146 results about "Service cloud" patented technology

The invention relates to the technical field of operation and maintenance management, in particular to an operation and maintenance service cloud platform of a mine intelligent system, which comprises a node pressure monitoring module, a path task mapping module, a conflict density identification module, a time window adjustment module and an operation and maintenance scheduling matching module. According to the method, a node group consistent in direction is extracted through a pressure difference value and a flowing direction, a dynamic response relationship is constructed, the real-time performance and accuracy of path extraction are improved, path and task mapping is combined with a direction label, the adaptation degree of a task and a physical path is enhanced, task occupancy rate calculation supports high-density section identification, accurate avoidance of a scheduling peak is realized, and the scheduling efficiency is improved. Starting time and ending time extend to form candidate windows, task execution cycles are reconstructed according to density levels, task scheduling flexibility is enhanced, response units are screened according to reachable paths and path conflict conditions in resource allocation, and dual optimization of spatial distance and path safety is achieved; and the real-time adaptability, the path configuration reasonability and the resource calling efficiency of the scheduling scheme are improved.

The present disclosure relates to an edge-cloud collaboration system and method, enabling edge data to be inferred at a suitable location among an edge device and a cloud server according to the type and objective of the edge data, and enabling easy updating of the configuration of the edge device and the cloud server. A collaboration system may be provided in which an edge device comprises: a service coordinator which, for each of a plurality of services provided by the collaboration system, controls the flow of edge data in the collaboration service, the edge data being collected by at least one sensor; and an edge inferencer which may have at least one edge artificial intelligence model for receiving the edge data as input data for inference and outputting an inference result for each of at least one service among the plurality of services. A cloud server comprises: a cloud inferencer which comprises at least one cloud artificial intelligence model for receiving the edge data as input data for inference and outputting an inference result for each of at least one service among the plurality of services; and a collaboration manager for changing the configuration of at least one of the edge inferencer and the cloud inferencer on the basis of log information of the edge inferencer and the cloud inferencer.

The invention provides a cyclic feedback scheduling collaboration method based on an intelligent agent and cloud computing power service. The method comprises the following steps: memory recall: the intelligent agent receives a task demand, accesses a memory library to obtain historical experience entries, performs memory matching and memory fusion, generates memory recall information, and outputs the memory recall information to the cloud computing power service; cloud task planning: a cloud big language model understands task demand intentions based on memory recall information, decomposes tasks and generates executable descriptions, and an agent generates a preliminary task plan and calls a proper tool; performing action observation: performing operation by the intelligent agent, acquiring feedback data in real time, comparing an actual result with an expected target adjustment strategy, selecting a more suitable tool, and performing repeated execution until a task is completed; summarizing and reflecting: generating task execution tracks, integrating into experience entries, and storing into a memory bank. According to the method, historical memory, dynamic feedback and cloud computing power are combined, and the autonomous decision-making ability, execution efficiency and accuracy of the intelligent agent in a complex task are remarkably improved.

The invention discloses a cloud platform virtual machine operating system anomaly detection and recovery method and device and a medium, and the method comprises the steps: creating and monitoring a socket file, transmitting a descriptor of the socket file to a qemu process when a virtual machine is created, and when the qemu process obtains an IO error returned by a storage rear end, returning the IO error to a virtual machine operating system layer, the IO error is written into the socket file monitored by the Libvirt; the Libvirt component integrates the monitored IO errors and reports the IO errors to a computing service of a cloud platform, and the computing service of the cloud platform obtains an abnormal event of a virtual machine operating system through an interrupt function registered in Libvirt in advance; the cloud platform computing service performs state detection on an operating system of the virtual machine, detects networks of all virtual machines on a host machine at regular time, and reports abnormal information to a monitoring alarm component; and the monitoring alarm component displays the abnormal information and recovers the virtual machine. The working stability and reliability of the virtual machine in the cloud platform are improved.

The invention discloses a micro-service cloud platform transverse network performance real-time monitoring operation and maintenance method and system, and relates to the technical field of operation and maintenance, and the method comprises the steps: collecting flow information among a container Pod, a node Node and a host in a micro-service cloud platform, and constructing an application service topological graph, a node topological graph and a host topological graph; based on the collected data, the system carries out network flow index analysis and network fault alarm analysis to help to identify abnormal links and network load abnormalities; network flow information is acquired in real time through a plurality of acquisition components of a virtual machine and a container environment, and link faults are automatically identified and alarmed. According to the method, the accuracy of network fault diagnosis is improved, data support is provided for network optimization and resource allocation, the fault processing time is shortened, the service interruption risk caused by network problems is reduced, the fault response speed is improved, and stable operation and service continuity of a micro-service cloud platform are guaranteed.

