Mapping Abstract Complex Workflows onto Grid Environments

By Ewa Deelman, J. Blythe, Yolanda Gil, Carl Kesselman, Gaurang Mehta, Karan Vahi, Kent Blackburn, A. Lazzarini, A. Arbree, R. Cavanaugh and 1 more. Journal of Grid Computing, 2003

561 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Information Systems and Management, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/2870e7b0c569359727c7daf288c74cf46cfa921d

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

1. Rajkumar Buyya
2. Jia Yu
3. Ewa Deelman
4. Jun Zhang
5. Gaurang Mehta
6. Wei-neng Chen
7. Karan Vahi
8. John Good

In Information Systems and Management

1. Rajkumar Buyya
2. Jia Yu
3. Ewa Deelman
4. Jun Zhang
5. Wei-neng Chen
6. Chen-Khong Tham
7. John Good
8. Gurmeet Singh

In Management Science and Operations Research

1. Rajkumar Buyya
2. Jia Yu
3. Aram Galstyan
4. Kristina Lerman
5. Jun Zhang

Citations in the corpus

• A taxonomy of scientific workflow systems for grid computing (2005, unknown): “Pegasus [6] DAG Abstract User-directed”
• An Ant Colony Optimization Approach to a Grid Workflow Scheduling Problem With Various QoS Requirements (2009, methodology): “In this four-level model, mapping the abstract workflow into the concrete workflow with QoS considerations is the most important step in grid applications [34].”
• Pegasus: A framework for mapping complex scientific workflows onto distributed systems (2005, background): “Many applications today are being built by large scientific collaborations such as those in physics [1] [2], astronomy [3], biology [4], earthquake science [5], and many others.”
• Cost-based scheduling of scientific workflow applications on utility grids (2005, background): “Grids Proceedings of the First International Conference on e-Science and Grid Computing (e-Science'05) 0-7695-2448-6/05 $20.00 © 2005 IEEE major steps in workflow scheduling: performance estimation, workflow planning and workflow execution with run-time rescheduling.”
• GreenSlot: Scheduling energy consumption in green datacenters (2011, methodology): “Then, we present our model for solar energy prediction and discuss how GreenSlot adjusts the predictions when it finds inaccuracies.”
• Scheduling scientific workflow applications with deadline and budget constraints using genetic algorithms (2006, methodology): “workflow management systems [6,8,14,16,19,21,26, 30] with scheduling algorithms have been developed.”
• A Taxonomy of Workflow Management Systems for Grid Computing (2005, methodology): “Pegasus [40][41][42] (Planning for Execution in Grids) is a workflow manger in GriPhyN developed by the University of Southern California.”
• Resource allocation in the grid using reinforcement learning (2004, methodology): “A more sophisticated planning component uses AI techniques to forward plan optimal placement of all components of such a complex workflow [12].”