160results about How to "Improve task execution efficiency" patented technology

The invention provides a system and a method for distributed asynchronous task queue execution in a cloud environment. The system comprises an interface device, a task queue device and a plurality of task execution devices. The interface device is used for receiving a task execution request submitted by a user, verifying whether the quota of the user is overrun, and receiving tasks submitted by the user and writing the basic information of the tasks into a database under the condition that the quota of the user is not overrun. The task queue device is used for judging whether the tasks submitted by the user are tasks needing to be executed in a parallel mode or tasks needing to be executed in a serial mode, and correspondingly putting the tasks submitted by the user in a parallel task queue and a serial task queue. The task execution devices are used for executing parallel tasks and serial tasks pushed by the task queue device, the task execution devices judge whether the degree of concurrency exceeds the limit of the user when the task queue device pushes parallel tasks, and the task execution devices execute the parallel tasks when the degree of concurrency does not exceed the limit of the user. The system of the invention has the advantages of high task execution efficiency and good performance.

The invention provides a distributed resource scheduling method and system. The method comprises the steps of allocating tasks to a corresponding priority waiting queue according to assessed priorities of new task processing requests; according to the priority waiting queue obtaining the tasks, selecting a current scheduling queue; and according to the selected scheduling queue, calling a resourceallocation policy to allocate available distributed node resources. The system comprises a queue manager, a queue scheduler, a task monitor and a resource allocator. According to the technical schemeprovided by the distributed resource scheduling method and system, the total task completion time cost and the total task completion cost is effectively balanced according to a user demand; the resource utilization rate is improved; the task execution efficiency is improved; the service quality is guaranteed; and the user satisfaction is improved.

The invention discloses a task scheduling method and a task scheduling device, wherein the method comprises the following steps of obtaining request information of TaskTrackers, wherein the request information is task requesting information sent when the TaskTrackers have an idle work groove; calculating the resource consumption features and the rest task proportion of each task queue, wherein the resource construction feature of any one task queue is obtained through calculation according to the CPU (Central Processing Unit) occupation rate, the memory occupation rate and the bandwidth occupation rate of operating tasks in the task queue, and the rest task proportion of any one task queue is the ratio value of non-operating tasks to all of the tasks in the task queue; selecting the task array achieving the effect that the product of the resource consumption feature and the rest task proportion in the task queue is not smaller than that of other task queues as a target task queue; and processing the non-operating tasks in the target task queue by using the idle work groove. Therefore the non-operating tasks in the task queue in urgent need of being processed are preferably processed, and the task execution efficiency is greatly improved.

The embodiment of the invention provides a task scheduling method and device in a heterogeneous cluster and electronic equipment, and the method can comprise the steps: determining each task scheduledto a computing node for each computing node; dividing each sub-task into a plurality of sub-tasks; when the parent-child tasks corresponding to the child tasks are executed, adding the sub-task intoa ready child task queue; for each first sub-task in the ready sub-task queue, when the execution rate of the first sub-task in a GPU computing unit is greater than that of the first sub-task in a CPUcomputing unit, adding the first sub-task to the GPU sub-task queue; and scheduling each second sub-task to a target GPU corresponding to the second sub-task according to an interference relationshipbetween each second sub-task in the GPU sub-task queue and the sub-task being executed by the GPU. Therefore, the resource utilization rate can be improved, and the system throughput of the heterogeneous cluster is improved.

The present invention relates to the technical field of unmanned aerial vehicles, especially to an unmanned aerial vehicle taking-off and landing method and system based on a mobile platform. The mobile platform is provided with a control device configured to control taking-off and landing of the unmanned aerial vehicle, the unmanned aerial vehicle taking-off and landing method comprises a taking-off process and a landing process, the taking-off process comprises the steps that: the control device sends a taking-off command to the unmanned aerial vehicle, the unmanned aerial vehicle determinesthat when the unmanned aerial vehicle itself meets a taking-off condition, the unmanned aerial vehicle executes the taking-off motion, and the landing process comprises the steps that: the unmanned aerial vehicle collects relative position information between the unmanned aerial vehicle itself and the mobile platform and flies to the position above the mobile platform to execute landing motion when determining that the unmanned aerial vehicle meets a landing condition until landing onto the mobile platform. The method and the system allow the unmanned aerial vehicle to achieve taking-off andlanding on a support platform in a mobile state so as to enlarge the motion range of the unmanned aerial vehicle and reduce the time cost of the unmanned aerial vehicle for task execution.

