215 results about "Cloud computing services" patented technology

The invention discloses an elastic management and optimal scheduling method and system for cloud computing resources, and belongs to the technical field of cloud computing resource management.The method comprises the steps that a cluster composed of multiple types of intelligent agents is constructed, and the intelligent agents comprise a resource evaluation intelligent agent, an elastic telescopic intelligent agent, a load balancing intelligent agent and a fault recovery intelligent agent; the intelligent agents are distributed and deployed on different nodes of a cloud computing data center, and information interaction is realized through a communication interface based on RESTful API and a distributed message bus constructed by a gRPC protocol; a unified agent management platform is set up and is responsible for registration, monitoring, scheduling and dynamic adjustment of agents, and orderly operation and efficient cooperation of the whole multi-agent system are ensured. According to the method, the functions of efficient elastic allocation, intelligent load balancing, rapid fault recovery, continuous optimization evolution and the like of resources in the cloud computing data center can be realized, and the quality and competitiveness of cloud computing services are effectively improved.

The present disclosure provides a resilient (radio) access network ((R)AN) slicing framework encompassing a resource planning engine and distributed dynamic slice-aware scheduling modules at one or more network access nodes, edge compute nodes, or cloud computing service. The resilient (R)AN slicing framework includes resource planning and slice-aware scheduling, as well as signaling exchanges for provisioning resilient (R)AN slicing. The intelligent (R)AN slicing framework can realize resource isolation in a more efficient and agile manner than existing network slicing technologies. Other embodiments may be described and / or claimed.

The invention relates to the technical field of forest fire management, in particular to an integrated forest fire intelligent analysis method and system. The system comprises a background service system, a central intelligent analysis system and a mobile intelligent analysis system. The background service system is deployed in a cloud computing server cluster and is used for uniformly storing personnel information, fire scene information and geographic information data and realizing multi-source data fusion and authority management through a standardized API (Application Program Interface); the central intelligent analysis system is deployed in a high-performance computer, integrates a forest fire danger auxiliary decision-making model, a forest fire spreading trend prediction model, a force distribution dynamic display module and a collaborative plotting module, and supports fire spreading prediction and real-time decision-making instruction issuing based on multi-dimensional data such as weather, terrain and vegetation; the mobile intelligent analysis system realizes fire spreading trend analysis, mobile plotting and instruction receiving in an offline environment, supports offline data caching and calling in an emergency scene, and effectively improves forest fire emergency response efficiency and resource scheduling accuracy.

An indoor air cleaning system is disclosed and includes an air pollution treatment device, and a networked cloud computing service device. The air pollution treatment device includes an air cleaning device, a central control and regulation device and a communication module for detecting, locating, circulating and filtering the air pollution in an indoor field. A gas detection module detects and transmits air pollution data to the communication module. The central control and regulation device communicates with and controls the gas detecting module, to control the air cleaning device for filtration. The networked cloud computing service device receives and stores the air pollution data to form an database. A control command is intelligently selected, and transmitted to the gas detection module. Consequently, the air cleaning device is controlled to filter the air pollution, and a gas state in the indoor field reaches a clean room requirement of ZAPClean Room 1˜9.

The embodiment of the invention discloses a real-time monitoring method and equipment for a cloud computing server room and a medium, relates to the technical field of equipment supervision, and is used for solving the problems of multiple blind areas and low reliability and real-time performance in the existing monitoring. The method comprises the following steps: collecting multi-source data in real time through a heterogeneous sensor network deployed in a cloud computing server room, and preprocessing the multi-source data based on edge computing nodes to obtain multi-source data features; performing alignment processing on the multi-source data features based on a preset space-time calibration algorithm so as to construct a global dynamic topology matrix of the cloud computing server room based on a preset machine room digital twin model and the aligned multi-source data features; based on the historical operation data and the global dynamic topology matrix of the cloud computing server room, constructing a multi-dimensional prediction map of the cloud computing server room; and inputting the multi-dimensional prediction map into a preset space-time diagram convolutional neural network model to identify a current abnormal event of the cloud computing server room and carry out early warning.

