105 results about "Containerization" patented technology

The invention discloses an AI model automatic deployment platform based on a containerization technology, which relates to the technical field of automatic deployment of an artificial intelligence model, and comprises a container construction and intelligent configuration module, a transmission and cache management module, a security and multi-version warehouse module, a resource scheduling and optimization module and a deployment and interface management module, the container construction and intelligent configuration module adopts a three-layer mirror image construction strategy of a base layer, a framework layer and a model layer. According to the invention, all the modules cooperate to form a closed loop, after the container construction module generates an incremental packet and the incremental packet is subjected to security signature verification, the transmission module distributes the incremental packet according to network quality, the resource scheduling module dynamically adjusts bandwidth and quota, and the deployment module starts the container and monitors the container in real time. The problems of efficiency, safety and resource optimization of model deployment in an edge environment are solved, and cross-platform compatibility and service continuity are improved.

The invention relates to the technical field of distributed simulation based on containerized deployment and elastic expansion and contraction, and discloses a distributed simulation method and system based on containerized deployment and elastic expansion and contraction. According to the distributed simulation method and system based on containerized deployment and elastic expansion, real-time resource monitoring and historical load trend data of a simulation task are collected, and unified load evaluation is carried out in combination with a simulation calculation complexity parameter and an I / O density parameter; the refined modeling and resource demand pre-judgment of the simulation task are realized, and the accuracy of task scheduling and allocation is improved; modularized deployment of simulation tasks is achieved through subtask segmentation based on minimum executable units and a standard containerization packaging mechanism in cooperation with a container arrangement platform, and then concurrent execution and elastic scheduling in a multi-node environment are supported.

The invention relates to the technical field of computers, in particular to a containerized scene fault prediction and self-healing method and device, equipment and a storage medium. The containerized scene fault prediction and self-healing method comprises the following steps: obtaining resource use data related to a container in real time by using a sliding window, carrying out noise filtering on the resource use data, generating time sequence characteristics, and obtaining preprocessed data; analyzing the preprocessed data by adopting an isolated forest model to obtain an abnormal score, and judging whether a node of the container has a fault risk or not according to the abnormal score; and carrying out corresponding self-healing operation on the fault node according to the fault type by adopting a pre-constructed self-healing strategy. By analyzing the container resource data, the fault nodes and the types of the fault nodes can be effectively identified, the self-healing operation is pertinently executed, the resource utilization rate is effectively increased, and the core service continuity is guaranteed.

The invention discloses an operating system containerization kernel compatibility method based on shadow structure mapping, which comprises the following steps of: constructing a multi-dimensional mapping rule base by analyzing the difference of data structures between a container system and a standard system, and creating a shadow structure comprising a data area, a metadata area and an expansion area when the container system runs on a host system; the host system allocates a shadow memory space and a memory pool, establishes mapping between a shadow structure and a physical memory page and bidirectional mapping between the shadow structure and a host structure, intercepts system call of a container application, obtains a target structure and allocates a shadow structure and a host structure memory, and sends the shadow structure and the host structure memory to the host system; according to the method, conversion from the target structure to the host structure is completed according to the multi-dimensional mapping rule base, the host machine completes calling through the host structure, then the calling result is reversely converted into the target structure and returned to the container application, and seamless compatibility of the container system and the host system is achieved under the condition that a user mode program of the container system is not modified.

The invention belongs to the technical field of containerization packaging, and discloses a rapid containerization packaging method, system and device for generative AI applications and a medium. The system comprises a dynamic adjustment decision module, an adjustment decision automatic execution module, a load prediction analysis module and a predictive optimization execution module, carries out dynamic adjustment processing based on a processing data set to obtain an adjustment decision report, executes the adjustment decision report, obtains a decision execution report according to an execution result, and carries out load prediction analysis according to the decision execution report. The method comprises the following steps: performing analysis based on a historical processing data set and a historical decision execution report to obtain a load prediction report, optimizing resource pre-configuration based on the load prediction report, and performing execution according to an optimization result to obtain a predictive execution report. The method has the remarkable advantages of being high in data monitoring comprehensiveness, good in system adjustment response effect and high in prospective resource cooperation capability.