The invention discloses a balance scheduling center, method, system and device of distributed tasks. The method comprises the steps that according to a function or type, multiple task groups are created, and a corresponding scheduling strategy is distributed for each task group; multiple scheduling plans are formulated for each task group, and each scheduling plan corresponds to an executable taskset; the execution amount of current tasks of each task group is monitored, and according to configuration parameters, the scheduling amount of each scheduling plan is calculated and obtained; according to the execution amount of the current tasks of each task group, the task issuing amount of each task main unit is calculated according to configuration parameters; according to the issuing amountof each task main unit, an executable task is issued for the corresponding task main unit. The scheduling center comprises a configuration module, a task scheduling module, a task issuing module anda task cache and monitoring module. According to the balance scheduling center, the task execution efficiency and use rate of the task main unit are effectively improved, and the load of the task mainunit is balanced.

The invention relates to a task scheduling method and a task scheduling system facing mixed load in a heterogeneous cluster. The method comprises the following steps: a resource scheduler is used for receivingthe beats of machines and maintaining the cluster attributes of the machines; a job manager is used for receiving and resolving operation to obtain a plurality of tasks; the job manager is used for setting the attribute cluster and restrain demand for the task, and transmitting the task information to a resource manager; the resource scheduler is an optimal machine which is used for meeting the restraint of task matching, and returning a matching relation between the task and the machine to the job manager; and the job manager is used for transmitting the task to an actuator on the matched machine for executing tasks. The attribute and task requirement of the heterogeneous machine can be indicated by an easily expandable description method, and the optimal machine is distributed for the task based on taking the hard constraint as a filtration standard and the soft constraint as a selection standard, therefore the executing efficiency of the task and the integral performance of the system can be obviously improved.

The invention discloses a multi-agent cooperation method applied in a wireless multimedia sensor network, which is mainly used for solving problems existing in the multimedia sensor network, such as large data transmission quantity, complicated network tasks, and the like, and is provided with the following characteristics: a mobile agent is generated by user parameter, which contains all network task information; the mobile agent determines a working state per se according to a current network task and determines a working threshold according to the parameter; the agent carries out negotiation through data exchange in an element space, and only one agent works in each working time slice; the agent management module of a leader cluster node can assign tasks to the multi-agent according to compression fusion algorithm and can carry out cluster distributed acquisition; the agent on each node can lead the agent to change the working state per se according to an enabling agent dispatched by a user and can carry out target identifying acquisition; and each leader cluster node can dynamically generate a return agent so as to return multimedia information to a server terminal.

The invention discloses an environment monitoring laboratory management information system and an operating method thereof. A plan management platform maintains an environment monitoring task plan. A task generating device obtains the environment monitoring task plan to generate an environment monitoring task comprising a sample collection sub-task and a sample analysis sub-task. A tag generating device generates sample identification tags for samples needing to be collected by the sample collection sub-task. A task issuing device issues the sample collection sub-task and the sample analysis sub-task of the environment monitoring task to a sampling platform and an analysis platform respectively. The sampling platform carries out sampling on site according to the sample collection sub-task, and binds the samples with the corresponding sample identification tags. A sample management platform completes sample switching on the basis of the sample identification tags. The analysis platform takes samples from the sample management platform and analyzes the samples according to the corresponding sample analysis sub-task to obtain analysis data which are fed back to an execution result processing platform. The execution result processing platform conducts corresponding processing on the task analysis result.