A system for situation awareness guided energy harvesting (SAGEH) in vehicles includes a cloud computing server, and sensors capturing information about a host vehicle and remote vehicles, and their environments. The vehicles and server each have a controller that executes a SAGEH application including triggering collection of host and remote vehicle information and environmental information, continuously observing a traffic signal and traffic situation along a host vehicle path along a road segment, generating an estimate of a quantity of time for the traffic signal to change status and generating an estimated quantity of time for the host vehicle to stop at the traffic signal, in response to one or more of the estimated quantities of time, generating a control output command. The control output command causes the host vehicle to dynamically, automatically, and adaptively harvest energy by engaging one or more of a stop / start system, and a regenerative braking system.

The invention belongs to the technical field of order management, and discloses an order management method based on cloud computing service. The method comprises the steps that the cloud platform receives a passenger position sent by a passenger terminal; acquiring real-time traffic data, defining a screening radius, and generating an order dispatching area for passenger positions; driver positions sent by all driver ends in the order sending area are received; road traffic information is obtained, the road traffic information, the passenger position and all driver positions are fused, the shortest driving time from each driver position to the passenger position is calculated, and a time sorting table is generated; the order is sent to the driver end with the shortest receiving time, and if the driver end does not receive the order, the order is sent to the driver end in sequence according to the time sorting table; according to the invention, cloud computing and big data analysis technologies are fully utilized, intelligent optimization and dynamic adjustment of order distribution are realized, the waiting time of passengers and the unloaded driving rate of drivers can be effectively reduced, the user experience is effectively improved, and the overall operation efficiency is improved.

The invention relates to the technical field of server management and cloud computing, in particular to a dynamic load-oriented intelligent identification heterogeneous server resource expansion method. The method aims at optimizing the resource management efficiency, the hardware expansion flexibility and the overall operation stability of the system in a data center and a cloud computing environment by integrating an advanced intelligent identification technology, a real-time data analysis capability and a self-adaptive resource scheduling mechanism. The method is particularly suitable for modern data center scenes requiring high concurrent processing capability, dynamic load adaptability and high reliability, such as a large-scale cloud computing service platform, an enterprise-level distributed storage system and an artificial intelligence computing cluster.

The invention discloses a resource unified scheduling method and device in a heterogeneous cloud environment and a medium, belongs to the technical field of cloud platforms, and aims to solve the technical problems of low resource utilization rate, unbalanced allocation and mismatching of service characteristics of the cloud platform in the heterogeneous cloud computing environment. According to the technical scheme, the method comprises the steps that virtual resource centers are established in a cloud platform, logic isolation and integration are conducted on one or more virtual data centers, the virtual resource centers are created and allocated to users for use, differences of calculation, storage and network resources of a bottom layer heterogeneous IaaS environment are shielded, the unified virtual resource centers are generated, and the virtual resource centers are distributed to the users for use. Unified computing, storage and network resources required by cloud computing service are provided for the upper layer of the cloud platform, and dynamic scheduling and multiplexing of the resources are supported; the method specifically comprises the following steps: accessing a virtualization environment; carrying out resource tagging management; creating a virtual resource center and a virtual data center; and scheduling service resources.

In one embodiment, a computer-implemented method comprises using a script automation processor that is hosted using a virtual compute instance and a virtual storage instance associated with one or more second non-transitory computer-readable storage media storing one or more second sequences of instructions defining an API implementation of the API, a graph server, and one or more programming language runtime interpreters, receiving a user pipeline automation script comprising one or more first sequences of instructions specifying one or more API calls to an application programming interface (API), and a user application; using the script automation processor, creating and storing one or more programmatic containers in memory of the script automation processor, the containers corresponding to functions that user pipeline automation script and user application invoke; using the script automation processor, creating and storing a directed acyclic graph (DAG) in the memory of the script processor, the DAG comprising nodes and edges corresponding to dependencies of the containers; using the script automation processor, interpreting the user pipeline automation script using a particular programming language runtime interpreter among the one or more programming language runtime interpreters; using the script automation processor, running the user pipeline automation script to automatically build, test, or deploy the user application in a cloud computing service.

An indoor air cleaning system with a networking mechanism is disclosed and applied in an indoor field (A) for detecting and cleaning air pollution completely. A real-time air quality monitoring in the indoor field (A) is achieved by arranging plural gas detectors (A), at least one gas molecule control hardware device (2), at least one air conditioning device (3) and a networked cloud computing service device (4) in the indoor field (A) and forming an intelligent linked system by the arranged gas detectors (1) in an outdoor filed and the indoor field (A). Meanwhile, the air pollution in the indoor field (A) is also detected and intelligently compared with an ambient air quality status, and an air guiding volume of an air guiding fan (21) is instantly controlled according to the air quality. Whereby an energy saving benefit of the effective controlling operation of the purification device is achieved.

