Task (computing)

About: Task (computing) is a research topic. Over the lifetime, 9718 publications have been published within this topic receiving 129364 citations.

Turkomatic: automatic, recursive task and workflow design for mechanical turk

Abstract: On today's human computation systems, designing tasks and workflows is a difficult and labor-intensive process. Can workers from the crowd be used to help plan workflows? We explore this question with Turkomatic, a new interface to microwork platforms that uses crowd workers to help plan workflows for complex tasks. Turkomatic uses a general-purpose divide-and-conquer algorithm to solve arbitrary natural-language requests posed by end users. The interface includes a novel real-time visual workflow editor that enables requesters to observe and edit workflows while the tasks are being completed. Crowd verification of work and the division of labor among members of the crowd can be handled automatically by Turkomatic, which substantially simplifies the process of using human computation systems. These features enable a novel means of interaction with crowds of online workers to support successful execution of complex work.

Amended hybrid multi-verse optimizer with genetic algorithm for solving task scheduling problem in cloud computing

Abstract: The central cloud facilities based on virtual machines offer many benefits to reduce the scheduling costs and improve service availability and accessibility. The approach of cloud computing is practical due to the combination of security features and online services. In the tasks transfer, the source and target domains have differing feature spaces. This challenge becomes more complicated in network traffic, which leads to data transfer delay, and some critical tasks could not deliver at the right time. This paper proposes an efficient optimization method for task scheduling based on a hybrid multi-verse optimizer with a genetic algorithm called MVO-GA. The proposed MVO-GA is proposed to enhance the performance of tasks transfer via the cloud network based on cloud resources' workload. It is necessary to provide adequate transfer decisions to reschedule the transfer tasks based on the gathered tasks' efficiency weight in the cloud. The proposed method (MVO-GA) works on multiple properties of cloud resources: speed, capacity, task size, number of tasks, number of virtual machines, and throughput. The proposed method successfully optimizes the task scheduling of a large number of tasks (i.e., 1000–2000). The proposed MVO-GA got promising results in optimizing the large cloud tasks' transfer time, which reflects its effectiveness. The proposed method is evaluated based on using the simulation environment of the cloud using MATLAB distrusted system.

Strategic capacity sharing between two tasks: evidence from tasks with the same and with different task sets

Abstract: The goal of the present study was to investigate the costs and benefits of different degrees of strategic parallel processing between two tasks In a series of experiments with the dual-task flanker paradigm, participants were either instructed to process the tasks serially or in parallel, or—in a control condition—they received no specific instruction Results showed that the participants were able to adjust the degree of parallel processing as instructed in a flexible manner Parallel processing of the two tasks repeatedly led to large costs in performance and to high crosstalk effects compared to more serial processing In spite of the costs, a moderate degree of parallel processing was preferred in the condition with no specific instruction This pattern of results was observed if the same task set was used for the two tasks, but also if different ones were applied Furthermore, a modified version of the central capacity sharing (CCS) model (Tombu and Jolicoeur in J Exp Psychol Hum Percept Perform 29:3–18, 2003) was proposed that accounts also for crosstalk effects in dual tasks The modified CCS model was then evaluated by fitting it successfully to the present data

Information processing apparatus, processing method thereof, and power supply control method therefor

Abstract: An information processing apparatus, which operates in a multi-task mode, calculates a total consumption power of devices used by each task, and assigns higher execution priority to a task which uses a device with the largest consumption power, thereby shortening the execution time of the device with the largest consumption power, and suppressing the total consumption power of the apparatus. When a device is started upon switching of tasks, if the total consumption power exceeds the allowable power of the apparatus by a power consumed upon restarting of the device, the task is set in a waiting state until operations of other devices are completed, the consumption power is lowered, and it is ready to use the device by the task.

Efficient channel and control unit for host computer

Abstract: An I/O system including a processor, a multitasking operating system and DMA hardware efficiently controls a transfer of data between a main memory and memories of different types of devices by minimizing context switches between tasks and wait times of the tasks. A plurality of validation routines are used to validate a plurality of commands when the validation routines are called. Each of the commands corresponds to a specific type of I/O operation and a specific one of the device memories to participate in the I/O operation with the main memory. Each of the validation routines is device type specific and command type specific. A general routine responds to each of the commands by identifying and calling the validation routine which corresponds to the type of I/O operation and type of device which are specified in the command. The general routine initiates I/O hardware after the validation routine validates the command. After the I/O hardware completes the I/O operation, it signals a command completion routine which is command specific and device type specific. In response, the command completion routine signals to the general routine a state of the I/O operation. Each of the validation routines executes on the same task as the general routine to minimize context switches, and each of the command completion routines executes on a different task than the general routine to minimize wait time for the command completion routine.