239 results about "Task number" patented technology

The invention provides a distributed computing resource allocation system and a task processing method. The distributed computing resource allocation system comprises a central server and a plurality of node servers. The central server is used for receiving video image tasks sent by a user and allocating the video image tasks to corresponding node servers through central ends of computing units based on the types of the video image tasks as well as the current task number and load conditions of the node servers. The node servers are used for processing the video image tasks through node ends of the computing units corresponding to the video image tasks. According to the distributed computing resource allocation system and the task processing method provided by the invention, different types of video image tasks can be processed by using multiple servers of one server cluster, and the utilization rate of the server cluster can be increased.

The invention relates to a solution for multiple mobile robot path conflict based on dense storage regions. The technical scheme of the solution comprises steps of (1), establishing an initialized mesh path image by dispatching a server; (2), detecting a cargo access task and dividing the task into a plurality of sub-tasks; (3), outputting task paths of current sub-tasks by using an image search method; (4), determining whether target points of sub-tasks are released by a last task; (5), marking all task paths by using task numbers; (6), returning to the step (2) after marking all task paths; (7), seizing resource variables through all tasks in a task executing queue; (8), dividing conflict regions; (9) determining whether conflict regions are released completely; (10), sending a task execution command to a mobile robot; and (11) returning to the step (7) after releasing resource variables to the server. The solution has the advantages of being reasonable in design, capable of distributing tasks at any time, planning tasks at any time and avoiding conflict at any time, high in accuracy, simple in calculation and practical.

The invention discloses a task scheduling method and a task scheduling system, relates to the technical field of network communication, and is used for solving the problem of low task scheduling efficiency. The task scheduling method comprises the following steps of receiving a task completion message transmitted by an operating platform by a scheduling server through a message bus, updating the task states of a current task and a subsequent task of the current task; acquiring ready tasks, grouping the ready tasks according to task types, and sequencing the ready tasks in each group according to static priority; acquiring a maximum concurrency number, a ready task number and a task-in-operation number of each task type; adjusting the maximum concurrency number of each task type through the maximum concurrency number, the ready task number and the task-in-operation number of each task type, distributing the ready tasks of each task type to respective operating platform for operating according to the sequence of the ready tasks in each group until the task-in-operation number of each task type reaches the maximum concurrency number of the respective task type. The scheme provided by the invention is applicable to task scheduling.

The invention discloses a big data task scheduling system and method. The big data task scheduling method comprises the following steps that: a task configuration module acquires a task configuration command, and configures a task parameter according to the task configuration command; a task scheduling center node generates an executable task according to the task parameter, performs statistics to obtain the number of tasks running on the task running node and a data source, and controls a concurrency degree of the tasks according to the task number and a preset threshold value, so that the task number is small than the preset threshold value; and task distribution is performed when the concurrency degree of the tasks is in a preset threshold value range and satisfies dependence, and the task running node runs the executable task allocated by the task scheduling center node. In the method, the concurrency degree of current tasks is obtained by statistics, and whether the number of run tasks exceeds the preset threshold value or not is judged to determine whether to continue issuing the executable task or not, so that over high system load caused by simultaneous running of excessive tasks is avoided. Through adoption of the system and the method, the concurrency degree of big data tasks is controlled, so that the running efficiency of the big data tasks is ensured.

The invention relates to a task scheduling method in a multi-core DSP system. A shared task pool is established in a shared memory in the multi-core DSP system, tasks are input into the task pool, the tasks are firstly classified into two categories of time-related and non-time-related, then each task is carried out the numbering, the time-related tasks have the same serial number, the non-time-related tasks are independently carried out the numbering, the initial states of the tasks with the different serial numbers are set as the non-locked states; and a task obtaining device of each idle slave core carries out the inquiry to the shared task pool and carries out the processing of the task after obtaining the task. The task scheduling method changes the technical proposal of using a main core for distributing tasks by the traditional multi-core DSP system and adopts the method of using the slave cores to actively obtain the tasks during the idle time, which can effectively reduce the requirements on the reliability of priori knowledge and reduce the load balance of the multi-core system.

