79results about How to "Improve resource allocation efficiency" patented technology

The invention provides a resource configuration prediction method and equipment, applied to predicting resource configuration of a cloud service system. According to the method and equipment, the resource distribution efficiency is improved, and the cost of the cloud service system is reduced. The method provided by the embodiment of the invention comprises the steps of acquiring original data ofthe cloud service system, wherein the original data comprises running data of the cloud service system in a production or quasi-production environment; acquiring training data according to the original data; performing deep learning according to the training data to build a resource configuration prediction model; when resource requirement data input by a user is acquired, generating input data ofthe resource configuration prediction model according to the resource requirement data; and predicting according to the input data and the resource configuration prediction model, to acquire resourceconfiguration data of the cloud service system.

A dynamic resource allocation method is introduced herein. The method is adapted to a base station. The method includes the following steps. A number of contending devices in the random access slot is estimated. A reference value is calculated according to the number of the contending devices and a resource allocation parameter. A number of specific resources is calculated according to the number of the contending devices, a number of acknowledgeable machine-type communication devices of the base station at the random access slot and a preamble detection probability. A number of reserved random access opportunities is determined according to a maximum number of the random access opportunities, the number of the specific resources and the reference value. The resources are allocated to the at least one machine-type communication device according to the number of the reserved random access opportunities.

The embodiment of the invention provides a resource configuration method and system for a container application, and a storage medium, and relates to the technical field of cloud computing, being able to be applied to a PaaS platform. The resource configuration method comprises the steps: if a resource configuration request of a container application is received, obtaining application mirror image information of the container application; obtaining pre-configured resource parameter information corresponding to the application mirror image information from a database; packaging the pre-configured resource parameter information into an object; and uploading the object to a container arrangement tool so as to configure the resources of the container application by utilizing the container arrangement tool according to the resource parameter information in the object. According to the embodiment of the invention, resource configuration is carried out on all the container instances of the container application at a time through the container arrangement tool, and manual configuration does not need to be carried out after logging in the container instances one by one, so that the speed and efficiency of resource configuration of the container application are improved, and configuration omission is avoided.

The invention discloses a joint distribution method for uplink power and time slots of a multi-beam MF-TDMA cognitive satellite network. The joint distribution method adopts an on-board resource management architecture and an iterative resource calculation method based on distributed calculation and resource allocation parameter assistance, can effectively reduce the calculation overhead of a network management center, can increase the resource calculation convergence speed, under the condition that the cognitive satellite user accesses the ground microwave base station to serve as the main user at the same frequency band, can guarantee that interference borne by the microwave base station is below the maximum interference threshold while guaranteeing the communication quality requirementof the cognitive satellite user, and can improve the overall capacity of the network. The joint distribution method has the advantages that the convergence speed is higher than that of a traditional central resource allocation method, the resource allocation efficiency and flexibility are improved through multi-user and multi-beam computing units, and the network capacity is improved by combiningtwo-dimensional resource optimization. The joint distribution method is particularly suitable for optimizing the uplink of the multi-beam MF-TDMA cognitive satellite network with limited resources anda flexible networking mode.

The invention discloses a simultaneous wireless information and energy transmission method based on 5G high and low frequency band. Firstly, a wireless information and energy transmission network based on 5G high and low frequency band is designed, a model of resource allocation in high-low mixing network is established, finally, combined with the optimal matching theory and Lagrange dual decomposition, an optimal algorithm for joint power and channel assignment is designed, the coverage area of the network includes hot spot area and wide area coverage area, users located in the wide area coverage area can only receive information from the base station through the low frequency band, users located in the hot spot area can receive information from the base station through the high frequencyband, and at the same time collect energy through the low frequency band, the energy collected by the equipment in the hot spot area comes from the data signal of users in the wide area coverage area. Compared with the traditional single frequency network, the invention not only can improve the throughput of the cell edge user, but also can improve the energy collection efficiency of the cell center user, and has great advantages in energy collection efficiency and user fairness.