The invention relates to a mobile agent acquisition and storage system suitable for Internet of things, which is an acquisition and storage scheme applied to the Internet of things and is mainly used for solving the problems of large data transmission quantity, complex network task and the like under the environment of the Internet of things. The mobile agent storage and management system suitable for the Internet of things is developed and has the characteristics that: a multimedia node acquires image information in real time and stores the image information in a local storage space module; an interaction agent is generated by nodes, carries the image information identifier and the storage space information of the node, performs interaction on nodes in a traversal cluster and allows an acquisition node to adjust the working state per se according to the storage space information of other nodes; an inquiry agent is generated by user parameters and comprises all inquiry parameter information; after receiving the inquiry agent, a cluster head node generates a return agent traversal node according to task parameters and returns a matched image block to the cluster head node through the acquisition node; and the cluster head node directly returns an identifier-attached image block to a base station server and performs image fusion through a terminal so as to form a complete and clear monitoring area image.

A system for space-based global quick delivery of a disaster relief unmanned aerial vehicle is characterized by comprising a carrying relay transmission spacecraft (1), an autonomous reentry delivery cabin (2) and an unmanned aerial vehicle (3). The carrying relay transmission spacecraft (1) runs on a satellite orbit, the autonomous reentry delivery cabin (2) is connected with the carrying relay transmission spacecraft (1), and the autonomous reentry delivery cabin (2) carries the unmanned aerial vehicle (3). The characteristics that an on-orbit spacecraft can reach any place globally quickly and the characteristics that the unmanned aerial vehicle can go deep into a disaster core area to collect information in a close range are utilized comprehensively. The unmanned aerial vehicle is loaded on the spacecraft to perform on-orbit flight, the global coverage characteristics of the unmanned aerial vehicle are utilized to break through voyage and speed limitation of a conventional spacecraft, the disaster emergency response speed is improved, reentry means is utilized to deliver the unmanned aerial vehicle above a disaster area to perform closing up reconnaissance, the problem that the satellite imaging resolution is not enough is solved, and the disaster emergency response efficiency is improved.

The invention discloses a task scheduling method and a task scheduling device. The method comprises the following steps of creating a task priority queue for a task cluster formed by networked task nodes; selecting a task from the task priority queue as a current task according to a priority sequence, and calculating a resource utilization rate of the current task; judging whether certain resources remain or not according to the resource utilization rate of the current task, and if certain resources remain, selecting at least one task which requires resources fewer than the remaining resources and of which an EST (Expressed Sequence Tag) is 0 from the task priority queue as the current task; simultaneously executing each current task; subtracting 1 from the EST of a parent task of each level of each current task, and returning to execute the operation of selecting the current task from the task priority queue. Compared with the prior art, the task scheduling method and the task scheduling device have the advantage that the remaining resources of the cluster are fully utilized, so that task execution efficiency is improved.

The invention discloses a task processing method. The method comprises the following steps: receiving a to-be-executed task; according to the task type of the to-be-executed task, the to-be-executed task is inserted into a corresponding task queue, the task queue is preset, and the task queue is used for placing the to-be-executed task into a corresponding thread pool so as to execute the to-be-executed task; and when a preset condition is met, calling a callback function corresponding to the to-be-executed task to return an execution result of the to-be-executed task. The embodiment of the invention further provides a corresponding task processing device. According to the technical scheme, the to-be-executed task is inserted into the corresponding task queue according to the task type ofthe to-be-executed task, so that the corresponding thread pool executes the to-be-executed task, the to-be-executed task which can be asynchronously operated is prevented from being executed in a synchronous mode, and the task execution efficiency is improved.

The invention provides a remote operation and maintenance method and system, a storage medium and electronic equipment. The method comprises the steps that the method is applied to an operation and maintenance center platform, and the operation and maintenance center platform comprises a configuration center and a remote proxy; the configuration center acquires operation information of operation and maintenance personnel, generates a task instruction according to the information and sends the task instruction to the remote proxy; the remote proxy generates a task request according to the taskinstruction and sends the task request to a message queue, selects a target task request from the message queue, generates task information through a template generator and sends the task informationto a remote terminal; and the remote terminal executes corresponding operation according to the task information. According to the invention, an application and a database on a remote terminal can bemaintained remotely, manual on-site maintenance is avoided, and a large amount of repeated work is saved, so that the working efficiency is improved.

