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• W84695003 abstract "Scheduling algorithms play an important role in heterogeneous computing systems. These algorithms guarantee a good load balance, also reducing the communication overhead. In particular, Quadratic Self-Scheduling (QSS) and Exponential Self-Scheduling (ESS) are flexible enough to adapt to distributed systems, thanks to their adjustable parameters. This flexibility becomes very important when the environment is dynamic because only algorithms that can shape the workload will be able to handle dynamic environment such as an Internet-based Grids of computers. In this sense, we propose a new adaptive approach that allows to obtain the optimal parameters of QSS and ESS each time that the properties of the environment change. We find that using this approach, the QSS algorithm improves its performance around a 25%. However, it is shown that the performance of ESS decreases when there is a large number of tasks. Finally, the overall time spent by the adaptive approach to generate new optimal sets of parameters is just a bit higher than the time to obtain just once. However, it is not proportional to the number of new sets of parameters generated. This is because the number of tasks decreases each time that we obtain new optimal parameters." @default.
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• W84695003 date "2009-01-01" @default.
• W84695003 modified "2023-10-12" @default.
• W84695003 title "An Adaptive Approach to Task Scheduling Optimization in Dynamic Grid Environments." @default.
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