49 results about "Elastic cloud" patented technology

Provided is a computing-system monitor configured to monitor a plurality of computing-systems each having a plurality of monitored computing-instances. The computing-system monitor may include a plurality of collectors, each collector executed by one of a plurality of monitored computing-instances, wherein the plurality of monitored computing-instances each are part of one of a plurality of separately monitored computing systems, and wherein each of the collectors is operable to output metrics of a corresponding monitored computing-instance executing that collector. The computing-system monitor may also include an analytics platform, the analytics platform having a plurality of analytic computing-instances, the analytics platform being operable to receive metrics output by the plurality of collectors, calculate statistics with the analytic computing-instances based on the received metrics, and output the calculated statistics.

The invention provides an elastic cloud distributed massive request processing method, device and system, and can instantaneously and automatically carry out expansion when a server cannot respond to a peak value. The method comprises the steps that: S1: a cloud computing management platform creates a container, and a message queue cluster, a ZooKeeper cluster, a service instance and a data storage cluster are respectively constructed on the container; S2: a client sends requests containing time to a load balancing server, the load balancing server distributes the requests to the message queue cluster, and after being synchronized by the ZooKeeper cluster, the requests are rearranged according to a time sequence; S3: the service instance acquires the requests from the message queue cluster, processes the requests, then stores a processing result to the data storage cluster, and returns the processing result to the client; and in the process of S1 to S3, the cloud computing management platform monitors a state of the container where the service instance is positioned, and when a state index exceeds a preset threshold, a new container is created by duplicating the container so as to improve a processing speed.

The invention relates to the technical field of the optimization of computer performance and particularly relates to a dispatching method for working load of an elastic cloud computing platform. Thedispatching method comprises the steps of initializing virtual machines and tasks and combining the virtual machines according to the relative load among the tasks; dividing the total execution time of the tasks into setting number of scheduling phases, and working out an optimal scheduling policy according to the working load of a current task by a dispatching system; then dividing or combining the scheduling phases according to the degree of similarity of the working loads of two adjacent scheduling phases; finally adjusting the number of times of simulation to the sequence of the divided or combined scheduling phases in a self-adaption way so as to determine the computing time of the next scheduling phase until the end of the program. According to the dispatching method, the adaptive multi-tasking load change stage can be configured reasonably, so that the dispatching performance of a whole system is improved, and the test time is reduced.

The invention provides an architecture of elastic cloud. The architecture of elastic cloud comprises a cloud resource control end, an internal network, a storage device, a reverse proxy server, an external network and a server cluster, wherein the cloud resource control end, the internal network and the storage device are connected in sequence, the reverse proxy server and the external network are connected in sequence, the cloud resource control end is connected with the reverse proxy server, a software provider has access to the cloud resource control end, virtual machine images and configuration files are uploaded and are stored in the storage device by the cloud resource control end through the internal network, virtual machines are registered in the server cluster and instantiated, and the configuration files of the reverse server are modified. According to the architecture of elastic cloud, by monitoring the virtual machines running in elastic cloud, service in the elastic loud is guaranteed to be always in the healthy state according to the load dynamic flexible service capacity of the virtual machines, and it is guaranteed that after the server cluster changes, a user request can not be sent to the service virtual machines which do not exist any more.

The invention provides an edge application management method and system, and the method comprises the steps: generating an edge application template for deploying an edge application managed by an edge cloud node, and enabling the edge application template to comprise the resource configuration information for deploying edge cloud node resources and the system application data of an elastic cloudserver in a cloud data center; synchronizing the system application data to an edge cloud node to be deployed; and deploying resources of the to-be-deployed edge cloud node according to the resource configuration information to realize management of the edge application. By applying the scheme provided by the embodiment of the invention, the unified deployment of the edge applications managed by the edge cloud node can be realized through the edge application template, and the deployment workload of a user and the management difficulty of the edge applications are reduced.

The invention discloses an intelligent contract running method, device and system and a computer readable storage medium, and relates to the field of computer technologies. The intelligent contract running method comprises the steps of reading data of an intelligent contract from a block chain, wherein the data of the intelligent contract includes an intelligent contract code; obtaining parameterinformation of the intelligent contract code from the data of the intelligent contract; constructing a script of the intelligent contract according to the parameter information; and running the scriptso as to construct and start an intelligent contract module by adopting the intelligent contract code, thereby enabling a core module of the block chain to exchange execution data of the intelligentcontract with the started intelligent contract module through a communication agent layer of block chain nodes. According to the embodiment of the invention, the script of the intelligent contract canbe constructed according to the code of the intelligent contract, and the intelligent contracts runs through starting the script, thereby being capable of still executing and starting the intelligentcontract when the block chain nodes are deployed in an elastic cloud environment, and improving the universality of the intelligent contract.

