924results about How to "Improve deployment efficiency" patented technology

The present invention describes a method that is operative within a clinical environment in which real-time locations of personnel and resources are tracked. The method begins in association with entry of a patient into the clinical environment, such as when a patient is in transit, or has been admitted, to an emergency room or to a hospital. In response, a given care guideline is identified. Using the care guideline, a set of one or more process rules, and information associated with at least one “encounter,” the system generates a patient-specific care protocol; the protocol includes a set of steps through which the patient is expected to proceed while in the clinical environment. An encounter occurs when two or more of objects (e.g., the patient, clinical personnel, and a clinical resource) are in a given physical proximity for a given time period at determined by the at least one process rule. According to the method, at least one event that occurs during at least a first step of the patient-specific care protocol is then monitored. Using information generated by the monitoring step and at least one process rule, the system then determines whether the patient moves to a next step in the patient-specific care protocol.

The invention provides a cloud management platform based on a micro-service architecture. The cloud management platform comprises a user interface layer for processing a function request instruction of a terminal user, at least one cloud micro-service module for providing function services for the terminal user via an API interface and a message queue cluster for completing information interaction between the user interface layer and the cloud micro-service modules, wherein the cloud micro-service modules are service components into which cloud application functions are decomposed by a function boundary. In the cloud management platform based on the micro-service architecture, the cloud application functions are decomposed into the service components by the function boundary; each service component corresponds to one cloud micro-service module; the plurality of cloud micro-service modules are utilized to realize the functions of the cloud applications; due to the own characteristics of micro-services, the cloud management platform based on the micro-service architecture is capable of realizing real-time deployment; besides, micro-services have independent running processes so that each cloud micro-service in the cloud management platform can be independently deployed, and therefore, the deployment efficiency of the cloud management platform is improved.

The invention discloses a Hadoop cluster system and Hadoop cluster rapid establishment method based on a container technology and relates to the technical field of big data and cloud computing. The method comprises the steps of configuring that containers between different container operation nodes communicate through a VXLAN, and configuring that virtual network bridges of the container operation nodes are not located in the same network segment; installing SSH and JAVA operating environments, producing packaging files of a DNS service mirror image, a Hadoop master service mirror image and hadoop slave service mirror images, packaging the mirror images, and transmitting the packaged mirror images to a mirror image warehouse for storage; and submitting requests for deploying three pieces of services to a container management node in sequence by a user through a client, scheduling the corresponding requests to the container operating nodes for deployment by the container management node, and registering the corresponding service. According to the system and the method, a Hadoop cluster can be deployed rapidly, the condition that the number of servers is insufficient is solved, and the availability of a Hadoop container cluster deployed on a Docker platform is improved.

The present invention discloses a method for automatically balancing increased load of a cloud application container. According to the method, a load balancing container instance or virtual machine node does not need to be configured externally and separately in a cloud application deployment process of a container, and the cloud application load balancing service of the container can be provided by automatically enabling a proxy instance container operated by a host node according to the needs so as to ensure that cloud application deployment steps can be simplified, the deployment efficiency can be increased, and the workload of operation and maintenance staff for deploying cloud application of the container in a production environment can be saved; and meanwhile, the number of running cloud application containers can be automatically increased and reduced according to the access request load conditions in different time periods in combination with collected resource occupancy situations, the resource usage can be saved, the crash probability of the cloud application container can be reduced, and the availability of the cloud application container can be improved.

The invention discloses a machine learning device, a machine learning method based on the machine learning device, and a big data platform using the machine learning device and the machine learning method thereof. The machine learning device comprises a user-defined process module, a configuration module, a database and an event server, wherein the user-defined process module comprises a logic module, the logic module can receive an executable file contained in a request initiated by a user, and can be called by the event server; and the database binds a front-end development application with the executable file through a configuration file written by the configuration module. According to the machine learning method, the machine learning device and the big data platform, the service logic component is completed by means of the user-defined process module, the adaptability and universality of the machine learning method, the machine learning device and the big data platform for various application scenarios are realized, efficient operation of data mining and machine learning involved in the development process of standardized big data are achieved, the development process of the standardized big data is simplified, and the development and deployment efficiency of the standardized big data is improved.

