47 results about "Cloud resource management" patented technology

Systems and methods of the disclosure include: identifying, by a cloud resource management system, a cloud resource consumption model associated with one or more cloud resources; generating, by the cloud resource management system, a sequence of instructions implementing a smart contract based on the cloud resource consumption model; sending, to a distributed ledger network, the smart contract; receiving, by the cloud resource management system, cloud resource usage data associated with the one or more cloud resources; and causing, by transmitting a message reflecting the cloud resource usage data to the distributed ledger, the smart contract to be executed.

The invention discloses an operation and maintenance data management system based on cloud computing, particularly relates to the field of data management, and comprises a distributed data acquisition module, a cloud native data processing module, an intelligent analysis module, a visualization and decision module and a cloud resource management center module. According to the method, heterogeneous data are collected in real time through the lightweight agent, and high efficiency is guaranteed by adopting multi-thread and self-adaptive sampling; data cleaning, standardization and mixed storage are realized by using a stream batch integrated architecture; the intelligent analysis module fuses an improved Robust Z-Score, an LSTM-Attention model and a complex event processing engine, and supports dynamic anomaly detection and fault tracing; the visual assembly builds an instrument panel in a dragging mode, alarm strategies are aggregated in a grading mode, and storm is restrained; the cloud resource management center deeply integrates Kubernetes, predicts demands based on reinforcement learning, automatically expands and shrinks capacity and optimizes cost, and deals with burst traffic in combination with a burst capacity pool.

The invention discloses an intelligent scheduling interaction system of an intelligent operation centralized control center, which relates to the technical field of power scheduling and comprises a centralized control cloud platform, an intelligent centralized control platform, a data analysis platform, a database and a real-time data monitoring terminal, the centralized control cloud platform comprises basic resources such as a computing resource pool, a storage resource pool, an east-west security resource pool, a network resource pool and a cloud resource management tool, and the basic resources are provided for construction of the intelligent centralized control center. And real-time updating and upgrading can be realized, so that the interaction system capability and the application capability are ensured to advance with the times, the system is ensured to have relatively long vitality and expansion capability, and the stability and the safety of the technology are ensured while the advancement of the system is ensured.

The invention relates to the technical field of vehicle function research and development, in particular to a remote debugging method and device for functions of a vehicle-mounted entertainment system, electronic equipment and a medium, and the method comprises the steps: determining a current remote debugging demand, determining an item to be debugged according to the current remote debugging demand, and generating a resource downloading instruction according to the item to be debugged, and sending a resource downloading instruction to the target debugging equipment, so that the target debugging equipment pulls the debugging resource based on the resource downloading instruction, debugging the vehicle-mounted entertainment system function of the vehicle based on a preset debugging instruction when an adjustable prompt of the target debugging equipment is received, and generating a debugging result after debugging is completed. Therefore, the problems of long distance between test equipment and developers, low debugging efficiency, difficulty in vehicle management, high maintenance cost and the like caused by real vehicle testing are solved, and an efficient and low-cost debugging process is realized through remote communication, cloud resource management and multi-equipment cooperation.

The application provides a cloud resource management method, device, equipment and storage medium. The method comprises the following steps: receiving a cloud resource management task, determining a required cloud resource pool based on the cloud resource management task, newly creating a target cloud area to synchronize data of the cloud resource pool; the cloud resource management task is used to indicate a management requirement and a management scenario; calling a corresponding management process and a management time from a SOP document based on the management requirement, and newly adding a target special area based on the management scenario; the management process is a standardized execution process defined in advance for implementing the management work; obtaining cloud resource management information from the target cloud area based on the management requirement, standardizing the cloud resource management information according to a predefined format, obtaining target data, and distributing the target data and the management process to the target special area, so as to perform management processing on the target data based on the management process within the management time. The method of the application can improve the management efficiency by standardizing the management process and the management related files.