The invention, which is suitable for the technical field of data processing, provides a robot avoidance driving method and device and a robot. The method comprises: acquiring a topology path map of anenvironment in which a to-be-processed robot is located, priority values of all robots in the environment, and current positions and driving parameters of the robots in the topology path map; on thebasis of the topology path map and the priority values and current positions of all robots, searching for all high-priority robots having the priority values higher than that of the to-be-processed robot in an environmental area with the preset size in which the to-be-processed robot is located; identifying an area scene type of the environmental area under the condition of being larger than zeroby the number of the high-priority robots; and controlling the to-be-processed robot to carry out avoidance driving for the high-priority robots based on a corresponding preset avoidance mode, an environment path map, and the current positions and driving parameters of the to-be-processed robot and the high-priority robots under the condition of belonging to a preset conflict scene type by the area scene type. Therefore, the avoidance driving of the robot becomes flexible and efficient.

The invention discloses a condition-based task scheduling method and device, equipment and a storage medium. The method comprises the steps of obtaining a target sub-task node in a task execution instruction when the task execution instruction is received, and determining a target task execution condition corresponding to the target sub-task node according to a description task file correspondingto a workflow to which the target sub-task node belongs; determining a parent task node corresponding to the target sub-task node, obtaining current execution information of the parent task node, andjudging whether the current execution information meets the target task execution condition or not; and if the current execution information conforms to the target task execution condition, correspondingly executing the target sub-task node. Based on the execution condition and the current execution information of the parent task node, the corresponding target sub-task node is correspondingly executed, so that the task execution efficiency is improved, the system load is reduced, and the junk data is reduced.

Embodiments of the invention disclose a task processing method and device, an electronic device and a storage medium. The method comprises: determining whether a next process of a target task is a decision-making process or a transactional process; if the next process is a decision-making process, pausing the processing of the target task and detecting a user instruction acting on a user interfaceUI, the user instruction being used for triggering the execution of the next process and / or providing an operation parameter for the execution of the next process; and if the next flow is the transactional flow, automatically executing the next flow.

The present invention discloses an adaptive data request processing method. The method comprises: acquiring a dependency relationship between at least two data request processing tasks in a to-be-executed data request queue, and establishing a dependency relationship table; and according to the dependency relationship table, uniformly and adaptively scheduling the at least two data request processing tasks in the data request queue, and driving and executing the at least two data request processing tasks. The present invention also discloses an adaptive data request processing apparatus, a task scheduler and an adaptive data request processing system. According to the adaptive data request processing method and apparatus, the task scheduler and the adaptive data request processing system, when the task queue with the dependency relationships is executed, the highest degree of concurrency is acquired; the task execution efficiency is improved; data request processing is efficiently completed; and meanwhile, the adaptive data request processing method and apparatus, the task scheduler and the adaptive data request processing system are beneficial to later maintenance and expansion.

The invention relates to an ROS based control system for unmanned aerial vehicles, and belongs to the technical field of aircraft cooperative control. The system comprises a communication module, a first power supply module and the unmanned aerial vehicles, and each unmanned aerial vehicle comprises a group control system and a flight control system; the group control system is used for acquiringposition information of each unmanned aerial vehicle in the system, acquiring GPS coordinates of the corresponding unmanned aerial vehicle, issuing the GPS coordinates to other unmanned aerial vehicles in the system, receiving control data sent by a ground control station, and sending the control data to the flight control system for operation after data processing; the flight control system is used for receiving a control instruction of the group control system, collecting position information and speed information of the unmanned aerial vehicle and controlling the flight mode, height, speedand heading of the unmanned aerial vehicle; the group control system makes information interaction with each unmanned aerial vehicle through the communication module, and the unmanned aerial vehiclescommunicate with one other through the communication module; and the first power supply module is used for supplying power to the group control system and the flight control system. The task executionefficiency can be improved, and the stability of cooperative application of multiple unmanned aerial vehicles can be improved.

