Genetic-Based solutions for independent batch scheduling in Data Grids
Author
Kołodziej, Joanna
Szmajduch, Magdalena
Khan, Samee U.
Wang, Lizhe
Chen, Dan
Release date
2013
Place of publication
[Norway]
Publisher
EMCS
Published in
ECMS 2013 : 27th European Conference on Modelling and Simulation, Aalesund, Norway, May 27th–30th, 2013 : proceedings / W. Rekdalsbakken, R. T. Bye, H. Zhang
Language
English
ISBN
978-0-9564944-6-7
DOI
10.7148/2013
Keywords
Data Grid, scheduling, Data Center, expected time to transmit, data replication, genetic algorithm
Abstract
Scheduling in traditional distributed systems has been mainly studied for system performance parameters without data transmission requirements. With the emergence of Data Grids (DGs) and Data Centers, data-aware scheduling has become a major research issue. In this work we present two implementations of classical genetic-based data-aware schedulers of independent tasks submitted to the grid environment. The results of a simple. empirical analysis confirm the high effectiveness of the genetic algorithms in solving very complex data intensive combinatorial optimization problems.
PKT classification
410000 Informatyka
Department
Faculty of Physics, Mathematics and Computer Science
