Real-coded genetic algorithms for optimal static load balancing in distributed computing system with communication delays

V. Mani; S. Suresh; H. J. Kim

doi:10.1007/11424925_30

Real-coded genetic algorithms for optimal static load balancing in distributed computing system with communication delays

V. Mani, S. Suresh, H. J. Kim

Research output: Contribution to journal › Conference article › peer-review

9 Citations (Scopus)

Abstract

We consider the problem of static load balancing with the objective of minimizing the job response times. The jobs that arrive at a central scheduler are allocated to various processors in the system with certain probabilities. This optimization problem is solved using real-coded genetic algorithms. A comparison of this approach with the standard optimization methods are presented.

Original language	English
Pages (from-to)	269-279
Number of pages	11
Journal	Lecture Notes in Computer Science
Volume	3483
Issue number	IV
DOIs	https://doi.org/10.1007/11424925_30
Publication status	Published - 2005
Externally published	Yes
Event	International Conference on Computational Science and Its Applications - ICCSA 2005 - , Singapore Duration: 2005 May 9 → 2005 May 12

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

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10.1007/11424925_30

Cite this

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abstract = "We consider the problem of static load balancing with the objective of minimizing the job response times. The jobs that arrive at a central scheduler are allocated to various processors in the system with certain probabilities. This optimization problem is solved using real-coded genetic algorithms. A comparison of this approach with the standard optimization methods are presented.",

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AB - We consider the problem of static load balancing with the objective of minimizing the job response times. The jobs that arrive at a central scheduler are allocated to various processors in the system with certain probabilities. This optimization problem is solved using real-coded genetic algorithms. A comparison of this approach with the standard optimization methods are presented.

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M3 - Conference article

AN - SCOPUS:24944456856

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

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

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Y2 - 9 May 2005 through 12 May 2005

ER -

Real-coded genetic algorithms for optimal static load balancing in distributed computing system with communication delays

Abstract

ASJC Scopus subject areas

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