The invention discloses a method for implementing an in-orbit maneuvering imaging task of an agile earth observing satellite. Command parameters required for maneuvering imaging are transmitted to a satellite by a user through a satellite-ground link; the satellite can generate a command set automatically; an on-satellite computer stores commands by adopting a two-dimensional index data structure of a task number and time information and simultaneously is matched with a program control data block which is noted on the ground surface and is used for an agile maneuvering task; and the operation of adding task, deleting the tasks, operating the tasks and interrupting the tasks are realized according to the requirements of a ground user. In addition, the on-satellite computer can perform backup and storage on the commands relative to the tasks through an internal emergency data recovery module, and the commands can be recovered after the on-satellite computer is reset or shut down, so that the overall satellite continuously executes the tasks according to a predetermined mode. By the method, the application performance of the satellite can be improved greatly with low cost; moreover, the capability of dealing with in-orbit urgent tasks and state change of the satellite can be enhanced; the dependence on ground surface measurement and control is reduce; and the safety and the reliability are improved.

An optimizing apparatus (300a) for a mounter equipped with a line gang pickup head which picks up a plurality of components and mounts them on a board comprises: a nozzle set determination unit (305a) for determining a nozzle set which reduces a mounting time in view of the number of times interchanging pickup nozzles and a total task number necessary for mounting the plural components; a nozzle pattern determination unit (305b) for determining an optimal nozzle pattern as well as an arrangement of pickup nozzles (nozzle arrangement) at a nozzle station (119), based on the nozzle set determined by the nozzle set determination unit (305a); and Z-axis arrangement / mounting order optimization unit (305c) for determining an array order of component feeders and a mounting order of components while maintaining the determined nozzle set and nozzle pattern.

The invention relates to a multi-robot task allocation and path planning method. The method comprises: step one, information of multiple robots and tasks is initialized; to be specific, initial state parameters of robots and task information in an environment are obtained; and positions, speeds, maximum power of the robots and task locations are obtained; step two, multi-robot task allocation is carried out; to be specific, comprehensive cost data between all robots and tasks are calculated, factors including the power, working time, and maximum task numbers of the robots are considered, and tasks are allocated to the robots based on a criterion of comprehensive cost minimization; and step three, a robot path planning method is executed; to be specific, path planning of robots is carried out by using an improved immune genetic algorithm. With the method provided by the invention, multiple tasks can be distributed to multiple robots effectively; and the improved immune genetic algorithm is implemented during the robot path planning process to reduce the iteration frequency of the algorithm, thereby improving the searching efficiency of the globally optimal solution of the immune genetic algorithm and obtaining a short optimal solution.

The invention relates to an RDF data storage and query method combined with star figure coding. The RDF data storage and query method comprises the steps that S1, RDF data are preprocessed, and the RDF data are presented in an RDF data map mode; S2, an input SPARQL query statement is presented in an SPARQL query graph mode, and query decomposition is carried out; S3, the SPARQL query statement is preprocessed, and the task number of whole query, the connecting sequence of query star sub-nodes and relevant information of the query star sub-nodes are obtained; S4, the SPARQL query statement is executed, query connection planning is carried out, a Map Reduce parallel computation frame of Hadoop is adopted, and the number of times of starting a query task Job is decided according to the relevance of the SPARQL query statement; S5, subgraph query is carried out, and a Map function is adopted; S6, a result connecting algorithm is carried out, and a Reduce function is adopted. Due to the fact that a Hash coding index query strategy based on star configuration is adopted, stored data redundancy and the number of query tasks are reduced, and query efficiency is improved.

