54 results about "Capacity management" patented technology

The invention discloses an energy storage capacity prediction method based on meteorological parameters, and particularly relates to the technical field of graph neural networks. Collecting multi-source meteorological data to construct an original time sequence matrix, and extracting a disturbance feature tensor based on a local disturbance window; the disturbance characteristics are mapped to a high-order space, and a multi-scale capacity response factor is constructed; modeling a causal link of meteorological disturbance and capacity fluctuation based on a graph structure, and extracting a dynamic dependency path; and the lightweight convolution model is combined to complete capacity prediction. In addition, through reverse feedback of prediction errors, disturbance window parameters are dynamically optimized, and self-adaptive evolution of an input feature structure is achieved; the capacity prediction precision and generalization ability of the energy storage system under the complex meteorological condition are improved, and the method is suitable for capacity management and scheduling optimization in distributed energy storage, micro-grids and other scenes.

The invention provides a cloud platform database storage use prediction method based on time sequence modeling, and belongs to the technical field of cloud computing operation and maintenance management. The method comprises the steps that historical storage use data of a target database in a cloud platform is collected, a time sequence prediction model is built based on the historical storage use data, and the time sequence prediction model is a Prophet model supporting trend term and periodic term modeling; using the time sequence prediction model to predict the storage usage amount of the target database in a future preset period, and generating a prediction result value; and comparing the prediction result value with a preset capacity threshold value, and if the prediction result value exceeds the preset capacity threshold value, generating capacity early warning information. By automatically and accurately predicting the use trend of database storage and providing early warning information, the automation and foresight of database capacity management are improved.

The invention relates to the technical field of online car-hailing, and discloses an online car-hailing transport capacity prediction method and device, computer equipment and a storage medium, and the method comprises the steps: dividing a target geographic region in an electronic map into a plurality of hexagonal grid units; acquiring real-time state data of each vehicle in each hexagonal grid unit, and determining real-time transport capacity data of each hexagonal grid unit according to the real-time state data; and predicting the transport capacity demand change condition of each hexagonal grid unit in a future time period based on the real-time transport capacity data. According to the method, the problems of inaccurate scheduling and response lag caused by insufficient grid division precision and lack of prediction capability in the existing online car-hailing transport capacity management are solved.

The application discloses a SIP multi-terminal concurrent registration and intelligent call distribution method and device, in the method, a terminal type classification system based on bitmap enumeration is constructed, each terminal type occupies an independent bit; a custom header field carrying a device mark is defined in the SIP REGISTER, persistent storage is carried out and multiple filtering modes are designed; a double pool capacity management mechanism is deployed, independent capacity pools are set for self-developed terminals and third-party phones and intelligent expulsion is triggered; when a call comes in, a virtual contact record containing a device mark is generated for each device instance of an offline terminal and is deduplicated; in call routing, contacts are filtered based on terminal types and device marks, device marks are injected and repeated ringing is prevented based on a number and mark binary tuple; when an answer or a rejection is given, a corresponding channel is precisely hung up based on the device mark. The application realizes terminal type level and device instance level control, and improves call distribution efficiency in a multi-terminal concurrent scene.

The application discloses a garbage collection method and device of a satellite-borne solid state disk, a storage medium and equipment, and relates to the technical field of satellite remote sensing. The method comprises the following steps: acquiring the directly writable capacity, the to-be-recovered capacity and the capacity management threshold of the solid state disk of the satellite payload after the execution of the current task, and determining whether the solid state disk meets the capacity requirement; if the capacity requirement is not met, data is deleted, and the to-be-recovered capacity is re-acquired; according to the re-acquired to-be-recovered capacity, the garbage collection operation of the solid state disk is controlled to be executed by the satellite payload, and it is determined whether the garbage collection operation of the solid state disk is overdue; if the garbage collection operation is overdue, first telemetry information is sent to a ground terminal, wherein the ground terminal is used to determine whether the garbage collection operation is overdue and affects the execution of the next task according to the first telemetry information; if the garbage collection operation is overdue and affects the execution of the next task, it is determined that the garbage collection operation of the solid state disk is executed before the execution of the next task. The application controls the satellite-borne solid state disk to execute the garbage collection deterministically.

