1120results about How to "Improve scheduling efficiency" patented technology

The invention discloses a virtualized resource scheduling method and a system. A request from an external management user is received, or a scheduling request is triggered according to a preset strategy; according to the resource requirement information of a virtual machine and a physical server in the current system, a virtualized resource scheduling scheme is calculated and obtained; according to physical server resource flowing information contained in the received resource scheduling scheme, the resource of the relevant physical server is scheduled; according to the volume information contained in the virtualized resource scheduling scheme, the resource channel of the volume is built with the corresponding physical server; and scheduling resource is obtained from a mapping physical server to provide scheduled virtual resource for an external business entity. According to the virtualized resource scheduling method and the system, the resource scheduling efficiency can be improved, and the resource can be optimally scheduled in the whole situation.

This invention aims at conducting a scheduling work of print processing efficiently. A device scheduler refers to print job composition information registered in step control information of the step “printer reservation” of other print job (other order) in a workflow information table, and a schedule information table. The device scheduler searches both other print jobs (proof print jobs and regular print jobs) that a to-be-registered proof print job having a processing time of the proof print job described above affects and other print jobs (proof print jobs and regular print jobs) that affect the to-be-registered proof print job. The device scheduler determines whether the to-be-registered proof print job can be registered in a schedule (there is no search result in Step 2017 described above). When the registration is not possible, the device scheduler informs an operator of the result that automatic scheduling is impossible.

The invention discloses an intelligent warehousing route planning method and system based on multiple AGVs. The method comprises the following steps: S100, defining a task distribution rule; dividing the priorities when the storage tasks are generated; S200, adjusting the dynamic priority; carrying out dynamic priority adjustment on the task of the AGV load in transportation; S300, planning an optimal path: dynamically and accurately calculating and locking a time window to reset a path so as to avoid conflicts, respectively carrying out coping strategy research on predictable vertical meeting conflicts and opposite meeting conflicts, and finally finding out a conflict-free shortest path; s400, predictively avoiding a conflict strategy; carrying out traffic rule making and unpredictable conflict detection and processing on traffic problems which may be encountered by a plurality of AGVs in the transportation process of a storage workshop. According to the system, the time cost of warehousing workshop tasks is reduced to the minimum, it is guaranteed that the path cost of the AGV is the minimum under the condition that vehicles are free of collision, and meanwhile the task scheduling efficiency and the vehicle scheduling efficiency are improved.

There is provided a method and system for scheduling a job in a cluster, the cluster comprises multiple computing nodes, and the method comprises: defining rules for constructing virtual sub-clusters of the multiple computing nodes; constructing the multiple nodes in the cluster into multiple virtual sub-clusters based on the rules, wherein one computing node can only be included in one virtual sub-cluster; dispatching a received job to a selected virtual sub-cluster; and scheduling at least one computing node for the dispatched job in the selected virtual sub-cluster. Further, the job is dispatched to the selected virtual sub-cluster based on characteristics of the job and/or characteristics of virtual sub-clusters. The present invention can increase the throughput of scheduling effectively.

The invention relates to a self-adaptive multilevel cache system for three-dimensional spatial data based on a data content, the multilevel cache for the three-dimensional spatial data of the system adopts the design idea of a buffer pool, and the three-dimensional spatial data is classified and managed in separate pools when in cache by a three-dimensional spatial data classification method based on the data content; wherein the cache comprises a three-dimensional spatial data drawing cache (first-level cache) located at a client, a three-dimensional spatial data memory cache (second-level cache), a three-dimensional spatial data file cache (third-level cache) and a three-dimensional spatial data engine service cache (fourth-level cache) located at a database server end. The four level caches are respectively controlled by individual cache management modules, a centralized management to the multilevel caches at the client and the database server end is performed by the self-adaptive multilevel cache management modules, and a self-adaptive adjustment of each cache is realized. The self-adaptive multilevel cache system improves the large-scale dynamic dispatching efficiency of the three-dimensional spatial data, and provides an effective solution to the three-dimensional real-time visualization.

