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

Fingerprint

Data Partitioning
Real-coded Genetic Algorithm
Release Time
Genetic algorithms
Scheduling
Divisible Loads
Computer Communication Networks
Load Distribution
Combinatorial optimization
Distributed computer systems
Arbitrary
Processing
Distributed Computing
Combinatorial Optimization Problem
Genetic Algorithm
Entire

ASJC Scopus subject areas

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

Cite this

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

A real coded genetic algorithm for data partitioning and scheduling in networks with arbitrary processor release time. / Suresh, S.; Mani, V.; Omkar, S. N.; Kim, Hyong Joong.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 3740 LNCS 2005. p. 529-539 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3740 LNCS).

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

Suresh, S, Mani, V, Omkar, SN & Kim, HJ 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, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3740 LNCS, pp. 529-539, 10th Asia-Pacific Conference on Advances in Computer Systems Architecture, ACSAC 2005, Singapore, Singapore, 05/10/24. https://doi.org/10.1007/11572961_43
Suresh S, Mani V, Omkar SN, Kim HJ. 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. 2005. p. 529-539. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/11572961_43
Suresh, S. ; Mani, V. ; Omkar, S. N. ; Kim, Hyong Joong. / A real coded genetic algorithm for data partitioning and scheduling in networks with arbitrary processor release time. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 3740 LNCS 2005. pp. 529-539 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
@inproceedings{e06b213283d845b1b7432e692891a0d2,
title = "A real coded genetic algorithm for data partitioning and scheduling in networks with arbitrary processor release time",
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.",
author = "S. Suresh and V. Mani and Omkar, {S. N.} and Kim, {Hyong Joong}",
year = "2005",
doi = "10.1007/11572961_43",
language = "English",
isbn = "3540296433",
volume = "3740 LNCS",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "529--539",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

}

TY - GEN

T1 - A real coded genetic algorithm for data partitioning and scheduling in networks with arbitrary processor release time

AU - Suresh, S.

AU - Mani, V.

AU - Omkar, S. N.

AU - Kim, Hyong Joong

PY - 2005

Y1 - 2005

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=33646508555&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=33646508555&partnerID=8YFLogxK

U2 - 10.1007/11572961_43

DO - 10.1007/11572961_43

M3 - Conference contribution

AN - SCOPUS:33646508555

SN - 3540296433

SN - 9783540296430

VL - 3740 LNCS

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 529

EP - 539

BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

ER -