The invention relates to a task scheduling technology in a network downloading system. The technical problem that the invention aims to solve is to provide a network downloading method for a downloading system to automatically conduct downloading task scheduling. The network downloading method of the invention is added with technical measures of downloading task number limitation, downloading-speed detection, downloading task PRI, downloading mode mutex, error processing mechanism, and the like which ensure that the invention can more effectively use the network resource to more rapidly download content resource, and is applicable to various multi-mode multi-task network downloading systems.

The invention discloses a task allocation method and a system for unmanned distribution vehicles, and an unmanned distribution vehicle, which relate to the field of unmanned distribution. The method comprises the following steps: each unmanned distribution vehicle determines a distribution task set, wherein the distance from the position of a task point in each distribution task set to the position of the corresponding unmanned distribution vehicle is smaller than a distance threshold, and the difference in task number between any two unmanned distribution task sets is smaller than a number threshold; negotiation task sets between adjacent unmanned distribution vehicles are built using a clustering algorithm based on the distribution task sets; and the unmanned distribution vehicles complete task allocation through a negotiation mechanism according to the negotiation task sets between adjacent unmanned distribution vehicles. Each unmanned distribution vehicle is enabled to acquire reasonable allocation task points in the absence of a central computing node or main node, and uniform task load is achieved. In addition, by building the negotiation task sets between adjacent unmanned distribution vehicles using a clustering algorithm, the number of negotiation tasks is reduced greatly, and the execution efficiency of unmanned distribution vehicles is improved.

The invention discloses a processing method for upwards injecting a multi-parameter instruction by an agile satellite. According to the method, instructions generated when an on-satellite attitude control subsystem, a data transmission subsystem, a camera subsystem, a satellite affairs subsystem and other subsystems of the agile satellite execute mobile imaging tasks are formed into multiple instruction templates depending on typical working modes of various on-satellite subsystems and are stored in an on-satellite computer; the instruction templates corresponding to the types of the mobile imaging tasks are selected by a ground user, and a task number, an instruction template number and instruction parameters in the instruction templates are transmitted onto the satellite in accordance with a determined format of the satellite and the earth, and then an instruction set can be automatically generated by the on-satellite computer. Meanwhile, the on-satellite computer can modify contents in the instruction templates, add the instruction templates, and delete the instruction templates and the like at any time in accordance with an instruction on the ground. According to the method, not only can the complexity degree of instruction arrangement of the ground user be simplified, the upwards injecting data volume is greatly reduced, but also the reliability of instruction arrangement can be improved; particularly, the method provides a technique guarantee for task management and applications of the agile satellite.

The invention discloses a parallel recovery method of a main memory database, which comprises the following steps: a. logs are imported in a buffer memory by adopting a plurality of tasks and are read in parallel by a log system, and the tasks for reading the logs reorganize the logs by a certain protocols in a memory according to a sequence in the original log file; b. the log sequence is distributed to a plurality of queues by a distribution module by an equally loaded algorithm, and the distribution work abides by two rules of log synchronization; c. a plurality of tasks in parallel execute the log recovery, acquire logs from respective corresponding queues and then execute the log recovery, and a plurality of log recovery tasks abide by the two rules of the log synchronization. The method adopts a scheduling algorithm of importing tasks, a scheduling algorithm of in parallel recovering tasks, an equally loaded algorithm of recovering tasks and a balance algorithm of self-adaption of log file import task number and recovery task number, and can realize the quick recovery of the main memory database.

The invention discloses a RFID (Radio Frequency Identification)-based AGV (Automatic Guided Vehicle) multi-task positioning method. The method comprises the following steps: card writing: carrying out unique numbering on each guidepost radio frequency card; task association: according to an AGV task, planning a corresponding path, and writing a function code corresponding to each station on the path into the radio frequency card; task distribution: sending the function code in the step 2 and the corresponding ID of the function code to a controller, storing the function code into EEPOM (Electrically Erasable Programmable Read-Only Memory) space which is distributed in advance according to a corresponding task number by the controller, and recording and storing by utilizing an address variable; and task guidepost matching: copying a task list of the task number disclosed by the EEPOM space to a SRAM (Static Random Access Memory) temporary task buffer area, inquiring the guidepost number of the radio frequency card in fixed time when the AGV operates, uniting the guidepost number and the task number after the guidepost number is obtained, finding a unique function code matched with a set matching algorithm according to the set matching algorithm in the task buffer area, and finally finishing setting action according to the function code.

