University of Birmingham > Talks@bham > Artificial Intelligence and Natural Computation seminars > Hierarchic Genetic-Based Scheduler of Independent Jobs in Computational Grids

Hierarchic Genetic-Based Scheduler of Independent Jobs in Computational Grids

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In this talk we will focus on resolution methods, namely meta-heuristic approaches for solving Grid Scheduling problems. Genetic Algorithms, and specifically an implementation of Hierarchic Genetic Strategy (HGS) for Independent Job Scheduling in Computational Grids will be presented. In HGS approach both makespan and flowtime parameters are simultaneously optimized. Our objective is to present the results of a simple experimental and theoretical analysis of HGS -scheduler and compare its efficiency with some selected single-population genetic algorithms for the benchmark of static scheduling in Grids.

This talk is part of the Artificial Intelligence and Natural Computation seminars series.

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