The invention discloses a one-cloud multi-core heterogeneous resource hybrid scheduling method, which comprises the following steps of: calculating a node resource availability score RAS and a task type affinity score TAS, carrying out comprehensive scoring on nodes in combination with a weight factor so as to realize intelligent scheduling of Pod, and collecting and analyzing node resource data in real time by utilizing a Promeheus open source monitoring solution, so as to realize real-time scheduling of the Pod. By predicting the resource pressure index RP I and the resource pressure trend index RT I and optimizing the scheduling decision, the method is suitable for the cloud computing environment, and particularly, when complex and diversified computing tasks are processed, the resource management efficiency and the cluster performance can be remarkably improved, and efficient and reliable cloud computing services are provided for users.

The present disclosure provides a resilient (radio) access network ((R)AN) slicing framework encompassing a resource planning engine and distributed dynamic slice-aware scheduling modules at one or more network access nodes, edge compute nodes, or cloud computing service. The resilient (R)AN slicing framework includes resource planning and slice-aware scheduling, as well as signaling exchanges for provisioning resilient (R)AN slicing. The intelligent (R)AN slicing framework can realize resource isolation in a more efficient and agile manner than existing network slicing technologies. Other embodiments may be described.

Malware detection logic executed by a secured device residing in a home network may receive a message from an unsecured device of a first unsecured network and intended for a destination device of the home network, the destination device comprising a security client. The malware detection logic may establish a secure communication channel between the malware detection logic of the secured device and the security client of the destination device. The malware detection logic may execute a validation test on the message to determine that the message includes malware. The malware detection logic may report an alarm to the security client of the destination device. The malware detection logic may transmit information related to the malware to a cloud computing server. The malware detection logic may prevent an application associated with the destination device from processing the message.

Systems, devices, and techniques are disclosed for detecting misconfiguration of guest account security permissions. User personas may be generated from user activity data generated by access using guest accounts to controllers of a cloud computing server system. Clusters of user personas may be generated from the user personas. Anomalous user personas may be identified based on the clusters of user personas. A database query that was made to a database of the cloud computing server system, is associated with an identified user persona, and requested sensitive data may be identified from database query logs. A size of a response from the database to the identified database query may be identified from the database query logs. The size of the response may indicate that the response included the sensitive data. The cloud computing server system may prevent use of the guest account associated with the user persona.

The invention relates to the field of cloud computing and server operation and maintenance monitoring, and discloses a cloud computing server operation fault state monitoring method which comprises the following steps: deploying a lightweight monitoring agent at each server node, and collecting performance index data of a server in real time; preprocessing the acquired performance index data; performing fault prediction on the preprocessed performance index data based on a deep learning model, and outputting a fault prediction result; according to the fault prediction result, an alarm threshold value is adjusted in combination with the current load condition of the server; based on the fault prediction result, the severity of the fault is evaluated, and the alarm level and the monitoring frequency are automatically adjusted; and adjusting the priority and resource allocation of the monitoring task through an optimization algorithm. Through real-time acquisition and intelligent analysis of server performance data, in combination with deep learning and optimization algorithms, the fault prediction accuracy and the response speed of a monitoring system are significantly improved, false alarms are effectively reduced, and the resource utilization efficiency is improved.

A user terminal emulation server establishes a secure channel connection with a first I / O user device using a session identifier and an identifier associated with the first I / O user device to determine a first I / O user device specific key generated from a master key, the first I / O user device specific key and the session identifier being used for secure communication of messages with the first I / O user device. An indication of an I / O user interface capability of the first I / O user device is received through the secure channel connection with the first I / O user device. The user terminal emulation server communicates with the first I / O user device to use the I / O user interface capability to provide at least part of the communication service for a user.