The invention discloses an AI component calling method and device, a medium and a computer program product, and relates to the technical field of container mirroring, the method comprises the following steps: when a first calling request sent by a large model application through a gateway is detected, determining a target AI component container instance corresponding to the first calling request, the AI component container instance is a container instance obtained after containerization packaging processing is carried out on an AI component capable of being deployed independently, and comprises a model file and a protocol adapter; performing format conversion on the first calling request through a protocol adapter in the target AI component container instance according to a preset protocol format to obtain a second calling request; calling a model corresponding to the model file according to the second calling request for task processing to obtain a processing result; and packaging the processing result into a response message through the protocol adapter according to a preset protocol format, and sending the response message to the large model application through the gateway. According to the method, the calling efficiency of calling each AI component by the large model application is improved.

The invention discloses a multi-modal intelligent question and answer system and interaction method based on a privatized deployment large language model. The system comprises a model containerization deployment module, a multi-round question and answer and intention recognition module, a document analysis and multi-modal question and answer module, a knowledge base construction and retrieval enhancement generation module and a system integration and monitoring module. A DeepSeekR1 large language model, an inference service and a dependency library are packaged into a container mirror image through a containerization operation environment Docker, and unified scheduling and dynamic capacity expansion and contraction are achieved through Kubernetes; realizing context understanding and task distribution by adopting a dialogue state management and intention recognition technology; in combination with OCR, an embedded model BGE / SimCSE and a vector database FAISS / Milvus, semantic analysis and intelligent question and answer of multi-format documents such as PDF, Word and images are supported; and a hierarchical knowledge base is constructed and a retrieval enhancement generation technology is fused to improve the answer accuracy. According to the invention, safe, efficient and intelligent management and interaction of enterprise knowledge are realized.

The invention discloses a cross-platform desktop application barrier-free test method and system based on a containerization environment, and the method comprises the steps: constructing a test container containing an AT-SPI proxy DBus communication module, enabling the read-only of the test container to mount a host machine DBus socket and limit the right, and enabling a host machine to deploy a DBus bridging proxy as a cross-environment channel; the test container communicates with a host machine, other containers or desktop applications of a sandbox through the channel according to a target type, and the bridging agent dynamically analyzes a virtual DBus address forwarding request in a sandbox scene; the test container sends an AT-SPI request, and interface element capture is completed after returned control data is verified by the bridging agent; and finally executing an automatic test based on the element data and verifying a result. The invention aims to realize dynamic capture and automatic test of desktop application interface elements across host machines and containers / sandboxes.

The invention discloses an LLMOps-based large model efficient operation and maintenance method and system, belongs to the technical field of artificial intelligence, and aims to solve the technical problems of how to realize large model efficient operation and maintenance, ensure that the large model quickly responds to business requirements in the application process and maintain the performance and stability of the large model. Comprising the steps that an LLMOps tool chain is constructed based on a model deployment tool, a model detection tool, a model upgrading tool, a model running tool and a model iteration tool, and the model deployment tool deploys a large model based on containerization and standardization and CI / CD assembly line automation; the model detection tool is integrated with a verification framework and a real-time monitoring system; the model upgrading tool applies a service network technology to implement gray level upgrading and A / B testing; the model running tool realizes elastic expansion and load balancing of the model service based on an automatic capacity expansion and contraction mechanism of the container arrangement platform; and a model dynamic iteration mechanism based on feedback driving is configured in the model iteration tool.