The embodiment of the invention provides a containerization management system based on micro-service, which comprises a Kubernetes cluster, wherein a plurality of nodes are arranged in the Kubernetescluster, at least one docker container is arranged on each node, and the docker containers are micro-service operation bearing platforms; The log component which is used for collecting log informationof the micro-service borne by each docker container and generating visual data according to the log information; And the monitoring assembly which is used for acquiring the monitoring data of the micro-service borne by each docker container and generating time sequence data according to the monitoring data, wherein the time sequence data is used for displaying the operation of the micro-service.According to the embodiment, resource sharing between services can be effectively realized, the deployment efficiency is improved, and the system operation and maintenance difficulty is reduced.

The invention provides a realization method for fast deploying a containerized cloud computing test platform. The method comprises the following steps: S1, describing basic information of a file configuration deployment node by use of a virtual machine of Vagrant, running a vagrant up command to get a preinstalled Linux operation system from a public warehouse, and running in a Virtual Box; installing a Docker in the deployment node and creating a private container warehouse by use of the Docker; manufacturing a container mirror image file of each service of Openstack by use of Kolla, saving the container mirror image file to the private container warehouse; and S2, traversing the process of executing the step S1 so as to deploy the container mirror image file to a target node. By use of the method provided by the invention, the deployment step of the cloud computing test platform is simplified, the deployment efficiency and the flexibility in the deployment process are improved, the compatibility of the Openstack and the Linux operation system in different versions published by different manufacturers is improved, and the flexible capacity expansion can be performed as required after the deployment is finished.

The invention discloses an integrated online monitoring system for drainage pipeline liquid level and flow. The system is composed of a data center and at least one monitoring subsystem. Each monitoring subsystem comprises a monitoring point and a monitoring device installed on the monitoring point. The monitoring devices collect related monitoring data of the monitoring points and send the monitoring data to the data center for processing and real-time dynamic displaying. The integrated online monitoring system for the drainage pipeline liquid level and flow can be applied to liquid level and flow online monitoring, waterlogging or overflowing early warning and alarming, monitoring data public issuing, monitoring data statistic analysis and the like of point locations such as a drainage pipeline, a drainage channel, a drainage inspection well, a drainage opening, a city sunken road, a city underground parking garage and a city receiving water body.

The embodiment of the invention provides a deployment system and a deployment method of an application program. In a process that container resources are deployed for each physical node in a cluster, firstly, Service corresponding to each piece of business is created by aiming at the business, the container resources are deployed to each physical node in the cluster through the Service, so that each piece of container resource can know the business corresponding to the container resource, and logical grouping is realized on an aspect of business so as to bring convenience for managing the container resources. In addition, the configuration parameters of the Service contain a container amount and a container mirror image, the simultaneous deployment of all physical nodes can be realized according to the container amount through the characteristics of the container mirror image in docker, time for deploying the container resources in the cluster is shortened, and efficiency for deploying the container resources is improved.

The invention discloses a method, a device and a system for deploying application program operation environment, relating to the network technology field. The invention solves the low efficiency of deploying the operation environment in the prior art. The method disclosed by the invention comprises steps of obtaining a target application program by a service terminal, wherein the target application program is developed based on the operation system on the service terminal, adding the operation environment of the target application program into a container file and transmitting the container file to a client terminal, wherein the operation environment is the operation environment of the operation system of the corresponding service terminal, receiving the container file transmitted by the client terminal, starting up the container engine program and running the container file, and loading the operation environment in the client terminal operation system. The invention is mainly applied in the process of deploying the application program in the intranet of the enterprise.