A system for optimizing performance, managing network traffic, and enhancing user experience includes a host device a cloud computing server and controllers. The controllers execute control logic including a prediction application (PA) that obtains sensor data from the sensors, sends control and user plane data to infrastructure, and to the cloud computing servers, and accesses prior knowledge data stored within memory of the cloud computing servers. Additional control logic performs a Granger causality test on the user and control plane data, and utilizes a prediction model to generate a prediction from fused user and control plane data. A prediction verifier is applied to the prediction from the prediction model, and the PA enables the host device to adapt to dynamic wireless communications network conditions.

The present disclosure relates to a computer-implemented method (100) at a processing unit (11, 203) for determining one or more optimization parameters in order to optimize the operation of a thermodynamic system (1) of a liquefied natural gas, LNG, plant. The present disclosure also relates to server (200) for providing cloud computing services that is remotely located with respect to a thermodynamic system (1) and which comprises a processing unit (203) for determining one or more optimization parameters in order to optimize the operation of a thermodynamic system (1) of the LNG plant.

The specification provides a workload prediction method, device, medium and computer system in a cloud computing service, the method comprising: in response to a first trigger event, obtaining first time series data corresponding to system state data in a first time period; based on the first time series data, performing a first prediction for a future first time domain range to obtain a first prediction result; in response to a second trigger event, obtaining second time series data corresponding to system state data in a second time period; based on the second time series data, performing a second prediction for a future second time domain range to obtain a second prediction result; evaluating the accuracy of the first prediction result to obtain an evaluation result; and determining a target prediction result of the workload according to the evaluation result, the first prediction result and the second prediction result.

An intelligent networked energy recovery ventilator includes a main body, a filtering component, an air guiding fan, a heat exchange core, a host driving controller and a gas detection module. The gas detection module is disposed in the main body and electrically connected to the host driving controller. The gas detection module detects temperature, humidity and air pollution in the air to generate detection data, the detection data is transmitted to a networked cloud computing service device through IoT communication, and the networked cloud computing service device collects, analyzes and monitors the detection data in real time and intelligently selects a control instruction for transmitting to the gas detection module to control the host driving controller to enable the air guiding fan and dynamically adjust operation frequency and output air volume of the air guiding fan, thereby achieving gas exchange and heat exchange between indoor field and outdoor field.

The embodiment of the invention provides a data processing method, device and system, a hot upgrade method and device of a data forwarding unit, computing equipment, a computer readable storage medium and a computer program product. The method is applied to a cloud computing server, and the cloud computing server comprises a data processing unit and the data forwarding unit. The method comprises the steps of creating a newly added process corresponding to a data forwarding unit under the condition of determining that the data forwarding unit is subjected to hot upgrade updating, and establishing communication connection between an initial process and the newly added process; switching an initial process of any one of the data processing unit and the storage unit in communication connection with the data forwarding unit into a newly added process; and sending the data processing request received by the data processing unit to the storage unit for execution according to the newly added process and the initial process of the other one of the data processing unit and the storage unit in communication connection with the data forwarding unit, and by adopting the method, the data processing efficiency can be improved.

The application discloses a data terminal fire-fighting monitoring system based on cloud computing services, and relates to the technical field of monitoring systems, which comprises a host body, three bearing plates are equidistantly arranged in the host body, two sliding rails are slidingly connected to the top of the upper two bearing plates, and an installation plate is connected to the top of the two sliding rails. The application is provided with a series of structures, which improves the sensitivity, accuracy and reliability of early fire detection, effectively overcomes the problem of single function of traditional detectors, easy false alarm and missed alarm, improves the environmental adaptability and power supply reliability of the equipment, effectively avoids monitoring interruption caused by external environmental interference and sudden power failure, can more accurately judge the authenticity, type and level of fire, and execute grading and cooperative control strategy from early warning to emergency linkage according to the judgment, forms efficient closed-loop management, can flexibly deploy single or multiple host bodies according to the monitoring scene requirements, and realizes unlimited expansion of the monitoring range.

Technologies for facilitating testing for a communications network are disclosed. An example method includes maintaining a hierarchy of testing environments that replicate at least part of a network core of the 5G communications network to be consistent with a current declared state of the communications network. The network core of the communications network is established virtually using a cloud computing service and the hierarchy of testing environments are generated via the cloud computing service. The method also includes evaluating network functions for entry into or exiting testing environments in the hierarchy, and tracking and recording data associated with testing of the network functions in individual testing environments.

