16 results about "Cyclic scheduling" patented technology

According to the tray cycle scheduling system and the application method, historical data and a production plan are fused, an improved algorithm is adopted to predict tray requirements, and an attention mechanism is introduced to improve precision; the method comprises the following steps: acquiring multi-dimensional state information of a tray through a multi-modal sensor, eliminating noise by using a data fusion algorithm, and constructing a digital twin model to realize state synchronization; a double-layer optimization architecture is constructed, an upper layer solves a global scheme by combining an improved particle swarm and a simulated annealing algorithm, and a lower layer dynamically adjusts a path through reinforcement learning; an instruction is generated based on a digital twin model, an event triggering mechanism is adopted to reduce communication load, and virtual-real interaction closed-loop control is realized; a real-time evaluation index system is established, a meta-learning algorithm is utilized to quickly adapt to a new environment, and system parameters are continuously optimized. Multi-module collaborative innovation is achieved, the tray scheduling efficiency and the intelligent level are remarkably improved, production logistics whole-process collaborative optimization is achieved, and core support is provided for cost reduction and efficiency improvement of enterprises.

The invention discloses a cyclic resource scheduling method, system and device based on Kubernetes and a medium, and the method specifically comprises the steps: collecting resource use data of Pod and nodes in a Kubernetes cluster in real time, and predicting a load trend; dividing the resources into a hot resource pool, a cold resource pool and an idle resource pool based on the prediction results of the resource use data and the load trend; according to the electricity price and carbon emission data of each region, dynamically adjusting task distribution, and preferentially scheduling the task of the thermal resource pool to a region with a high renewable energy source proportion; for the cold resource pool and the idle resource pool, executing a progressive dormancy process by monitoring the power consumption change in real time; and training a reinforcement learning scheduling strategy by taking the queue length of the hot resource pool, the recovery time of the cold resource pool and the calling frequency of the idle resource pool as input. According to the invention, intelligent cyclic scheduling of Kubernetes cluster resources is realized, the resource utilization rate is improved, the energy consumption cost is reduced, the service continuity is guaranteed, and the intelligent level of scheduling decision is improved.

Deterministic flow transmission methods and systems, and electronic devices are provided by the present application. In embodiments of the present application, the first service packet sent by the first transmission node within a certain scheduling cycle is specified to enter a certain cyclic scheduling queue of the second transmission node (that is, the specified cyclic scheduling queue), so as to ensure that the first service packet is scheduled and forwarded on time by the second transmission node. As such, even if there is jitter on the transmission link between the first transmission node and the second transmission node, due to both a scheduling cycle for the first transmission node to schedule and transmit the first service packet and a scheduling cycle for the second transmission node to schedule and transmit the first service packet can be directly determined, it can be ensured that the above-mentioned jitter has no influence on deterministic parameters of the first service packet (which is equivalent to de-jittering the above-mentioned jitter), and a deterministic flow transmission for the first service packet is realized.

The application discloses a loop scheduling method in the form of a dynamic task chain, relates to the technical field of dynamic task scheduling of a heterogeneous multi-core computing system, and is suitable for dynamic task scheduling of a heterogeneous multi-core computing system based on a coarse-grained reconfigurable architecture and oriented to dense computing applications. The loop body task is regarded as a whole, and a unified priority is given. In the first round of executing the loop task, the loop body task is sequentially scheduled and the loop task scheduling result is recorded to generate a dynamic task chain. In the loop after the first round, the dynamic task chain is used for scheduling. In the subsequent loop execution process, only the input and output of the dynamic task chain are scheduled, and secondary scheduling in the loop body is avoided. The loop scheduling method in the technical scheme of the application is specially used for scheduling in the second round and the subsequent rounds of the loop body task, solves the defect that the original dynamic scheduling method does not support loop task scheduling, and effectively avoids scheduling bottlenecks caused by repeated scheduling of the same structure task.

The invention relates to the technical field of metal rolling linear control, in particular to a linear repetition process sliding mode control method and system based on event triggering. According to the control method, a linear repetitive process model, a cyclic scheduling mechanism, a dynamic event triggering mechanism and a sliding mode control strategy are combined, so that the problem that stability, real-time performance and energy consumption are difficult to consider under the scenes of strong channel coupling, large mismatching disturbance, high communication load, internal and external dual-dimensional dynamic coupling of the channel and the like in a traditional control method is solved; and the stability, the control precision and the communication efficiency of the repeated industrial process in a complex environment are improved.

