10 results about "Cloud resource management" patented technology

The application provides a method, device, medium and program product for implementing multi-level cloud resource management, which comprises the following steps: receiving a request of a senior user for requesting a junior user to execute an action through a user request agent; obtaining a trust score of the senior user at the current time through a dynamic trust engine, and determining a policy related to the action; modeling real-time credibility of the senior user when proxying the junior user resources as a Bayesian learning process by the dynamic trust engine; the trust score is subject to Beta distribution; according to a pre-constructed objective function and constraint condition, calculating an activation vector of an optimal policy related to the operation to obtain an optimal solution; when the optimal solution is greater than or equal to a predetermined utility threshold, determining whether the permission range of the senior user contains the operation according to the activation vector, and if yes, calculating a token survival time of the operation b and issuing a corresponding dynamic proxy token. By using the above technical scheme, fine-grained and dynamic multi-level cloud resource management can be realized for the proxy behavior.

The invention provides a label-based multi-cloud resource management method and equipment. The method comprises the following steps: acquiring resource instance information on a plurality of cloud platforms; setting the resource instance information of each cloud platform as a unified standard cloud resource label; setting the target use efficiency of each cloud resource label; obtaining monitoring data of the resource monitoring item of each cloud resource label; calculating the total resource use efficiency of the cloud resource label; and according to the total resource use efficiency and the target use efficiency, adjusting the configuration of the resource instance under the cloud resource label or providing prompt information for adjusting the configuration.

The present application relates to the technical field of cloud resource management, and particularly relates to a water affair private cloud load prediction method, comprising: constructing a data processing and modeling framework for cloud physical host load prediction; adopting a deep learning model combining a convolutional neural network (CNN) with a bidirectional long short-term memory network (BiLSTM) and fusing SE attention mechanism to fully extract data features of cloud load; and performing global search optimization on model hyperparameters by an improved intelligent optimization algorithm INRBO to obtain an optimal training parameter combination and improve model prediction performance. The present application fully considers the complexity and volatility of load sequences in a private cloud environment, and proposes a cloud load prediction model INRBO-CNN-BiLSTM-Attention fusing feature enhancement and parameter optimization mechanism, which can effectively capture load change trends and significantly improve prediction accuracy and stability, and is consistent with actual private cloud computing scenarios.

This application discloses a cloud resource management method and a cloud management platform based on a cloud management platform. This method can reduce operational and time costs during the tenant's cloud resource application process, thereby improving the tenant's experience. The method includes: when a first tenant needs to use cloud resources to complete its business, the first tenant can send a first cloud resource acquisition request to the resource acquisition interface provided by the cloud management platform. Since the first cloud resource acquisition request indicates the first specification of the cloud resources required by the first tenant, the cloud management platform can detect whether there are any idle cloud resources in the cloud resource pool that meet the first specification. If not, the cloud management platform can select a first cloud resource from the cloud resource pool that meets the first specification but is not idle, obtain the first waiting time required for the first tenant to use the first cloud resource, and then notify the first tenant of the first waiting time.

This invention proposes a collaborative disaster recovery and backup system and method for rail transit vehicles-ground-cloud. In this system, a unified multi-cloud resource management platform determines the link quality of deterministic network transmission paths between different cloud center nodes; an intelligent disaster recovery scheduling engine selects another physically isolated cloud node as a backup node based on the link quality of the deterministic network transmission paths between different cloud center nodes; a deterministic network controller establishes deterministic network transmission paths between onboard equipment, station edge cloud, and central cloud; once the high availability management and automatic migration module detects a failure in the primary node, it immediately triggers a predefined migration process, activates a backup service instance, and directs service traffic to the backup node. Through the deterministic network transmission path, it provides deterministic low-latency, low-jitter, and low-packet-loss data transmission capabilities, ensuring the reliability and efficiency of data synchronization between the production cloud center and the disaster recovery center.

This disclosure relates to a resource management method, apparatus, and electronic device for hybrid cloud. The method includes: receiving a copy submission request, the request including an application identifier and a copy of the application to be submitted; if a target configuration item is configured in the container group declaration file corresponding to the copy, determining the target cloud platform indicated by the target configuration item; determining the resource quota information of the application in the target cloud platform based on the identifier; if, based on the resource quota information, a first idle resource exists in the target cloud platform for running the copy, creating a first container group for running the copy; and performing resource scheduling on the first container group based on the resources in the target cloud platform. The target configuration item allows copies of the application to run on different cloud platforms, utilizing resources on cloud platforms other than the currently deployed cloud platform, thereby improving resource utilization.

The application discloses a cloud resource processing method and device, a computing device cluster and a terminal, and belongs to the technical field of cloud computing. The method comprises the following steps: receiving a first processing request for at least one cloud resource sent by a terminal, wherein the first processing request carries first cloud resource indication information, the identity of a first cloud vendor to which at least one cloud resource belongs, and first processing type indication information, the first cloud resource indication information is used for indicating that the cloud resource to be processed is at least one cloud resource, the terminal logs in a cloud resource management account, and the first cloud vendor is a cloud vendor corresponding to any cloud vendor account in at least one cloud vendor account associated with the cloud resource management account. The cloud resource management device of the first cloud vendor performs the processing indicated by the first processing type indication information on the at least one cloud resource. The application can improve the efficiency of cloud resource processing.

1. The name of the design product: a cloud resource management system for electronic devices. 2. The use of the design product: the design product is used to manage the full life cycle of GPU card resources and computing nodes in a virtualized environment through a cloud resource management system in electronic devices, to maximize resource utilization and optimize task execution efficiency. 3. The design points of the design product: the content of the graphical user interface. 4. The picture or photo that best indicates the design points: front view. 5. No left view, right view, top view, bottom view, rear view is omitted, which does not involve the design points and is the usual design. 6. The use of the graphical user interface: to display the full life cycle management function of the cloud resource management system for GPU card resources and computing nodes in a virtualized environment. 7. The change state of the graphical user interface: the main view is the graphical interface displayed when the user opens the cloud resource management system; interface change state figure 1 is the graphical interface displayed after the user clicks "card resources" in the left navigation bar of the main view; interface change state figure 2 is the image interface displayed after the user selects a GPU card information and clicks "view" on the right side.