According to one aspect of the concepts and technologies disclosed herein, a cloud computing system can include a load adaptation architecture framework that performs operations for orchestrating and managing one or more services that may operate within at least one of layers 4 through 7 of the Open Systems Interconnection (“OSP”) communication model. The cloud computing system also can include a virtual resource layer. The virtual resource layer can include a virtual network function that provides, at least in part, a service. The cloud computing system also can include a hardware resource layer. The hardware resource layer can include a hardware resource that is controlled by a virtualization layer. The virtualization layer can cause the virtual network function to be instantiated on the hardware resource so that the virtual network function can be used to support the service.

The invention relates to the technical field of cloud manufacturing, in particular to a cloud manufacturing service combination and scheduling integrated optimization method. Comprising the steps that 1, a complex matching network of cloud manufacturing services and cloud manufacturing tasks is established, the cloud manufacturing services are divided into cloud manufacturing production services and cloud manufacturing logistics services, and the cloud manufacturing tasks also comprise cloud manufacturing production tasks and cloud manufacturing logistics tasks; 2, a cloud manufacturing service combination and scheduling integration optimization model is established, QoS of all cloud manufacturing services in the network is quantified through weighted summation of a service quality parameter and a service reliability parameter, the two parameters are dynamically described by a time domain, and an initial value is an evaluation value obtained in advance; and step 3, solving the integrated optimization model by adopting a multi-population co-evolution algorithm based on meta-knowledge adaptive migration to obtain a multi-objective optimization Pareto solution set, and decoding the multi-objective optimization Pareto solution set into an optimization scheduling scheme. And performing combined configuration and scheduling optimization on services in the cloud manufacturing platform.

Technology for applying artificial intelligence to decide when to, and / or when not to, send a consumer of a computer system a communication recommending that the computer system be revised to include a more recent version of at least one of the following: a hardware component (for example, microprocessor(s)) and / or a software component (for example, an updated version of an app). The computer system, that is subject to modernization, may be owned outright by the consumer, or it may be purchased as a service (for example, infrastructure as a service, software as a service, package of cloud services). Some embodiments focus on modernization recommendations specifically tailored to cloud orchestration software that deploys containers.

The embodiment of the invention provides a resource configuration method, a resource configuration device, electronic equipment, a chip, a storage medium and a computer program product. The resource configuration method comprises the steps of collecting terminal side user data and service cloud side node data; and based on the terminal side user data and the service cloud side node data, configuring network resources for the terminal side user.

The invention provides an industrial Internet of Things service information processing system and method based on a service cloud platform. The system comprises an industrial Internet of Things subsystem and the service cloud platform. The industrial Internet of Things subsystem comprises an industrial Internet of Things user platform, an industrial Internet of Things service platform, an industrial Internet of Things management platform, an industrial Internet of Things sensing network platform and an industrial Internet of Things sensing control platform; the industrial Internet of Things user platform is configured to receive application data and upload the application data to the industrial Internet of Things service platform; the industrial Internet of Things service platform is configured to generate second data and upload the second data to the service cloud platform; the industrial Internet of Things management platform is configured to determine a monitoring operation instruction and send the monitoring operation instruction to the industrial Internet of Things sensing control platform; the industrial Internet of Things sensing control platform is configured to obtain and upload first data to the industrial Internet of Things service platform; the service cloud platform is configured to determine service data and recommend operation data. Through the system and the method, more accurate service data can be provided for the user.

The invention discloses a bill verification method and related equipment, the bill verification method is applied to a cloud transaction platform, the cloud transaction platform is used for providing transaction of software resources, and the method comprises the following steps: the cloud transaction platform obtains first software information of a first user; the cloud transaction platform displays a software selection interface to the second user; the cloud transaction platform deploys a first cloud service according to the selection of the second user on the first software; the cloud transaction platform provides the function of the first software for the second user by using the first cloud service; the cloud transaction platform obtains a first bill uploaded by the first user, wherein the first bill is associated with the use cost of the first software by the second user; the cloud transaction platform verifies the first bill according to the use information of the second user on the first cloud service; and the cloud transaction platform processes the account of the second user according to the verification result of the first bill, so that the transaction reliability can be improved.

Provided is a method for controlling a virtual machine, an electronic device and a storage medium, relating to the field of computer technology, and in particular to application fields of cloud service, cloud computing and big data processing. The method includes: obtaining a virtual machine control request; generating a control operation instruction for a target virtual machine based on the virtual machine control request by using a computing node service deployed on the smart card; and sending the control operation instruction to a virtualization control program deployed on the physical machine; where the virtualization control program is used to perform a control operation on the target virtual machine based on the control operation instruction.