The invention discloses a waste incineration intelligent control system based on artificial intelligence and containerization architecture, and relates to the technical field of waste incineration. Comprising a model reasoning server and a model training server, the model reasoning server and the model training server carry out micro-service packaging of functional modules through a containerization technology, standardized data interaction is carried out between containers based on an HTTP protocol, and the containers are compatible with industrial protocols such as OPC and RTSP to be in butt joint with external equipment. According to the scheme, a distributed containerization architecture design is adopted, a model training server and a model reasoning server are taken as core hardware carriers, micro-servitization packaging of functional modules is realized through a Docker container technology, standardized data interaction is carried out between containers based on an HTTP protocol, and meanwhile, industrial protocols such as OPC and RTSP are compatible to be butted with external equipment, so that the data interaction between the functional modules is realized. And meanwhile, the incineration working condition is predicted in real time through an artificial intelligence model, equipment parameters are dynamically adjusted in combination with a control algorithm, and the incineration efficiency optimization target is achieved.

System and method are provided where parcels or packages are associated or grouped, into logical group or logical containerization of parcels or packages, without need for physical container, such that parcels or packages can be tracked as a group, for example with a unique group ID. Logical group may be tracked within a specified logical zone, transported, sorted and / or otherwise processed as unique logical group in container, or without need to be contained in physical container. System and method for automated sortation can accumulate set number or set volume of packages, and then process the accumulated set number or volume of packages.

The invention discloses a service adaptation method and device based on a skill dependence graph and QoS perception, and a robot method comprises the steps: responding to a task execution request sent by a client, and according to task demand information carried by the task execution request, presetting the skill dependence graph, and retrieving a plurality of available alternative atomic micro-services; the preset skill dependence graph is composed of a plurality of nodes and edges between the nodes; under the resource constraint of a preset multi-objective optimization model, determining an optimal service combination scheme from the plurality of alternative atomic micro-services; carrying out containerization deployment on each atomic micro-service in the optimal service combination scheme to obtain a deployed micro-service instance for task execution; in the execution process, when it is detected that service performance degradation or resource bottleneck exists according to the QoS index and resource information sensed in real time, the optimal service combination scheme is optimized, and the step of containerization deployment continues to be executed. Therefore, by adopting the embodiment of the invention, the execution efficiency of the task can be improved.

The invention relates to the technical field of research and development of container liquid bag materials, and discloses a composite film for manufacturing a container liquid bag and a preparation process of the composite film, specifically, on the basis of a Friedel-Crafts alkylation reaction mechanism, phenyl-POSS functional polyethylene and phenyl-POSS functional polypropylene are grafted on the surface of alkenyl functional interlamellar spacing stable montmorillonite, and the composite film is prepared through the following steps: grafting phenyl-POSS functional polyethylene and phenyl-POSS functional polypropylene on the surface of alkenyl functional interlamellar spacing stable montmorillonite; the organic and inorganic hybrid high-strength filler used for modifying the polyolefin matrix is prepared by using the organic and inorganic hybrid high-strength filler, the composite film is prepared through an eleven-layer co-extrusion blow molding process, and the film product meets the technical requirements specified in the standard of TB / T 2689.4-2018 Part 4 of Railway Cargo Containerization Transport: Disposable Container Liquid Container Bag, and can be used as an inner bag material of a disposable Container Liquid Bag.

The utility model discloses an end cover packaging and cleaning device which comprises a packaging frame, the packaging frame comprises a storage rack and a packaging cage for containing the storage rack, the storage rack is provided with a plurality of fixing rods, and one side of the packaging cage is provided with a lifting grabbing lug; the turnover device comprises a turnover base and a turnover base table rotationally connected with the turnover base, and a turnover driving device is arranged in the turnover base and the turnover base table in a penetrating mode; the functional cleaning tank comprises an ultrasonic cleaning tank, a first cold water tank, a second cold water tank, a hot water tank and an anti-rust liquid tank which are arranged in sequence; the lifting device is used for lifting the pallet from the turnover device to the functional cleaning tank; the electric vehicle end cover cleaning device can effectively solve the problem that an existing cleaning mode is poor in batch cleaning efficiency, and an efficient and feasible solution is provided for the electric vehicle end cover cleaning industry.

