168 results about "Cloud computing systems" patented technology

A distributed cloud computing system is disclosed that includes a controller configured to deploy network constructs including any of transit gateways, spoke gateways, subnets, or private networks and logic that, upon execution by one or more processors, causes performance of operations including: causing rendering of a graphical user interface that includes a display panel configured to display progress of a build process for a network topology graph, receiving first user input through the graphical user interface indicating selection of a first cloud service provider, a first access account, and a first cloud region, receiving second user input through the graphical user interface indicating selection of one or more of the network constructs to be deployed in the first cloud region, instructing the controller to deploy the one or more of the network constructs in the first cloud region according to the first user input and the second user input.

Described systems and methods may enable a cloud-computing system to use data model-based analysis to manage maintenance of an industrial automation system based on life stage predictions and real-time evaluations. Based on the data model-based analyses, the cloud-computing system may instruct an industrial control system of the industrial automation system to implement recommended adjustments and / or to confirm a part replacement occurred in situ. The recommended adjustment may include a part replacement. The cloud-computing system may generate instructions to cause shipment of the part to be installed as part of the part replacement to the industrial automation system.

A method of displaying an operational parameter of a surgical system is disclosed. The method includes receiving, by a cloud computing system of the surgical system, first usage data, from a first subset of surgical hubs of the surgical system; receiving, by the cloud computing system, second usage data, from a second subset of surgical hubs of the surgical system; analyzing, by the cloud computing system, the first and the second usage data to correlate the first and the second usage data with surgical outcome data; determining, by the cloud computing system, based on the correlation, a recommended medical resource usage configuration; and displaying, on respective displays on the first and the second subset of surgical hubs, indications of the recommended medical resource usage configuration.

The described technology pertains to a distributed computing environment, specifically implementing a streaming protocol on a scalable object storage service. The technical problem addressed is the high computing resource demand of distributed streaming platforms. The solution involves separating content from location metadata, allowing centralized, scalable storage of metadata. Brokers store content in object storage services based on specific metrics, such as fast read / write times or greater storage capacity. A background platform remaps metadata sequences based on logical timestamps, optimizing data retrieval. This system enhances the efficiency of computing resources by reducing the load on brokers and improving data access speeds. A use can be in cloud computing systems for efficient content streaming and storage management.

Disclosed are systems, methods, devices, and computer-readable media for offloading lattice-based cryptographic operations to hybrid cloud computing system. In one embodiment, a method is disclosed comprising receiving a first network request from a client device via a secure application programming interface (API), the request including unencrypted data; encrypting the unencrypted data using an algorithm that generates homomorphically encrypted data; issuing a second network request to a second API of a cloud platform, the second network request including the encrypted data; receiving a response from the cloud platform in response to the second network request; and transmitting, in response to the first network request, a result to the client device based on the response, the result obtained by decrypting an encrypted output returned by the cloud platform.

Methods, systems, and devices for providing firmware management using a firmware management engine of a cloud computing system are described. The firmware management engine supports using a hot-plugged memory (e.g., Compute Express Link (CXL) pooled memory) to temporarily migrate system memory (e.g., Central Processing Unit (CPU) local memory or CXL attached memory) of a server node, while performing firmware management operations (e.g., a firmware update) on the server node. The hot-plugged memory can be CXL pooled memory that is a shared at a rack level, the CXL pooled memory can be used to store system memory data of system memory while updating and activating new memory initialization firmware code. A virtual machine associated with the server node stays operational temporarily using the hot-plugged memory. Firmware management is performed on a server node while virtual machines associated with the server node and the system memory of the server node remain operational.

The invention discloses a software development cloud computing system with a big data processing module, which relates to the technical field of computer systems and data processing, and comprises a development input acquisition module used for receiving source code data, construction script data, dependency declaration data, configuration file data and development environment description data, and respectively executing integrity verification, structure analysis, dependency analysis, parameter extraction and environmental element analysis processing to form a standardized development input data set. According to the method, unified feature abstracting and aggregation are carried out on source codes, construction scripts, dependency declarations, configuration parameters and development environment elements, version fingerprint data capable of stably representing the software version state is formed, the strict degree of analysis, verification and influence analysis is remarkably enhanced in a high-difference version scene, and the software version state can be stably represented. Therefore, the problems of misjudgment, missed judgment or resource waste caused by adoption of a fixed threshold value or manual parameter configuration in the prior art are avoided.

