387 results about "Idle time" patented technology

The invention discloses a pipe production task management method and system, and belongs to the technical field of pipe production, and in the pipe production task management method and system, factors such as order priority, equipment state and raw material supply are analyzed through an intelligent algorithm, and the production schedule is automatically optimized, so that production resources are utilized more reasonably and efficiently. Resource waste can be avoided, idle time in the production process is shortened, and therefore production efficiency and the productivity utilization rate are improved. The urgency degree and the delivery date of the order are analyzed through an intelligent algorithm, and the enterprise can preferentially arrange the production of the urgent order to ensure that the customer demand is met in time. Meanwhile, production tasks are reasonably distributed according to the running state of the equipment and the raw material supply condition, and the use efficiency of the equipment and the utilization rate of raw materials are improved. The dynamic adjustment mechanism monitors the production progress in real time and automatically adjusts the production plan according to the actual situation, so that the system can rapidly adjust the production plan and distribute the tasks to other devices, and continuity and on-time delivery of the production tasks are ensured.

The invention discloses a block chain transaction parallel execution method based on pre-execution conflict detection, and belongs to the field of block chains. The method specifically comprises the steps that a node receives a transaction sent by a user, and a verification node carries out pre-execution operation on the received transaction in idle time waiting for proposal of a main node; judging whether the transaction packaged by the elected main node is a pre-execution transaction, and if so, generating a transaction conflict graph according to the read-write set of each transaction; an independent set is solved repeatedly, and the main node performs optimistic parallel execution to obtain a transaction dependency graph and packages the transaction dependency graph into a proposal block; otherwise, the main node performs optimistic parallel execution on the transactions which are not pre-executed, constructs a directed acyclic transaction dependency graph, and packages the directed acyclic transaction dependency graph to generate proposal blocks; and finally, each verification node sequentially executes corresponding transactions according to the transaction dependency graph and performs comparison verification on an execution result and an execution result of the main node, and when the results are consistent, the proposal block is successfully linked, and the consensus of the round is completed. The optimistic parallel execution efficiency is improved.

The invention provides a processing and assembling combined production workshop scheduling optimization method considering dynamic disturbance, and the method comprises the steps: building a combined scheduling model: dividing a product production process into a part processing process, an assembling process and an assembling subsequent process, defining the correlation constraint of processing and assembling, and carrying out the processing and assembling operation; comprising part machining sequence consistency, part machining completion requirements before assembly, buffer area capacity limitation and a dynamic disturbance event response mechanism; establishing a multi-objective optimization function: taking minimization of maximum completion time, equipment idle time, processing energy consumption cost and tool switching times as optimization objectives, and generating a scheduling model in combination with process time dependence, machine selection uniqueness and tool switching time constraint; dynamic disturbance processing: when an equipment fault occurs or a new order is inserted, updating an available machine state or combining tasks to be processed, and triggering rescheduling to generate a new scheme; an improved MOEA / D algorithm is used for solving; and outputting and applying a scheduling scheme: selecting a final scheme for production guidance according to the non-dominated solution set.

The invention relates to the technical field of production management, in particular to a production scheduling optimization system based on data analysis, which comprises a process data trend analysis module, a station resource real-time acquisition module, a scheduling sequence optimization judgment module, a rhythm coordination check module and a scheduling dynamic optimization module. According to the method, the process duration trend is analyzed in real time, continuous growth is accurately recognized, rhythm parameters are dynamically corrected, the stable process rhythm is ensured, efficient resource connection is achieved based on the station task completion time and the matching task and station idle starting time, the task sequence is dynamically adjusted according to the station idle state, and task connection is optimized; the beat proportion of adjacent tasks is verified, the task interval is adjusted, the beat difference is controlled within a reasonable range, beat sudden change is prevented from interfering with production, the rapid response ability to production changes is integrally enhanced, task and resource collaborative optimization is achieved, the overall scheduling efficiency and beat consistency are improved, and the production continuity and the resource utilization rate are improved.

