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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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Patent
15 May 2007
TL;DR: In this paper, the authors present a workflow management environment that provides different workflow management perspectives with different views on a variety of reusable workflow components or workflow resources, such as a swim lane view having multiple separate sections that each represents a different performer and a list view that represents the resources in transactional order.
Abstract: Methods and apparatuses enable providing a workflow management environment that provides different workflow management perspectives with different views on a variety of reusable workflow components or workflow resources. The different views may include a swim lane view having multiple separate sections that each represents a different performer, and a list view that represents the resources in transactional order. The workflow management environment defines reusable workflow components and associates the components with the different performers and with each other. The defining of the components and the relationships can define a portion of a workflow.

161 citations

Proceedings ArticleDOI
05 Jul 2010
TL;DR: SciCumulus is a cloud middleware that explores parameter sweep and data fragmentation parallelism in scientific workflow activities (with provenance support) and works between the SWfMS and the cloud.
Abstract: Most of the large-scale scientific experiments modeled as scientific workflows produce a large amount of data and require workflow parallelism to reduce workflow execution time. Some of the existing Scientific Workflow Management Systems (SWfMS) explore parallelism techniques - such as parameter sweep and data fragmentation. In those systems, several computing resources are used to accomplish many computational tasks in homogeneous environments, such as multiprocessor machines or cluster systems. Cloud computing has become a popular high performance computing model in which (virtualized) resources are provided as services over the Web. Some scientists are starting to adopt the cloud model in scientific domains and are moving their scientific workflows (programs and data) from local environments to the cloud. Nevertheless, it is still difficult for the scientist to express a parallel computing paradigm for the workflow on the cloud. Capturing distributed provenance data at the cloud is also an issue. Existing approaches for executing scientific workflows using parallel processing are mainly focused on homogeneous environments whereas, in the cloud, the scientist has to manage new aspects such as initialization of virtualized instances, scheduling over different cloud environments, impact of data transferring and management of instance images. In this paper we propose SciCumulus, a cloud middleware that explores parameter sweep and data fragmentation parallelism in scientific workflow activities (with provenance support). It works between the SWfMS and the cloud. SciCumulus is designed considering cloud specificities. We have evaluated our approach by executing simulated experiments to analyze the overhead imposed by clouds on the workflow execution time.

161 citations

Journal ArticleDOI
TL;DR: This paper discusses the current shortcomings of approaches in the light of virtual teamwork based on models and underlying metaphors and presents a novel approach for virtual teamwork by tightly integrating all associations between processes, artifacts, and resources.
Abstract: Organizations increasingly define many business processes as projects executed by “virtual (project) teams”, where team members from within an organization cooperate with “outside” experts. Virtual teams require and enable people to collaborate across geographical distance and professional (organizational) boundaries and have a somewhat stable team configuration with roles and responsibilities assigned to team members. Different people, coming from different organizations will have their own preferences and experiences and cannot be expected to undergo a long learning cycle before participating in team activities. Thus, efficient communication, coordination, and process-aware collaboration remain a fundamental challenge. In this paper we discuss the current shortcomings of approaches in the light of virtual teamwork (mainly Workflow, Groupware, and Project Management) based on models and underlying metaphors. Furthermore, we present a novel approach for virtual teamwork by tightly integrating all associations between processes, artifacts, and resources. In this paper we analyze (a) the relevant criteria for process-aware collaboration system metaphors, (b) coordination models and constructs for organizational structures of virtual teams as well as for ad hoc and collaborative processes composed out of tasks, and (c) architectural considerations as well as design and implementation issues for an integrated process-aware collaboration system for virtual teams on the Internet.

161 citations

Journal ArticleDOI
TL;DR: This work addresses the challenge to record uniform and usable provenance metadata that meets the domain needs while minimizing the modification burden on the service authors and the performance overhead on the workflow engine and the services.
Abstract: The increasing ability for the sciences to sense the world around us is resulting in a growing need for datadriven e-Science applications that are under the control of workflows composed of services on the Grid. The focus of our work is on provenance collection for these workflows that are necessary to validate the workflow and to determine quality of generated data products. The challenge we address is to record uniform and usable provenance metadata that meets the domain needs while minimizing the modification burden on the service authors and the performance overhead on the workflow engine and the services. The framework is based on generating discrete provenance activities during the lifecycle of a workflow execution that can be aggregated to form complex data and process provenance graphs that can span across workflows. The implementation uses a loosely coupled publish-subscribe architecture for propagating these activities, and the capabilities of the system satisfy the needs of detailed provenance collection. A performance evaluation of a prototype finds a minimal performance overhead (in the range of 1% for an eight-service workflow using 271 data products).

161 citations

Proceedings ArticleDOI
19 Sep 2007
TL;DR: This paper proposes a workflow execution planning approach using multi-objective evolutionary algorithms (MOEAs) to generate a set of trade-off scheduling solutions according to the users QoS requirements, and shows that MOEAs are able to find a range of compromise solutions in a short computational time.
Abstract: Utility grids create an infrastructure for enabling users to consume services transparently over a global network. When optimizing workflow execution on utility grids, we need to consider multiple quality of service (QoS) parameters including service prices and execution time. These optimization objectives may be in conflict. In this paper, we have proposed a workflow execution planning approach using multi-objective evolutionary algorithms (MOEAs). Our goal was to generate a set of trade-off scheduling solutions according to the users QoS requirements. The alternative trade-off solutions offer more flexibility to users when estimating their QoS requirements of workflow executions. Simulation results show that MOEAs are able to find a range of compromise solutions in a short computational time.

160 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20241
20234,414
20229,010
20211,461
20201,579
20191,702