A microcomputer includes a bus, a CPU coupled to the bus, a trace data generating circuit coupled to the bus to output trace data of a process executed by the CPU at an output node, a memory coupled to the output node of the trace data generating circuit to store the trace data, a first register coupled to the bus to store a task number indicative of a task being executed by the CPU, and a control unit coupled to the first register to control on / off of outputting of the trace data from the trace data generating circuit in response to the task number.

The invention vigorously supports a process of allocating tasks numbering several thousand to units numbering several hundred and allows a streamlined task assignment to be obtained in a short time. The computer system of the invention comprises the following: Task list storing memory 2 stores, on a by-task basis, task times, and task location within a product. Unit list storing memory 4 stores, on a by-unit basis, tasks allocated to the unit and task order within the unit. Walking time calculation means 6 calculates walking time of a worker from the task order within the unit and task location within the product. Task assignment visual display screen displaying means 8 displays a visual display screens about task assignment in which task times and walking times are displayed along the Y-axis in accordance with the task order within a unit at a location corresponding to the unit on the screen in which the units are arranged along the X-axis. Sifting means 30 allows a planner to designate and shift a certain task in the task assignment visual display screen. Updating means 32 updates the contents stored in the unit list storing means 4 in accordance with the result of shift by the shifting means 30.

The invention relates to a client, a signaling tracking server, a protocol module and a signaling tracking method. The signaling tracking server comprises a task node establishing unit, a tracking request message sending unit and a response message processing unit, wherein the task node establishing unit is used for generating a task number corresponding to a tracking request message received fromthe client, filling in the task number, the protocol type, a client identifier and a tracking condition list in an idle task node, and setting the task node to be the use state, and the tracking condition list comprises a tracking condition and a protocol module identifier which are associated mutually; the tracking request message sending unit is used for sending the tracking request message with preset format to the protocol module, and the tracking request message with preset format comprises the task number, the protocol type and the tracking condition; and the response message processingunit is used for responding a tracking request response message received from the protocol module to the client, and the tracking request response message comprises the task number and the symbol ofthe tracking whether is successfully established or not. The invention can improve the reusage and the maintenance of codes.

The invention discloses a material tray warehousing method and system guaranteeing accurate material receiving by an automatic guided vehicle. The material tray warehousing method comprises the steps that when the automatic guided vehicle arrives at a material receiving platform and gets ready for fetching materials, a material receiving information verification request is sent to a warehouse dispatching platform; the warehouse dispatching platform acquires the current index number Index l of the automatic guided vehicle and searches for the corresponding predistribution transfer task number task 1 according to the index number Index l; the warehouse dispatching platform compares the task 1 and a current transfer task number task 2 provided by an electric control unit, wherein the task 2 is the transfer task number corresponding to a material container on the material receiving platform currently; if the task 1 is equal to the task 2, the warehouse dispatching platform sends a verification success instruction to the automatic navigation trolley; the automatic guided vehicle continues to receive the materials and transfer the material container to a target position. According to the material tray warehousing method and system guaranteeing accurate material receiving by the automatic guided vehicle, it is guaranteed that the AGV does not receive the material incorrectly in the material receiving process, an extra guarantee is provided for conformance between system record information and reality after the container is warehoused, and therefore production quality accidents caused by container warehousing dislocation can be avoided as far as possible.