The application relates to the technical field of construction ship scheduling management, and discloses a construction ship scheduling management method under multi-section cross operation, which comprises the following steps: S1, acquiring real-time data of each section to construct a multi-dimensional feature vector containing time, resources, operation and risk; S2, establishing a dynamic coupling network model representing time-varying coupling relationship based on the vector; S3, adaptively adjusting the task scheduling priority according to the global state change of the network; S4, using a leader-follower game optimization method combining the network model and the priority to solve the scheduling strategy in a rolling window; and S5, outputting an execution strategy and performing cyclic scheduling through a sliding time window until the task is completed. Through the dynamic coupling network model and the game optimization method combined with the dynamic priority, the application can resolve conflicts among multiple parties and improve the global coordination and dynamic adaptability of ship scheduling under a complex cross-operation environment.

The invention relates to the technical field of water conservancy and hydropower engineering, discloses a method and a system for real-time scheduling of earthwork in a construction period based on rule coupling, and aims to solve the problem that an existing earthwork balancing method has a weak practical guiding effect on a construction process. And real-time state information of each link is collected in real time, and according to the global dispatching matching matrix and a preset earth-rock dispatching macroscopic rule, multi-stage material source distribution taking direct dam-climbing priority and cost optimization as principles and transport vehicle assignment taking vehicle utilization rate balance as a target are dynamically executed. According to the method, static planning and dynamic response are combined, real-time and intelligent earthwork scheduling is realized, the direct dam climbing rate and the transportation resource utilization efficiency are effectively improved, and the comprehensive construction cost is reduced.

Methods of data processing and data processing apparatuses are disclosed. When performing data processing operations in response to program instructions, a scheduler is operated to support cooperative scheduling of multiple processes with reference to a circular scheduler queue comprising one or more queue elements. Each process of the multiple processes, when active as a currently executing process, is arranged to yield execution at a yield instruction to allow a next process of the multiple processes to continue execution. When the currently executing process yields, the scheduler initiates execution of the next process by reading context data for the next process from a queue element pointed to by a schedule pointer and writes the context data for the currently executing process to the same queue element, before advancing the schedule pointer. Lightweight cooperative scheduling is thereby supported.

The invention relates to a sparse convolutional neural network accelerator, a data processing method and a medium. The accelerator architecture comprises a convolution accelerator module, a weight compression module, a computing unit array and a load balancing module. A compression weight vector and a weight mask are generated through a weight compression technology, so that the data storage and transmission quantity is remarkably reduced; a dynamic skipping mechanism based on mask and zero value detection is introduced into a calculation unit, and invalid calculation is effectively eliminated; and a weight weighted polling and characteristic value cyclic scheduling dual load balancing strategy is adopted, so that load balancing of each unit of the calculation array is ensured, and the hardware utilization rate is greatly improved. The sparse convolutional neural network accelerator provided by the invention supports efficient sparse convolutional calculation, reduces the calculation amount of the convolutional neural network, is suitable for edge calculation, automatic driving and other scenes, the actual measurement shows that the utilization rate of a calculation unit can reach 92%, the performance is improved by 2.78 times compared with that of a traditional scheme, and meanwhile, the power consumption and storage bandwidth requirements are remarkably reduced.

The invention provides a DAG (Directed Acyclic Graph) task scheduling control method based on neural network scoring, which belongs to the technical field of task scheduling control and comprises the following steps of: 1, constructing a DAG task dependency graph according to tasks and dependency relationships thereof; 2, extracting multi-dimensional task features from the DAG task dependency graph and system historical data; 3, inputting core task characteristics, and outputting task scheduling priority scores; 4, performing resource availability judgment on the task; step 5, dynamically adjusting the maximum degree of parallelism of the task; step 6, when the scheduling task is executed, performing task execution monitoring and state updating at the same time; and 7, cyclically scheduling and repeatedly executing the processes from the step 2 to the step 6 until all tasks in the DAG task dependency graph are completed. By constructing a multi-dimensional task feature system, designing a hybrid neural network scoring model and dynamically optimizing a scheduling strategy and the degree of parallelism, efficient, intelligent and adaptive task scheduling oriented to a complex distributed environment is realized.