A method and is provided for obtaining a vetted certificate for a microservice in an elastic cloud environment. The microservice receives a one-time authentication credential. The microservice utilizes the one-time authentication credential to obtain a client secret. The microservice obtains an access token and CSR (Certificate Signing Request) attributes using the client secret and constructs a CSR utilizing the CSR attributes. The microservice requests a vetted certificate from a Certificate Authority (CA) and includes the access token and the CSR in the request. If the access token and the CSR pass vetting at the CA, the CA sends a vetted certificate to the microservice.

The invention discloses a method for predicting elastic cloud computing resources based on an SARIMA-WNN model. The method comprises the steps that complementary advantages are achieved by using a seasonal autoregressive integrated moving average (SARIMA) model combining with a wavelet neural network (WNN) prediction model to improve the prediction accuracy; according to the SARIMA, seasonal periodic factors are added on the basis of an ARIMA model, periodic cloud resource demand data of a past section is input to a SARIMA (q, d, q)(P, D, Q) s model to obtain d, p, q, D, P and Q respectively;prediction is conducted on tranquilized and sequenced codes by using the SARIMA model, and a prediction result is marked as and an L residual value is marked as rt, wherein the prediction result andthe residual value can be obtained through the prediction; a model which conforms to elastic cloud source prediction is obtained through conducting training on the WNN network by using training samples, prediction is conducted aiming at the residual sequence rt, and the prediction result is marked as ; finally the prediction result of the SARIMA-WNN combined model is obtained. By means of the method, the problems of inaccuracy of a single model, poor effects of other combined models and the like are solved.

The invention discloses an electric power big data elastic cloud computing storage platform architecture method. The electric power big data elastic cloud computing storage platform architecture method comprises the following steps that a cloud computing based storage platform bottom-layer architecture is firstly erected, a cloud computing based storage platform high-layer architecture is secondly erected, and a cloud computing based storage platform architecture disk is finally partitioned. The novel electric power big data elastic cloud computing storage platform architecture method and a cloud infrastructure solution easy to achieve and extend and rich in function are provided by designing the cloud computing based storage platform architecture and a disk partition scheme. The cloud computing based storage platform architecture provided by the electric power big data elastic cloud computing storage platform architecture method can also provide a novel storage method for smart power grid big data, and the problems of slow call and low computing when electric power big data is used are solved.

The invention relates to a peer-to-peer architecture based elastic cloud distribution method. The stability and expandability of distribution nodes are improved by functionally dividing the distribution nodes into distribution center nodes and peer nodes methodically and forming a hybrid peer-to-peer network. Meanwhile, different conditions of whether a cache system hits the target are distinguished, and the method comprises the steps of basic distribution and extended distribution, thus improving the data distribution efficiency. The method has the advantages that large-scale distribution service can be supported, the data distribution speed can be increased, the problems of network bandwidth of a single data source and server performance bottleneck are broken through, the network access quality is optimized, and the method has a better application value.

A digital content management system comprises a technology and process, which provides for personalized searching and browsing of digital content in a Digital Content Storefront based upon a real-time contextual merge of cloud-based Digital Content Catalog metadata and individualized, consumer-personalization Contextual Metadata, wherein the Contextual Metadata and Digital Content Catalog metadata are respectively delivered from a set of consumer web services provided at a managed datacenter in combination with a real-time elastic cloud cache, preferably provided by a Content Delivery Network. This system focuses on and expedites end-to-end delivery, caching, and real-time consumer application metadata merging to offer highly scalable and responsive contextual Catalog search and browse results.

The automatic deployment method for improving the remote login safety of the elastic cloud host comprises the following steps that S1, a PC end initiates a login request to a system, a remote access processing module checks whether a port is open or not, if yes, the next step is executed, If not, a data packet is discarded, and the request is ended; S2, the remote access processing module checks whether the IP of the PC end is in a white list or not, if yes, the next step is executed, otherwise, the data packet is discarded, and the request is ended; s3, the remote access processing module informs the PC that the available authentication protocol is only the secret key; s4, the PC terminal sends the user name and the secret key, and the remote access processing module checks whether the private key and the public key are paired or not and carries out judgment; s501, pairing the private key with the public key, and establishing connection between the PC terminal and the cloud host; andS502, if the private key is not matched with the public key, the remote access processing module informs the PC of login failure and returns to the step S4. According to the method, safety reinforcement is triggered every time a new cloud host is created successfully, the application is wide, and the expansibility is high.