The invention relates to a resource scheduling method based on kubernetes. The method comprises steps of calculating all Node scores in the cluster according to a fixed rule to generate a first node priority queue, and obtaining a Pod priority queue by using a dynamic priority algorithm, wherein the two queues filter Node which cannot be scheduled to generate a second node priority queue; selecting the node with the highest priority from the Pod priority queues to bind with the Pod popped by the Pod priority queues; and if the binding succeeds, entering the next Pod scheduling cycle, if the binding fails, adopting a built-in priority algorithm to optimize Node binding from the second node priority queue, and if the binding fails again, enabling the Pod to run without an appropriate Node, and entering the next Pod scheduling cycle. The method comprises the steps of static scheduling and dynamic resource load balancing, scheduling efficiency is improved, task deployment efficiency is improved, task operation integrity and load balance of the whole cluster are improved, load balance of the cluster is actively adjusted, and resource utilization efficiency of the cluster is improved.

The present invention relates to an AGV avoidance scheduling control method, a device and a system. The method comprises the steps of planning a current task walking path of a current AGV; detecting whether a collision point exists on the current task walking path or not; if yes, turning to an avoidance judging step; otherwise, planning a current executing path and turning to a task execution step; finding out a farthest non-conflict point as the current executing path, and turning to the task execution step upon detecting that the current executing path is not empty; judging whether a conflict AGV is an idle AGV or not upon detecting that the current executing path is empty; if yes, planning an avoidance task for the conflict AGV; otherwise, turning to a conflict point detection step after waiting for a preset period of time; controlling the current AGV to proceed and execute a task, and judging whether a remaining path exists in the current task or not after the completion of the current executing path; if yes, turning to the conflict point detection step; otherwise, switching the current AGV to be in the idle state. According to the technical scheme of the invention, an avoidance path is selected and planned for an idle AGV on the path, so that the operation efficiency of the AGV is ensured.

The invention provides a method for high-efficiency task scheduling of a heterogeneous multi-core processor. The method comprises the following steps of: clustering certain special tasks which are large in communication overhead and easy to cluster in a task image to a precursor node of the tasks by adopting a linear task clustering method; starting from a topological structure of the whole task image, selecting parameters capable of comprehensively reflecting the importance of the task in the whole task image as priority weights; selecting a free critical path node to perform allocation first, and if multiple free critical path nodes exist, allocating the free critical path nodes in a sequence from high to low according to the node priority weights, and allocating all non-critical path free nodes in a sequence from high to low according to the priority weights; performing redundancy judgment, and deleting redundant tasks in a scheduling result; and performing adjustment according to the scheduling result after deleting the redundant tasks, and recalculating the earliest finish time of each task. According to the method, the efficiency of the task scheduling of the heterogeneous multi-core processor is improved, the power consumption of the processor is reduced, and the performance of the multi-core processor is promoted.

The invention provides a dispatching method of a virtual machine under a multi-core environment. The dispatching method divides zones for CUP resources according to dispatching strategy types when a system is started, monitors the CPU loading condition of all divided zones in real time when the system operates, and dynamically adjusts the size of the CPU resources in the divided zones. The dispatching method carries out dispatching in the same divided zone by using the same dispatching strategy, thus improving dispatching efficiency, achieving the purpose of resource loading balance by dynamically adjusting the size of the CPU resources of the divided zone, realizing the full utilization of resources and reducing waste of resources.

The invention relates to an intelligent group call answer taxi appointment method which comprises the steps that a taxi appointment platform receives a taxi appointment request sent by a mobile terminal, including a number and position information of the mobile terminal; the number of the mobile terminal is cached; periphery parameters are determined according to a geographic environment corresponding to the position information; no-load taxies are looked up according to the periphery parameters; position information of the no-load taxies and the position information of the mobile terminal are subjected to time consuming analysis; sequencing is conducted according to the consumed time; the priority level is determined; the no-load taxi to be called is determined; a group call answer flow is started; taxi appointment demand information is informed to the no-load taxi answering successfully; and relevant information of the no-load taxi answering successfully is sent to the mobile terminal. The invention further relates to the taxi appointment platform and an intelligent group call answer taxi appointment system. According to the method, the taxi appointment platform, and the system, a direct, efficient and practical information communication channel and an interactive mode are established between the taxies and a passenger, so that the circulation process of carrying the passenger for the taxi is accelerated, and the dispatching efficiency is improved.

