Grid Resource Management

1. Front Matter

   Pages i-xxi

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2. Introduction to Grids and Resource Management

   1. Front Matter

      Pages 1-1

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   2. The Grid in a Nutshell

      • Ian Foster, Carl Kesselman

      Pages 3-13

   3. Ten Actions When Grid Scheduling

      • Jennifer M. Schopf

      Pages 15-23

   4. Application Requirements for Resource Brokering in a Grid Environment

      • Michael Russell, Gabrielle Allen, Tom Goodale, Jarek Nabrzyski, Ed Seidel

      Pages 25-40

   5. Attributes for Communication Between Grid Scheduling Instances

      • Uwe Schwiegelshohn, Ramin Yahyapour

      Pages 41-52

   6. Security Issues of Grid Resource Management

      • Mary R. Thompson, Keith R. Jackson

      Pages 53-69

3. Resource Management in Support of Collaborations

   1. Front Matter

      Pages 71-71

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   2. Scheduling in the Grid Application Development Software Project

      • Holly Dail, Otto Sievert, Fran Berman, Henri Casanova, Asim YarKhan, Sathish Vadhiyar et al.

      Pages 73-98

   3. Workflow Management in Griphyn

      • Ewa Deelman, James Blythe, Yolanda Gil, Carl Kesselman

      Pages 99-116

4. State of the Art Grid Resource Management

   1. Front Matter

      Pages 117-117

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   2. Grid Service Level Agreements

      • Karl Czajkowski, Ian Foster, Carl Kesselman, Steven Tuecke

      Pages 119-134

   3. Condor and Preemptive Resume Scheduling

      • Alain Roy, Miron Livny

      Pages 135-144

   4. Grid Resource Management in Legion

      • Anand Natrajan, Marty A. Humphrey, Andrew S. Grimshaw

      Pages 145-160

   5. Grid Scheduling with Maui/Silver

      • David B. Jackson

      Pages 161-170

   6. Scheduling Attributes and Platform LSF

      • Ian Lumb, Chris Smith

      Pages 171-182

   7. PBS Pro: Grid Computing and Scheduling Attributes

      • Bill Nitzberg, Jennifer M. Schopf, James Patton Jones

      Pages 183-190

5. Prediction and Matching for Grid Resource Management

   1. Front Matter

      Pages 191-191

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   2. Performance Information Services for Computational Grids

      • Rich Wolski, Lawrence J. Miller, Graziano Obertelli, Martin Swany

      Pages 193-213

   3. Using Predicted Variance for Conservative Scheduling on Shared Resources

      • Jennifer M. Schopf, Lingyun Yang

      Pages 215-236

Grid Resource Management: State of the Art and Future Trends presents an overview of the state of the field and describes both the real experiences and the current research available today. Grid computing is a rapidly developing and changing field, involving the shared and coordinated use of dynamic, multi-institutional resources. Grid resource management is the process of identifying requirements, matching resources to applications, allocating those resources, and scheduling and monitoring Grid resources over time in order to run Grid applications as efficiently as possible.
While Grids have become almost commonplace, the use of good Grid resource management tools is far from ubiquitous because of the many open issues of the field, including the multiple layers of schedulers, the lack of control over resources, the fact that resources are shared, and that users and administrators have conflicting performance goals.

• Operations Research
• QoS
• Scheduling
• Workflow Management
• algorithms
• architecture
• metaheuristic
• security

• Poznań Supercomputing and Networking Center, Poland

  Jarek Nabrzyski

• Argonne National Laboratory, USA

  Jennifer M. Schopf

• Institute of Computing Science, Poznań University of Technology, Poland

  Jan Węglarz

Policies and ethics