The invention discloses a multi-dimensional end-to-end network slice generation device and method. The problems that in the prior art, a user plane only sends a slice request, slices are not created,resource division is not thorough enough, and the generated general abstract topology cannot accurately reflect the actual connection situation between network function units are solved. The method comprises the implementation steps of: (1) creating an application container, (2) generating a user plane network slice, (3) dividing a virtual network according to a flow space rule, (4) generating a control plane network slice, and (5) generating a multi-dimensional end-to-end network slice. In the process of designing the multi-dimensional end-to-end network slice generation device and method, network slices are generated from two dimensions of a user plane and a control plane, and functionally and logically isolated end-to-end network slices are generated.

The invention discloses a resource distribution method used for device to device signal transmission and an apparatus. The resource distribution method comprises the following steps of determining an online condition of user equipment UE in a D2D communication group; according to the determined online condition, sending auxiliary information to the UE, wherein the auxiliary information comprises at least one of an indication whether the UE in the D2D communication group is online and indication information used for indicating a resource pool used by the UE to transmit a D2D signal. A base station sends the auxiliary information to the UE so that the resource pool used by the online UE is defined according to the online condition of the UE in the current D2D communication group. The online UE and offline UE can be guaranteed to use a resource transmission D2D signal in the same resource pool so that normal transmission of the D2D signal is guaranteed; resource distribution efficiency is increased and D2D communication performance is improved.

The invention discloses a resource scheduling method. The method comprises the following steps: generating category information of user terminals based on capability information sent by the user terminals and establishment information carried by the service of the user terminals, obtaining scheduling parameters of the user terminals, calculating scheduling weights of the user terminals based on the scheduling parameters of the user terminals, distributing the user terminals needing to transmit data into a scheduling queue matched with the category information of the user terminals, ranking theuser terminals in the scheduling queue based on the scheduling weights of the user terminals from large to small, and allocating transmission resources to the user terminals based on the sequence ofthe user terminals in the scheduling queue from front to back. The complexity and calculation amount of the base station scheduling processing are reduced, the resource allocation efficiency is improved, the processing load and processing time of the base station are reduced, and a single base station can process more service requests of the user terminals.

The invention discloses an improved FMEA method based on language weighted geometric operators and fuzzy prioritization, aiming at the problems of uncertain expert evaluation information and equivalent expert weight in traditional failure mode and effect analysis (FMEA) risk assessment methods, a method based on group language information is proposed Gathered improved FMEA method. First, regard the three major risk factors assessed by FMEA as linguistic variables, and introduce the language weighted geometry (LWG) operator to directly perform algebraic operations on the expert assessment results, overcoming the drawbacks of fuzzy theory that requires secondary conversion and loss of decision-making information; on this basis Above all, using the fuzzy priority algorithm, an expert weight calculation formula based on the consistency degree of expert ranking is proposed, and the experts who deviate from the group priority are given lower weights to reduce the impact of unfairness on the evaluation results. Taking the failure mode risk assessment of a CNC machine tool bedside box as an example, the effectiveness and practicability of the method are verified.

The invention discloses a method and system for improving the toughness of a power distribution network, and the method comprises the steps of carrying out the importance evaluation of a power distribution network assembly in typhoon weather, building an element fault rate model under the action of storm wind, carrying out the sampling of the state of a wind power generation system through a non-sequential Monte Carlo simulation method, and establishing an optimal recovery strategy model and sorting the importance degrees of the components; when a disaster occurs, a fault condition is obtained, recovering elements with high importance preferentially according to a determined sequence, and improving the robustness of the power distribution network; forming a plurality of micro-grids through pre-deployment of mobile emergency generator cars before disasters and real-time scheduling after disasters, building a target function by taking minimization of power failure time of important loads in different scenes as a target, forming an MILP problem through the target function and constraint conditions, obtaining the real-time distribution condition of the mobile emergency generator cars after disasters by solving the corresponding problem, and completing power distribution network recovery and promotion. According to the invention, the robustness of the power distribution network is improved; the power distribution network fault recovery time is shortened, and the power distribution network recovery rapidness is realized.