A system can monitor a containerized function for a number of iterations of the containerized function. The system can, for the respective iterations, determine respective upper limits of amounts of time for which the containerized function is idle, and determine respective numbers of cold starts of the containerized function. The system can determine whether a percentage of the respective iterations, for which corresponding upper limits, of the respective upper limits, on amount of time for which the containerized function is idle, is below a threshold idleness value, and for which corresponding numbers of cold starts, of the respective numbers of cold starts, are above a threshold cold start value. The system can, in response to determining that the percentage of the respective iterations is above a threshold successful probes value, deploy a microservice that is configured to execute the function.

The invention provides a measurement and control task scheduling method based on an equipment idle time period. The measurement and control task scheduling method comprises the following steps: S1, acquiring a task demand, a resource scheduling scheme and forecast data; s2, extracting demand information of each task demand, screening according to the demand information to obtain consistent forecast data, and generating an equipment selectable task segmental arc matrix; s3, extracting an idle time period of each antenna device to construct a task scheduling plan matrix; s4, according to the idle time period of each antenna device and the demand information of each task demand, re-planning selectable task arc segments in the device selectable task arc segment matrix and recording the re-planned selectable task arc segments into a task scheduling plan matrix; and S5, controlling each antenna device to execute a measurement and control task and / or a data transmission task on each satellite, and analyzing to obtain a measurement and control task satisfaction degree and a data transmission task satisfaction degree. The method has the beneficial effects that the idle time period of the antenna equipment can be effectively utilized for task replanning, and the equipment utilization rate and the task completion rate are improved.

The invention belongs to the technical field of firmware upgrading, and relates to a firmware upgrading method and device, an upper computer and a storage medium. The state of each lower computer is sensed in real time through the upper computer, and the idle lower computer is dynamically selected based on the equipment selection rule for upgrading operation, so that the idle time of the upper computer is fully utilized to distribute upgrading tasks to other lower computers in a staggered manner in a firmware upgrading process executed by the target lower computer, and parallel alternative upgrading operation among multiple equipment is realized. Besides, by receiving the upgrading feedback instruction returned by each lower computer and updating the equipment selection rule according to the upgrading feedback instruction, the upper computer can flexibly schedule the upgrading sequence, and the scheduling efficiency and the response flexibility of the upgrading process are improved. And meanwhile, through continuous iteration of the upgrading circulation process, it is ensured that each lower computer can receive the next round of upgrading data at a proper time, and the OTA upgrading efficiency and the system resource utilization rate of the multi-MCU equipment are remarkably improved.

The invention discloses a software upgrading control method and device supporting multiple platforms and an automobile. The method comprises the steps that a terminal periodically and automatically detects whether available systems or application programs are updated or not; when an available system or application program is detected to be updated, intelligently selecting a corresponding idle time and a spatial network mode to download an update package according to the network condition of the terminal and a preset user update downloading setting; when the update package is downloaded, automatically detecting and analyzing the use condition of the terminal, and judging whether the terminal is in an idle state or not; the specific platform type and the upgrading strategy of the terminal are analyzed, and an upgrading scheme of the terminal is automatically generated; and when detecting that the terminal is in an idle state, automatically installing and updating in a silent manner according to the generated upgrading scheme. The invention provides the method and the system capable of automatically detecting, downloading, installing and updating, and simultaneously supports a plurality of upgrading modes, so that the use experience of a user and the safety of equipment are improved, and convenience is provided for the use of the user.

The invention discloses an airport parking space distribution method, system and device and a medium, and relates to the technical field of parking space distribution, and the method comprises the steps: obtaining a plurality of parking spaces and flights of different airport models; the corresponding relation between the parking spaces and the flights is used as a decision variable, and the most balanced parking space idle time, the minimum passenger walking distance and the least far parking space distribution number are used as objective functions. Taking the maximum utilization rate of the large-scale gate position, the maximum overall utilization rate of the gate position, and the maximum gate position and flight matching rate as constraint conditions to construct a gate position distribution optimization model; an improved sparrow search algorithm is adopted to solve the gate position distribution optimization model, and a global optimal solution and the fitness of the global optimal solution are generated; and allocating the airport parking spaces according to the global optimal solution and the fitness thereof.

