A Pareto Frontier for Optimizing Data Transfer and Job Execution in Grids

Abstract

This work presents a Genetic Algorithm (GA) based optimization technique, called GA-ParFnt, to find the Pareto frontier for optimizing data transfer versus job execution time in grids. As the performance of a generic GA is not suitable to find such Pareto relationship, several modifications are applied to it so that it can efficiently discover such… (More)
DOI: 10.1109/IPDPSW.2012.263

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Cite this paper

@article{Taheri2012APF, title={A Pareto Frontier for Optimizing Data Transfer and Job Execution in Grids}, author={Javid Taheri and Albert Y. Zomaya}, journal={2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops & PhD Forum}, year={2012}, pages={2130-2139} }