Effective and efficient mapping algorithms for multisite parallel applications are fundamental to exploit the potentials of grid computing. Since the problem of optimally mapping is NP-complete, evolutionary techniques can help to find near-optimal solutions. Here a multiobjective Differential Evolution is investigated to face the mapping problem in a grid environment aiming at reducing the degree of use of the grid resources while, at the same time, maximizing Quality of Service requirements in terms of reliability. The proposed mapper is tested on different scenarios.
Multiobjective differential evolution for mapping in a grid environment
I De Falco;U Scafuri;E Tarantino
2007
Abstract
Effective and efficient mapping algorithms for multisite parallel applications are fundamental to exploit the potentials of grid computing. Since the problem of optimally mapping is NP-complete, evolutionary techniques can help to find near-optimal solutions. Here a multiobjective Differential Evolution is investigated to face the mapping problem in a grid environment aiming at reducing the degree of use of the grid resources while, at the same time, maximizing Quality of Service requirements in terms of reliability. The proposed mapper is tested on different scenarios.File in questo prodotto:
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