The invention discloses a data center energy consumption management method and system based on dynamic frequency modulation. The method comprises frequency modulation energy conservation of a single server and task scheduling of energy awareness among servers, wherein the frequency modulation energy conservation of the single server comprises the steps of taking a time quantum of a constant task number as a frequency modulation unit, estimating dissipative energy of each unit according to an energy consumption model and task information, and utilizing a heuristic algorithm to select a frequency modulation mode which enables the sum of energy consumption of all units to be minimum so as to adjust the frequency of a processor; the task scheduling of energy awareness among the servers comprises the steps of selecting a candidate server according to the state of each server and the task information when a task reaches, utilizing a frequency modulation energy conservation method on the single server by each server according the task information to estimate the energy consumption change, selecting the server with the minimum energy consumption change by a controller to distribute a new task, and utilizing the frequency modulation energy conservation method on the single server by the selected server to modulate the frequency and operate the new task. According to the invention, the energy consumption of the servers in a data center is reduced by frequency modulation and task distribution, and energy saving and emission reduction effects are achieved.

The invention discloses a backup and recovery method capable of supporting online concurrency of multi-level data and a database. Backup data recovery is performed by executing the following steps of starting up all backup proxy servers and backup data servers, and registering to a master control server; selecting a backup task category by a supervisor console, wherein the backup task category comprises a catalog backup or a user full backup; issuing a backup data task request message or a database backup task request message to the backup data servers and the backup proxy servers by the master control server; start uploading or downloading a data command after the backup data task request message or the database backup task request message is received by the backup data servers, establishing a backup file storage catalog according to a task number, then, enabling a file transmission service, and receiving file upload or download links of the backup proxy servers; sending a task completion message to the master control server after the transmission of received uploaded or downloaded file data is ended. The backup and recovery method disclosed by the invention meets the massive data storage and backup requirement, and supports online data backup and recovery.

The invention relates to the technical fields of computer and bioinformatics, disclosing a distributed gene sequence alignment method based on Basic Local Alignment Search Tool (BLAST). The method comprises the following steps: S1, the program analyzes user parameters, determines MPI thread serial number and reads query sequence file; query sequences are divided based on task number, and every MPI thread reads corresponding MPI thread serial number; S2, according to the MPI thread serial number, the program judges if the present MPI thread is head node; if the present MPI thread is a head node, the program waits for communication requests of other MPI threads; if a communication request exists, the response exists and then the present task is allocated to the thread making the request; the program continuously allocates task; if the present MPI thread is not a head node, the program requests a task serial number from the head node, reads the query sequence file segment according to the task serial number and performs BLAST to obtain BLAST alignment result; the program subtracts 1 in the task serial number and requests the task serial number after performing BLAST; and S3, the program combines all BLAST alignment results. The method can reduce hardware cost of the bioinformatics research.

The invention discloses a multi-core CPU video transcoding scheduling method, which belongs to the field of video transcoding. Before a scheduling scheme is implemented, a static pressure test is carried out for a transcoding server in order to measure the maximum concurrent transcoding task number of a single CPU core; the scheduling scheme is started; the number of currently executed tasks of all the CPU cores is initialized as 0; if a new transcoding task arrives, then scheduling is carried out according to an allocation and scheduling method for new tasks; if a transcoding task is stopped, then scheduling is carried out according to an allocation and scheduling method for existing tasks; if a message for stopping all transcoding tasks is received, then a program is closed, and otherwise, the method rejudges whether a new transcoding task arrives, and carries out circular processing. The invention ensures that the transcoding tasks can be operated in the same CPU core to the greatest extent, thus effectively increasing the hit rate of the CPU cache and the operation efficiency of the system, and moreover, the loads of all the CPU cores can be balanced to the greatest extent.

