36results about How to "Improve resource scheduling efficiency" patented technology

The invention provides a kubernetes-based container number flexible adjustment implementation method and device. The method comprises the steps that the access number of different services of the container cluster is acquired; the load condition of each POD of the container cluster is acquired, and the maximum loading service access number of the POD under each service is determined according to the load condition of each POD; the access processable threshold of different services of the POD is determined, the dynamic adjustment mechanism is triggered to adjust the container number when the index of the service access number of the container cluster reaches the set threshold, the POD number required to be adjusted is calculated by monitoring the service request number and the total load condition of the processing service POD, then the POD number is dynamically adjusted according to kubernetes and the POD number is quickly increased at the service peak so as to achieve the effect of shunting and pressure reduction; and excess POD is closed at the service steady period to save the serve resource so that the container operation efficiency and stability can be enhanced, and the resource scheduling efficiency of the Kubernetes-based container clustering management system can be enhanced.

The invention discloses a multi-target tracking method and a corresponding video analysis system for implementing the scheme. The method comprises the following steps: acquiring detection position information of a target; obtaining predicted position information of the target; matching the obtained prediction position information with the detection position information; updating the state information of the target based on the detection position of the target under the condition that the detection position information of the target is judged to be matched with the prediction position information of the target; under the condition that it is judged that the prediction position of a certain target has no detection position matched with the prediction position, judging that the target is an extinction target; and judging that the target is a new target or a reappeared target under the condition of judging that the detection position of a certain target is not matched with the detection position of the target. Therefore, through reasonable allocation of the functional modules, high tracking precision requirements can be met while low-computing-power high-speed tracking is realized.

The present invention provides a grid resource scheduling method based on a continuous two-way auction mechanism, which belongs to the field of network technology and includes a preparation period, a screening period, and an auction period. The scheduling method of the present invention uses the auction mode as the grid resource capacity pricing method, and The allocation of grid resources in this way can well reflect market information and fully mobilize the majority of users to add idle resources to the grid, improving the efficiency of resource scheduling in the grid environment; improving the original continuous two-way auction mechanism, It is suitable for the scheduling of grid resources divided by block capacity, and a matching method in the state of grid resource oversupply is designed, which is more suitable for the actual short-term grid resource scheduling situation.

The invention provides a grid resource scheduling method based on a simultaneous upward-offering auction mechanism, belonging to the technical field of networks. The grid resource scheduling method includes a preparation period, a screening period and an auction period. In the grid resource scheduling method, auction is adopted as a manner for pricing the grid resource capacity, and the pricing manner is used for allocating grid resources, thus the market information can be well reflected, and masses of customers are fully aroused to arrange idle resources into a grid so as to improve the resource scheduling efficiency in the grid environment; and the original simultaneous upward-offering auction mechanism is improved so that the mechanism is suitable for scheduling grid resources subjected to ribbon capacity division, and a grid resource auction winner standard identifying method is designed through combination of the grid resource scheduling method and a genetic algorithm, thus the grid resource scheduling method is better applicable to an actual long-term grid resource scheduling condition.

The embodiment of the invention provides a resource scheduling method and system, electronic equipment and a readable storage medium, which are applied to the technical field of disaster prevention and reduction, and the method comprises the following steps: after receiving a rescue task, a cloud center server divides the rescue task into sub-tasks and sends the sub-tasks to edge servers; each edge server determines local optimal resources in the available resources according to the transportation cost and the transportation time of the available resources corresponding to the subtasks when itis judged that the available resources corresponding to the subtasks exist according to the information of each type of resources in a locally stored resource table and resource types required by each subtask , and the local optimal resources are sent to the cloud center server; and the cloud center server selects global optimal resources in the local optimal resources of the sub-tasks accordingto the execution sequence of the sub-tasks and for each sub-task, and schedules the global optimal resources to the positions of the rescue tasks. The resource scheduling efficiency can be improved.

The embodiment of the invention discloses a vehicle order processing method and a server. The method comprises: receiving vehicle order information, wherein the vehicle order information at least comprises a pick-up departure place; and if a driver terminal, having distance, from the pick-up departure place, which is in a first preset range, has no order receiving response in order receiving timeintervals, sending the vehicle order information to a driver terminal in a second preset range. The server disclosed by the embodiment of the invention is configured to execute the method mentioned above. The method can enlarge a preset range of vehicle order usage to improve vehicle resource scheduling efficiency and reduce user waiting time so as to increase users' vehicle calling experience.

