24. Experimental Study of GA-Based Schedulers in Dynamic Distributed Computing Environments

  1. Enrique Alba2,
  2. Christian Blum3,
  3. Pedro Isasi4,
  4. Coromoto León5 and
  5. Juan Antonio Gómez6
  1. F. Xhafa3 and
  2. J. Carretero1

Published Online: 16 MAY 2008

DOI: 10.1002/9780470411353.ch24

Optimization Techniques for Solving Complex Problems

Optimization Techniques for Solving Complex Problems

How to Cite

Xhafa, F. and Carretero, J. (2009) Experimental Study of GA-Based Schedulers in Dynamic Distributed Computing Environments, in Optimization Techniques for Solving Complex Problems (eds E. Alba, C. Blum, P. Isasi, C. León and J. A. Gómez), John Wiley & Sons, Inc., Hoboken, NJ, USA. doi: 10.1002/9780470411353.ch24

Editor Information

  1. 2

    Universidad de Málaga, Dpto. de Lenguajes y Ciencias de la Computación, Málaga, Spain

  2. 3

    Universitat Politècnica de Catalunya, Dpto. de Llenguatges i Sistemes Informàtics, Barcelona, Spain

  3. 4

    Universidad Carlos III de Madrid, Dpto. de Informática, Escuela Politécnica Superior, Madrid, Spain

  4. 5

    Universidad de La Laguna, Dpto. de Estadística, I.O. y Computación, La Laguna, Spain

  5. 6

    Universidad de Extremadura, Dpto. de Tecnologías de Computadores y Comunicaciones, Escuela Politécnica, Cáceres, Spain

Author Information

  1. 1

    Universitat Politècnica de Catalunya, Dpto. d'Arquitectura de Computadors, Barcelona, Spain

  2. 3

    Universitat Politècnica de Catalunya, Dpto. de Llenguatges i Sistemes Informàtics, Barcelona, Spain

Publication History

  1. Published Online: 16 MAY 2008
  2. Published Print: 6 FEB 2009

Book Series:

  1. Wiley Series on Parallel and Distributed Computing

Book Series Editors:

  1. Albert Y. Zomaya

ISBN Information

Print ISBN: 9780470293324

Online ISBN: 9780470411353

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Keywords:

  • minimum completion time (MCT);
  • GA-based scheduler;
  • expected time to compute (ETC)

Summary

This chapter contains sections titled:

  • Introduction

  • Related Work

  • Independent Job Scheduling Problem

  • Genetic Algorithms for Scheduling in Grid Systems

  • Grid Simulator

  • Interface for Using a GA-Based Scheduler with the Grid Simulator

  • Experimental Analysis

  • Conclusions

  • References