The invention provides a deep Q network based regional power-grid operation point dispatching optimization method. The method comprises the steps that a dispatching configuration of a regional power-grid operation point dispatching center is determined; a dynamic decision process for dispatching operation points of regional power grid is modeled into a corresponding Markov decision process model which comprises state, action, cost and optimization target function; the deep Q network is used to carry out strategy resolution on the Markov dynamic decision process; the operation point of the regional power grid comprises a routine thermal power set output of a next dispatching period, thermal power set output and the flexible load reduction amount; and dispatching of the operation point of the region power grid comprises, at least, that the power grid operation point in the next dispatching period is determined dynamically according to wind power and load power short-term prediction information and operation point information in the present period. Thus, effective response to randomness of the new energy output and load demands can be made, source-load interactive dispatching potential gives a full play, dynamic balance of the power of the regional power grid is maintained, and the operation efficiency of the power grid system is improved.

The invention discloses a kernel virtual machine scheduling policy-based implementation method. The method comprises two major steps of: 1, dividing Linux processes into a common process, a virtual machine process and a real-time process, making the priority of the virtual machine process between those of the common process and the real-time process, and providing a special scheduling algorithm for the virtual machine process; and 2, dividing virtual machines into a compute-intensive virtual machine and an I/O-intensive virtual machine according to demands of services in the virtual machines, and dynamically adjusting resources of each virtual machine to make the virtual machines better adaptive to the demands of the services in a client operating system. Due to the method, a kernel virtual machine has the priority to be scheduled during the scheduling process, each virtual machine can be fairly treated among a plurality of virtual machines, the resources of the virtual machines can be dynamically adjusted according to the service demands in the virtual machines, and the scheduling requirement of the kernel virtual machine is perfectly met. The method has a practical value and a wide application prospect in the technical field of computer virtual machine schedulers.

The invention discloses a channel state information (CSI) reporting method and a device thereof. The CSI reporting method comprises the steps of determining a CSI reference resource according to one piece of information selected from the information of a preset number of repetition times, a frequency hopping pattern, downlink control information (DCI) and a random access response (RAR), wherein the CSI reference resource comprises a CSI frequency domain reference resource and a CSI time domain reference resource; and reporting the CSI which corresponds with the preset number of repetition times by the UE. Through the channel state information reporting method and the device thereof, more useful reference information can be supplied for base station scheduling in reporting the CSI by the UE, thereby improving scheduling efficiency of the base station.

The invention discloses a scheduling method and device. The scheduling method comprises the following steps of: selecting a first register with a first value from a high-priority group of a register group, wherein the first register corresponds to a first to-be-processed event; and scheduling a first thread corresponding to the first register to process the first to-be-processed event. The scheduling device comprises a command queue, a micro instruction memory, a micro instruction execution unit, the register group, a scheduler and an NVM medium interface, wherein the register group is used for indicating to-be-processed events and priorities of the to-be-processed events; the scheduler is used for scheduling threads according to registers in the register group; and the micro instruction execution unit is used for receiving the indication of the scheduler and executing the scheduled threads.

The invention relates to an MPSoC (multi-processor system-on-chip)-oriented multithread scheduling method, which has the technical scheme comprising the following steps of: dividing a plurality of processor cores on the MPSoC into processor core sets according to a physical position relationship, and dividing adjacent processor cores into the same processor core set; dividing the threads in the same process into a same thread set; scheduling the thread set according to a configuration table of the processor core set; in the same processor core set, scheduling the threads by utilizing a time-share scheduling or rotating scheduling algorithm; and finally, optimizing the thread scheduling, namely moving the threads in the same process from the busy processor core set to the idle processor core set, wherein the number Mi of the moved threads is equal to the number Cs of the processor cores in the idle processor core set. According to the method, a plurality of threads are divided into different thread sets and the thread sets are scheduled on the core sets, thereby lowering the communication cost among the threads and increasing the scheduling efficiency.