The invention provides a resource capacity management method and device, electronic equipment and a storage medium, and the method comprises the steps: firstly configuring a data source parameter, and synchronizing target resource data from a data source to a resource space according to the parameter; constructing a training data set based on the target resource data, outputting a resource demand prediction value of a specific period in the future after training by using a hybrid model, and carrying out multi-level early warning on a residual resource space representing the residual capacity of the resource space in combination with a preset threshold rule to generate early warning information; and finally, when the early warning information meets a specific condition, determining utilization rate information of specific resource data in a preset period in the resource space, identifying low-efficiency resources from the utilization rate information according to a preset efficiency rule, and further generating suggestion information for the low-efficiency resources. According to the invention, systematicness, accuracy and perspectiveness of resource capacity management can be effectively improved.

The invention provides a cloud product resource use condition determination method and device, a processor and a storage medium, and belongs to the field of computers, and the method comprises the steps: obtaining resource data of a cloud product; wherein the resource data comprises static asset data and dynamic business data; counting the resource data according to a plurality of preset dimensions to generate corresponding standard measurement data; wherein the preset dimension comprises but is not limited to a capacity management unit, a technology stack and an available area; executing a calculation task on the standard measurement data based on a preset calculation rule to generate a resource configuration result; wherein the calculation rule is determined based on historical dynamic business data; and carrying out visual display on the resource configuration result. Through the method, different heterogeneous data sources are unified, so that the resource configuration decision can closely follow the actual demand of business development, and the resource utilization rate, the cost effectiveness and the overall management efficiency are improved.

The technology disclosed herein provides a method including determining a location of a storage device in a storage enclosure, based on the location of a storage device in a storage enclosure, determining environmental associated with the location of the storage device, determining achievable capacity of the storage device based on the environmental parameters associated with the location of the storage device, and formatting the storage device based on the determined achievable capacity.

Resource allocation and configuration of equipment in colocation data centers, including predicting hierarchical capacity demand for each of the tenants of the colocation data centers using internal demand signals and external demand signals; determining remaining capacity available for the each of the tenants; determining additional capacity needed for the each of the tenants based on the remaining capacity available and the predicted hierarchical capacity demand of the each of the tenants; generating a recommended configuration for the each of the tenants determined to require additional capacity based on a current configuration of the each of the tenants and the determined additional capacity needed; for the recommended configuration being accepted, while the recommended configuration is being implemented, optimize allocation of resources to the recommended configuration based on tenant priority score function, current allocation, and remaining capacity; and controlling the colocation data centers to allocate the resources according to the optimization.

Methods and apparatus for managing capacity in a Citizens Broadband Radio Service (CBRS) network. An exemplary method embodiment includes operating a Citizens Broadband Radio Service Device (CBSD) of a cell to perform the steps of: receiving a power down message; decreasing, in response to the power down message, UE inactivity timer length for one or more UEs from a first length to a second length; and continuing to transmit packets to UEs at an edge of the cell. An exemplary system embodiment includes: a CBSD of a cell that comprises: a network receiver that receives a power down message; a first processor that controls the first CBSD to decrease, in response to the power down message, UE inactivity timer length for one or more UEs from a first length to a second length; and a wireless transmitter that continues to transmit packets to UEs at an edge of the cell.

The invention discloses a capacity management and control device and method for a semiconductor factory service system, and the device comprises a demand end module which is used for obtaining the position information and consumption demand information of machine equipment in a semiconductor factory; the supply end module is used for acquiring pipeline position information and pipeline supply capacity of a factory affair system in the semiconductor factory; the capacity management and control module is used for receiving the machine equipment position information given by the demand end module and the pipeline position information given by the supply end module, realizing column network matching of each machine equipment and each pipeline, and receiving the use amount demand information given by the demand end module and the pipeline supply capacity given by the supply end module, and the capacity management and control of the semiconductor factory service system is realized in combination with a point location distribution mode. According to the method, the power capacity of the whole factory is comprehensively and dynamically controlled through data communication between the factory affair system in the semiconductor factory and the machine equipment in the spatial dimension, and cost waste caused by mismatching of the demand end and the supply end is avoided.