Embodiments of the invention provide a server production environment deployment method and apparatus, an electronic device and a storage medium. The method comprises the steps of creating a mirror image in a server by using a mirror image creation command of an application container engine docker; according to a production environment required by an installation package about to run in the server, configuring the mirror image, and generating a target mirror image consistent with the production environment required by the installation package, wherein the production environment is a bottom running environment required by the installation package about to run in the server; and starting a container, and loading the mirror image used for deploying the production environment of the installation package. The server production environment is deployed through the docker, so that quick deployment of the server production environment and quick running and starting of the production environment are realized.

The invention discloses a large-scale network monitoring oriented virtual deployment system and method. The system is provided with a deployment center platform and a plurality of deployment target machines communicated with the deployment center platform via a network. The deployment center platform is responsible for uniformly planning and managing a topology structure of measurement probe deployment in an entire computer network, issuing a deployment task according to the existing measurement probe deployment condition and network congestion condition, and executing management and version control on the deployed measurement probes. The deployment target machines receive and execute commands from the deployment center platform, and automatically execute corresponding operations so as to enable the measurement probes to be usable in the network; and a software dependency detection mechanism and a process matching rule are respectively used for realizing the platform independency of deployment and verifying the achievement of deployment. The system and the method can be used for solving a plurality of problems, such as dependency detection for deployment environment of the target machines, upgrading and maintaining of a management system version, concurrent deployment, automatic installation and detection of the plurality of target machines, dynamic scheduling and the like, in the prior art, and have better promotion and application prospects.

Disclosed are a distributed testing method and device. The method comprises the steps executed on a testing control side and the steps executed on testing executing sides. In the steps executed on the testing control side, activation instructions, used for activating a testing side, of all the testing executing side are received; the effectiveness of attribute information of all the testing executing sides is verified and communication is established with the testing executing side with the effective attribute information; a configuration file is generated according to attribute information of the testing control side, testing programs and the configuration file are packaged to obtain a testing program package, and the testing program package is sent to the testing executing side; testing instructions used for starting all the testing executing sides are received and testing cases are sent to the corresponding testing executing sides according to the testing instructions. In the steps executed on the testing executing sides, the testing program package sent by the testing control side is received, and testing programs in the testing program package are installed; communication with the testing control side is established according to the configuration file in the testing program package and the existence states of the testing executing sides are fed back to the testing control side; the testing cases are received and testing is conducted on a system to be tested according to the testing cases. By means of the distributed testing method and device, the efficiency is improved.

The invention discloses a distributed service integrated system for a service-oriented architecture and an application method thereof and belongs to computer application technique. The defects that a present service system cannot perform dynamic management, the automatic expanding and contracting capacities of service component examples are poor and the simultaneous proceeding of large-scale service system examples cannot be supported are overcome. The distributed service integrated system is mainly composed of a deploying node cluster, a service control processor, a resource control server, a Web gateway and a service access point. According to the distributed service integrated system provided by the invention, the operations by a service provider and a user are simplified; a stable operation environment is provided; multiple operation requests of service systems are concurrently processed; when the deploying nodes are subjected to fault crash, the relation thereof is analyzed, and the corresponding examples are informed of registered information and are caused to correspondingly process, so that the service supplied by the service system can be recovered and be reusable within a short period of time and the high applicability of the system is realized; and the distributed service integrated system is suitable for being popularized and applied.

The invention relates to a Ceph-based network target range rear-end storage system design method, and relates to the technical field of information security. The invention provides a construction method of a network target range rear-end storage system under a cloud architecture in order to solve the problems existing in an existing network target range rear-end storage system. According to the method, the Ceph is combined with the OpenStack, the Ceph is used as Nova in the OpenStack; an identity authentication service Keystone of the OpenStack is bound with a Ceph object gateway at a storagerear end of a Glance, Cinder native component, and secondary development of management application is carried out based on a Ceph gateway module. The method can effectively improve the deployment efficiency and the storage security of the network target range. Therefore, the functions of second-speed starting of the virtual machine, real-time migration of the virtual machine, data fragmentation storage, data full backup, data incremental backup and the like in the network target range are achieved.