The invention discloses a control method of an integrative interruption maintenance plan. The control method comprises the steps of tracking and monitoring equipment state, comparing with data stored in a central processing unit (CPU) by integrally online monitoring and live detecting input equipment state data, and determining whether the maintenance is necessary, wherein the CPU obtains a resource scheduling fitness matrix according to the maintenance state and the fitness relation between the interruption maintenance benefit, efficiency in a maintenance resource number determining region and the interruption maintenance task; the CPU determines an optimized objective and constraint conditions according to an interruption rule and target setting; the CPU encodes the task set and randomly generates an antibody; and the CPU adopts calculates by adopting an efficient immune genetic algorithm so as to obtain the optimization result in global convergence. The global co-allocation of the resource and the task in the maintenance plan is realized, the resource scheduling benefit and efficiency of the interruption inspection are improved, and the time, cost and price are reduced.

The application discloses a physics channel resource scheduling method and device, and relates to applications in narrowband internet of things; the method comprises the following steps: a base station obtains coverage grades of M user devices, wherein M is a positive integer; the base station determines an initial resource scheduling bias time and scheduling scope of each user device according tothe coverage grades of the M user devices; the base station determines a scheduling section corresponding to each user device according to the initial resource scheduling bias time and scheduling scope of each user device; the base station schedules a narrowband physics downlink control channel NPDCCH for the user device according to the scheduling section corresponding to each user device.

The invention discloses a multi-base-station multi-user proportional-fairness scheduling method with guarantee of the service quality, and mainly solves the problem that resource scheduling is unfair in the prior art due to neglect of the user service quality. The method comprises the steps that 1) parameters are set according to a practical scheduling problem; 2) the user weight is calculated according to the time averaging throughput of each user; 3) a base station determines the user to serve in the present time slot according to the user weight and the time averaging throughput; 4) after the user to serve in the present time slot is determined, the base station updates the local user throughput, and broadcasts local user throughput information to other bases stations in the network; and 5) scheduling in the roll is terminated according to a scheduling termination condition, and a scheduling result which satisfies the proportional fairness is obtained. Satisfied scheduling result can be obtained when the resources are sufficient or insufficient, the computational complexity is low, the base station scheduling efficiency in the time-varying channels is improved, and the method can be applied to large-scale wireless local area network with multiple adjacent wireless routers.

The invention discloses a resource scheduling method based on a cognitive radio terminal reconfiguration system. By utilizing the resource scheduling method, the defects of overhigh computation complexity and low resource scheduling efficiency in the prior art are overcome. The resource scheduling method is implemented through the following steps of: (1) constructing a signal processing module set of the system and a directed edge set for describing a data transmission situation among modules; (2) constructing a directed acyclic graph (DAG) model of the system according to the module set and the directed edge set; (3) defining a stage value for the modules according to the DAG model; (4) acquiring an expense matrix according to parameters of the system, and calculating cluster gains among the modules according to the expense matrix and a data sending quantity among the modules; (5) dividing the module set into a plurality of sub sets according to the cluster gains; and (6) distributing processors to the modules in each state sequentially by calculating the priority level of the processors according to the respective modules and the precursor and subsequent sub sets of the modules. By utilizing the resource scheduling method, the resource scheduling efficiency can be improved, and the reconstruction time of a cognitive radio terminal is shortened.

The invention provides a grid resource scheduling method based on the English-style restricted combination auction mechanism, which belongs to the field of network technology and includes a preparation period, a screening period, and an auction period. The scheduling method of the invention uses the auction mode as the pricing method of grid resource capabilities , and use this to configure grid resources, which can well reflect market information and fully mobilize the majority of users to add idle resources to the grid, improving resource scheduling efficiency in the grid environment; improving the original British restrictions Combining the auction mechanism to make it suitable for the scheduling of grid resources divided by zonal capacity, and combined with the genetic algorithm to design the grid resource auction winning confirmation method, which is more suitable for the actual special grid resource scheduling situation.