The invention relates to the field of intelligent scheduling allocation, in particular to an edge cloud computing resource allocation optimization method based on deep learning, which adopts a space-time prediction algorithm based on multi-head attention and gating mechanism optimization to design time coding and space coding. The spatial relationship and interaction between time sequence characteristics of the computing power load and edge server nodes are captured, and meanwhile, a multi-head attention mechanism and expansion causal convolution are combined, so that instantaneous computing power load fluctuation can be captured, and the long-term trend of the computing power load can be mined; therefore, a reliable basis is provided for subsequent computing power scheduling by predicting an accurate computing power load. The invention designs an alternating direction multiplier method based on genetic algorithm optimization, which is not only suitable for a nonlinear and multi-constraint optimization problem, but also can be expanded to a larger-scale distributed edge node cloud computing system, and meanwhile, a global optimal solution is quickly approached through the genetic algorithm, so that the quality of an initial solution is improved, and model convergence is accelerated; and the distributed collaborative allocation scheduling efficiency is improved.

The invention discloses a public network flow forwarding method, device and equipment for a cloud computing system and a medium, and relates to the technical field of cloud computing. The public network flow forwarding method for the cloud computing system comprises the steps that a virtual switch and a virtual machine are deployed on a host machine; a cloud computing system is built in a manner of deploying a virtual gateway on a cloud computing gateway, so that only a first message of public network flow in a cloud computing network is forwarded by a gateway node and a high-speed forwarding table is generated, and the gateway node does not need to participate in subsequent other public network flow messages which are not the first message. Public network traffic forwarding between hosts is directly carried out only by utilizing the generated high-speed forwarding table and the host information table, so that the technical problems of high load and high delay of public network traffic forwarding of the existing gateway node are solved, the forwarding efficiency of the public network traffic in the cloud computing network is greatly improved, and the forwarding efficiency of the public network traffic in the cloud computing network is improved. And meanwhile, the loss and the load pressure of the gateway node are greatly reduced.

A computer-implemented method can be used for distributing workload in a cloud computing system that includes a number of data sources. Each data source includes one or more queues. A plurality of replicas of a microservice are instantiated. Each replica is configured to process data from the data sources. Each replica receives information regarding a total number of active replicas and an identifier specific to that replica. Each replica determines a starting queue based on the total number of active replicas and the specific identifier. Each replica processes data from its determined starting queue and subsequent queues in a predefined order.

Techniques disclosed herein can include receiving an instruction to perform a stress test on one or more cloud computing resources of a cloud computing system. Worker nodes of the cloud computing system can be provisioned by a resource manager to perform the stress test on the cloud computing resources. The resource manager can instruct the one or more worker nodes of the cloud computing system to perform the stress test. Data generated by the worker nodes during the stress test can be received by the resource manager and used to train a projection framework comprising a trained machine learning model. The projection framework can generate a resource projection and the projection can be used to provision cloud computing resources to host the cloud service.

Systems and methods generate requests for encrypted (e.g., secured) credentials and data using one of a plurality of API plugins that are selected based on an access protocol for a network partition at which requested data is determined to be stored. Through the use of the dynamically-selected API plugins, the systems and methods may provide the aforementioned functions while being compatible with the different access protocols that may be encountered when providing central management across a diverse spectrum of user accounts, networks, and / or cloud platforms.

A method for managing credentials in a heterogeneous cloud computing system, includes receiving, at a local computing system, a request to access a cloud resource on behalf of an end user, the request including a unique identifier associated with the end user and a resource identifier associated with the cloud resource, identifying, using the resource identifier, a predefined procedure for obtaining credentials for accessing the cloud resource, performing the predefined procedure to obtain the credentials for accessing the cloud resource, and accessing the cloud resource on behalf of the end user using the credentials.

Systems and methods generate requests for encrypted (e.g., secured) credentials and data using one of a plurality of API plugins that are selected based on an access protocol for a network partition at which requested data is determined to be stored. Through the use of the dynamically-selected API plugins, the systems and methods may provide the aforementioned functions while being compatible with the different access protocols that may be encountered when providing central management across a diverse spectrum of user accounts, networks, and / or cloud platforms.

A refuse vehicle includes a first controller area network (CAN) bus for body functions of the refuse vehicle. The refuse vehicle also includes multiple controllable elements of a body of the refuse vehicle communicably coupled with the first CAN bus. The refuse vehicle includes a second CAN bus for chassis functions of the refuse vehicle. The refuse vehicle includes multiple controllable elements of a chassis of the refuse vehicle communicably coupled with the second CAN bus. The refuse vehicle includes a telematics module communicably coupled with both the first CAN bus and the second CAN bus. The telematics module is configured to monitor communications on both the first CAN bus and the second CAN bus and transmit the communications to a cloud computing system. The first CAN bus and the second CAN bus are communicatively separate and do not communicate with each other directly.