The application suitable for the technical field of cloud provides a cluster deployment method and device, terminal equipment and a storage medium. According to the cluster deployment method, a node to be deployed of a cluster host is determined and a preset first configuration file is invoked; a deployment environment of the cluster host is initialized according to the first configuration file; asecond configuration file of a to-be-deployed node of the cluster host, is generated so as to generate a corresponding configuration file for the to-be-deployed node of the cluster host without manually configuring node parameters for each node by a user; according to the second configuration file, a node corresponding to the cluster host is deployed in the initialized deployment environment, sothat the system can deploy the node of the cluster host according to the second configuration file to complete cluster deployment. Therefore, according to the cluster deployment method provided by theembodiment of the invention, manual configuration of a user is not needed from environment deployment of the host to node deployment of the host, one-key cluster deployment is realized, and the deployment efficiency is improved.

The invention discloses a virtual network function deployment method of a service function chain. The method comprises steps of successively selecting un-deployed VNFs in the service function chain; when the current VNF is not the last VNF, calculating the reliability value from each top point in a top point set to a source point s; when a non-target top point meets a preset constraint, using thereliability value from the top point to the source point s to update the preset reliability value of the top point; selecting a non-target top point corresponding to the biggest top point reliabilityvalue to deploy the current VNF; when the current VNF is the last VNF in the service function chain, calculating a first calculation value; when the top point meets a preset condition, using the ratioof the first calculation value of the current top point to an attribute reliability value of the current top point to update a preset threshold of the current top point; and when all the top points in the top point set are traversed, selecting the top point corresponding to the biggest set threshold in all the top points to deploy the last VNF, and outputting a deployment scheme.

The invention discloses a wireless network node dynamic deployment method based on network flow, and the wireless network node dynamic deployment method based on the network flow solves the problem that mobile energy consumption is too large due to blindness of moving of sensor nodes during the changing process of coverage area of wireless sensor network, with mobility, of the sensor nodes. The wireless sensor network node dynamic deployment method based on the network flow comprises the following steps that when an area, to be observed, of the wireless sensor network changes, a heuristic type area coverage optimization method based on a genetic algorithm is utilized to calculate the position where the sensor nodes need to be deployed, then a network flow algorithm is used for planning the moving route of the sensor nodes reasonably according to the all-sensor-node shortest total route principle. The wireless network node dynamic deployment method based on the network flow can calculate the best objective positions to be covered of the wireless sensor network nodes and the shortest moving route of the sensor nodes in the coverage area of the sensor nodes, and reduces moving energy consumption of the sensor nodes in the network coverage deployment.

The invention provides an automatic trunked network management device configuration method based on XML (Extensible Markup Language). The method depends on a trunked network management function, the so-called trunked network management means that a trunked network management system can manage all the devices connected by a trunked proxy device, and also can identify different device types and the positions of the devices. By the information, configuration files can be dynamically issued to the devices, thus, the problem of how to issue the configuration commands to the devices in the whole network is solved, and the difficult problem of network development is solved to a large extent. Moreover, the network development and management efficiency can be improved greatly. A user network management worker at a network management center can realize dynamic configuration of all the devices in the whole network through the network management system.

The embodiment of the invention provides a data shunting method and system for an edge application. The method is applied to a mobile edge computing MEC platform. The MEC platform comprises a serviceregistration center SR network element, an edge session management function SMF network element and at least one user plane function UPF network element. At least one edge application is deployed on an MEC platform, the edge application can provide edge service, and an SR network element receives a registration request message of the edge service provided by the edge application and sends a registration request response message to the edge application. The SR network element configures a shunting rule matched with the edge service according to the registration request response message, and sends the shunting rule to the SMF network element, the SMF network element receives the shunting rule, the UPF network element is configured with the adaptive shunting rule, so that the UPF network element performs shunting processing on the data of the edge application, one-key deployment of the edge service is realized when the mobile edge computing MEC platform deploys the edge service, the process of sending the shunting rule by the edge service is reduced, and the deployment efficiency is improved.