The invention relates to a containerized method for the thermal treatment of contaminated solids, pasteous materials, and waste. The system comprises at least one thermally insulated container designed to minimize heat loss and enable material loading from a liftable top panel or a side panel, as well as at least one heat production unit featuring a burner control system and a combustion chamber capable of achieving oxidizing conditions for the complete destruction of contaminants. The method provides simultaneous thermal treatment of materials and vapor-phase contaminant destruction, supported by a ventilation system and a monitoring system for real-time adjustments. In a second aspect, the invention provides a containerized device with comparable operational features, designed for portability and modular deployment, facilitating on-site remediation in remote locations.

The invention relates to a part boxing feasibility discrimination method based on a graph neural network, and the method comprises the steps: S1, receiving the size information of a to-be-discriminated container, and the size information of all to-be-boxed parts; s2, constructing container nodes and part nodes; s3, generating feature representations of container nodes and part nodes; s4, establishing container part edges for connecting the container nodes and the part nodes respectively, and generating feature representations of the container part edges; s5, respectively establishing part edges connected with any two part nodes, and generating feature representation of each part edge based on the size information of the corresponding two parts; and S6, inputting the heterogeneous graph containing the container nodes, the part nodes, the container part edges and the part edges into the trained discrimination model to obtain a discrimination result. Compared with the prior art, the method has the advantages that the discrimination efficiency can be greatly improved under the condition that the high discrimination accuracy is guaranteed, and the like.

The application discloses an operating system containerization kernel compatibility method based on shadow structure mapping, constructs a multi-dimensional mapping rule library by analyzing the difference between the data structure of a container system and a standard system, creates a shadow structure containing a data area, a metadata area and an extension area when the container system runs on a host system, allocates shadow memory space and a memory pool by the host system, establishes the mapping between the shadow structure and a physical memory page and the bidirectional mapping between the shadow structure and a host structure, intercepts the system call of a container application by the host system, obtains a target structure and allocates the shadow structure and the host structure memory, completes the conversion of the target structure to the host structure according to the multi-dimensional mapping rule library, completes the call by the host computer using the host structure, reversely converts the call result into the target structure and returns the call result to the container application, and realizes the seamless compatibility between the container system and the host system without modifying the user state program of the container system.

The invention discloses an abnormity monitoring method, system, equipment and medium based on a plant station gateway metering point, and relates to the technical field of gateway metering point abnormity detection, and the method comprises the steps: collecting the real-time data of the plant station gateway metering point through an industrial protocol interface, loading a protocol stack in a collection gateway, carrying out the preprocessing of the preliminarily collected data, and carrying out the detection of the abnormity of the gateway metering point; data transmission is carried out on the preprocessed data through a real-time stream processing layer by utilizing a transmission protocol, the real-time data is stored in a memory database, historical data is stored in a distributed file system, data organization and management are carried out, and multi-mode anomaly detection is carried out on the stored data through an anomaly detection service deployed in a containerization mode. And identifying various abnormities, packaging and outputting a detection result, and dynamically rendering through a responsive front-end interface to display the detection result in real time. According to the invention, the multi-mode intelligent detection and containerized elastic architecture are fused, so that the leap-type improvement of the metering abnormity of the plant station from passive alarm to active early warning and deep diagnosis is realized.

The utility model discloses an assembly type highway steel bridge component containerization approach bridge mixed loading container unit which comprises a cross beam, an approach bridge mixed loading hanging scaffold is embedded into the inner side of the cross beam, a central bridge deck is placed on the rear side of a container, and slab lapping corners are placed at the bottom ends of the container and the central bridge deck. Steel bridge components such as cross beams, transition slab corners, central bridge decks, transition slab supports, curbs, U-shaped bolt sets and bridge deck bolt hole dustproof caps are assembled together with auxiliary assembling tools to form a general component assembling unit required by steel bridge approach bridges with different spans, loading is completed within the same time, more than six persons are needed for one component, and only two persons are needed after assembling; single pieces are stacked and easily slide down to cause accidents during truck loading, and can be prevented after container loading; 40 minutes are needed for completing loading of a single piece, and 5 minutes are needed for loading after container loading; the number of single pieces is large, the number of point positions is large, omission is prone to occurring, and only one piece is packaged; a single piece needs to be loaded for multiple times, long-time labor is needed, and one-time loading is needed after container loading.