A system and method of securing a Function as a Service (FaaS) cloud computing system without using access rights to operating system (OS) kernels of the cloud service system. The method includes receiving a request to invoke a user-function associated with a computing language. The method includes executing the user-function within an operating system that executes on a processing device of the cloud service system. The method includes monitoring, by the processing device, a real-time behavior of the user-function using a security sensor that executes within the operating system, wherein the security sensor is without access rights to a kernel of the operating system. The method includes acquiring behavioral data indicative of the real-time behavior of the user-function.

The invention discloses a cross-domain access control method based on a cloud management platform and the cloud management platform, which can reduce the operation of a tenant when making an access control strategy and provide convenience for the tenant so as to improve the experience of the tenant. The method comprises the following steps: for a plurality of domains contained in an organization of a tenant, when the tenant needs to perform access control on a first cloud service contained in a first domain in the plurality of domains, the tenant can input an access control strategy formulated by the tenant for the first cloud service of the first domain to an access control interface provided by a cloud management platform, therefore, the cloud management platform can receive the access control strategy through the access control interface. And if the access control strategy is used for indicating that the access authorization range of the first cloud service contained in the first domain is the second cloud service contained in the organization of the tenant, the cloud management platform allows the second cloud service contained in any domain in the organization of the tenant to access the first cloud service contained in the first domain.

The present invention relates to the technical field of data service cloud platforms, and specifically provides a comprehensive management system for an Internet-based data service cloud platform, including: a data cleaning and classification module, a load balancing module, a cache server, a server group, a mirror backup module, a disaster recovery module, and a visualization operation and maintenance module. By cleaning and classifying data, the huge data stream is diverted, and the smooth weighted round-robin algorithm is used to perform secondary diversion on the huge data stream. The sub-data stream is preferentially allocated to the servers with good load conditions, and the data of the server group of other data service cloud platforms is backed up. Sensors are used to judge whether a disaster signal is sent to improve the backup efficiency. At the same time, the overall load condition of the data service cloud platform is visualized, and the real-time data service ability is optimized based on the underlying architecture of the data center, providing an interface service integrating visualization, multi-services, and panoramic operation.

A system can include one or more processors and one or more non-transitory computer-readable media storing computing instructions that, when executed on the one or more processors, cause the one or more processors to perform operations. The operations can include connecting an edge device located at a vehicle service site to a centralized vehicle service cloud platform. The edge device can execute a site controller application to manage operations at the vehicle service site. The operations also can include configuring one or more IoT devices located at the vehicle service site to capture monitoring data. The operations further can include receiving the monitoring data for usage by the site controller application. The operations also can include receiving a service request for a vehicle. The operations also can include generating and dynamically updating a schedule for the vehicle service site. Other embodiments are disclosed.

Cloud services, such as a storage service, are able to communicate through a virtual PCI request over a non-PCI bus by using a modified device driver that communicates with a network interface. One or more cloud services can execute on a same board or within a same Integrated Circuit (IC) as the network interface. The network interface adapts communications from the one or more services by allowing the services to use a PCI protocol despite that the services are not communicating with the network interface over a PCI bus.

Provided are a method, a system, and a storage medium for determining a demand level of service information. The method includes: obtaining first sensor information of a first production line; determining, based on the first sensor information, a candidate push object and a push demand value of the candidate push object; determining a target push object based on the push demand value; determining reference information of the target push object based on the first sensor information, and sending the reference information to an IIoT user platform corresponding to the target push object; in response to receiving a recommended demand, generating a recommended production parameter and / or a recommended monitoring parameter based on the reference information, and sending the parameter(s) to the IIoT user platform corresponding to the target push object to obtain confirmation information; and generating, based on the confirmation information, an adjustment instruction.

The invention belongs to the technical field of network cloud authentication, and relates to an SRv6-based network cloud authentication method, storage medium and device, and the method comprises the steps that a network client sends an SRv6-based network authentication request message to a network management cloud through a basic network; after receiving the SRv6-based network authentication request message, the network management cloud replies an SRv6 path packet to the network client initiating the request message; after receiving the SRv6 path packet, the network client processes the identity authentication information and sends the processed identity authentication information to the network service cloud; the network service cloud authenticates the identity authentication information, if the authentication succeeds, the network client accesses the network service cloud, and if the authentication fails, the network client does not access the network service cloud; according to the method provided by the invention, the identity authentication information of the network client is divided into a plurality of parts and is sent to the network service cloud through a plurality of paths, so that the sub-identity authentication information is forwarded according to different paths, and line repetition is effectively avoided.