This application provides a network link capacity management method, apparatus, device, and medium, relating to the field of computer technology. The method includes: collecting link traffic of a network link; statistically analyzing the bandwidth utilization of the network link within a first period based on the link traffic and the link bandwidth of the network link, obtaining a first statistical bandwidth utilization rate corresponding to the first period, wherein the first period includes multiple service time periods; comparing the first statistical bandwidth utilization rate with a capacity expansion threshold; and if the first statistical bandwidth utilization rate is greater than the capacity expansion threshold, then expanding the link bandwidth of the network link. Thus, by using the statistical bandwidth utilization rate of the network link within a time period containing multiple service time periods as an evaluation indicator for whether network link capacity expansion is needed, the accuracy of capacity expansion judgment is improved, achieving economical and reliable management of network link capacity.

The invention relates to an order allocation method and device, computer equipment and a storage medium. The method comprises the following steps: in response to a distribution request of a current order, extracting distribution address information of the current order, and obtaining address information of a physical site corresponding to at least one pre-created virtual site, and determining a first target virtual site from the virtual sites according to the delivery address information and the address information of the physical sites, obtaining rider information bound with the first target virtual site, determining a target rider according to the rider information, and allocating the current order to the target rider. By adopting the method, the efficiency of order allocation and the efficiency of transport capacity management and control can be improved.

The invention relates to the technical field of multimodal transport, and discloses a multimodal transport capacity management method and system, electronic equipment and a storage medium. In the multimodal transport capacity management method, a first message of in-transit goods is acquired, and the first message comprises goods basic information and goods transport information; acquiring a second message about the waterway transportation ship, wherein the second message comprises the residual warehouse capacity and the route; analyzing the first message and the second message to obtain that the first in-transit cargo meets the transportation requirement of the first waterway transportation ship in the next transportation section, and generating a first scheduling scheme; a first transport tool where the first in-transit goods are located is dispatched to drive into the transfer site, and a first waterway transport ship is dispatched to transfer the first in-transit goods. According to the technical scheme of the invention, the scheduling management waterway and land transportation modes are joined into multimodal transportation, the multimodal transportation mode is guided to organize services, the transportation capacity and the transportation efficiency of the multimodal transportation are optimized, and the effects of reducing the logistics cost and improving the organization efficiency are realized.

The present disclosure provides a capacity management method and related equipment, and relates to the technical field of big data. The method comprises the following steps: acquiring a used resource amount of a first cluster, a maximum resource amount of the first cluster, and historical information corresponding to a second cluster, the first cluster and the second cluster being different server clusters corresponding to the same user; predicting a resource amount growth rate of the first cluster according to multiple resource amount data; determining a remaining available time of the first cluster according to the used resource amount, the maximum resource amount and the resource amount growth rate, the remaining available time being a ratio of a resource amount difference and the resource amount growth rate, the resource amount difference being a difference between the maximum resource amount and the used resource amount; and outputting an alarm information in the case that the remaining available time is less than an alarm time. The present disclosure can avoid the business interference problem caused by limiting the write operation of the user, and the robustness of the service running in the current server cluster is improved.

A method and node of a network of clusters supporting containerized workloads running in workload cluster namespaces in communication with at least one workload cluster are disclosed. In one aspect, a method implemented in a workload cluster in a network of workload clusters supporting containerized workloads running in cluster namespaces in communication with at least one workload cluster is provided. A request is received from a cluster user quota controller, the request containing a proposed set of resource limits for a cluster namespace of the cluster user. The proposed set of resource limits to be evaluated is relayed to a cluster administrator quota controller. A request is received from a cluster administrator quota controller. The request contains a first set of resource limits selected from the proposed set of resource limits to apply to a cluster namespace of the cluster user.

This disclosure describes a content capacity system that provides a framework for solving computational capacity management problems for content providers that provide real-time content distribution. For example, the content capacity system generates and implements resource capacity policies that enable content providers to identify a target distribution location with available resources to provide optimal content types when applied to incoming content requests. Additionally, the content capacity system ensures that resources are efficiently used for the content type with the highest utility and avoids processing infeasible locations and content types, as well as exceeding computational capacities.

The invention provides a capacity management method and device. The method comprises the following steps: determining a first feature tensor according to a preset time window, business event features and environment features; wherein the first feature tensor comprises a plurality of data dimensions; inputting the first feature tensor into a hybrid neural network model, and predicting the resource demand quantity at a specific time point in the future to obtain prediction information corresponding to the resource demand quantity at the specific time point in the future; performing abnormal data identification on the real-time data flow according to an unsupervised learning algorithm to obtain abnormal information; and determining an optimal capacity management strategy according to the prediction information and the abnormal information. Through the embodiment of the invention, the problem of low capacity management efficiency caused by the fact that the traditional CMP passively responds to resource alarm, depends on manual decision and execution and cannot predict future demands or global optimization in the related technology is solved.