The application discloses a secondary radar S mode time slot rearrangement adaptive scheduling method based on detection efficiency improvement, which comprises the following steps: a PPC carries out comprehensive time slot planning for S mode target captured in each cycle to make S mode roll call inquiry, establishes an S mode inquiry demand chain table in units of sectors, and sends the S mode inquiry demand chain table to an FPGA in units of sectors at the starting moment of each cycle, so that the FPGA establishes an initial cache area to store the S mode inquiry demand chain table; S mode inquiry demand information in the S mode inquiry demand chain table comprises S mode inquiry data, an S mode address, a BDS code number and a target predicted distance; at the starting moment of each sector or the starting moment of inquiry chain table cyclic scheduling in the sector, the data of the sector in the initial cache area is subjected to deduplication processing, and the FPGA is used to remove the matched inquiry time slot and rearrange the time sequence of the inquiry chain table of the current sector in real time. The application improves inquiry time slot use and target detection efficiency, and reduces spatial domain same frequency band radiation interference.

This invention belongs to the field of mobile communication technology and discloses a service flow scheduling method for high-speed rail millimeter-wave communication scenarios assisted by unmanned aerial vehicles (UAVs). By configuring system parameters such as node location and link parameters, it acquires information such as mobile relay location, candidate link status, and service requirements in real time. It calculates the propagation distance based on the node and mobile relay locations, and uses link parameters to obtain the average load per time slot within a frame. Then, it calculates the minimum number of time slots required for each mobile relay to complete the service through candidate links. Links exceeding the remaining budget of the resource pool are then eliminated to form a feasible candidate set. This scheme can accurately select effective links, avoid resource conflicts and underutilization, and ensure reasonable resource allocation. Based on a scoring system, it selects the optimal link and dynamically updates the candidate set, taking into account both service priority and starvation status. This avoids the problem of high-priority services being squeezed out and weak link services being starved. Furthermore, frame-level cyclic scheduling reduces algorithm complexity and meets the real-time scheduling requirements of high-speed rail scenarios.

The invention discloses a batch job scheduling method, device and equipment, a medium and a program product. The method comprises the following steps: dividing a target task into M jobs to be scheduled according to a task granularity division rule; taking the M jobs to be scheduled as current alternative jobs to be scheduled; extracting a to-be-scheduled job meeting a scheduling condition from the current alternative to-be-scheduled jobs as a current target to-be-scheduled job according to a dependency relationship between the current alternative to-be-scheduled jobs; performing batch scheduling on the current target to-be-scheduled job through a distributed batch framework; and if the M to-be-scheduled jobs are not completely scheduled, taking the remaining to-be-scheduled jobs in the M to-be-scheduled jobs as current alternative to-be-scheduled jobs, and repeating the operation until the M to-be-scheduled jobs are completely scheduled. Through reasonable task granularity division, accurate dependency relationship processing and an efficient cycle scheduling mechanism, the problems of scheduling delay, blocking, dependency conflicts and the like in an existing batch job scheduling scheme are solved.

The invention provides a directional fuzzy testing method and system based on interpretable artificial intelligence association variation and exploration and development of double-queue circular scheduling. The objective of the invention is to solve the problems of low test efficiency, difficulty in vulnerability triggering and the like caused by lack of relevance between a sample and a target code, imbalance in exploration and development, insufficient model interpretability and lack of a man-machine cooperation mechanism in the existing directional fuzzy test technology. By introducing an interpretable artificial intelligence (XAI) technology, explicit association between an input byte and a target code is established, and a protected sample mask is generated to guide accurate variation; designing a double-queue dynamic scheduling algorithm, and adaptively balancing resource allocation of path exploration and target area test; according to the method, a real-time visual interface is combined, expert experience is fused into an automatic testing process (namely, a tester can adjust a sample mask in real time), finally, efficient detection and accurate triggering of deep vulnerabilities in complex software are achieved, and meanwhile resource consumption of invalid testing is reduced.

The application discloses a two-stage scheduling model and a scheduling method based on a heterogeneous multi-core processor, and relates to the technical field of computer science.The model comprises an associated subtask acquisition module, a container allocation analysis module, a static priority configuration module, a container scheduling structure generation module, a window allocation execution module and a task cross-container dependency processing module.The associated subtask acquisition module is used for analyzing a target task and generating a plurality of associated subtasks.The container allocation analysis module performs first-stage scheduling and allocates the subtasks to K task containers.The static priority configuration module performs second-stage scheduling on the subtasks according to a dependency relationship and generates a processing priority sequence.The container scheduling structure generation module creates a container scheduling structure.The window allocation execution module forms a cyclic scheduling subsequence.The task cross-container dependency processing module performs cross-container dependency management in a task execution process, thereby ensuring scheduling continuity and dependency relationship execution.The application solves the technical problems of low scheduling efficiency and unstable task execution in the existing heterogeneous multi-core processor, and achieves the technical effects of improving task scheduling efficiency and task execution stability.