The invention discloses a VoIP bandwidth quality improving method and system based on elastic cloud. The method includes the steps of firstly, setting up virtual channel connection between a client side software assembly DBO-C and a server node software assembly DBO-S, wherein the server node software assembly DBO-S can be installed on the elastic cloud in a mutual information collision mode and in the form of a mirror image gear; secondly, packing or unpacking VoIP protocol signaling or media at the two ends of a virtual channel, and subsequently forwarding the VoIP protocol signaling or media through the server node software assembly DBO-S at one end of the virtual channel according to the destination address of the VoIP protocol signaling or media by means of an optimized route. A high-efficiency and high-cost-performance bandwidth optimizing solution is provided for small and medium-sized ITSPs and enterprises which use VoIP on a large scale; by means of the VoIP bandwidth quality improving method and system, quality of the VoIP voice service can be improved, a large number of bandwidth and server trusteeship expenses are reduced, and meanwhile the time of the system for responding to the client demands can be shortened.

The invention discloses an elastic cloud platform storage and scheduling system model based on the XEN. Virtual machines in the platform all run on the XEN. Virtual disks required by the virtual machines are stimulated from a distributed virtual block storage device DVBD which is based on an Hbase and an HDFS (Hadoop distributed file system). The HDFS is a distributed file system on a Hadoop, and all data on the HDFS are redundant and back-up while security of data in the virtual machines is guaranteed; and otherwise, the data on the HDFS are distributed and free of physical locations, so that the virtual machines are free of physical locations. When one virtual machine is in failure, the virtual machine can be switched off or removed by the platform. Reliability and sustainability of the data are guaranteed. The platform further comprises a scheduling system which is used for performing source scheduling of the virtual machines of the platform.

The invention relates to a multi-point access method based on an elastic cloud. A plurality of local area networks can be connected to realize data interaction among all nodes inside the elastic cloud. The multi-point access method comprises the following characteristics: a general standard communication protocol and an interface specification are adopted to meet a requirement of data interaction of different business systems, a communication layer is unrelated to an application; the general standard communication protocol and the interface specification are adopted to ensure that different applications are coordinated on a general communication bottom layer. A uniform communication module is provided for call: to unify the communication between a service system server end and a client end, the bottom layer communication module is used for realizing communication and is packaged together with some communication protocols, and a server end program and a client end program uniformly call the bottom layer communication modules and are connected and communicated by adopting a TCP long connection manner. The development of an application program focuses on realization of the function of the application program without considering realization of a communication part.

The invention relates to a container-based batch processing job scheduling method and device, computer equipment and a storage medium. The method comprises the steps that a workload packaging module reads a workload description configured by a user to obtain a corresponding operation unit container mirror image, and packages the workload description and the operation unit container mirror image toobtain a workload; a workload queue management module adjusts the sequence of the workload queues according to a scheduling priority strategy through a multi-queue queuing system comprising a preemption queue, a resource sensitive queue and a common queue; and a workload scheduling module takes out load scheduling execution and the workload operation monitoring module carries out operation monitoring. According to the invention, the efficiency of containerized batch processing job scheduling can be improved, and the balance between the resource utilization rate of the elastic cloud operationenvironment and the workload execution efficiency is realized.

The invention relates to an automatic flower watering device for achieving remote monitoring and control based on a cloud server. The device comprises a power supply system, a monitoring system, a watering system, a service system and a remote management system. The watering system is only provided with a water inlet, multiple water outlets are independently controlled by multiple electromagneticvalves, and multiple flower pots in a house can be watered. A monitoring control module and a main chip CC3200 of a watering control module are on-chip internet wireless MCU modules which are high inintegration level and small in size, the monitoring system is more conveniently placed in the flower pots, the CC3200 is connected with a router through WIFI, and all the range of the house can be covered. The elastic cloud server is adopted for the service system, in cooperation with a database, the access demand of a user can be met in time, and meanwhile the service cost is greatly lowered. Monitoring data, flower knowledge and flower cultivation experience are storage through the database. The mode of using an APP and a website is adopted for the remote management system, and more convenience is provided for remote management of the user.

The invention provides computer equipment, a virtualization chip and a data transmission method. The computer equipment comprises a physical machine and a virtualization chip, and the virtualization chip is connected with the physical machine through a high-speed serial bus; the virtualization chip is used for processing according to data interacted between the physical machine and target equipment. Through the technical scheme of the invention, the performance and high isolation of the physical machine can be ensured, and the elastic cloud deployment of the virtual machine is kept, so that the physical machine has the elasticity of the virtual machine, and can support the rapid deployment and migration of the physical machine, support the starting of a cloud disk, mount the cloud disk andautomatically operate and maintain the cloud disk.

