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We consider the problem of scheduling a set of jobs, under precedence constraints, on a set of speed scalable parallel processors. The goal is to minimize the makespan of the schedule, i.e. the time at which the last job finishes its execution, without violating a given energy budget. This situation finds applications in computer devices whose lifetime depends on a limited battery efficiency. In order to handle the energy consumption we use the energy model introduced in [Yao et al., FOCS'95], which captures the intuitive idea that the higher is the processor's speed the higher is the energy consumption. We propose a (2-1/m)-approximation algorithm improving the best known poly-log(m)-approximation algorithm for the problem [Pruhs et al., TOCS 2008], where m is the number of the processors. We also extend the simple idea used for the above problem, in order to propose a generalized framework that finds applications to other scheduling problems in the speed scaling setting.
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Bampis et al. (2014) studied this question.
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