The invention discloses an edge cloud resource management collaborative scheduling method based on artificial intelligence, which relates to the technical field of resource scheduling, and comprises the following steps: obtaining resource states of edge nodes to obtain an edge resource state set; performing task matching according to the edge resource state set to obtain a matching feature set; performing matching score calculation according to the matching feature set to obtain a node matching score table; generating a minimum time delay scheduling path according to the node matching score table to obtain a task scheduling distribution table; performing task scheduling execution time prediction according to the task scheduling distribution table to obtain an execution time feedback set; and performing parameter optimization according to the execution time feedback set to obtain an optimization result. According to the method, the adaptability of scheduling is improved, the multi-target balance of scheduling is improved, scheduling conflicts and node congestion are effectively reduced, and the timeliness of scheduling and the resource utilization efficiency are improved.

The invention discloses a cloud resource management method and device, electronic equipment and a storage medium, and relates to the technical field of financial science and technology and operation and maintenance, and the method comprises the steps: obtaining a predicted use quota according to the maximum resource quota and the allocated quota of each user in response to the detection that remaining cloud resources in a resource pool meet a global capacity reduction rule, obtaining a predicted application quota according to the predicted use quota and the allocated quota; and obtaining a target user whose unallocated quota is greater than the predicted application quota, and sending a capacity reduction suggestion to the target user so as to perform capacity reduction processing on the maximum resource quota according to a feedback result of the target user. According to the technical scheme provided by the embodiment of the invention, the capacity reduction suggestion is actively sent to the user with the idle quota through the triggered global capacity reduction rule, so that the idle quota phenomenon is avoided, and meanwhile, the resource reduction quota is accurately estimated; in addition, the human cost and the time cost of cloud resource management are reduced, and the cloud resource management efficiency is improved.

In some examples, systems and methods for managing cloud resources (e.g., distributed resources) are provided. For example, a method includes: receiving a request to create a data bucket from a client application, the request including a bucket template; generating a cryptographic key for the data bucket; generating the data bucket in a cloud platform based at least in part on the bucket template; associating the cryptographic key to the generated data bucket; generating metadata associated with the generated data bucket; and providing the metadata associated with the generated data bucket to the client application.

A cloud resource management system detects resource misconfiguration for resources in a cloud including cloud policy misconfigurations and resource vulnerabilities. An attack chain analyzer identifies attack chains from misconfigured resources ordered according to stages in an attack framework that models sequential behavior for malicious attacks. The attack chains are detected according to a depth-first search traversal of adjacent resources that have pairwise exposure according to characteristics indicated in the cloud policy misconfigurations and resource vulnerabilities. The attack chain analyzer generates further diagnostics that inform remediation of resource misconfigurations for malicious attack prevention.

The invention discloses a cloud resource management platform, a cloud resource management method, equipment and a storage medium, and relates to the technical field of resource management, the cloud resource management platform comprises a user demand application module used for obtaining a cloud resource application request of a target user; the user demand management module is used for carrying out application limit query and order grading on the cloud resource application request to obtain a request approval type; the user demand approval module is used for performing demand approval on the cloud resource application request according to the request approval type to obtain an application approval result; and the cloud resource delivery management module is used for performing resource scheduling on a target cloud resource according to the application approval result and the cloud resource application request, and creating a cloud resource instance corresponding to the cloud resource application request so as to perform resource delivery management.

Systems and methods for implementing a policy-based framework for O-Cloud Resource Management and Orchestration Services are provided. The method includes: determining, a network function (NF) hosted on a O-Cloud node to be instantiated on another O-Cloud nodes; creating an instantiation policy for the determined NF for the ORMOS; sending the instantiation policy via an R1 interface to the ORMOS; requesting an instantiation implementation of the determined NF via an O2 interface to at least one O-Cloud management service; instantiating a NF on the other O-Cloud nodes according to the implementation request; sending a registration and configuration request for the instantiated NF to NF-related RAN OAM Services; sending a configuration notice for the instantiated NF to the ORMOS; and sending instructions to finalize the instantiation implementation of the determined NF to the at least one O-Cloud management service.

Methods and apparatus are disclosed, including in one example a method for scheduling resources, associated with a plurality of components of a communication network, for providing a network service to a user equipment (UE). The method comprises receiving a service request for providing the network service, wherein the service request includes one or more service constraints. The method also comprises, for each of the plurality of network components, determining component resources that are needed to fulfill the service request according to the service constraints, sending, to a manager function associated with the particular component, a resource request that includes identification of the determined component resources and information related to the service constraints, and receiving, from the manager function, service information associated with the particular component. The method also includes, based on the service information and a cost function, determining a resource schedule for the plurality of network components that fulfils the service request.