The embodiment of the invention belongs to the technical field of data analysis, and particularly relates to a rail transit large passenger flow track analysis method based on elastic cloud, a terminal and a storage medium, the rail transit large passenger flow track analysis method based on the elastic cloud comprises the following steps of: acquiring real-time multi-source passenger flow data, fitting large passenger flow track information on the basis, subjecting the multi-source passenger flow data to correlation fusion through correlation, comparison and crossing methods, verifying the fitted large passenger flow track information, thus improving the integrity and accuracy of overall data analysis, and performing real-time analysis processing after verification, thus improving the accuracy and precision of generating real-time rail transit large passenger flow track data covering flow density, flow direction and flow velocity. The bottleneck that analysis result errors are too large when single data source analysis is used is broken through, and the human resource investment cost is reduced.

The invention discloses a virtual terminal distributed system based on an elastic cloud server and an intelligent terminal. The virtual terminal distributed system is an entity terminal for presentingcloud server virtual terminals (mobile phones, computers, watches, bracelets, projection and virtual reality) by using intelligent glasses and head-mounted equipment (head-mounted display) wearable equipment to log in the cloud server; through interaction, opening of the elastic cloud server is completed in a self-service mode, a CPU, a memory, an operating system, specifications and a login authentication mode are specified, and meanwhile the specifications of the elastic cloud server can be adjusted at any time according to needs. The virtual terminal distributed system based on an elasticcloud server and an intelligent terminal is used for presenting and using an entity terminal of a cloud server virtual terminal, has the advantages of being easy and convenient to use, small in size and the like, brings more convenience to life, study and work of people, becomes an important growth point of future intelligent science and technology products, and helps more organizations, enterprises and personal consumers to easily seize the opportunity in the era of internet of things and intelligent internet of things.

The invention discloses a medical image-based digital film and report acquisition method and system. The method comprises the following steps of photographing a medical image of a patient through a medical image instrument, generating an electronic film image, and transmitting the electronic film image to a workstation host. The workstation host receives the electronic film image transmitted by the medical image instrument, analyzes and processes the electronic film image and generates an inspection report. An elastic cloud server receives the user information, and the corresponding electronicfilm image and the inspection report of the workstation host and sends the user information, the corresponding electronic film image and inspection report to a cloud database for storage; and a userterminal receives and checks the electronic film image and the inspection report. By adopting the electronic film image and electronic inspection report, the user can obtain and view the electronic film image and the inspection report through the user terminal, convenience is brought to the user, the medical treatment speed is increased, manpower and material resources are saved, the image and theinspection report are convenient to obtain, and besides, the cost is low.

The invention discloses an autonomous elastic cloud system management method. The method comprises four modules, namely an application program elastic editor, a cloud elastic intermediate component, asupervised virtual machine and a main virtual machine. By continuously and randomly changing the cloud execution environment and the platform type, especially an internal attacker, the current execution environment and vulnerabilities existing in the current execution environment are difficult to find, so that the system can escape from attacks. According to the cloud service behavior fuzzy algorithm, the space-time behavior confusion and moving target defense are utilized, so that the active computing nodes and the internal resources thereof of the system are continuously changed, and therefore, attackers are avoided. In addition, diversity is achieved by using different execution of each software component, and the ARCM method is adopted, so that the normal operation of the cloud application program is difficult to interrupt by attacks. The dynamic changes in the execution environment can effectively hide potential vulnerabilities of the system, and an automatic management algorithmis adopted to provide a dynamically changing configuration capability and hide a cloud execution environment.

Systems, and methods are described to provide voice search in an elastic cloud environment communicating with a set-top box (STB) by receiving by a voice cloud search server pulse-code modulation (PCM) audio packets transmitted from the STB; sending the PCM audio packets to a natural language processing (NLP) service for converting to text; sending the text sets to an elastic voice cloud search server for querying an electronic program guide (EPG) service, channel and program data associated with the text sets wherein the EPG service to at least return identified channel and program data; in response to an identified return of channel and television program data, sending sets of text to a third-party search service for performing an independent search for related data and returning search results of video and image content which is then stripped of dynamic scripts to return to the STB.

