Database Reference
In-Depth Information
Chapter 13
Scientific Process Automation
and Workflow Management
Bertram Ludascher,
1
Ilkay Altintas,
2
Shawn Bowers,
1
Julian Cummings,
3
Terence Critchlow,
4
Ewa Deelman,
5
David De Roure,
6
Juliana Freire,
10
Carole Goble,
7
Matthew Jones,
8
Scott Klasky,
9
Timothy McPhillips,
1
Norbert Podhorszki,
9
Claudio Silva,
10
Ian Taylor,
11
and Mladen Vouk
12
1
University of California, Davis
2
San Diego Supercomputer Center
3
California Institute of Technology, Pasadena
4
Pacific Northwest National Laboratory
5
USC Information Science Institute, Marina del Rey
6
University of Southampton, United Kingdom
7
The University of Manchester, United Kingdom
8
University of California, Santa Barbara
9
Oak Ridge National Laboratory
10
University of Utah
11
Cardiff University, United Kingdom
12
North Carolina State University
Contents
13.1 Introduction
..........................................................
468
13.2 Features of Scientific Workflows
.....................................
470
13.2.1 The Scientific Workflow Life Cycle
...........................
470
.................................
13.2.2 Types of Scientific Workflows
471
.......................................
13.2.3 Models of Computation
472
13.2.4 Benefits of Scientific Workflows
..............................
473
13.3 Case Study: Fusion Simulation Management
........................
474
13.3.1 Overview of the Simulation Monitoring Workflow
...........
475
13.3.2 Issues in Simulation Management
............................
478
13.4 Grid Workflows and the Scientific Workflow Life Cycle
.............
481
13.4.1 Workflow Design and Composition
...........................
481
13.4.2 Mapping Workflows to Resources
............................
484
13.4.3 Workflow Execution
..........................................
486
467