The invention relates to the technical field of artificial intelligence, and discloses a containerization-based AI model full life cycle management system and method, and the system comprises a data preprocessing module, an environment construction module, a flow arrangement module and a link control module. The method corresponds to the system. According to the containerization-based AI model full-life-cycle management system and method provided by the invention, the independent container mirror image of each stage is constructed, the multi-modal data is preprocessed, and automatic process arrangement and version and deployment management and control are carried out, so that the environment standardization isolation of each stage is realized to solve dependency conflicts, the multi-modal data is uniformly processed to avoid the format compatibility problem, and the management efficiency is improved. Human errors are reduced through full-process automatic cooperation, versions are traceable, the method adapts to various deployment environments, AI model management pain points are solved in a multi-dimensional mode, and development, iteration and large-scale landing of the AI model are efficiently supported.

The utility model relates to a kind of installation and fixing device of container radio frequency card, including base, sliding table, clamping mechanism and ejecting mechanism, the base is connected with sliding table, the back of sliding table is equipped with recess, recess is equipped with clamping mechanism, sliding table is connected with ejecting mechanism, the ejecting mechanism includes ejecting slide, ejecting hanging pole, locking slide and ejecting tension spring, the ejecting slide is supported on base, sliding table is slidably connected with ejecting slide, the sliding table moves axially forward and backward along base, the sliding table side edge is hung and is connected with ejecting tension spring, the rear end of ejecting hanging pole is inserted in base pivot hole, and its front end is slid along locking slide, the locking slide includes locking limiting recess and ejecting recess, the ejecting recess is lower than locking limiting recess and is in echelon, and constitute sliding table locking / ejecting mechanism.The utility model can realize the quick locking and ejecting of radio frequency card, solve the fixing problem of informatization label in containerization transportation.

Systems and methods for containerization are provided. Various embodiments provide containerization systems and methods deploying an initial container image associated with a startup script, a pre-service script and post-service script. This deployment includes executing the startup script associated with the initial container image, and the executing including copying configuration information for the initial container image into a volume and generating a marker file for the initial container image. The containerization systems and methods also deploying a main container image associated with a startup script. This deployment includes executing the startup script associated with the main container image and copying the configuration information from the volume to a local system. This deployment also includes executing the main container, including executing the pre-service script associated with the initial container image, configuring the main container, executing a main service, and executing the post-service script associated with the initial container image.

The application discloses a kind of based on containerization's application intelligent deployment method and device, the method includes: receiving the application deployment instruction of target application, and according to application deployment instruction, determine the deployment information of target application;According to each target release package, generate each target release package corresponding container, as the all deployment containers of target application corresponding;For each deployment container, deployment container is deployed to corresponding target partition;Start all deployment containers, to carry out deployment to target application by all deployment containers.It can be seen that the application can be deployed intelligently by deployment container, without manual full-process participation in the whole application deployment process, which can not only improve the deployment efficiency of the application, but also reduce the occurrence of runtime environment error, thereby improving the deployment reliability and accuracy of the application, so that the service of the application program can be started smoothly.

A portable container filling system for filling bottles or cans with a fluid may include a first container housing a first plurality of equipment for depalletizing and filling containers with the fluid, and a second container housing a second plurality of equipment for packaging and palletizing filled containers. At least one piece of equipment from among the first plurality of equipment or the second plurality of equipment may be configured to be movable between a transportation configuration and an operative configuration. Movement of at least one piece of equipment may not require removal of equipment from the first container or the second container. A clean room environment may be established within at least one of the containers by creating positive air pressure with filtered air surrounding a portion of the containerization equipment. A chiller system housed within the containers may cool a fluid product before filling.