The invention provides a resource allocation method based on an activity task, and the method comprises the steps: pushing an activity page to a user terminal, and receiving confirmation information that a user participates in an activity through the activity page; when activity participation information of the user is received, generating an invitation code and associating the invitation code with the user; generating an invitation URL according to the invitation code, wherein the invitation URL comprises the invitation code and a new user guide page address, and pushing a sharing page to theuser terminal; monitoring an invitation code and page submission information returned by the new user guide page, and associating the page submission information with the user according to the invitation code; and judging the completion condition of the user for the activity task according to the page submission information associated with the user and a predetermined activity rule, and allocating corresponding resources to the user according to the completion condition. According to the method, resource allocation can be carried out more effectively, the resource allocation efficiency is improved, and the resource allocation cost is reduced.

The invention discloses a resource allocation method and device, user equipment, a base station, and a readable storage medium. The method comprises the steps: acquiring the location information of resource blocks of a first type after the initial cell selection or cell reselection is completed in an idle state; acquiring the reference point offset indication information sent by a base station, wherein the reference point offset indication information includes a frequency domain offset N of a reference point indicated by the base station relative to a specified resource block, and the specified resource block is one of the specified resource blocks of the firs type, wherein N is an integer; calculating the frequency domain location of a reference point according to the obtained location information of the resource blocks of the first type and the reference point offset indication information; and determining a resource block that receives a physical downlink shared channel according tothe frequency domain location of the reference point and the resource allocation information included in the scheduling information when receiving the scheduling information sent by a base station. According to the above solution, the method can improve the resource allocation efficiency of a system in an idle state.

The invention relates to the technical field of computer vision, and discloses a crowd density estimation recognition and crowd behavior analysis algorithm. The algorithm has the advantages that a system can automatically remind each point location abnormal condition, a passenger flow peak period can be predicted to make a deployment scheme in advance, and after a dangerous condition occurs, the system automatically makes a chain reaction to minimize the life and property safety loss of people. The crowd density estimation and recognition system uses current advanced machine vision, graphic image video analysis technique, human body pattern recognition technology, and artificial intelligence machine learning technology, to detect the mobile people flow density of a preset area at a second-level speed. The method has the advantages that the influence of light, shadow and heat can be effectively eliminated through node passenger flow quantity and queuing length statistics, interference objects in a detection area can be self-calibrated and eliminated every two minutes, when the monitored passenger flow quantity reaches a set threshold value, passenger flow alarming is carried out, acorresponding early warning scheme is started, and safety accidents are prevented.

The invention discloses a resource allocation method and device, which are used to reduce the calculation amount required for resource allocation, thereby improving resource allocation efficiency. A resource allocation method provided by the present invention includes: determining the UE that currently needs to allocate frequency domain resources according to the priority weight of each user equipment UE, wherein the priority weight of the UE is based on the radio bearer corresponding to the UE The priority value of the RB is determined; the frequency domain resources are allocated to UEs that currently need to allocate frequency domain resources.

The present invention discloses a decoration platform based on the internet of things and a design method thereof. The method comprises the steps of: performing collection of three-dimensional space environment data of a field to be decorated through a space data collection module, and sending the collected three-dimensional space environment data to a space model construction module; performing three-dimensional space modeling of the field to be decorated through the space model construction module according to the collected three-dimensional space environment data; referring to the three-dimensional space modeling parameters of the field to be decorated, and constructing a home decoration model in the space model through a home decoration model customization module; matching the constructed three-dimensional space model and the home decoration model through a model matching module to form a decoration scene; and performing panorama display of the matched three-dimensional space modeland home decoration model decoration scene through a panorama display module. The decoration platform based on the internet of things and the design method thereof are high in performance cost ratio,save money, allow decoration to become transparent and simple, allow personalized decoration demands to maximally achieve standardization, solve the industry chain lengthiness problem, solve the problem of industry standard, are transparent in quotation and charge, transparent in decoration flow and high in attached value.

The invention discloses a carrier wave resource allocation method. The method comprises the following steps: at the beginning of a business connection, a terminal sends a message to a base station for applying for the allocation of absolute carrier wave resource; when the demand of the terminal on the carrier wave resource changes, the terminal sends a message to the base station for applying for the allocation of relative carrier wave resource; and the base station allocates corresponding carrier wave resource to the terminal according to the messages sent by the terminal. The flexible carrier wave resource allocation method is beneficial to the base station which carries out the allocation of carrier wave according to the concrete business connection circumstances.

