Task (computing)

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

Flexible and extensible combination user interfaces

Abstract: Flexible and extensible combination user interfaces are described. Combination user interfaces combine task-based and deductive user interfaces in such a manner that complex user interactions can be facilitated using a more meaningful and intuitive user interface than would have been possible using task-based or deductive user interfaces exclusively. The described combination user interfaces are flexible and extensible. They are flexible in that users can work on multiple tasks or switch between tasks without first needing to complete another task. They are extensible in that they can be extended to add, modify, or remove tasks or portions of tasks. User interfaces can be extended by manipulating metadata associated with the user interfaces. The combination user interface can be combined with an Inbox concept to facilitate saving and assigning tasks. The Inbox represents a work queue for a user.

Prioritized multi-task motion control of redundant robots under hard joint constraints

Abstract: We present an efficient method for motion control of redundant robots performing multiple prioritized tasks in the presence of hard bounds on joint range, velocity, and acceleration/ torque. This is an extension of our recently proposed SNS (Saturation in the Null Space) algorithm developed for single tasks. The method is defined at the level of acceleration commands and proceeds by successively discarding one at a time the commands that would exceed their bounds for a task of given priority, and reintroducing them at their saturated levels by projection in the null space of a suitable Jacobian associated to the already considered tasks. When processing all tasks in their priority order, a correct preemptive strategy is realized in this way, i.e., a task of higher priority uses in the best way the feasible robot capabilities it needs, while lower priority tasks are accommodated with the residual capability and do not interfere with the execution of higher priority tasks. The algorithm automatically integrates a multi-task least possible scaling strategy, when some ordered set of original tasks is found to be unfeasible. Simulation and experimental results on a 7-dof lightweight KUKA LWR IV robot illustrate the good performance of the method.

Task allocation for distributed stream processing

Abstract: There is a growing demand for live, on-the-fly processing of increasingly large amounts of data. In order to ensure the timely and reliable processing of streaming data, a variety of distributed stream processing architectures and platforms have been developed, which handle the fundamental tasks of (dynamically) assigning processing tasks to the currently available physical resources and routing streaming data between these resources. However, while there are plenty of platforms offering such functionality, the theory behind it is not well understood. In particular, it is unclear how to best allocate the processing tasks to the given resources. In this paper, we establish a theoretical foundation by formally defining a task allocation problem for distributed stream processing, which we prove to be NP-hard. Furthermore, we propose an approximation algorithm for the class of series-parallel decomposable graphs, which captures a broad range of common stream processing applications. The algorithm achieves a constant-factor approximation under the assumptions that the number of resources scales at least logarithmically with the number of computational tasks and the computational cost of the tasks dominates the cost of communication.

POST: Parallel Offloading of Splittable Tasks in Heterogeneous Fog Networks

Abstract: Fog computing has been promoted to support delay-sensitive applications in future Internet of Things (IoT). For a general heterogeneous fog network consisting of many dispersive fog nodes (FNs), it may well happen that some of them have delay-sensitive tasks to process, i.e., task nodes (TNs), and some have spare resources to help the TNs to process tasks, i.e., helper nodes (HNs). It remains a fundamental challenge to effectively map multiple tasks or TNs into multiple HNs to minimize every task’s service delay in a distributed manner, i.e., the multitask multihelper (MTMH) problem. The problem becomes more challenging as tasks are splittable, i.e., tasks can be divided into multiple subtasks and offloaded to multiple HNs to further reduce the service delay via the scheme similar to distributed computing, because it introduces the more complicated task division problem which results in a much larger and more complex solution space. To tackle this challenge, in this article, a generalized Nash equilibrium problem (GNEP), called parallel offloading of splittable tasks (POST), is formulated and studied thoroughly. The structural properties of the problem are characterized and thus the existence of generalized Nash equilibrium (GNE) is proven via the fixed-point theorem. Furthermore, the corresponding distributed task offloading algorithm is developed via the Gauss–Seidel-type method. The simulation results show that the proposed POST algorithm can offer much better performance in terms of the system average delay, individual delay, delay reduction ratio (DRR), and number of beneficial TNs, compared with the existing solution to the counterpart problem for nonsplittable tasks.

Reliability-aware Co-synthesis for Embedded Systems

Abstract: As technology scales, transient faults have emerged as a key challenge for reliable embedded system design. This paper proposes a design methodology that incorporates reliability into hardware---software co-design paradigm for embedded systems. We introduce an allocation and scheduling algorithm that efficiently handles conditional execution in multi-rate embedded systems, and selectively duplicates critical tasks to detect or correct transient errors, such that the reliability of the system is improved. Two methods are proposed to insert duplicated tasks into the schedule. The improved reliability is achieved by utilizing the otherwise idle computation resources and taking advantage of the overlapping schedule for mutually exclusive tasks in the conditional task graph, such that it incurs no resource or performance penalty.