Topic
Workflow
About: Workflow is a research topic. Over the lifetime, 31996 publications have been published within this topic receiving 498339 citations.
Papers published on a yearly basis
Papers
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TL;DR: The goal is to provide timeliness and energy efficiency by trading off result precision, while keeping the result quality of the completed jobs at an acceptable standard and the monetary cost required for the execution of the jobs at a reasonable level.
92 citations
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29 Sep 2020
TL;DR: Wang et al. as mentioned in this paper studied implicit knowledge in industrial Internet of things (IIoT) by using collaborative learning techniques, considering the increased dimensions and dynamics of IoT devices, and explored the possible relationships between users and between APIs.
Abstract: The industrial Internet of things (IIoT), a new computing mode in Industry 4.0, is deployed to connect IoT devices and use communication technology to respond to control commands and handle industrial data. IIoT is typically employed to improve the efficiency of computing and sensing and can be used in many scenarios, such as intelligent manufacturing and video surveillance. To build an IIoT system, we need a collection of software to manage and monitor each system component when there are large-scale devices. Application programming interface (API) is an effective way to invoke public services provided by different platforms. Developers can invoke different APIs to operate IoT devices without knowing the implementation process. We can design a workflow to configure how and when to invoke target APIs. Thus, APIs are a powerful tool for rapidly developing industrial systems. However, the increasing number of APIs exacerbates the problem of finding suitable APIs. Current related recommendation methods have defects. For example, most existing methods focus on the relation between users and APIs but neglect the valuable relations among the users or APIs themselves. To address these problems, this article studies implicit knowledge in IIoT by using collaborative learning techniques. Considering the increased dimensions and dynamics of IoT devices, we explore the possible relationships between users and between APIs. We enhance the matrix factorization (MF) model with the mined implicit knowledge that are implicit relationships on both sides. We build an ensemble model by using all implicit knowledge. We conduct experiments on a collected real-world dataset and simulate industrial system scenarios. The experimental results verify the effectiveness and superiority of the proposed models.
92 citations
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TL;DR: Signac as discussed by the authors is a framework designed to assist in the integration of various specialized data formats, tools and workflows, simplifying data access and modification through a homogeneous data interface that is largely agnostic to the data source.
92 citations
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27 Aug 2006TL;DR: A trace-based semantic model for Orc is shown, which induces a congruence on Orc programs and facilitates reasoning about them, and allows for a variety of useful orchestration tasks.
Abstract: Orc is a new language for task orchestration, a form of concurrent programming with applications in workflow, business process management, and web service orchestration. Orc provides constructs to orchestrate the concurrent invocation of services – while managing time-outs, priorities, and failure of services or communication. In this paper, we show a trace-based semantic model for Orc, which induces a congruence on Orc programs and facilitates reasoning about them. Despite the simplicity of the language and its semantic model, Orc is able to express a variety of useful orchestration tasks.
91 citations
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TL;DR: This article has discussed the existing workflow systems and the trends in applications of workflow based systems.
91 citations