The application discloses a kind of collaborative robot system and service process for active power grid marketing, belong to artificial intelligence and electric power marketing service technical field.System includes: robot perception interaction end, cloud intelligent analysis hub and dynamic customer memory bank, robot perception interaction end deploys lightweight vision model, real-time identification customer emotion, body state and explicit feature, and initiatively trigger service;Cloud intelligent analysis hub uses power grid knowledge enhanced large language model, carries out depth demand analysis and individualized strategy generation to multi-modal data;Dynamic customer memory bank stores customer historical interaction record and portrait information in the form of knowledge graph, realizes the continuity and memory of service.The application is through edge small model+cloud big model collaborative architecture, general AI capability and power grid business knowledge are deeply fused, so that robot can actively identify customer demand, provide marketing service, improve customer experience and marketing conversion rate of electric power business hall.

The application discloses an intelligent pipe cooling circulation control system and method based on ship lock construction, which comprises the following steps: dividing a ship lock construction structure into A pipe cooling circulation control subareas; covering the A pipe cooling circulation control subareas by B cooling circulation pipelines; receiving multi-dimensional data of each pipe cooling circulation control subarea by each edge key control node, and transmitting the data to a cloud cooling control service; after receiving the data, the cloud cooling control service generates A cooling circulation load demand risk coefficients based on a first deep learning algorithm; if it is judged that at least one of the A cooling circulation load demand risk coefficients is at risk, then the B cooling circulation pipelines are subjected to pipe cooling circulation control based on a second algorithm, and a PID control algorithm is used to adjust the cooling water flow and the cooling water temperature of the pipelines; the application realizes precise pipe cooling circulation control adjustment, improves the ship lock construction quality and reduces the risk of concrete hardening cracking through deep learning algorithm prediction and monitoring and the introduction of an unmanned aerial vehicle for the inspection of the outer surface of the cooling pipe.

The application discloses a lithium battery energy storage station cloud-edge collaborative intelligent fire-fighting linkage system and an implementation method. It comprises a fire service cloud platform system, a network layer, a sensing layer and a control layer. The sensing layer reports various data in real time. The network layer extracts a feature vector set to construct an effective feature parameter identification classifier. The control layer realizes comprehensive linkage fire extinguishing control. The fire service cloud platform system is used for processing data logic of a program and is responsible for accessing data in a database. The application has the beneficial effect that a plurality of operating state parameters representing lithium batteries of an energy storage station are preprocessed on an edge gateway side, such as feature extraction, statistical analysis, dimension reduction optimization and the like, and then trained and dynamically identified through an improved BP neural network model deployed in an intelligent fire service cloud platform. According to the identification result, early warning information is sent out. In combination with a fire-fighting linkage control system, a complete cloud-edge collaborative intelligent fire-fighting linkage control method is formed, so that the operating safety risk is greatly reduced.

Disclosed herein are system, method, and computer program product embodiments for identifying and removing orphan data in a Database-as-a-Service (DBaaS) cloud computing platform. In embodiments, a workflow is executed that accesses an event service database of the platform to obtain a list of deleted customer entities, queries a control plane of the platform to obtain a list of existing DBaaS instances, determines that a particular existing DBaaS instance is associated with a particular deleted customer entity, identifies the particular existing DBaaS instance as a potential orphan DBaaS instance, validates that the particular existing DBaaS instance is an orphan DBaaS instance, and in response to validating that the particular existing DBaaS instance is an orphan DBaaS instance, performs one or more of generating an alert that identifies the particular existing DBaaS instance as an orphan DBaaS instance or removing the particular existing DBaaS instance from the DBaaS cloud computing platform.

The invention discloses a highway networking charging management and information resource wide-area fusion scheduling system, relates to the technical field of intelligent traffic charging management, and constructs a highway networking charging management architecture with multi-level management from top to bottom in a management area, and establishes mutual access channels through a cloud service network. The global center management node supervises the working state of each resource scheduling management node, overall plans business cooperation among the resource scheduling management nodes according to the working state, and issues a scheduling instruction to each resource scheduling management node; the resource scheduling management nodes are mutually standby nodes, the corresponding toll lane systems and cloud seats are managed according to scheduling instructions, a road network resource scheduling management network is generated and maintained, the toll lane systems provide services for users passing through toll lanes of a toll plaza, and the cloud seats are used for remotely receiving and processing manual service requests. Through cross-regional scheduling and multi-warehouse mutual backup of the human resources, comprehensive clouding and unified scheduling of the computing resources and the human resources are realized.