The invention discloses a cloud computing resource scheduling system and method. The cloud computing resource scheduling method includes that building a resource distribution model according to task number and resource number, and defining a resource distribution matrix, a resource scheduling time matrix and a scheduling target; generating codes of an initial population according to a code rule; computing the fitness value of the population according to fitness functions; selecting a dominant population according to the fitness value; updating the population through learning factors, and generating the next generation of new population according to the updating result; judging whether conforming to stop conditions, if so, stopping, and obtaining the optimal solution; otherwise, returning to compute the fitness value; decoding the optimal solution according to a decoding rule to obtain the resource distribution result. The cloud computing resource scheduling system and method are capable of well solving the cloud computing resource distribution problem.

An optimizing apparatus for optimizing a mounter equipped with a line gang pickup head which picks up a plurality of components and mounts them on a board. The apparatus includes a nozzle set determination unit for determining a nozzle set which reduces a mounting time in view of a number of times interchanging pickup nozzles and a total task number necessary for mounting the plural components, a nozzle pattern determination unit for determining an optimal nozzle pattern as well as an arrangement of pickup nozzles (nozzle arrangement) at a nozzle station, based on the nozzle set determined by the nozzle set determination unit, and Z-axis arrangement / mounting order optimization unit for determining an array order of component feeders and a mounting order of components while maintaining the determined nozzle set and nozzle pattern.

The invention discloses an automation equipment communication method based on a CAN bus. The communication method is based on a CAN bus protocol, and an application layer protocol employs a CAN data frame with an expansion frame format. An arbitration domain comprises a priority identification domain, a source address domain, a target address domain, a source task number domain and a target task number domain. The communication method comprises the following steps that the CAN data frame sent by a sender via the CAN bus is received; priority of the CAN data frame is acquired; whether the priority of the CAN data frame is the highest priority is judged; if the judgment result is yes, data interaction is performed between the CAN data frame and a CAN application communication layer via a high-speed communication mode; and if the judgment result is no, the CAN data frame is sent to a queue with the corresponding priority, and data interaction is performed between the CAN data frame and the CAN application communication layer via an information queue mode. According to the automation equipment communication method based on the CAN bus, real-time and multitask processing can be performed on a data message.

The invention provides an intelligent virtual assembly action recognition method and belongs to the field of virtual assembly. The method comprises the following steps of determining a current operation object in a scene according to a task number and a current operation number in a scene model; recognizing an action of a user to obtain a user action recognition result; and taking operational attribute of the current operation object and the user action recognition result as a fact, traversing a rule base of an expert system, searching a rule matched with a rule premise and reasoning out a conclusion, namely an operation intention of the user.

The invention relates to a multi-database-based data query method. The method is characterized by comprising the following steps of obtaining a database query request, and generating a query instruction according to the query request, wherein the query request carries query information; determining a central task number and a plurality of corresponding sub-task numbers according to query information; sending the sub-task numbers to corresponding sub-databases, thereby enabling the sub-databases to obtain the query instruction according to the sub-task numbers; and receiving and collecting query results fed back by the sub-databases. According to the method, related information in the sub-task numbers can be queried once without querying the sub-task numbers one by one, so that the query efficiency is improved. In addition, the invention provides a multi-database-based data query system and apparatus.

The invention discloses a distributed video transcoding scheduling method. Servers with the same number of running tasks are stored in a double linked list; two arrays of which the length is equal to the total number of the servers are used for describing the double linked list, one array indicates subsequent server nodes of the servers in the double linked list, and the other array indicates precursor server nodes of the servers in the double linked list; a linked list entry table is used for storing double linked list head nodes of each task number; and a variable is used for storing the current smallest task number. When a new transcoding task arrives, a first server with the smallest number of running tasks is found through a linked list entry with the smallest task number so as to perform new transcoding task processing; the server is deleted from the original double linked list, and is inserted into the head of a double linked list with the task number plus one; and when a certain server completes a transcoding task, the server is deleted from the original double linked list and is inserted into a double linked list with the task number minus one. The time complexity for video transcoding scheduling is lower.