The invention discloses a method for creating a multi-tenant elastic file system based on cloud computing, which comprises the following steps that: a management and control center of the elastic filesystem selects a proper cloud node and issues a first task for creating the elastic file system to a scheduling service of the cloud node, and a lightweight virtualization technology is used in a cloud network security isolation environment of a cloud platform; a plurality of elastic cloud nodes are created, scheduling services and storage access services in the cloud nodes execute instructions for creating an elastic file system, each tenant uses and manages own independent resources, reliable file system services are provided for multiple tenants conveniently and quickly, data of the multiple tenants can be isolated safely, capacity and performance can be changed quickly, and the system performance is improved. The cost is low and the resource utilization rate is high.

Systems, and methods are described to provide voice search in an elastic cloud environment communicating with a set-top box (STB) by receiving by a voice cloud search server pulse-code modulation (PCM) audio packets transmitted from the STB; sending the PCM audio packets to a natural language processing (NLP) service for converting to text; sending the text sets to an elastic voice cloud search server for querying an electronic program guide (EPG) service, channel and program data associated with the text sets wherein the EPG service to at least return identified channel and program data; in response to an identified return of channel and television program data, sending sets of text to a third-party search service for performing an independent search for related data and returning search results of video and image content which is then stripped of dynamic scripts to return to the STB.

Described embodiments provide systems and methods of managing storage of data of a user across storage service providers. A storage service may receive a request to store data by a user. The storage service may communicate with storage service providers and may maintain storage vectors for each storage service provider. The storage service may identify a policy for the user. The policy may specify usage of the storage service providers based on a user profile. The storage service may determine, based on the policy, storage service providers to use to store the data of the user. The storage service may store a first portion of the data to a first storage vector of a first storage service provider. The storage service may store a second portion of the data to one of a second storage vector of a second storage service provider or a storage of the storage service.

Systems, and methods are described to provide voice search in an elastic cloud environment communicating with a set-top box (STB) by receiving by a voice cloud search server pulse-code modulation (PCM) audio packets transmitted from the STB; sending the PCM audio packets to a natural language processing (NLP) service for converting to text; sending the text sets to an elastic voice cloud search server for querying an electronic program guide (EPG) service, channel and program data associated with the text sets wherein the EPG service to at least return identified channel and program data; in response to an identified return of channel and television program data, sending sets of text to a search service for performing an elastic search for related data from a plurality of different search sources and returning search results and error codes to a requester.

The invention discloses a Quota-based cluster fuzzy control capacity planning method, which comprises the following steps: 1, converting daily data increment into Quota according to a storage period provided by a user side; 2, creating a cluster region, and designing and abstracting concepts rack and region of two layers of logics to plan a cluster; 3, reserving a free-rack buffer pool, and positioning the free-rack buffer pool at 10% of the free-rack buffer pool, wherein all the clusters share a free pool of one elastic cloud; 4, calculating the adjustment amount count of each region according to a fuzzy control capacity planning strategy; 5, carrying out duplicate removal operation; and 6, querying the task of each region, and sequentially checking the capacity expansion and shrinkage task and the capacity shrinkage task which are being executed by each region. The cluster resource utilization rate is improved.

The invention discloses a method for predicting elastic cloud computing resources based on the SARIMA-WNN model, which uses the seasonal time series model (SARIMA) combined with the wavelet neural network (WNN) prediction model to realize complementary advantages and improve prediction accuracy; SARIMA is based on the ARIMA model The seasonal periodicity factor is added on the basis of , and the cloud resource demand data of the past period is input into SARIMA (q, d, q) (P, D, Q) s In the model, d, p, q, D, P, Q are respectively obtained; the SARIMA model is used to predict the code after the smoothed sequence, and the prediction result can be obtained through the prediction and the L residual value is marked as r t ; Use the training samples to train the WNN network to obtain a model that is consistent with the prediction of elastic cloud resources, and then for the residual sequence r t Prediction is carried out, and the prediction result is marked as; Finally, the result predicted by the SARIMA-WNN combination model is obtained. The present invention solves the problems of inaccurate single model and poor effect of other combination models.

The embodiment of the invention discloses a virtualized computing organization control management system and method, and the system comprises a data center module which is used for binding a pluralityof hosts, so as to enable an elastic cloud server to select an operation host or an operation host unit; a host management module which is used for selecting a host on the available host set according to the selected Flaver template when the user creates the virtual machine; a scheduling module which is used for automatically selecting a more suitable host according to the data center pool, the host unit or the host resource condition when a user creates an elastic cloud server or needs to select the host; a data processing module which is used for managing related data of each host; and a local storage module which is used for creating volume by the user according to the required elastic cloud server, and independently mounting and dismounting the volume. The related services of the elastic cloud server are managed according to the requirements of the user for the virtual machine and the dynamic change of the resources of the running hosts, so that the management efficiency is improved, and the error rate of manually configuring migration data is reduced.