In one embodiment, a system includes: a robotic system and a plurality of components coupled to a cloud computing system. Each of the plurality of components is configured to either: store ingredients under predetermined environmental conditions; store food preparation tools; dispense ingredients; blend, cook, or assemble ingredients into a completed food item; provide cleaning functionality to the system and / or components thereof; provide user access to completed food items; or display information relevant to a food item or preparation thereof to users. Methods of using such systems to prepare and dispense food items are also disclosed, and generally include translating recipes into instructions executable by the robotic system and / or components of the system, communicating such instructions, and executing such instructions.

The invention discloses an application program resource monitoring method and device, electronic equipment and a storage medium, and relates to the technical field of computers, and the application program resource monitoring method comprises the steps that an out-of-band monitoring module is adopted to collect application program resource data, isolation of a monitoring channel and a service channel is achieved, and the service channel is monitored. Meanwhile, a resource use model of a time dimension is constructed based on real data to simulate production environment resource behaviors, and then performance pressure measurement and fault reproduction analysis are supported, so that the problems that in an existing monitoring and control method, due to the fact that an internal agent of a virtual machine is adopted and the virtual machine is not isolated from a service channel, monitoring data distortion is caused, application program operation is disturbed, and the service performance is affected can be solved. According to the technical scheme of the invention, the technical problems in the prior art are solved, and the technical effects of guaranteeing the accuracy of monitoring data, avoiding the interference on the operation of the application program, improving the performance optimization effect and effectively supporting the performance pressure measurement and fault reproduction analysis of the cloud computing system are achieved.

The application discloses a kind of multi-star on-orbit cooperation observation task planning method and system, by designing heuristic initial solution generation strategy, roulette selection algorithm based on Boltzmann selection probability, adaptive crossover operator and mutation operator based on population dispersion degree, stop condition based on population convergence coefficient, from initial solution, selection operator, crossover operator, mutation operator, stop condition etc. Various angles improve the genetic algorithm for multi-star cooperative observation task planning, compared with the genetic algorithm based on circle next cross, variation, significantly improve the execution benefit of observation task and the observation number of target point, construct the scheduling system of constellation cloud computing system, reach the purpose of on-orbit cooperation multi-star efficient execution observation task.

The application discloses a software development cloud computing system with a big data processing module, and relates to the technical fields of computer systems and data processing.The system comprises a development input collection module, which is used for receiving source code data, construction script data, dependency declaration data, configuration file data and development environment description data, and performing integrity check, structure analysis, dependency analysis, parameter extraction and environment element analysis processing, respectively, to form a standardized development input data set.In the application, unified feature abstraction and aggregation are performed on the source code, construction script, dependency declaration, configuration parameter and development environment element to form version fingerprint data capable of stably representing the software version state, thereby significantly enhancing the strictness of analysis, check and influence analysis in a high-difference version scene, and avoiding the misjudgment, omission or resource waste caused by the fixed threshold or artificial configuration parameter in the prior art.

Techniques for a service of a cloud computing system to generate and present users with visualizations of computing resources and their network relationships in private networks of the users. The cloud system obtains resource and network connection data from private networks of users and determines overall network architectures for the computing resources and their network connections. The cloud system generates visualizations that represent the overall network architectures for private networks. The visualizations may comprise single pane-of-glass views for users to quickly understand the architectures and networking inside of their private networks. The visualizations may be interactive in that users can interact with visual depictions of resources and be dynamically presented with networking connections and details for the particular resources.

The embodiment of the present application provides a method and device for installing components, which are used for a cloud computing system, and the method comprises the following steps: receiving parameter information, wherein the parameter information at least comprises component information of a target component to be installed; determining a target node for installing the target component in each node of the cloud computing system according to the parameter information, and establishing a connection with the target node; searching for an installation package corresponding to the target component in a preset installation source according to current version information of the cloud computing system and the component information of the target component; and transmitting the installation package to the target node, so that the target node realizes automatic installation of the target component by running the installation package. Through the present application, the target component can be automatically installed under the cloud computing system, so that the labor cost can be reduced and the efficiency of installing components can be improved.

Systems and methods are provided for identifying cloud inefficiencies. The method includes obtaining telemetric log data for services, distinct from the server, executing on cloud computing systems. The method also includes determining disaggregation data for the services based on the telemetric log data by applying disaggregation algorithms. The method also includes forming feature vectors based on the telemetric log data. The method also includes identifying software of service types and cloud wastage templates by inputting the feature vectors to trained classifiers, wherein the cloud wastage templates follow conventions of a domain specific language (DSL) that describe the cloud computing systems. Each classifier is a machine-learning model trained to identify cloud wastages for predetermined states of the cloud computing systems. The method also includes determining cloud states of computing resources used by the services based on the disaggregation data. The method also includes cataloging cloud inefficiencies using the cloud wastage templates.