The application relates to the technical field of distributed simulation based on containerization deployment and elasticity, and discloses a distributed simulation method and system based on containerization deployment and elasticity, which comprises the following steps: collecting real-time resource monitoring and historical load trend data of a simulation task, and combining simulation calculation complexity parameters and I / O density parameters to perform unified load evaluation, so that fine modeling of the simulation task and resource demand prediction are realized, and the accuracy of task scheduling and distribution is improved; through subtask segmentation based on the minimum executable unit and a standard containerization packaging mechanism, and in cooperation with a container arrangement platform, modular deployment of the simulation task is realized, and then concurrent execution and elastic scheduling in a multi-node environment are supported.

An inventory system may include an inventory field, a transfer apparatus, and an induction station and / or a receiving station. The inventory field may include a plurality of inventory holders. The induction station may include an input area, and a transfer apparatus disposed at a boundary of the inventory field to transfer items between the input area and an inventory holder of the inventory field. The receiving station may include a receiving area and a transfer apparatus disposed at the boundary of the inventory field to transfer items between the receiving area and another inventory holder of the inventory field. The receiving area may be arranged such that an operator receives an item from the second inventory holder at a specified receiving level for comfortable handling of the items.

The invention relates to the technical field of cross-platform software transplantation, in particular to a migration adaptation method for regional numerical weather forecast software. According to the method, through the software adaptation step, the problem of compatibility of an instruction set and a system environment when existing regional numerical weather forecast software migrates from an X86 architecture to an ARM architecture is solved, and native operation of the regional numerical weather forecast software on a domestic platform is achieved; through a containerization packaging step, software and a complete dependency environment thereof are packaged into a standard mirror image, so that one-time construction and deployment at any place are realized, and the problem of deployment complexity in different operating system environments is thoroughly solved; through the verification step, containerized software is operated, strict cross-platform comparison testing is carried out, prediction precision is quantitatively evaluated, service functions are ensured to be complete, results are reliable, and key technical support is provided for autonomous controllable and safe sustainable development of a meteorological core service system.

This invention discloses a cross-platform operating system upgrade patch automatic deployment method and system, relating to the field of operating system patch management technology. The method includes analyzing patch dependencies and dynamically adjusting the deployment order; performing isolated deployment based on containerization technology; and real-time monitoring of the status of each container, providing real-time monitoring and feedback optimization of the deployment results. The method described in this invention achieves precise control over patch deployment in complex heterogeneous environments, reducing the failure rate caused by dependency conflicts, while also reducing deployment time, improving system stability and reliability, ensuring the independence of patches, and avoiding system crashes due to patch incompatibility or failure. While improving deployment efficiency, it achieves efficient container isolation and a highly compatible patch deployment process, enhancing the system's autonomous adaptability and long-term stability, and providing strong technical support for complex and ever-changing patch deployment scenarios.

The invention discloses an NSR virtualization method based on a network operating system, and relates to the technical field of switch virtualization. According to the method, NSR function modules are decoupled into independent services through a containerization technology, and uninterrupted operation, uninterrupted maintenance and flexible deployment of NSR services are achieved in combination with high-availability guarantee (fault isolation and automatic recovery), dynamic upgrade (hot update and rolling replacement), lightweight resource management (quota control) and standardized packaging (cross-platform mirroring). According to the method, the system reliability can be improved, the resource utilization rate is optimized, the new function online period is shortened, and the method is suitable for high-availability requirements of a cloud data center and an operator network.

The application discloses a kind of microservice order processing system and method based on dynamic load balancing, it is related to the technical field of microservice, the system is applied to microservice architecture, system includes: event monitoring module, the instance lifecycle event stream of containerization management layer is monitored in real time, the logical relationship of microservice instance and the state attribute of the logical relationship are determined according to instance lifecycle event stream;Intelligent decision module is used to when receiving order task request: according to the real-time load index of microservice instance, determine candidate instance set;The microservice instance in replacement relationship and the state attribute for closing is removed from candidate instance set, obtain safe candidate instance set;Based on the real-time load index of each instance in safe candidate instance set, determine target microservice instance;Order task request and target microservice instance are sent to load balancing layer.The application improves the distribution ability of load balancer in microservice architecture to order task request.