The embodiment of the invention provides a method and a device for adjusting wireless gateway equipment. The method comprises the following steps: determining capacity index data of a service corresponding to a network slice according to operation data of the network slice in a wireless network; operation indication information of the network slice is determined according to the capacity index data, and the operation indication information is used for indicating execution of capacity management operation on wireless gateway equipment in the network slice; based on the operation indication information of the network slice, the capacity management operation is executed on the wireless gateway devices in the network slice, and the capacity management operation is used for managing the number of the wireless gateway devices in the network slice. According to the embodiment of the invention, the problem that the wireless gateway equipment in the wireless mesh network cannot be flexibly scheduled in the related technology, so that the wireless gateway equipment of partial network slices is insufficient in flow and large in service load is solved.

An example method of managing hardware capacity in a multi-cloud computing system includes: obtaining, by a hardware inventory service executing in the multi-cloud computing system, hardware information for physical servers, in a public cloud, for which a customer has a subscription entitling bare-metal management of the physical servers; maintaining, by the hardware inventory service, an inventory of hardware capacity comprising a physical server pool that includes the physical servers; receiving, at the hardware inventory service, a request to consume the hardware capacity; and providing, by the hardware inventory service, a response to the request that identifies the physical server pool for deploying software to execute therein.

A teaching switch port automatic mapping method based on incremental clustering and capacity constraint comprises the steps that a scene is determined through an LLDP and a wiring panel, a course / group capacity and seat template is obtained, port time sequence, physical negotiation, DHCP control message and naming information are collected, seeds are analyzed according to the naming template, and a teaching switch port is obtained. Clustering and confidence correction are carried out in combination with time sequence / physics / manufacturer consistency and seat topology; constructing a port-seat bipartite graph, and completing mapping from a port to a group / seat / VLAN (Virtual Local Area Network) through hard evidence priority and depth-limited replacement; and carrying out non-inductive verification and correction by passive receipt of the group exclusive DHCP option, finally issuing effective configuration, and establishing class hour viscous binding and capacity management. According to the scheme, inter-group isolation and capacity control can be automatically and interpretably realized, mismatching and disturbance are reduced, and late access and prior accumulation are supported.

The application discloses a dry-type transformer and UPS collaborative system for a modular data center, and particularly relates to the technical field of power supply and distribution collaborative control of a modular data center, and is used for solving the problems of insufficient cooperation between a dry-type transformer and an uninterruptible power supply in the existing modular data center, and local overload and insufficient utilization of redundancy during maintenance switching and capacity expansion. By constructing power distribution topology modeling, state modeling, working condition acquisition, scene identification, capacity envelope and collaborative execution integrated control link in the collaborative control device, the dry-type transformer thermal time domain margin, the uninterruptible power supply redundancy capability and the power distribution topology and operation scene are uniformly included in capacity constraint and switching evaluation logic, so that the technical effects of automatically planning and checking load migration path during maintenance switching, fault switching and capacity expansion process, avoiding over-limit operation of the transformer and the uninterruptible power supply, and guaranteeing continuous power supply and collaborative capacity management of the modular data center are achieved.

The invention relates to the technical field of online car hailing, and discloses a transport capacity management method and device and computer equipment, and the method comprises the steps: a server side receives an original position point reported by a user side in a preset range, updates the original transport capacity distribution information of a geographic grid corresponding to the preset range in a server map according to the original position point, and stores the original transport capacity distribution information; generating a corresponding transport capacity scheduling strategy; and the user side sends an original position point of the user side to the server side, receives a push data packet returned by the server side based on the original position point, analyzes the scheduling suggestion information and the transport capacity feedback information in the push data packet, executes an updating operation of a user side map according to the transport capacity feedback information, and executes a reminding operation of the scheduling suggestion information at the same time. Through interactive cooperation of the server side and the user side, dynamic updating and accurate scheduling of transport capacity distribution are realized, and the utilization efficiency of transport capacity resources is effectively improved. According to the invention, the problem of unbalanced supply and demand of transport capacity caused by asymmetry of driver and passenger information in the prior art is solved.