A job shop operation planning and rescheduling method for complex aeronautical equipment structures is disclosed. an operational workshop planning model for aerospace complex equipment structural components is constructured with the equipment equalization rate and on-time delivery rate as objective functions. The model solving method is designed based on multi-layer coding genetic algorithm. Considering the application scenarios of for both the capacity surplus and the insufficient capacity, the plan-making and the rescheduling algorithm flow is designed. The rescheduling algorithm can identify the task being produced and the task of not starting production, and judge the allowable start time of the machine, the allowable start time of the next process of the workpiece, etc. according to the completion time of the process being processed, and reshcheduing is performed while the remaining workpieces meet the target the constraint. The method of the invention is suitable for most discrete enterprises with multi-variety and small batch production, and has good adaptability and versatility.

The invention discloses a method for transmitting control information, user equipment and a base station. The method comprises the following steps of: acquiring a transmission mode of a data channel configured by the base station; determining a downlink control information DCI format set corresponding to the transmission mode, wherein the DCI format set comprises a first DCI format, and the first DCI format comprises single code word control information; and detecting a control signaling which is sent by the base station and corresponds to the DCI format set according to the DCI format set. The user equipment comprises a first acquisition module, a first determination module and a detection module. The base station comprises a configuration module, a first determination module and a first sending module. By the method for transmitting the control information, the user equipment and the base station, the transmission mode of the data channel at least corresponds to two transmission modes, so that the control channel can be enhanced, the expense of the control channel is reduced, and the system scheduling efficiency and flexibility are improved; and moreover, the problem of blocking of the control channel can be solved, and the utilization rate of control channel resources of a system can be increased.

The invention discloses a large-scale operation workshop scheduling method based on bottleneck equipment decomposition. The large-scale operation workshop scheduling method based on the bottleneck equipment decomposition comprises the following steps of (1) acquiring data and modeling; (2) carrying out recognition on bottleneck equipment based on a key path method; (3) sorting and encoding the bottleneck equipment and non-bottleneck equipment; (4) generating an initial chromosome population; (5) carrying out cross and mutation operations on the chromosome population; (6) inoculating an immune operator to the chromosome population; (7) carrying out decoding and fitness value calculation operations on chromosomes; (8) updating an optimal chromosome and an optimal fitness value of an algorithm; (9) judging whether a method ending rule is achieved or not, starting a step (10) if the method ending rule is achieved, and otherwise, jumping to the step (5) to carry out the next iteration; (10) finding out the optimal chromosome from the step (9) to decode, and obtaining a scheduling command to schedule. According to the large-scale operation workshop scheduling method based on the bottleneck equipment decomposition, which is disclosed by the invention, a satisfactory scheduling scheme can be obtained in a shorter time, the production efficiency of an operation workshop can be improved, and the large-scale operation workshop scheduling method based on the bottleneck equipment decomposition can be applied to scheduling management and optimization of the production process of the workshop.

The invention provides a method for managing and dispatching cloud resources, which comprises the following steps: dividing a value range of each attribute of the resource into a plurality of attribute areas, distributing corresponding logic area index number to each attribute area, mapping each resource to a united area index determined by the logic area index number attributed to each attribute value of the resource, when receiving a resource request of a user, determining the logic area index number of the restrict upper limit and the restrict lower limit of each attribute of the requested resource, gaining a plurality of united area indexes satisfying the resource request, then selecting one united area index from the united area indexes, selecting one resource from a logic resource pool corresponding to the selected united area index, and providing the resource to the user. The method can satisfy the requirements of the user resource request with high concurrence degree and the resource renovation with high frequency in the cloud computing environment.

The invention discloses a dynamic data scheduling method in a multi-path transmission control protocol (MPTCP), comprising the following steps: the round-trip time RTT and the round-trip time variation RTTVAR of each path are measured; whether each path is available is judged according to the RTT and RTTVAR, the congested paths are abandoned, and the available paths are retained; the data transmission capacity of each path is estimated; and a data transmission quota is allocated for each path based on the estimated data transmission capacity and the current sending window, and a scheduler allocates transmission data according to the transmission quota. According to the scheme, the essence of a TCP Vegas algorithm is absorbed on the basis of Lowest_RTT, and improvement is made on the basis, which is equivalent to adding a congestion avoidance control function to the scheduler. The method has far-reaching significance to avoiding path congestion and enhancing the overall transmission capacity of the paths.