The invention discloses a scheduling method for calling multi-manufacturer AI capability by an intelligent cloud call center, which comprises the following steps of: S1, extracting manufacturer data under a certain condition, and marking a manufacturer process; S2, initiating an intelligent outbound call, obtaining a maximum total score of an intelligent call flow according to the object data mark and the algorithm model, and initiating a call according to an intelligent call service flow; S3, for the historical service data, reversely calculating the flow service quality, and marking the data; and S4, realizing intelligent calling of multi-resource scheduling among multiple manufacturers according to the step S2 and the step S3, and selecting an optimal manufacturer route. According to the invention, through an iterative algorithm, the flexibility of intelligent call-out multi-manufacturer resource scheduling is improved, the bottleneck problem of resource waste caused by a fixed parameter algorithm is avoided, the efficiency of intelligent call multi-manufacturer resource scheduling is also improved, the AI multi-manufacturer income is reasonably allocated, the service quality is improved, the intelligent call deployment risk is reduced, and the global benefit of the intelligent voice in the outbound call field is ensured.

The embodiment of the invention provides a resource scheduling system and method. The resource scheduling system comprises a task processor, a scheduler and a resource processing node, wherein the task processor is configured to determine a target sub-task according to task information of a to-be-processed task, determine a sub-task unit in the target sub-task, and submit a resource acquisition request of the target sub-task to the scheduler; the scheduler is configured to acquire schedulable resource information of the initial processing node in response to the resource acquisition request, calculate a resource scheduling result of the target subtask according to the resource acquisition request and the schedulable resource information, and send the resource scheduling result to the task processor and the resource processing node; the task processor is configured to send the sub-task units to the resource processing node according to the resource scheduling result; and the resource processing node is configured to receive the resource scheduling result and the subtask unit, and execute the subtask unit based on the target resource corresponding to the resource scheduling result.

The invention discloses a method, device and electronic equipment for dynamic scheduling of system data resources. The method includes counting all request data received within a first preset time length, and generating a unique call based on each request data information corresponding to each request data. String; select the target request data one by one in each request data group in turn, and after constructing the request data sequence table based on the selection sequence of each target request data, divide the request data sequence table in sequence based on random numbers; receive each of the request processing nodes Based on the request processing results fed back, the node processing time curve is fitted for each request data group based on the request processing results; The allocation request data is allocated to the request processing node with the shortest estimated processing time. The invention improves the efficiency of resource scheduling and ensures the optimal solution of global resource scheduling.

The invention discloses a multi-base station multi-user proportional fair scheduling method that guarantees service quality, and mainly solves the problem of unfair resource scheduling caused by ignoring user service quality in the prior art. The implementation steps are: 1. Set parameters according to the actual scheduling problem; 2. Calculate user weights according to the user's time average throughput; 3. The base station selects the user to be served in the current time slot according to the user weight and the user's historical average throughput; 4. The base station updates the local user throughput after determining the user served in the current time slot, and broadcasts the local user throughput information to other base stations in the network; 5. Terminates this round of scheduling according to the scheduling termination condition, so as to obtain a scheduling result that satisfies proportional fairness . The present invention can obtain satisfactory scheduling results in both sufficient and insufficient resources, and has low computational complexity, improves the scheduling efficiency of base stations in the case of time-varying channels, and can be used in large-scale wireless local area networks with multiple adjacent wireless routers .

The present application relates to a resource scheduling method, device, computer equipment and storage medium. The method relates to the field of cloud technology, and the method includes: receiving a service association request, where the service association request includes a service identifier and a policy identifier; responding to the service association request, associating a target service corresponding to the service identifier with a target policy object corresponding to the policy identifier; Execute the scheduling policy associated with the target policy object for the target service; receive the resource scheduling request for the target service; respond to the resource scheduling request, and schedule the resources that meet the scheduling policy to run the target service. Adopting this method can ensure the two-way selection between resources and services, reduce the workload and difficulty of operation and maintenance personnel, and improve the efficiency of resource scheduling.

The invention provides a data migration method and device in a cluster, computer equipment and a storage medium, the method is applied to an OpenStack controller of the cluster, the data migration method in the cluster comprises the following steps: obtaining a detection domain in the cluster, and carrying out partition processing on the detection domain to obtain a plurality of detection subdomains; determining a main node in each detection subdomain, and configuring the Corosync software in the main node; on the basis of the cluster node in each detection subdomain, carrying out heartbeat detection by adopting Corosync software to obtain a detection result, and sending the detection result to an OpenStack controller; and migrating the data in the cluster according to a detection result.Cluster center hop detection is effectively prevented from being limited by the scale of nodes in the cluster, heartbeat detection time delay and network bandwidth occupied by heartbeat detection timedelay are reduced, and resource scheduling efficiency in the cluster is effectively improved.