The invention relates to the technical field of material conveying, and discloses a steel plate welding automatic conveying device which comprises a welding table body, a welding mechanism and two feeding pieces, the welding mechanism is arranged on the welding table body to weld steel plates, the number of the feeding pieces is two, and the two feeding pieces conduct staggered feeding. The two feeding pieces are connected through a driving piece, a tool table for welding and positioning a steel plate is arranged on the feeding pieces, the at least two feeding pieces are arranged for staggered feeding, when one feeding piece conveys the steel plate to welding equipment for welding, the other feeding piece can place the steel plate needing to be welded in advance, and therefore the steel plate can be welded conveniently and rapidly. After one steel plate is welded by the welding equipment, the steel plate on the other feeding piece can be directly moved to the welding equipment for next welding, so that the idle time of the welding equipment is avoided, the continuous automatic welding of the steel plate is realized, and the welding efficiency is greatly improved.

The invention discloses a shaping scheduling method and device for vehicle-mounted mixed traffic, a storage medium and equipment, and the method comprises the steps: dividing different traffic into a first type of traffic, a second type of traffic and a third type of traffic according to the source and importance of a control domain of vehicle-mounted network traffic; dividing the first type of traffic into a plurality of priorities, and periodically scheduling the first type of traffic according to the sequence of the priorities from high to low and the gate control switch state information list; dividing the second type of traffic into a first sub-type of traffic and a second sub-type of traffic, and alternately scheduling the two sub-type of traffic according to a preset credit adjustment rule; sequentially scheduling the third-class traffic of different queues according to the sequence of queue generation, and when an idle time slot exists between the current traffic queue of the third-class traffic and the adjacent next traffic queue, scheduling the third-class traffic according to a preset scheduling rule. And reading traffic from a plurality of to-be-scheduled traffic queues adjacent to the current traffic queue, and filling the traffic into an idle time slot for scheduling.

The invention discloses a task processing method and device, electronic equipment and a storage medium. The method comprises the steps that a to-be-processed task and a node idle period are obtained, and the to-be-processed task carries task starting time and task allowed delay time; performing idle period matching on the to-be-processed task based on the task starting time, the task allowable delay time and the node idle period, and determining an idle period matching result of the to-be-processed task; when the idle period matching result is successful matching, acquiring an idle node corresponding to the node idle period, and determining a target node based on the idle node; and scheduling the to-be-processed task to the target node, and executing the to-be-processed task on the target node. According to the scheme, the node resources in the idle time period are determined for the to-be-processed task, the node processing task in the idle time period is fully utilized, independent application and resource occupation for the to-be-processed task are not needed, the task processing efficiency is improved, node resource waste is avoided, and the utilization rate of the node resources in the idle time period is improved.

The invention provides a large model training system based on CPU-GPU double optimizers and SSD unloading, and belongs to the technical field of computers. The system comprises a parameter division manager, a CPU optimizer state exchanger, a CPU optimizer, a GPU optimizer state exchanger and a GPU optimizer, large model parameters are divided into a plurality of subgroups through the parameter division manager, and the subgroups are further divided into a CPU updating part and a GPU updating part; a CPU and GPU double optimizer structure is introduced, a double-SSD architecture is adopted to design an independent data path, GPU-CPU collaborative updating is achieved, optimizer state transition between a GPU or a CPU and an SSD is managed, I / O conflicts are eliminated, the GPU idle time is shortened, the influence of SSD read-write high delay is relieved, load balancing is guaranteed, and the training throughput is improved.

The present invention discloses a method for allocating entry and departure routes and time slots for a take-off and landing field for unmanned aerial vehicles, including: establishing a library of alternative corridors for arrival and departure of unmanned aerial vehicles; calculating the standard available time series and the allocable time series of each parking space in the task declaration stage according to the time interval of the unmanned aerial vehicle occupying the parking space; receiving the unmanned aerial vehicle task information declared by the operating unit, judging whether the task information is a plan declaration, a take-off application or a landing application according to the information format and content; judging whether the take-off or landing time declared by the operating unit has an idle time slot and an idle parking space to provide guarantee allocation when the plan declaration, take-off application or landing application is made, and obtaining the entry and departure routes. The present invention utilizes the altitude layer between the route and the take-off and landing field to divide a plurality of entry routes and departure routes, and adopts a unified parking space allocation management in the complete operation cycle of the unmanned aerial vehicle plan declaration, take-off and landing, so as to provide strong support for the simultaneous entry and departure of multiple unmanned aerial vehicles.