The invention discloses an imaging satellite autonomous task planning method based on machine learning. The imaging satellite autonomous task planning method comprises the steps that 1, ranking orbitelement tasks according to the starting time of a visible time window; And 2, when the current time is the decision time point, setting the meta-task as the current meta-task. 3, extracting a characteristic variable of the current meta-task, judging whether to execute the current meta-task or not through an on-board autonomous task planning model based on machine learning, outputting an observation time window of the current meta-task if the current meta-task is judged to be executed, executing the current meta-task when the observation time window starts, and deleting the current meta-task ifthe current meta-task cannot be executed; And 4, judging whether the rail element task is planned or not, if yes, ending, and if not, returning to the step 2. The method has the advantages that compared with a traditional satellite task planning method, the planning time is short, the task execution efficiency is high, and planning can be conducted in real time according to environment changes.

The invention discloses a task distributing method and a scanner. The method comprises the following steps that when the scanner of which the node type is a management node requires distributing tasks, operation is executed respectively for each scanner managed by the scanner, wherein the operation comprises the following steps of determining a resource consumption index when the scanner executes tasks to be distributed and the current rest load of the scanner, wherein the resource consumption index represents a resource consumption condition when the scanner executes the tasks; determining a load balancing factor when the scanner executes the tasks to be distributed according to the resource consumption index and the current rest load; selecting scanners meeting preset distribution conditions from the managed scanners according to the determined load balancing factor, and distributing the tasks to the distributed to the selected scanners. The technical scheme solves the problem that a load balancing effect is hardly guaranteed in the prior art.

The invention relates to a task scheduling method, device and system, electronic equipment and a storage medium. The method comprises the steps that a sample task record is obtained and comprises sample task information, robot information, personnel information and sample environment information, wherein the robot information, the personnel information and the sample environment information correspond to the sample task information, the robot information comprises robot position information, and the personnel information comprises personnel position information; according to the sample task record, a variable corresponding to a task scheduling scheme which meets preset optimal conditions is analyzed; and correspondence between the variable and the task planning scheme is established, and ascheduling model is obtained. Through the technical scheme, a robot executes tasks based on the scheduling scheme planned by a scheduling center, the task execution efficiency can be improved, and task execution time is shortened.

A metamorphic knuckle mechanism of a snake-imitation rescuing robot comprises a knuckle left end cover, a knuckle right end cover, two RRPRR branches and one RRPRR metamorphic branch. Metamorphic knuckles have two mechanism forms, and the work space and mobility can be changed. In the mechanism form I, a movable pair P in the RRPRR metamorphic branch is in an active moving state, a rotation pair R is in a following state, and then the knuckles have one moving freedom degree and two rotating freedom degrees. In the mechanism form II, the movable pair P in the RRPRR metamorphic branch is in a minimum displacement and locking state, the rotation pair R is in an active state, the knuckles are changed into parallel spherical knuckles in a metamorphic manner, and three rotation freedom degrees are achieved. The metamorphic knuckle mechanism has the beneficial effects of being good in flexibility, high in bearing capability and good in structural robustness and is suitable for the snake-imitation rescuing robot. By means of mutual cooperation of the two mechanism forms of the multiple metamorphic knuckles, the flexibility and adaptability of the snake-imitation rescuing robot under different environments can be effectively improved.

The invention belongs to the technical field of aircraft, in particular to a folding multi-rotor unmanned aerial vehicle frame. The folding multi-rotor unmanned aerial vehicle frame comprises a framemain body, an arm and a landing gear. The proximal end of the arm is articulated with the body, and the arm can be folded transversely with respect to the body; The distal end of the arm is hinged tothe landing gear which can be folded longitudinally relative to the arm. In addition, a self-locking mechanism for locking when the arm and landing gear are unfolded, a resilient telescopic landing gear for UAV take-off and landing cushioning, and a removable fixture for suspending the load device are included. The arm and the landing gear of the unmanned aerial vehicle can be folded, the volume occupation of the unmanned aerial vehicle is reduced, and the portability is enhanced. Resilient telescopic landing gear cushions the impact of UAV landing; Detachable fixtures allow users to quickly dismount and replace devices mounted on the drone, the portability and the task execution efficiency are improved.

