Topic
Workflow
About: Workflow is a research topic. Over the lifetime, 31996 publications have been published within this topic receiving 498339 citations.
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TL;DR: A novel service workflow reconfiguration architecture is designed to provide guidance, which ranges from monitoring to recommendations for project implementation, and experiments are conducted to demonstrate the effectiveness and efficiency of the proposed method.
97 citations
16 Nov 2014
TL;DR: The Skyport data analysis platform that provides scalable workflow execution environments for scientific data in the cloud, Skyport greatly reduces the complexity associated with providing the environment necessary to execute complex workflows.
Abstract: Recently, Linux container technology has been gaining attention as it promises to transform the way software is developed and deployed. The portability and ease of deployment makes Linux containers an ideal technology to be used in scientific workflow platforms. Skyport utilizes Docker Linux containers to solve software deployment problems and resource utilization inefficiencies inherent to all existing scientific workflow platforms. As an extension to AWE/Shock, our data analysis platform that provides scalable workflow execution environments for scientific data in the cloud, Skyport greatly reduces the complexity associated with providing the environment necessary to execute complex workflows.
97 citations
23 May 2011
TL;DR: A decentralized economic approach for dynamically adapting the cloud resources of various applications, so as to statistically meet their SLA performance and availability goals in the presence of varying loads or failures is proposed.
Abstract: Significant achievements have been made for automated allocation of cloud resources. However, the performance of applications may be poor in peak load periods, unless their cloud resources are dynamically adjusted. Moreover, although cloud resources dedicated to different applications are virtually isolated, performance fluctuations do occur because of resource sharing, and software or hardware failures (e.g. unstable virtual machines, power outages, etc.). In this paper, we propose a decentralized economic approach for dynamically adapting the cloud resources of various applications, so as to statistically meet their SLA performance and availability goals in the presence of varying loads or failures. According to our approach, the dynamic economic fitness of a Web service determines whether it is replicated or migrated to another server, or deleted. The economic fitness of a Web service depends on its individual performance constraints, its load, and the utilization of the resources where it resides. Cascading performance objectives are dynamically calculated for individual tasks in the application workflow according to the user requirements. By fully implementing our framework, we experimentally proved that our adaptive approach statistically meets the performance objectives under peak load periods or failures, as opposed to static resource settings.
97 citations
06 Sep 2000
TL;DR: This paper introduces and advocates the use of interacting proclets, i.e., light-weight workflow processes, by promoting interactions to first-class citizens to model complex workflows in a more natural manner, with improved expressive power and flexibility.
Abstract: The focus of traditional workflow management systems is on control flow within one process definition, that describes how a single case (i.e., work-flow instance) is handled in isolation. For many applications this paradigm is inadequate. Interaction between cases is at least as important. This paper introduces and advocates the use of interacting proclets, i.e., light-weight workflow processes. By promoting interactions to first-class citizens, it is possible to model complex workflows in a more natural manner, with improved expressive power and flexibility.
97 citations
31 Jan 2020
TL;DR: This paper argues that FAIR principles for workflows need to address their specific nature in terms of their composition of executable software steps, their provenance, and their development.
Abstract: Computational workflows describe the complex multi-step methods that are used for data collection, data preparation, analytics, predictive modelling, and simulation that lead to new data products. ...
97 citations