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PFS: A Productivity Forecasting System for Desktop Computers to Improve Grid Applications Performance in Enterprise Desktop Grid

Sergio Ariel Salinas, Carlos García Garino, Alejandro Zunino


An Enterprise Desktop Grid (EDG) is a low cost platform that gathers desktop computers spread over different institutions. This platform uses desktop computers idle time to run Grid applications. We argue that computers in these environments have a predictable productivity that affects a Grid application execution time. In this paper, we propose a system called PFS for computer productivity forecasting that improves Grid applications performance. We simulated 157.500 applications and compared the performance achieved by our proposal against two recent strategies. Our experiments show that a Grid scheduler based on PFS runs applications faster than schedulers based on other selection strategies.

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