A real coded genetic algorithm for data partitioning and scheduling in networks with arbitrary processor release time

S. Suresh, V. Mani, S. N. Omkar, Hyong Joong Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

The problem of scheduling divisible loads in distributed computing systems, in presence of processor release time is considered. The objective is to find the optimal sequence of load distribution and the optimal load fractions assigned to each processor in the system such that the processing time of the entire processing load is a minimum. This is a difficult combinatorial optimization problem and hence genetic algorithms approach is presented for its solution.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages529-539
Number of pages11
Volume3740 LNCS
DOIs
Publication statusPublished - 2005
Externally publishedYes
Event10th Asia-Pacific Conference on Advances in Computer Systems Architecture, ACSAC 2005 - Singapore, Singapore
Duration: 2005 Oct 242005 Oct 26

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3740 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other10th Asia-Pacific Conference on Advances in Computer Systems Architecture, ACSAC 2005
CountrySingapore
CitySingapore
Period05/10/2405/10/26

ASJC Scopus subject areas

  • Computer Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Theoretical Computer Science

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    Suresh, S., Mani, V., Omkar, S. N., & Kim, H. J. (2005). A real coded genetic algorithm for data partitioning and scheduling in networks with arbitrary processor release time. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3740 LNCS, pp. 529-539). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3740 LNCS). https://doi.org/10.1007/11572961_43