Workflows are widely used in applications that require coordinated use of computational
resources. Workflow definition languages typically abstract over some aspects of the way in …

Volunteer computing systems offer high computing power to the scientific communities to run
large data intensive scientific workflows. However, these computing environments provide …

Task clustering has proven to be an effective method to reduce execution overhead and to
improve the computational granularity of scientific workflow tasks executing on distributed …

Scientific workflow systems are increasingly used to automate complex data analyses,
largely due to their benefits over traditional approaches for workflow design, optimization …

For optimizing resources for a parallel data integration job, a job request is received, which
specifies a parallel data inte gration job to deploy in a grid. Grid resource utilizations are …

High computation power is required to execute complex scientific workflows. Cloud
computing resources are used viably to perform such complex workflows. Task clustering …

Scientific workflows are a topic of great interest in the grid community that sees in the
workflow model an attractive paradigm for programming distributed wide-area grid …

The recent increased use of workflow management systems by large scientific
collaborations presents the challenge of scheduling large-scale workflows onto distributed …

This paper aims to address the problem of scheduling large workflows onto multiple
execution sites with storage constraints. Three heuristics are proposed to first partition the …

Scientists increasingly rely on the execution of workflows in grids to obtain results from
complex mixtures of applications. However, the inherently dynamic nature of grid workflow …