGi framework on an application layer, and realizing hot plugging of the Docker container through the OSGi framework. According to the invention, the expandability, availability and maintenance efficiency of the system are improved.

The present disclosure relates to techniques for service orchestration in distributed pod-based systems. In particular, aspects relate to receiving, in a kernel residing in a distributed computing environment, a request to initiate deployment for a subservice or service on the distributed computing environment. The subservice or service has a type, and in order for the subservice or service to be deployed in the distributed computing environment, the subservice or service type must be one that the distributed computing environment is configured to support. In response to receiving the request and that the subservice or service type is one that the distributed computing environment is configured to support, specified resources are provisioned, and the subservice or service is deployed using a replica of a pod that includes the provisioned specified resources and a modified image for the subservice or service type.

The application provides a heterogeneous service dynamic arrangement method, an application method and an apparatus, comprising: setting a basic protocol, creating a service configuration of the basic protocol for a service adopting other protocols; dividing a service hierarchical structure and constructing a service connection component; defining parameters of the service as input parameters of an arranged starting service; performing logical calculation according to a preset rule engine according to a condition judge in the service connection component, executing service arrangement according to a judgment result, and performing decomposition, merging, deletion and other processing on service data by using a unpacker, a packer, a merger and a filter in the service connection component, and finally constructing a new service. The arrangement method provided by the application can improve arrangement efficiency and new service performance.

The invention discloses a service orchestration method and device, electronic equipment and a storage medium. The method comprises the following steps: in response to a first-class definition request, defining a service standardization mode according to a standardization protocol and a standardization conversion gateway in the first-class definition request; in response to the second type of definition request, defining a service calling guide mode according to the thinking chain and the cue word template in the second type of definition request; and in response to the third-class definition request, defining a service orchestration scheduling process according to the processing logic, the service standardization mode and the service calling guide mode in the third-class definition request. The technical scheme of the invention provides an intelligent service orchestration method, which is beneficial to the accurate and efficient calling of a large model to services.

The application discloses a hub AI travel small assistant working method based on multi-modal fusion and MaaS cooperation, which comprises the following steps: 1, collecting the demand of a user through a man-machine interaction interface, understanding the intention of the user through a natural language processing (NLP) module, and using a service arrangement engine to disassemble the demand of the user into several sub-services; 2, collecting the individual preference of the user according to all the sub-services; 3, automatically calling internal algorithm modules and external service provider interfaces in logical order; 4, using an AI large model to perform fusion analysis on multi-dimensional data obtained by using the internal algorithm modules and the external service provider interfaces, calculating the comprehensive utility of each travel scheme in real time, and performing sorting and recommendation; the sorting and recommendation is a recommended travel service mode combined with the individual preference; 5, realizing the corresponding sub-service through the external service provider interface. The application solves the fundamental contradiction between service fragmentation and demand diversification.