The invention belongs to the technical field of data center level or industrial level SSD arrays, and particularly relates to an FTL table item full-hardware acceleration module method based on logical address merge sorting, which comprises the following steps: a TU module receives a logical address sequence processed by a controller at a host end, and further splits logical addresses into a new mapping relationship; the CPU does not directly access table items in the dynamic random access memory, access is controlled through hardware, the hardware and the CPU work at the same time, the running efficiency of the CPU is improved, the code burden is reduced, code logic control is reduced, each command sequence only needs to be inserted into the TU for one time, follow-up operation is completed through the hardware, the use efficiency of the dynamic random access memory is improved, and the service life of the dynamic random access memory is prolonged. According to the method and the system, the adjacent mapping relation can be updated once by taking burst (a minimum trigger unit of once DMA transmission) as a unit, and for a high-performance SSD, more idle time slices can be reserved for a CPU to process functions such as regular routing inspection, read interference and Garage Collision, so that the utilization rate of the CPU is improved.

The embodiment of the invention provides a video exporting method and device and a storage medium, and the method comprises the steps: exporting a video editing draft according to historical exporting parameters in response to an exporting interface instruction of skipping to the video editing draft, so as to generate a first video; obtaining a current export parameter in the export page in response to a trigger instruction of an export control in the export interface; and if a target export parameter in the current export parameters is consistent with a target export parameter in the historical export parameters, adopting the first video as a target video exported by the video editing draft. According to the method, the export of the video editing draft is started in advance when the export page is opened, so that the idle time of the user in the export interface is fully utilized, the time of waiting for export of the user is shortened, and the user experience in the export process is improved.

The embodiment of the invention provides a dynamic event trigger consistency control method and system for a multi-agent system, and the method comprises the steps: setting a dual-threshold line based on a Lyapunov function, dividing a system state function into an activation time period, a holding time period and an idle time period, and dynamically switching the working mode of the controller, namely inputting a non-zero control quantity in an activation period to quickly converge a state, performing input zero setting in an idle period to save resources, maintaining control input at the previous moment in a keeping period to avoid frequent switching, and forcibly performing zero setting control input in a DoS attack period. Secondly, monitoring a measurement error (a deviation between a current state of the intelligent agent and a historical trigger state), a consistency error (a state deviation between the intelligent agent and a leader) and an auxiliary variable in real time, and if the weighted contribution of the measurement error in an activation time period exceeds the sum of the weighted contribution of the consistency error and the auxiliary variable, triggering a communication update state and reducing redundant communication;

The invention discloses a dynamic scheduling method for a multi-satellite collaborative observation task, which mainly comprises the following steps of: dispersing a scheduling period into time slices according to minimum overlapping observation time, and uniformly managing resources and time windows; a multi-objective optimization algorithm is used for initially scheduling fixed tasks, and the task completion rate and the minimum relay frequency are considered; detecting a satellite idle time slice based on the initial scheduling result and constructing an index; the method comprises the following steps of: preferentially performing plug-in scheduling on a temporary task, starting multi-satellite relay if a single satellite cannot complete the task, triggering collaborative rescheduling if the tasks fail, merging the fixed task and the temporary task for re-optimization, and simultaneously minimizing disturbance to the fixed task. According to the method, the resource utilization rate and the dynamic response capability are improved through the strategy of'insertion priority and rescheduling understanding ', the temporary task can be efficiently processed on the premise of guaranteeing fixed task execution, interference on an original fixed task plan is reduced, and the method is suitable for complex and changeable observation scenes.

Approaches presented herein provide systems and methods for dynamic allocation of processing units to increase computational density. Idle times between sequential processing tasks may be computed and, if the idle time exceeds a threshold capacity, additional sequential processing tasks may be allocated to a common processing unit. As a request, a first portion of a first sequential processing task may be executed, then a second portion of a second sequential processing task may be executed prior to executing a subsequent portion of the second sequential processing task. By using the idle time between portions of sequential processing tasks, output perform may be maintained while using additional processing capabilities that would otherwise remain idle.