Disclosed are systems, apparatuses, processes, and computer-readable media for caching prompts for a generative response engine. The present technology includes receiving, by a cloud computing service, a request including a first prompt including a natural language task to perform, wherein the request include an access key for accessing the cloud computing service; identifying a generative response engine for generating a response to the natural language task based on contents of the natural language task; transmitting the first prompt and a hash to the generative response engine; and receiving the response to the natural language task from the generative response engine, the response including a number of input tokens.

The utility model belongs to the technical field of server installation, and particularly relates to a cloud computing server installation device which comprises a cloud computing server installation box, an installation frame is arranged on the inner wall of the bottom of the cloud computing server installation box, a sliding-in groove is formed in the inner wall of the bottom of the cloud computing server installation box, and a sliding-in groove is formed in the sliding-in groove. Two inserting blocks are slidably mounted on the inner side of the mounting frame, inserting grooves are formed in the inner walls of the left side and the right side of the sliding-in groove, the cloud computing server mounting box is opened, and a worker can move the mounting frame and the server body above the mounting frame to the front of the cloud computing server mounting box by means of a movable trolley; the installation frame is aligned with the sliding-in groove, the installation frame can be pushed into the inner side of the sliding-in groove, a plurality of guide rails are arranged above the sliding-in groove, a plurality of balls are arranged on the inner sides of the guide rails, the friction force of the installation frame in the sliding-in process can be small through the balls, and operation of workers is convenient and rapid.

Providing persistent storage to transient cloud computing services, including: creating a cloud computing instance, wherein the cloud computing instance is created on on-premises cloud infrastructure; and storing, in non-volatile storage in a storage system that is communicatively coupled to the on-premises cloud infrastructure, data associated with the cloud computing instance.

The application discloses a kind of unmanned aerial vehicle group reconnaissance power scheduling method based on collaborative computing, the method is directed to how to realize information intercommunication and cluster resource comprehensive collaborative allocation in the process of collaborative detection without relying on ground mobile base station and cloud computing server, establish cluster information collaborative model and form cluster collaborative computing alliance, through mutual communication between unmanned aerial vehicle, reasonably coordinate cluster detection and computing resource, and realize cluster reconnaissance power optimal method.The present application includes that the system is based on task search vector in the detection topology optimization layer, optimizes the detection position of unmanned aerial vehicle, in the resource optimization layer, the system alternates task unloading proportion and computing resource allocation proportion to give the reconnaissance power under the current detection topology, the system is constantly optimized detection topology optimization layer and resource allocation optimization layer according to the feedback of reconnaissance power, finally obtain the optimal detection topology and resource allocation scheme of cluster, realize efficient detection.

The invention discloses a data security sharing method, device and equipment, a medium and a product. The method comprises the following steps: when a data owner detects that an online encryption condition is satisfied, sending a final ciphertext and a symmetric key to a cloud storage server, and uploading a verification code to a block chain; the attribute authorization mechanism performs time verification, identity verification and attribute domain verification in response to a data acquisition request sent by the data user, and generates an attribute key and sends the attribute key to the data user under the condition that the verification is passed; the data user determines a conversion key according to the attribute key and sends the conversion key to the cloud computing server so as to instruct the cloud computing server to feed back a conversion ciphertext to the data user; and the data user decrypts the data ciphertext according to the retrieval key, the verification code downloaded by the block chain and the conversion ciphertext fed back by the cloud computing server to obtain the original data, so that the data owner can share the data of the data user safely.

The present invention relates to the technical field of digital information transmission of cloud servers, and discloses a method, device and server for constructing a communication channel of a cloud platform server; the system includes a cloud server user access permission verification module, a cloud server communication channel simulation establishment module, and a cloud server optimal communication channel establishment module; by numerically measuring the maximum simulated communication channel signal-time ratio from the user side to the cloud server side, reliable data support is provided for accurately constructing the optimal communication channel from the user side to the cloud server side; based on the maximum simulated communication channel signal-time ratio from the user side to the cloud server side with the largest value by using an intelligent recognition algorithm, the optimal simulated communication channel parameters from the user side to the cloud server side are efficiently and intelligently generated, and the optimal communication channel from the user side to the cloud server side is accurately constructed, realizing the intelligentization of the construction of the cloud server communication channel, and improving the efficiency, security and quality of the cloud server cloud computing service.