Embodiments of the present invention provide a resource scheduling method, device and system. The embodiments of the present invention relate to the technical field of communication, and are used to solve the problem of resource scheduling in D2D communication. The method includes the first node sending first control signaling to the second node, where the first control signaling includes second control signaling transmission resource information and data transmission resource information. The second node receives the first control signaling sent by the first node, and uses the second control signaling transmission resource to send the second control signaling to the third node, and uses the data transmission resource to send data to the third node. The resource scheduling method, device, and system provided by the embodiments of the present invention can be applied to data transmission equipment that requires high delay performance.

The present invention proposes a data migration method and device in a cluster. The method is applied to the OpenStack controller of the cluster. The data migration method in the cluster includes acquiring detection domains in the cluster, and partitioning the detection domains to obtain multiple detection domains. Sub-domain; determine the master node in each detection sub-domain, and configure the Corosync software in the master node; based on the cluster nodes in each detection sub-domain, use Corosync software to perform heartbeat detection, obtain the detection results, and send the detection results to OpenStack controller; migrate data in the cluster according to the detection results. The present invention can effectively prevent the heartbeat detection of the cluster from being limited by the scale of nodes in the cluster, reduce the heartbeat detection time delay and the network bandwidth it occupies, and effectively improve the resource scheduling efficiency in the cluster.

The invention discloses a MU-MIMO-based proportional fair scheduling method for flow distribution, which mainly solves the problem of proportional fair scheduling ignoring user service quality in the prior art. The implementation steps are: 1. Set the corresponding parameters according to the actual scheduling problem; 2. Calculate the user weight in the utility function according to the mean value of the emission probability satisfying the normal distribution; 3. Generate the sample value of the emission probability and calculate it according to the user weight The utility function value of the sample; 4. Filter out the sample value with good performance to update the mean value of the normal distribution; 5. Record the change of the mean value and switch the variance of different stages according to the corresponding rules; 6. End the iterative process according to the termination condition, A scheduling result that satisfies proportional fairness is obtained. The present invention can obtain satisfactory dispatching results under both sufficient and insufficient available wireless resources, has low computational complexity and fewer iterations, improves dispatching efficiency of base stations, and can be used in a single base station system using MIMO technology.

The invention provides a Kubernetes scheduling method and device and a storage medium. The method comprises, removing Nodes which do not meet requirements by filtering according to a pre-selection algorithm; setting a queue for each Node according to the resource type; dividing priorities for a Pod to be scheduled; analyzing the state of the Pod to be scheduled; when the cluster resources are met, calculating the similarity of the Pod according to a first rule, and searching a first Node for scheduling; when cluster resources are not satisfied, carrying gout preemption scheduling, setting first rule calculation similarity and second rule priority preemption rules, and searching Nodes for preemption scheduling; and setting the maximum cycle index for the Pod which cannot be scheduled, wherein the Pod is scheduled preferentially when the maximum cycle index is reached. The problems that the priority is set by neglecting the actual condition of cluster resources, the resources cannot be reasonably arranged in the preemption process, and scheduling cannot be completed all the time are solved. According to the invention, the task operation integrity and the load balance of the whole cluster are improved, generation of resource fragments is reduced, the scheduling timeliness is improved, and the resource scheduling efficiency in a cluster management system is enhanced.

The present application provides a resource scheduling method, a terminal device and a network side device. The method includes: the terminal device sends first user plane data to the network side device, and the first user plane data carries application state information of the terminal device; the application state information is used to characterize the application status of the terminal device Running state: the terminal device obtains from the network side device the time-frequency resources scheduled by the network side device for the terminal device according to the application state information. With the method of the present application, the application state information does not need to be transmitted across the RRC layer, which improves the resource scheduling efficiency of the network side device, and also does not require the development of the terminal operating system or the baseband chip in the terminal device and the network side device from the operating system to the RRC The version of the transmission channel or transmission interface of the layer reduces the development cost of the terminal equipment.