The embodiment of the invention provides a cloud resource management method and device, electronic equipment and a storage medium, and relates to the field of databases, for example, the cloud resource management method and device can be applied to the field of distributed databases. The method comprises the following steps: acquiring current time sequence data corresponding to a current prediction operation of a tenant; determining a target statistical prediction model corresponding to the current prediction operation of the tenant from at least one preset candidate statistical prediction model based on the current time sequence data and a large language model; determining prediction data of the tenant in a current prediction period corresponding to the current prediction operation based on the current time sequence data of the tenant through a target statistical prediction model; based on the prediction data corresponding to the tenant in the current prediction period, determining a prediction resource demand corresponding to the tenant in the current prediction period; and adjusting the cloud resource of the tenant based on the predicted resource demand corresponding to the tenant in the current prediction period. According to the embodiment of the invention, the resource utilization rate is improved and the cost is saved.

The invention discloses a cloud resource management method and system, electronic equipment and a storage medium, and relates to the technical field of resource management, the method comprises the following steps: in response to a cost optimization instruction, identifying a target cloud resource carrying a cost optimization tag from a public cloud environment; a target optimization strategy matched with the resource type of the target cloud resource is searched in a preset resource portrait library, a mapping relation between each resource type and each cost optimization strategy is stored in the resource portrait library, and the mapping relation is determined by the cost attribute, the reconstruction constraint attribute and / or the service constraint attribute of each resource type; according to the target optimization strategy, cost optimization operation is carried out on the target cloud resources, and the cost optimization operation is destruction operation, reservation operation or configuration modification operation. According to the application, the service stability can be guaranteed while the cost is saved in a cloud service scene.

In order to solve the problem in existing low-level I / O peripheral abstraction method for cloud FPGAs that limits flexibility of cloud FPGAs'resource management and tenant usage, this invention introduces an implementation method and system of an FPGA bare metal server, in which the cloud FPGAs are treated as the first-class computing resources in the same manner of the general x86 host. Without customizing and developing new system component, the complexity of managing cloud FPGAs is reduced. Meanwhile, tenants are allowed to directly apply for, deploy and leverage the FPGA bare metal host in a pay-as-you-go manner without applying for additional general computing resources.

The method comprises: obtaining current time series data corresponding to a current prediction operation of a tenant; determining, based on the current time series data and a large language model, a target statistical prediction model corresponding to the current prediction operation of the tenant from at least one preset candidate statistical prediction model; determining, by using the target statistical prediction model and based on the current time series data of the tenant, prediction data of a current prediction period corresponding to the current prediction operation of the tenant; determining, based on the prediction data of the current prediction period corresponding to the tenant, a predicted resource requirement of the tenant in the current prediction period; and adjusting cloud resources of the tenant based on the predicted resource requirement of the tenant in the current prediction period. The method improves resource utilization and saves costs.

A system and method for implementing a policy-based framework for O-Cloud resource management and orchestration services is provided. The method includes determining a network function (NF) hosted on an O-Cloud node to be instantiated on another O-Cloud node, creating an instantiation policy for the determined NF for ORMOS, sending the instantiation policy to ORMOS via an R1 interface, requesting an instantiation implementation of the determined NF from at least one O-Cloud management service via an O2 interface, instantiating the NF on the other O-Cloud node according to the implementation request, sending a registration and configuration request for the instantiated NF to an NF-associated RAN OAM service, sending a configuration notification of the instantiated NF to ORMOS, and sending an instruction to the at least one O-Cloud management service to complete the instantiation implementation of the determined NF.

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 invention relates to the technical field of cloud resource management, and provides a cloud resource management method and device, equipment, a storage medium and a program product, and the cloud resource management method comprises the steps: processing various types of collected cloud resource data, and storing the processed data in a data platform; wherein dependence topology exists among various types of cloud resource data of the data platform; inputting the cloud resource data in the data platform into the classifier model to obtain a type label output by the classifier model; inputting the cloud resource data and the corresponding type label into a scoring device model to obtain a cloud resource health degree output by the scoring device model; and when the health degree of the cloud resources is lower than a first preset threshold value, giving an alarm prompt. According to the method, the cloud resource management cost can be reduced through the dependency topology; and automatic early warning is realized by monitoring the health degree of the cloud resources.