Example techniques relate to cloud queue synchronization. An example implementation may involve a playback device receiving, from a cloud computing system, data representing a play message comprising: (i) a play pointer representing a particular media item; (ii) an indication of one or more media items, the one or more media items including the particular media item; and (iii) a universal resource identifier (URI) representing a location of the particular media item at one or more servers of a streaming audio service. The playback device queues the one or more media items in a local queue stored in data storage of the playback device, streams the particular media item, and plays back the particular media item. After beginning playback of the particular media item, the playback device sends a playback started message comprising the play pointer, the play pointer representing the particular media item as the currently playing media item.

The present disclosure relates to a cluster resource control method and device and a cloud computing system, and relates to the technical field of computers. The method comprises: in the case that the resource to be controlled is a resource to be expanded, determining a binding relationship between the resource to be expanded and a corresponding application; adding the initialized resource to be expanded to a resource pool of the corresponding application according to the binding relationship; generating a to-be-executed data packet of the to-be-processed application according to a deployment type of the to-be-processed application; and deploying the to-be-executed data packet on the corresponding resource to be expanded in the resource pool of the to-be-processed application for execution.

A method includes a manager gateway receiving a baseboard management controller configuration over a WebSocket connection that supports communication over a wide area network (WAN) between the controller in a device-side private network and a system management application that runs in a cloud-side private network within a public cloud computing system, wherein the manager gateway connects the cloud-side private network to the WAN. The manager gateway creates, in response to receiving the configuration for the controller, a virtual network interface controller (vNIC) having a cloud-side local network address and creating a record in a cloud-side DNS Service to map the controller to the vNIC. When the manager gateway receives a request message over the cloud-side private network from the application at the virtual network interface controller, the manager gateway relays the request message to the controller over the WebSocket connection that the cloud-side DNS Service maps to the vNIC.

This application proposes an edge computing service edge computing method, a cloud computing center server applied to a cloud computing system, an edge server applied to the cloud computing system, an electronic device, and a non-transitory computer-readable storage medium. The edge computing method is applied to a cloud computing system, which includes a cloud computing center server and edge servers. The edge computing method includes sending edge service-related data, separated from service-related data provided by the cloud computing center server, to the edge server, enabling the edge server to deploy the edge service-related data to its motherboard management controller; and utilizing the edge services provided by the motherboard management controller of the edge server to achieve hardware management of the edge server. According to embodiments of this application, the service performance of cloud computing is improved without increasing costs or in-band resources.

The present disclosure relates to a method for establishing a secure remote access, SRA, connection between a cloud computing system, CCS, and an industrial automation system, IAS, the method comprising: receiving, by an SRA server component of the CCS, a first SRA connection establishment message from a first SRA client of the CCS or from a second SRA client of a user device connected to the CCS; receiving, by a connection orchestrator component of the CCS, an indication to establish the SRA connection between the CCS and the IAS, sending, by the connection orchestrator component and based at least in part on the indication, a machine-to-machine network protocol message to a third SRA client of the IAS comprising information for establishing the SRA connection between the IAS and the CCS, and receiving, by the SRA server component of the CCS, a second SRA connection establishment message from the third SRA client of the IAS, and establishing, via the SRA server component, the secure SRA connection between the first SRA client of the CCS and the third SRA client of the IAS or between the second SRA client of the user device and the third SRA client of the IAS. The present disclosure also relates to a corresponding computing system and a computer program.

The disclosure relates to utilizing an anomaly mitigation proposal system to determine root causes, summarize anomalous metrics, and report mitigation actions for service incidents in cloud computing systems. Based on receiving an incident report request, the anomaly mitigation proposal system utilizes a two-layer approach that implements large generative language models to generate incident reports that include clear and concise text narratives summarizing metric anomalies, root causes, and corresponding mitigation actions. For example, the anomaly mitigation proposal system initially utilizes an online generative language model to provide these incident reports and, when unavailable within a time threshold, a fallback model that references root cause datastores.

A method for managing credentials in a heterogeneous cloud computing system, includes receiving, at a local computing system, a request to access a cloud resource on behalf of an end user, the request including a unique identifier associated with the end user and a resource identifier associated with the cloud resource, identifying, using the resource identifier, a predefined procedure for obtaining credentials for accessing the cloud resource, performing the predefined procedure to obtain the credentials for accessing the cloud resource, and accessing the cloud resource on behalf of the end user using the credentials.