The invention relates to the technical field of network communication, and provides a secure access service edge fusion method and device. According to the invention, a VXLAN tunnel is constructed between a service cloud gateway and an LAN port of SD-WAN vCPE; the branch terminal sends the original message to the access cloud gateway; the access cloud gateway forwards a first message obtained based on the original message to the service cloud gateway; the service cloud gateway converts the first message into a second message, so that the second message is forwarded to the SD-WAN vCPE through the VXLAN tunnel; and the SD-WAN vCPE processes the received second message to obtain a third message, and forwards the third message to headquarters equipment, so as to transmit the traffic of the branch terminal to the headquarters equipment, thereby solving the problems of low efficiency, high cost and complex configuration of the existing remote networking scheme, or large data transmission quality fluctuation caused by strong dependence on a public network.

The invention provides a wide-area cloud manufacturing industrial service system and method based on an Internet of Things large model. The system comprises a service cloud platform and a user platform, wherein the service cloud platform is configured to obtain a constraint index; determining first service data from historical service data corresponding to the user based on the constraint index; responding to the condition that the first service data meets user requirements, and displaying the first service data to the user through a user platform; and in response to the condition that the first service data does not meet the user demand, taking one or more candidate service data of which the matching degree meets a preset matching condition as one or more second service data, and presenting the one or more second service data to the user through the user platform. Through the system, real demands of a manufacturing enterprise can be obtained, and accurately matched service data is provided for the manufacturing enterprise, so that high-quality operation of wide-area cloud manufacturing industrial services is supported.

The present disclosure provides a cloud application processing method and device, electronic equipment and storage medium, relates to the technical field of computers, in particular to the field of cloud application, cloud service and cloud computing. The specific implementation scheme is: in response to detecting that an activation operation for multiple cloud applications is triggered, encrypting binding information corresponding to the multiple cloud applications to obtain first encrypted information. The binding information includes first certificate information and hardware identification information of a first client; sending the first encrypted information to a server, so that the server decrypts the first encrypted information to obtain first decrypted information; in response to receiving second encrypted information from the server, decrypting the second encrypted information to obtain second decrypted information. The second decrypted information includes verification success information and activation information; in response to detecting the verification success information, completing the activation operation for the multiple cloud applications by using the activation information, so that the first client performs multi-opening operation for the multiple cloud applications.

This invention proposes a method for optimizing mobile social security services based on a distributed and microservice architecture. Its technological breakthroughs are manifested in three core aspects: Elastic Service Cloud Network: Based on the self-developed PDFC framework, Spring Cloud microservice architecture, and Kubernetes containerization technology, microservices are deployed in a split manner, enabling dynamic scaling of microservice container nodes and second-level fault self-healing. Intelligent Data Hub: A cross-domain data channel is built based on Apache Kafka, collecting social security business data and health record data in real time with millisecond-level transmission efficiency. Intelligent Reporting Engine: An innovative three-dimensional intelligent reporting system is constructed. Pre-event reports are generated by parsing physical examination information; during-event reports are generated through dynamic monitoring of risk warnings; and post-event reports are generated based on actual business processing, achieving an upgrade and transformation of the governance model from "people seeking services" to "services benefiting people."

A data storage method and apparatus, and a computing device are provided. The method includes: in a process in which the first node processes a plurality of access requests, locally storing or caching hot data in the first node, migrating cold data to a cloud storage service, and locally storing or caching metadata of the cold data in the first node, where the cloud storage service is a service deployed by a cloud computing platform in a cloud computing resource, the cloud computing platform deploys a cloud database system in the cloud computing resource managed by the cloud computing platform, the first node is a primary database node or a secondary database node of the cloud database system, the hot data and the cold data are different data tables of the database or different table partitions of the data table, and the hot data and the cold data are determined based on either or both of a quantity of times and a data amount of accessing a table partition of a data table. According to the method, data storage costs can be reduced without affecting performance.

The invention relates to a large-scale wireless network automatic test system and method, the system comprises a test tool, a tested device, a business cloud and a mechanical arm, the test tool and the tested device are respectively in communication connection with the business cloud and the mechanical arm, the test tool is used for determining a control instruction according to a pre-configured test case, and the control instruction is sent to the tested device. Controlling the tested equipment through a transparent transmission interface or a mechanical arm of the business cloud based on a control instruction, wherein the control instruction is an instruction irrelevant to a protocol; and the test tool is also used for acquiring a device state returned by the tested device in response to the control instruction through the service cloud, judging whether the device state is consistent with the control instruction, if so, executing the next test case until all test cases are executed, and outputting a test report.