The invention discloses a heterogeneous multi-AUV system task coordination method under time window constraints, and the heterogeneous multi-AUV system task coordination method belongs to the field ofmulti-AUV task coordination. The heterogeneous multi-AUV system task coordination method comprises the steps of: acquiring a basic Auv_Mission parameter matrix through coding AUVs, a sea area and task types; calculating state transition probabilities P of all possible paths according to starting point vectors and an end point matrix; selecting a next path by adopting a roulette method according to the state transition probabilities; and optimizing and recording all the traveled paths and waiting time before each task by adopting an ant colony algorithm, and calculating to obtain a task optimal allocation scheme and an execution sequence of each AUV. According to the heterogeneous multi-AUV system task coordination method, the subtasks are reasonably allocated to the plurality of AUVs withdifferent functions and different performance, thus the effect that the operating efficiency of the group is highest, and the entire complex task is completed through shared division and collaboration.

The invention discloses a visual workflow scheduling method and device and electronic equipment, and the method comprises the steps of visually displaying a workflow, and configuring subtasks in the workflow according to user operation; reading and analyzing a dependency relationship and task source information of the subtasks; sequentially putting the sub-tasks into a task queue according to the dependency relationship, and storing the task source information into a database; and reading the subtasks from the task queue, calling a corresponding heterogeneous system to execute the subtasks according to the types of the subtasks, and storing task logs and execution states of the subtasks into the database. According to the invention, the dependency relationship of the sub-tasks is read and analyzed, the sub-tasks are sequentially put into the task queue to be independently called and executed according to the dependency relationship, if a certain sub-task fails to be executed, the task can be independently called to be executed again, all the sub-tasks in the workflow do not need to be executed once, the resources can be effectively saved, and task execution efficiency is improved.

The invention discloses a task allocation method and device for a Jenkins platform. The method comprises the following steps: querying tasks to be executed in a database, wherein the tasks to be executed are the tasks which are not executed by task execution nodes, in sequence averagely allocating the tasks to be executed to all the task execution nodes on the Jenkins platform, further updating the states of the allocated tasks to be in executed states, when each task is executed, updating the state of the executed task to be completed, after a first preset time, determining that the number of the task execution nodes in idle states is greater than that of the task execution nodes in task backlog states, closing all the executing tasks, updating the states of the executing tasks into the states to be executed, after a second preset time, querying the tasks to be executed in the database again. The task allocation method and device for the Jenkins platform disclosed by the invention can solve the problem of resource waste and improve the overall task execution efficiency.

The invention relates to a foot robot traction control method and system based on an improved artificial potential field. The method comprises steps of constructing a robot target gravitational potential energy field function and an obstacle repulsion potential energy field function; calculating a target virtual force and an obstacle virtual force according to a potential energy field, and calculating the virtual resultant force generated by the environment; based on the virtual resultant force generated by the environment, calculating the robot's motion control signal; and according to the robot's motion control signal, calculating the input of a body pose controller. The method and the system adopt an improved artificial potential field theory to overcome the defect that the robot cannotreach the end point in a local area.

The invention provides an airline splicing method and system and a user terminal. The method comprises the following steps: acquiring a first route and a second route of an unmanned aerial vehicle; extracting a flying height of the highest waypoint with the highest flying height and a ground altitude of a series of waypoints between a first route ending waypoint and a second route starting waypoint from the first route and the second route; acquiring a flying height of a middle route according to the flying height and the ground altitude of a series of waypoints; and determining the middle route according to a first geographical position information of the first route ending waypoint, a second geographical position information of the second route starting waypoint and the flying height ofthe middle route, and splicing the first route and the second route according to the middle route to generate a spliced route. By implementing the invention, a plurality of routes can be executed by an unmanned aerial vehicle at one time, the task execution efficiency of the unmanned aerial vehicle is improved, the resources and time of the unmanned aerial vehicle are saved, and the selection fora user is enriched, thereby providing the user with more spaces for customizing planning routes.