Task (computing)

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

Determining storage tiers for placement of data sets during execution of tasks in a workflow

Abstract: Provided are a computer program product, system, and method for determining storage tiers for placement of data sets during execution of tasks in a workflow. A representation of a workflow execution pattern of tasks for a job indicates a dependency of the tasks and data sets operated on by the tasks. A determination is made of an assignment of the data sets for the tasks to a plurality of the storage tiers based on the dependency of the tasks indicated in the workflow execution pattern. A moving is scheduled of a subject data set of the data sets operated on by a subject task of the tasks that is subject to an event to an assigned storage tier indicated in the assignment for the subject task subject. The moving of the data set is scheduled to be performed in response to the event with respect to the subject task.

System and method for predictive idle-time task initiation

Abstract: A system automatically determines probable idle times for a computing system and performs maintenance tasks, such as virus scanning, during these times. A prediction of probable idle times is based on an assessment of a user's past use or by an aggregate of information from several users if a company wishes to determine optimal times for running such tasks or pushing software patches to employees. A policy table set by the user or a company determines the priority of maintenance tasks to be run during the predicted idle time.

Flexible Resource Assignment in Sensor Networks : A Hybrid Reasoning Approach

Abstract: Today, sensing resources3 are the most valuable assets of critical tasks (e.g., border monitoring). Although, there are various types of assets available, each with different capabilities, only a subset of these assets is useful for a specific task. This is due to the varying information needs of tasks. This gives rise to assigning useful assets to tasks such that the assets fully cover the information requirements of the individual tasks. The importance of this is amplified in the intelligence, surveillance, and reconnaissance (ISR) domain, especially in a coalition context. This is due to a variety of reasons such as the dynamic nature of the environment, scarcity of assets, high demand placed on available assets, sharing of assets among coalition parties, and so on. A significant amount of research been done by different communities to efficiently assign assets to tasks and deliver information to the end user. However, there is little work done to infer sound alternative means to satisfy the information requirements of tasks so that the satisfiable tasks are increased. In this paper, we propose a hybrid reasoning approach (viz., a combination of rule-based and ontology-based reasoning) based on current Semantic Web4 technologies to infer assets types that are necessary and sufficient to satisfy the requirements of tasks in a flexible manner.

Scalable transaction processing pipeline

Abstract: A system for processing a plurality of tasks is disclosed. Each task has a plurality of component subtasks. The system may process N tasks and each task includes a first subtask, and a second subtask. The system for processing the plurality of tasks comprises a scalable transaction processing pipeline (STPP). The STPP comprises a plurality of processing elements, including at least a first processing element and a second processing element, the first processing element is adapted to process the first subtask of each task. The second processing element is adapted to process the second subtask of each task. Each successive processing element is adapted to process a corresponding subtask or subtasks of each task. The first processing element processes the first subtask of each task. When the first processing element finishes the processing of the first subtask, the second processing element processes the second subtask of each task. The STPP further includes a plurality of data structures and a plurality of data managers. Each data manager is adapted to manage a data structure. An interconnect couples each processing element to at least one data manager. The interconnect manages the data flow between the interconnect and the processing elements, and between the interconnect and the data managers.

Stackelberg Game Based Incentive Mechanisms for Multiple Collaborative Tasks in Mobile Crowdsourcing

Abstract: In this paper, we tackle the problem of stimulating users to join mobile crowdsourcing applications with personal devices such as smartphones and tablets. Wireless personal networks facilitate to exploit the communication opportunity and makes diverse spare-resource of personal devices utilized. However, it is a challenge to motivate sufficient users to provide their resource of personal devices for achieving good quality of service. To address this problem, we propose an incentive framework based on Stackelberg game to model the interaction between the server and users. Traditional incentive mechanisms are applied for either single task or multiple dependent tasks, which fails to consider the interrelation among various tasks. In this paper, we focus on the common realistic scenario with multiple collaborative tasks, where each task requires a group of users to perform collaboratively. Specifically, participants would consider task priority and the server would design suitable reward functions to allocate the total payment. Considering the information of users' costs and the types of tasks, four incentive mechanisms are presented for various cases to the above problem, which are proved to have the Nash equilibrium solutions in all cases for maximizing the utility of the server. Moreover, online incentive mechanisms are further proposed for real time tasks. Through both rigid theoretical analysis and extensive simulations, we demonstrate that the proposed mechanisms have good performance and high computational efficiency in real world applications.