The invention relates to one sensor network data inquire process method based on mobile agent middle part, which comprises the following steps: regarding whole wireless sensor as one database; realizing on mobile agent middle part; executing user inquire task by mobile agent onto designed point to start operations till fulfilling inquire task to end its life circle or according to its task need onto other point; inquiring process system design to realize network base station to change inquire agent design.

The invention discloses an intelligent on-line liquid level monitoring and early warning system. The intelligent on-line liquid level monitoring and early warning system is composed of a data center and at least one liquid level monitoring and early warning subsystem, and is characterized in that the liquid level monitoring and early warning subsystem comprises a liquid level monitoring point, a liquid level monitoring host and a monitoring repeater; the liquid level monitoring host is used for carrying out continuous monitoring on the liquid level monitoring point, generating monitoring data and transmitting the monitoring data to the monitoring repeater according to a changeable transmission time interval, and the monitoring repeater is used for receiving the monitoring data and transmitting the monitoring data to the data center according to the changeable transmission time interval; the data center is used for processing the received monitoring data to obtain status data and various curves of the liquid level monitoring point and displaying and releasing the status data of the liquid level monitoring point in real time. By means of the intelligent on-line liquid level monitoring and early warning system, on-line liquid level monitoring, short-message warning, waterlogging early warning, short-time forecasting, monitoring data public release and the like can be carried out on points such as a drainage pipeline, a drainage channel, a drainage inspection well, a drainage exit, an urban sunken road, an urban underground parking garage and urban receiving water.

The embodiment of the invention provides a base station deployment method, a network server and an unmanned aerial vehicle. The method comprises the steps of determining a target geographical range where a base station is to be deployed; determining a first base station and a second base station, and a candidate geographical location for deploying the base station between the first base station and the second base station according to signal coverage quality of each base station within the target geographical range; and determining a target geographical location where the base station to be deployed according to the signal coverage quality of the first base station and the second base station when the unmanned aerial vehicle carrying the base station reaches each candidate geographical location. According to the base station deployment method, the network server and the unmanned aerial vehicle provided by the embodiment of the invention, the signal coverage quality of the base station is automatically measured by using the characteristic that the unmanned aerial vehicle is rapid and flexible to deploy the base station, so that the deployment time of the base station is reduced, the automation degree of deployment of the base station is increased, and deployment efficiency of the base station is improved.

The invention discloses a virtual network function deployment method based on a grey wolf algorithm. The method comprises the following steps of (1), inputting node information and link information ofa bottom layer network and inputting service function chains, wherein a service function chain request comprises a plurality of orderly constrained virtual network functions, taking a resource demandof deploying all virtual network functions in the service function chain request on computing nodes of the bottom layer network as a first constraint condition of a service function chain deploymentscheme, taking a bandwidth demand among all virtual network functions in the service function chain request as a second constraint condition of the service function chain deployment scheme, and takingtotal delay of service function chain deployment as an optimization object of the service function chain deployment scheme; (2) initializing a grey wolf population; (3), evaluating the grey wolf population; (4), updating position information of each grey wolf individual in the grey wolf population; and (5), judging whether the maximum iteration times arrives or not, and outputting the global optimum grey wolf. The method is high in efficiency, short in time and wide in application range.