The invention discloses a service platform resource scheduling processing method and device. Wherein, the method includes: obtaining work index information of each resource in the service platform through a fault collection interface, and obtaining a resource fault set according to the work index information and preset health index information used to indicate whether a resource fails; Wherein, the resource failure set includes resources that have failed in the current cycle; a data flow table is obtained through a data switch, and the data flow table includes resources that were in a normal working state in the previous cycle; according to the resource failure set, the The above data flow table, as well as the preset scheduling rules, determine the resources that need to be isolated and / or restored in the current period. The device is used to perform the above method. The service platform resource scheduling processing method and device provided by the present invention avoid using faulty resources in the resource scheduling process, thereby improving the efficiency of resource scheduling.

The invention discloses a service platform resource scheduling processing method and a service platform resource scheduling processing device. The method comprises the steps of acquiring performance index information of each resource in a service platform via a fault collection interface, and acquiring a resource fault set according to the performance index information and preset health degree index information used for representing whether faults occur in the resources, wherein the resource fault set comprises the resources in which faults occur in a current period; acquiring a data flow table via a data switch, wherein the data flow table comprises resources in normal working conditions in the previous period; and determining the resources needing to be isolated and / or recovered in the previous period according to the resource fault set, the data flow table and a preset scheduling rule. The device is used for executing the abovementioned method. According to the service platform resource scheduling processing method and device provided by the invention, the faulted resources are prevented from being used in a resource scheduling process, and thus the resource scheduling efficiency is improved.

The invention provides a Kubernetes scheduling method, device and storage medium, which filters out Node nodes that do not meet the requirements according to a pre-selection algorithm; sets queues for each Node node according to resource types; assigns priorities to Pods to be scheduled; analyzes Pods to be scheduled Status; when the cluster resources are satisfied, the Pod calculates the similarity according to the first rule, and searches for the first Node node for scheduling; when the cluster resources are not satisfied, it enters preemptive scheduling, sets the first rule to calculate the similarity and the second rule priority preemption rule, and searches for The Node node performs preemptive scheduling; set the maximum number of cycles for Pods that cannot be scheduled, and when the maximum is reached, priority is given to scheduling. The invention solves the problem that the priority is set regardless of the actual situation of the cluster resources, the resources cannot be reasonably arranged during the preemption process, and the scheduling cannot be completed all the time. The invention improves the integrity of task operation and the load balance of the entire cluster, reduces the generation of resource fragments, improves the timeliness of scheduling, and enhances the efficiency of resource scheduling in the cluster management system.

The invention discloses a multi-user multiple input multiple output (MU-MIMO) based stream distribution proportional fairness scheduling method, mainly solving the problem of proportional fairness scheduling ignoring user service quality in the prior art. The method comprises a first step of setting corresponding parameters according to a practical scheduling problem; a second step of computing a user weight in a utility function according to the fact that an emission probability meets mean values in normal distribution; a third step of generating sample values of the emission probability and computing a utility function value of a sample according to the user weight; a fourth step of screening out sample values with good performance so as to update the mean values in normal distribution; a fifth step of recording the change condition of the mean values and switching variances of different phases according to a corresponding rule; and a sixth step of ending an iterative process according to a termination condition, so as to obtain a scheduling result meeting proportional fairness. A satisfactory scheduling result can be obtained whether under the condition of sufficient available wireless resource or under the condition of insufficient available wireless resource, the computation complexity is low, the iterations are few, the scheduling efficiency of a base station is improved, and the method is applicable to a single base station system adopting an MIMO technology.

The embodiment of the present invention discloses a scheduling request transmission control method and related products, including: the terminal obtains the reference information of the first parameter that needs to be indicated to the network side device, and the first parameter is a parameter associated with the cached data to be transmitted of the terminal ; The terminal queries the mapping relationship between the preset information of the first parameter and the information of the second parameter of the physical uplink control channel PUCCH resource, and obtains the reference information of the second parameter of the PUCCH resource corresponding to the reference information of the first parameter. The second parameter is a parameter associated with the PUCCH resource used to transmit the SR; the terminal transmits the scheduling request SR used for scheduling buffered data on the PUCCH resource determined by the reference information of the second parameter. The embodiments are beneficial to improving the flexibility of transmitting and calling requests in the wireless communication system, and improving the resource scheduling efficiency of the data transmission channel in the wireless communication system.