The application discloses a capacity management method, device, equipment, medium and product, the method comprises: when detecting the warehousing / discharging operation of a target product, obtaining the inventory data of the target product; determining the inventory state of the target product according to the inventory data and the pre-configured sell-out / unsell-out threshold value; wherein the pre-configured sell-out / unsell-out threshold value is generated by a resource and product mapping model of the target product, and is optimized through periodic threshold value inspection; and performing corresponding sell-out / unsell-out capacity management operation on the target product according to the inventory state. The product warehousing / discharging operation can be used as a trigger point to obtain inventory data in real time and judge the state by comparing the sell-out / unsell-out threshold value configured by the resource and product mapping model, so as to perform sell-out / unsell-out operation without manual intervention, improve the accuracy and reliability of inventory state judgment, and improve the real-time performance and execution efficiency of capacity management.

The application relates to the technical field of resource scheduling, and specifically discloses a cross-platform marketing resource intelligent scheduling evaluation method and system, which comprises the following steps: acquiring resource node information of each platform at a resource facility layer, and acquiring a dynamic stability index of each platform according to the resource node information; constructing a cross-platform resource cooperation relationship graph according to the dynamic stability index of each platform and a cooperative calling relationship between resource nodes, and converting the cooperation relationship graph into a global resource state entropy matrix; acquiring user marketing activity information of each platform at a marketing application layer, and generating a resource demand feature vector of each micro task according to the user marketing activity information. The application forms a complete technical chain from state perception, correlation modeling, demand description, matching optimization, capacity management to effect evaluation, realizes accurate docking of a supply side and a demand side of cross-platform marketing resources, elastic adaptation of scheduling execution and capacity management, and an execution result.

The invention relates to the technical field of intelligent education management, and discloses a research and study travel personalized intelligent planning and management system. The system comprises a data acquisition module, a learner portrait construction module, a resource matching module, an intelligent planning module, a capacity management module, a conflict resolution module, a dynamic adjustment module and an evaluation feedback module. Personalized resource recommendation is realized by constructing a multi-dimensional learner portrait, a multi-objective optimization algorithm is adopted to generate an optimal study travel scheme, a dynamic capacity management and conflict resolution mechanism is established to intelligently process reservation conflicts, and a real-time dynamic adjustment mechanism is introduced to deal with a deviation condition in an execution process. And a closed-loop feedback mechanism is constructed to realize continuous optimization of the system. According to the invention, the organization efficiency and education effect of research and study travel can be obviously improved, and a complete intelligent solution is provided for schools and research and study institutions.

The invention relates to the technical field of big data analysis and supply chain capacity management, in particular to an enterprise intelligent operation decision support system based on big data, which is characterized in that a supply chain data acquisition unit acquires a one-week capacity decrease value and a fluctuation period identifier caused by raw material delay in real time; a fluctuation characteristic analysis unit generates a fluctuation amplitude grade identifier through continuous interval threshold matching, analyzes a period identifier to obtain a continuous period characteristic, and packages the continuous period characteristic into structured data; the dynamic fusion processing unit fuses real-time productivity, same-period historical fluctuation and global historical productivity mean data according to two dimensions of grades and periods, and distributes differentiation weights; and the reference capacity generation unit is based on real-time data, superposes historical capacity change trend coefficients, and outputs a dynamic reference capacity value retaining instantaneous fluctuation characteristics through global mean smooth calibration, so that reliable support is provided for an enterprise to formulate a distribution plan matched with the actual capacity of the current week, and the operation decision scientificity is improved.

The invention discloses a spaceborne solid state disk garbage collection method and device, a storage medium and equipment, and relates to the technical field of satellite remote sensing. The method comprises the following steps: acquiring direct writing capacity, to-be-recycled capacity and a capacity management threshold value of a solid state disk of a satellite load after a task is executed, and judging whether the solid state disk meets a capacity requirement or not; if the capacity requirement is not met, data deletion is carried out, and the to-be-recycled capacity is obtained again; according to the reacquired to-be-recycled capacity, controlling the satellite load to execute garbage recycling operation of the solid state disk, and judging whether the garbage recycling operation of the solid state disk is overtime or not; if yes, first telemetry information is sent to a ground terminal, and the ground terminal is used for judging whether the timeout of the garbage collection operation affects next task execution or not according to the first telemetry information; if yes, it is determined that the garbage collection operation of the solid state disk is executed before the next task is executed. The spaceborne solid state disk is controlled to deterministically execute garbage collection.