The invention discloses a container-based block chain deployment method. The method comprises the following steps: 1) establishing a kubernetes container cluster; 2) manufacturing a Docker mirror image comprising an operating system, a block chain installation package, a daemon process and a startup script; 3) creating a container arrangement file, and defining the number of container instances, aused mirror image ID, a running port, an NAT gateway ID and an elastic IP; 4) calling a Kubectl command line tool, connecting the container cluster created in the step 1), loading the docker image produced in the step 2) by using the container arrangement file created in the step 3), and creating a blockchain container application; 5) communicating with a daemon process in the container through the GRPC, calling a command for starting the block chain, transmitting a starting parameter, and starting the block chain; And calling a command for checking the block chain state, checking whether theblock chain is successfully started or not, and completing the deployment of the block chain. According to the invention, the container-based block chain deployment method is realized, and the problems of complex operation and low speed of block chain deployment are solved.

Disclosed are a data storage method and a data storage device. The method includes: obtaining data which comprises fields comprising field names and data contents; marking the field names; building an index of the field names, which comprises mapping relationships of the marking and the data contents of the fields; saving the index of the field names and the data contents of the fields as a data record which comprises an index area storing the index and a data storage area storing the data contents. By the method, consumption of storage resources is lowered and data searching efficiency are enhanced.

The invention discloses a distributed cluster deploying method and system. The method comprises: obtaining a cluster deploying instruction, providing an interface on a Web page for selecting an installation program according to the cluster deploying instruction; obtaining installation software selected on the Web page by a user, executing deploying a script corresponding to a installation program; executing the deploying script so that the installation program is installed at the corresponding terminal. Through the method, the installation software for deploying a cluster can be automatically installed at the appointed terminal; therefore the cluster constructing time is greatly reduced; and the cluster deploying efficiency is promoted.

The invention provides a deployment method of a cluster parallel computing environment, belonging to the field of deployment and implementation of high performance computing (HPC) clusters. The method comprises the following steps of: A, installing a linux system on a management node, and installing an operating system of a computing node and a lustre node through a network; B, mounting storage equipment on the lustre node through an optical fiber storage network, and deploying a lustre parallel file system; C, mounting the lustre parallel file system and a lustre parallel file catalog aimingat a management node and the computing node by using a high-speed network; D, configuring a password-free access environment, and implementing password-free access among the nodes; E, configuring nisand ntp services on the management node, and implementing user sharing and node time synchronization; F, deploying application software to the shared lustre file catalog; and G, configuring a monitoring tool, and monitoring the operating state of a cluster node in real time. By the efficient HPC implementation method, the implementation cost is reduced, and the stability and the reliability of the HPC cluster are enhanced.

The invention provides a wireless sensing network coverage optimization method based on a virtual force and a firefly algorithm. The method is characterized by firstly, taking a utilization rate of each sensor node in a wireless sensing network and an effective network coverage rate as optimization targets, and establishing a corresponding mathematical model; then, carrying out initial layout of the sensor nodes according to a virtual-force resultant force among the sensor nodes; and finally, through the firefly algorithm, carrying out adaptive dynamic deployment on the sensor nodes. In the invention, a service life of a wireless sensing network is prolonged and simultaneously network coverage efficiency is effectively increased.

The present invention discloses a system and a method for multi-cluster container deployment. The system comprises: a container engine configured to send a mirror image download address obtaining request to a local mirror image warehouse, wherein the request comprises a mirror image identifier, and a container mirror image is downloaded from the local mirror image warehouse through a mirror imagedownload URL; the local mirror image warehouse configured to inquire whether the container mirror image corresponding to the mirror image identifier has been stored or cached or not, wherein, if yes,the mirror image download URL is directly returned to the container engine, or else, the mirror image download URL pointing to a remote mirror image warehouse is inquired from the mirror image management center, a missing container mirror image is downloaded into the local mirror image cache from the remote mirror image warehouse to generate a mirror image download URL pointing to the local mirrorimage cache, and the mirror image download URL is reported to the mirror image management center and is returned back the container engine; and the mirror image management center configured to returnback the mirror image download URL pointing to the remote mirror image warehouse to the local mirror image warehouse. The system and the method for multi-cluster container deployment can improve thecontainer application cross-cluster deployment efficiency.