The invention discloses a business scheduling method and device, and fusion equipment. The business scheduling method and device are applied to the fuse equipment including a CDN (content distribution network) business unit for providing content distribution service and a network business unit for providing network access and bearer service, wherein the CDN business unit comprises a business processor and an internal storage device; the CDN business unit is connected with the external storage device; the resource of the business processor and the storage resource in the CDN business unit are divided into a plurality of business service unit groups, and the resource of the business processor, and the storage resource in the internal storage device or the external storage device are distributed for each business service unit group; and the CDN business unit schedules an application access request of a user to one business service unit group according to the attribute of the user, the accessed content, the application type or a source IP (internet protocol) address and/or port number when receiving the application access request of the user. According to the method and device disclosed by the invention, the fuse equipment can integrate the internal and external storage resources and the business processing capability, and uniformly schedules and processes the application of the user.

The invention discloses a public bicycle dynamic scheduling method based on site short-term demand prediction. The method comprises the steps of collecting a site free pile number time sequence, constructing a neural network model to predict the short-term demand of each site, calculating the scheduling time window and demand on the basis, constructing a dynamic scheduling model minimizing the cost of scheduling and maximizing satisfaction, solving a scheduling scheme, and adjusting the scheduling plan through information updating. By combining site short-term demand prediction and dynamic scheduling, the efficiency and accuracy of public bicycle scheduling are ensured, the service level of public bicycles is improved, and public bicycles are made more attractive.

The invention discloses a photovoltaic power generation prediction system based on a T-S-type fuzzy neural network. The photovoltaic power generation prediction system comprises a fuzzy neural network structure module, a fuzzy neural network training module and a fuzzy neural network prediction module. According to the photovoltaic power generation prediction system based on the T-S-type fuzzy neural network, prediction of solar photovoltaic power generation capacity is achieved, dynamic integration of a fuzzy inference system and a neural network learning system is achieved, algorithms are advanced, prediction accuracy is high, power grid dispatching efficiency is improved, safe operation of a power grid is guaranteed, meteorological factors are introduced, prediction accuracy and reliability are improved, technical support is provided for large-scale grid connection of solar photovoltaic power generation, transportability is high, simple modifications are only needed, and the power generation prediction system can also be provided for wind energy source and other new energy sources.

A computer implemented method and system for scheduling, the method comprises: initializing the scheduling configuration information according to the configuration instruction received by a receiving device, wherein the scheduling configuration information includes scheduling time bucket, shift, scheduling personnel and rest day type; solving the rest day set of each scheduling personnel in the scheduling time bucket according to the rest day type through a computing device, wherein the computing device performs the solving according to a preset first solving method; obtaining the working day set of each scheduling personnel through the computing device; and solving the shift of each scheduling personnel in his or her working day set according to the preset algorithm through the computing device. The automation of the scheduling method is implemented in the present application. The optimal scheduling results can be solved in the background automatically under the premise that the requirements of the scheduling configuration are met, and the solved scheduling results are sufficiently random, thus greatly reducing the complexity of scheduling and improving the efficiency of scheduling.

The invention discloses a method for configuring wireless parameters and transmitting signals and a device so as to solve the problem that a system has excessively high cost and expense caused by the fact that wireless parameter selection and signal transmitting methods are not suitable for wireless data transmission in application scenes of indoor areas and hot spot areas. According to the invention, a common LTE mobile communication system crystal oscillator principle is followed in subcarrier spacing selection. The subcarrier spacing is configured to be an integral multiple of LTE mobile communication system subcarrier spacing. Sampling frequency is an integral multiple of the LTE mobile communication system sampling frequency. FFT points are configured to be no less than the integer of a ratio of the sampling frequency to the subcarrier spacing. Therefore, FFT implementation cost is reduced, the system cost of covering the indoor areas and hot spots is greatly reduced, dispatching efficiency can be improved, the system expense is reduced, system throughput is improved and a demand of data traffic is met.