The invention discloses a time prediction method and semiconductor process equipment. The method comprises the following steps: obtaining the total residual processing time of each wafer in a scheduling task in a current real-time state; acquiring necessary idle time of each processing module in the scheduling task in the current real-time state; and according to the residual processing total time of each wafer and the necessary idle time of each processing module, obtaining the processing completion time of all wafers in the scheduling task in the current real-time state. In the process of predicting the processing completion time, all wafers in the scheduling task are traversed, the remaining processing total time of each wafer is considered, and the necessary idle time of all processing modules in the current real-time state is considered at the same time. Accurate prediction of the processing completion time of all wafers in the whole scheduling task under a certain processing state (namely the current real-time state) is realized.

A power consumption prediction and management method and system based on a solid state disk, a medium and a product relate to the field of solid state disks. The method comprises the following steps: predicting the workload intensity of a host in a first preset time window based on an I / O (Input / Output) instruction stream to obtain an expected host workload curve, and determining an expected host idle time period; calculating an expected host power consumption value in the expected host idle time period; extracting internal state parameters of the solid state disk according to the historical operation log data; establishing a background task triggering probability model, and calculating the triggering probability of starting the high-power-consumption background task by the solid state disk in a first preset time window; performing power consumption conflict judgment according to the expected host power consumption value and the triggering probability, and generating a comprehensive predicted power consumption value; and based on the comprehensive predicted power consumption value, determining an optimal target power consumption state, and instructing the solid state disk to be switched to the optimal target power consumption state. By implementing the technical scheme provided by the invention, the stability of state switching of the solid state disk is improved.

The invention provides a dual-runtime engine collaboration method and system for an industrial edge computing terminal. Relates to the technical field of industrial edge computing. The method is applied to a system comprising a real-time runtime engine, a non-real-time runtime engine, a shared memory module and a resource monitoring module, and comprises the following steps: executing a real-time task and / or a non-real-time task, and performing data interaction between the real-time runtime engine and the non-real-time runtime engine through the shared memory module, periodically acquiring a resource use state of a hardware platform through a resource monitoring module, and dynamically adjusting available resources allocated to an engine during non-real-time operation according to the resource use state; and when the idle time window exists in the scheduling period of the real-time runtime engine, executing the non-real-time task in the idle time window through the non-real-time runtime engine. According to the invention, collaborative optimization of the system on the aspects of time certainty, flexible resource allocation and low-latency data exchange can be realized.

The invention discloses an intelligent reminding method of a to-do list and a related device, relates to the field of artificial intelligence or finance, and aims at the to-do list which is short in time consumption, so that a worker only needs to be reminded to process the to-do list before the deadline. Obtaining a predicted busy time period of the target day based on the historical busy time period of the staff; and determining an idle time period of the target day based on the preset working time period and the predicted busy time period of the worker. In order to ensure whether the worker is really in the idle state in the idle time period, whether the use frequency of the working terminal of the worker is smaller than or equal to the preset frequency is further detected, if yes, it is confirmed that the worker is really in the idle state, and prompt information for prompting to handle the to-do list is sent. Therefore, the purpose of reminding the worker to process the to-do list for many times when the worker is in the idle state is achieved.

The invention discloses a low-power-consumption control device, system and method of a memory, electronic equipment and a chip, and relates to the technical field of chips, and the low-power-consumption control device of the memory comprises a timing unit and an adjusting unit; the timing unit is connected with the adjusting unit, the timing unit is externally connected with a memory access service queue module, and the adjusting unit is externally connected with a low-power-consumption control module; the timing unit is used for determining a target idle duration when the memory access service queue is in an idle state and a low-power-consumption duration when the target memory is in a PD low-power-consumption state; the adjusting unit is used for adjusting the countdown of the target memory entering the PD low-power-consumption mode according to the target idle duration and the target PD low-power-consumption duration, so that the duration before the target memory enters the PD low-power-consumption mode is controlled through the low-power-consumption control module. The countdown of the target memory before entering the PD low-power-consumption state can be dynamically adjusted, so that the duration of entering the PD low-power-consumption state of the target memory is adjusted.

