Genetic-Based solutions for independent batch scheduling in Data Grids
Autor
Kołodziej, Joanna
Szmajduch, Magdalena
Khan, Samee U.
Wang, Lizhe
Chen, Dan
Data wydania
2013
Miejsce wydania
[Norway]
Wydawca
EMCS
Opublikowane w
ECMS 2013 : 27th European Conference on Modelling and Simulation, Aalesund, Norway, May 27th–30th, 2013 : proceedings / W. Rekdalsbakken, R. T. Bye, H. Zhang
Język
angielski
ISBN
978-0-9564944-6-7
DOI
10.7148/2013
Słowa kluczowe
Data Grid, scheduling, Data Center, expected time to transmit, data replication, genetic algorithm
Abstrakt
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.
