Workflows have been used to model repeatable tasks or operations in manufacturing, business process, and software. In recent years, workflows are increasingly used for orchestration of science discovery tasks that use distributed resources and web services environments through resource models such as grid and cloud computing. Workflows have disparate re uirements and constraints that affects how they might be managed in distributed environments. In this paper, we present a multi-dimensional classification model illustrated by workflow examples obtained through a survey of scientists from different domains including bioinformatics and biomedical, weather and ocean modeling, astronomy detailing their data and computational requirements. The s...
Data-intensive scientific applications are posing many challenges in distributed computing systems. ...
eRunning scientific workflow applications usually need not only high performance computing resources...
e-Science usually involves a great number of data sets, computing resources, and large teams managed...
Abstract: Researchers working on the planning, scheduling, and execution of scientific workflows nee...
e-Science is a buzz word when it comes to connecting different kinds of sciences and communities wit...
Scientific workflow systems have become a necessary tool for many applications, enabling the composi...
Workflows have been used traditionally as a mean to describe and implement the computing usually par...
Workflows have recently emerged as a paradigm for representing and managing complex distributed scie...
Modern scientific collaborations have opened up the opportunity to solve complex problems that requi...
Workflow technologies are emerging as the dominant approach to coordinate groups of distributed serv...
In recent years, a number of scientific workflow management systems (SWFMSs) have been developed to ...
Automation of the execution of computational tasks is at the heart of improving scientific productiv...
Automation in science is increasingly marked by the use of workflow technology. The sharing of workf...
The wide availability of high-performance computing systems, Grids and Clouds, allowed scientists an...
Scientific workflows have recently emerged as a new paradigm for representing and managing complex d...
Data-intensive scientific applications are posing many challenges in distributed computing systems. ...
eRunning scientific workflow applications usually need not only high performance computing resources...
e-Science usually involves a great number of data sets, computing resources, and large teams managed...
Abstract: Researchers working on the planning, scheduling, and execution of scientific workflows nee...
e-Science is a buzz word when it comes to connecting different kinds of sciences and communities wit...
Scientific workflow systems have become a necessary tool for many applications, enabling the composi...
Workflows have been used traditionally as a mean to describe and implement the computing usually par...
Workflows have recently emerged as a paradigm for representing and managing complex distributed scie...
Modern scientific collaborations have opened up the opportunity to solve complex problems that requi...
Workflow technologies are emerging as the dominant approach to coordinate groups of distributed serv...
In recent years, a number of scientific workflow management systems (SWFMSs) have been developed to ...
Automation of the execution of computational tasks is at the heart of improving scientific productiv...
Automation in science is increasingly marked by the use of workflow technology. The sharing of workf...
The wide availability of high-performance computing systems, Grids and Clouds, allowed scientists an...
Scientific workflows have recently emerged as a new paradigm for representing and managing complex d...
Data-intensive scientific applications are posing many challenges in distributed computing systems. ...
eRunning scientific workflow applications usually need not only high performance computing resources...
e-Science usually involves a great number of data sets, computing resources, and large teams managed...