The invention provides an information processing method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining the track information of a pedestrian in avideo stream based on the video stream collected at a first target place; determining the number of first people streams entering the first target place and the number of second people streams passingthrough the first target place within a preset duration based on the track information of pedestrians in the video stream; and based on the first people flow quantity and the second people flow quantity, generating adjustment information for the displayed articles in the second target place.

The present invention discloses a personnel location method and system. The personnel location method comprises the following steps: obtaining the terminal information of a terminal entering a management range at present at the access of the management range; establishing mobile communication connection or wireless communication connection with the terminal in the management range based on the terminal information; and performing location according to the established mobile communication connection or the wireless communication connection to obtain location information. According to the embodiment of the invention, the terminal accessing the management range can be sensed, and a communication connection with the terminal is actively established for location, and compared to the location technology in the prior art, the personnel location method and system can accurately and completely obtain personnel location information in the more continuous time and wider range so as to effectively provide location data support for the application in the fields such as intelligent operation and the like.

The embodiment of the invention provides a cutoff identification method and device based on deep learning. The method comprises the steps of obtaining a cutoff node corresponding to a data cutoff record in a cutoff state and a cutoff service type from a data stream statistical record; extracting first feature information of each cutoff node in the data cutoff record and second feature informationof a data forwarding node associated with each cutoff node according to a feature extraction strategy corresponding to the cutoff service type, and then performing deep learning; therefore, the data flow in each service forwarding process is identified, the cutoff identification accuracy is improved, the resource configuration efficiency is effectively improved, and the user service experience isimproved.

The invention provides a resource allocation method and device, and a coupon allocation method and device. The resource allocation method comprises the steps: determining a plurality of objects and a plurality of resources corresponding to the objects, wherein the current object and any resource corresponding to the current object form a current distribution combination; determining whether the current distribution combination meets a conflict condition, if so, determining the current distribution combination as a target distribution combination, and the target distribution combination comprising a target object and any resource corresponding to the target object; and according to the plurality of target allocation combinations, determining the allocation resources and the allocation resource quantity of the target object.

The invention discloses a data acquisition method, device, system and equipment and a storage medium. The method comprises the steps that a controller sends a driving instruction to N communication chips; wherein the types of the N communication chips are different, N is greater than or equal to 2, and N is an integer; each communication chip sends a confirmation signal to an acquisition board group based on the driving instruction; wherein the acquisition board group comprises a plurality of acquisition boards; each acquisition board is provided with a plurality of analog front-end chips; if the communication chip receives a reply signal sent by the acquisition board group, determining the communication chip as a target communication chip; and the target communication chip establishes connection with the plurality of analog front-end chips of each acquisition board to form a plurality of data transmission channels, and acquires the state data of the battery cell based on the plurality of data transmission channels. According to the technical scheme, the problem that the mainboard needs to be replaced due to the fact that the types of the communication chips of the mainboard are not matched is solved.

The invention provides a resource allocation method of a storage system. The method comprises the steps of firstly obtaining hardware resource information of hardware needing to be configured in a storage system, then determining allocatable resource information of the hardware needing to be configured of the virtual machine according to a pre-configured resource allocation table, storing the allocatable resource information into a virtual machine starting configuration file, and finally starting the virtual machine and operating the virtual machine starting configuration file. Wherein the resource allocation table is a mapping table of hardware resource information and allocatable resource information; Therefore, for storage systems of different product models, resource distribution can be automatically carried out according to product specifications of the storage systems, the resource distribution efficiency and the product maintainability of the storage systems are effectively improved, and errors and risks caused by manual operation factors are avoided.

The invention discloses an inventory determination method for aging sensitive materials. The method comprises the following steps: collecting a first mapping relationship between historical consumption of a target aging sensitive material and time, a second mapping relationship between the number of historical consumption objects and time, and an initial inventory of the target aging sensitive material; according to the first mapping relation, the predicted consumption of the target aging sensitive material in a preset time period is determined; according to the predicted consumption, the second mapping relation and the initial inventory, determining the predicted inventory of the target aging sensitive material at each time point in the preset time period; according to the method, the more accurate real-time stock of the target aging sensitive material at the current moment and the future change trend of the predicted stock along with time can be obtained; therefore, the resource allocation efficiency of the aging sensitive material is improved, and the material allocation cost is reduced.