The invention discloses a cloud resource management method and apparatus, a device, a storage medium and a program product. The method comprises the steps of obtaining multi-dimensional associated data of cloud resources; wherein the multi-dimensional associated data comprises resource configuration information, a resource operation state, cloud provider information and cost information; constructing a multi-objective optimization model based on the multi-dimensional associated data; wherein the multi-objective optimization model takes reasonable resource cost, resource planning matching and no abnormal resource operation as optimization objectives; solving the multi-objective optimization model to obtain an optimization suggestion of the cloud resources; and carrying out life cycle management on the cloud resources according to the optimization suggestion. By adopting the embodiment of the invention, efficient adaptation of cloud resources and services can be realized, the management threshold and resource waste are reduced, and stable operation of the services is ensured.

Systems and methods for implementing a policy-based framework for O-Cloud Resource Management and Orchestration Services are provided. The method includes: determining, a network function (NF) hosted on a O-Cloud node to be instantiated on another O-Cloud nodes; creating an instantiation policy for the determined NF for the ORMOS; sending the instantiation policy via an R1 interface to the ORMOS; requesting an instantiation implementation of the determined NF via an O2 interface to at least one O-Cloud management service; instantiating a NF on the other O-Cloud nodes according to the implementation request; sending a registration and configuration request for the instantiated NF to NF-related RAN OAM Services; sending a configuration notice for the instantiated NF to the ORMOS; and sending instructions to finalize the instantiation implementation of the determined NF to the at least one O-Cloud management service.

Methods, systems, and devices are provided for managing the interaction between the O-Cloud Resource Management and Orchestration (ORMO) Service Management Orchestration Function (SMOF) and the Radio Access Network Operations Administration Maintenance (RANOAM) Function. The method may include ORMO receiving services related to the SMOF from Service Management and Exposure (SME), ORMO sending a request to the SMOF to drain traffic from at least one Network Function (NF), and ORMO sending a request to Topology Exposure and Inventory Management (TE / IV) to update the inventory.

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.

The invention relates to the technical field of cloud computing, and provides a cloud resource management method, device and system, and the method comprises the steps: carrying out the first management operation of a first resource in cloud resources according to the operation cycle of a target application, and enabling the first management operation to indicate the switching of the state of the first resource, the state of the first resource comprises allowing the first resource to run the target application or allowing the first resource to run the target application and the non-target application. The target application comprises the application running according to the running cycle in the multiple applications, and the non-target application comprises the applications except the target application in the multiple applications. The resource scheduling of the management cloud resources is realized to meet the resource requirements of the operation of various applications, the utilization rate of the cloud resources is improved, and the resource waste is reduced.

Embodiments of the present application provide a multi-cloud heterogeneous resource management method, device, storage medium and computer program product, the method comprising: a multi-cloud resource fusion manager acquiring relevant information of single-cloud resource topologies established by two or more single-cloud resource managers; managing the relevant information of each single-cloud resource topology as a leaf node of the multi-cloud resource fusion manager; the multi-cloud resource fusion manager being a root node; configuring time delay information between each leaf node and the root node on the multi-cloud resource fusion manager; the time delay information being measured and reported by each single-cloud resource manager.

The invention relates to the technical field of cloud computing resource management and online education platform optimization, in particular to an online education platform cloud resource management system and method based on intelligent analysis, and specifically relates to the field of ideological and political education. The method comprises the following steps: acquiring and preprocessing sensing data of a cloud server of an online education platform to obtain preprocessed sensor data; performing thermal imaging scanning on the cloud server according to the preprocessed sensor data to obtain a thermal distribution diagram; constructing a microenvironment feature vector according to the thermodynamic distribution diagram and the preprocessed sensor data; performing teaching task exception association analysis on the microenvironment feature vector to obtain a time sequence association feature table; and performing thermal-electric environmental factor identification according to the time sequence correlation feature table to obtain a key environmental factor list. According to the invention, through the cloud computing resource management and online education platform optimization technology, the stability and reliability of the online education platform in a high-load and key teaching period are improved.