A system and method for universal static multi-transmit CPU design with a static pipeline for automatically parallelizing code is presented. A multi-core and / or multi-processor integrated circuit (2) has a plurality of processing units (21) and / or processing pipelines (53) that simultaneously process instructions for data by executing parallel processing machine code (32). The execution of the parallelized processing code (32) by the parallel processing multi-core and / or multi-processor integrated circuit (2) comprises the occurrence of a delay time (26), wherein the delay time is given by an idle time between the processing unit (21) returning the data after processing a specific instruction block of the processing code (32) for the data and receiving the data required by the processing unit (21) to execute a consecutive instruction block of the processing code (32). The parallel pipeline (53) comprises means for: (i) forwarding by providing a data forwarding from a MEM stage as an EX / MEM register to an EX stage as an ID / EX-stage register; (ii) exchanging by making the results of the Ex-ME-phase registers accessible by the Ex phase of a parallel pipeline (53) to provide a result exchange between the pipelines; and (iii) implementing branch pipeline refresh by providing control conflicts by refreshing only those pipelines (53) dependent on one pipeline (53) based on branch address computation conditions.

The invention discloses an intelligent integrated management system for shuttle vehicles, and belongs to the technical field of shuttle vehicles, and the system comprises S1, a vehicle scheduling module which receives vehicle state information and schedules vehicles according to task priorities; s2, a task distribution module, wherein the task distribution module receives warehouse order tasks and distributes the tasks to corresponding shuttle vehicles; s3, a path planning module, wherein the step S3 comprises obtaining shelf position information and planning an optimal driving path; and S4, an equipment monitoring module. The system can plan the optimal path in real time and reduce the empty driving time and waiting time of the shuttle vehicles, so that the transportation efficiency is greatly improved, the system can improve the order processing speed, remarkably shorten the cargo turnover period, support simultaneous operation of multiple shuttle vehicles, realize parallel processing of tasks, further improve the overall efficiency of warehousing operation, and reduce the labor intensity of workers in peak hours. The system can flexibly deploy vehicles and ensure that orders are processed in time.

The present technology relates to an electronic device. According to the present technology, a host device may include a garbage collection controller and an idle time processor. The garbage collection controller may provide, to a storage device, a health information request command for requesting health information including a host write amount and a storage device write amount, provide, to the storage device, a first garbage collection control command for requesting garbage collection cost information based on the health information, provide, to the storage device, a second garbage collection control command for instructing to perform garbage collection based on the garbage collection cost information and an idle time of the storage device. The idle time processor may process information on the idle time.

The invention discloses a multi-experiment task production scheduling method, device and equipment and a storage medium, and the method comprises the steps: carrying out the sampling of a preset number of times for each production scheduling scheme based on the prior distribution of the duration of each experiment stage, and determining the starting time of each experiment operation, constructing a global time resource scheduling problem under the constraint conditions that the time window constraint of the experimental operation, the time period of the experimental operation belongs to the idle time period of the operation equipment and the time periods of the experimental operation distributed on the same operation equipment are not overlapped, and calculating the ratio of the infeasible times of the global time resource scheduling problem to the preset times; and if the risk value is lower than the risk threshold value, taking the production scheduling scheme as a target production scheduling scheme, and performing online scheduling of the experimental tasks according to the target production scheduling scheme, so that the method is suitable for production scheduling of high-throughput and diversified experimental tasks, and the risk of equipment resource conflict is reduced.

The invention relates to the technical field of engineering mechanical equipment lease management, in particular to a lease management method and system for engineering mechanical equipment. Comprising the following steps: S1, acquiring mechanical parameters, operation states, historical use data and historical maintenance data of engineering mechanical equipment, and dividing the engineering mechanical equipment into equipment to be leased and leased equipment; s2, performing performance index evaluation and working condition index evaluation on the to-be-leased equipment in combination with mechanical parameters, historical use data and historical maintenance data, and recording idle time of the to-be-leased equipment at the same time; s3, acquiring demand data of the leasing customer, performing combined analysis according to the demand data in combination with the performance index and the working condition index, acquiring to-be-leased equipment capable of meeting the demand data, and predicting the number of renewal days in the demand data; by accurately acquiring the mechanical parameters, the operation state and the historical use and maintenance data of the engineering mechanical equipment, the actual condition of each piece of equipment can be comprehensively known.

To achieve efficient and smooth schedule adjustment by eliminating trouble of performing adjustment of schedules by hand, automatically finding vacant time by referring to the schedule of a group, and adjusting the schedule through a chat.SOLUTION: A system includes: means for automatically performing adjustment of schedules; means for looking for vacant time referring to the schedule of a group; and means for adjusting the schedule using ZOOM.SELECTED DRAWING: Figure 1