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Optimizing throughput and energy in online deadline scheduling

机译:在在线截止日期调度中优化吞吐量和能源

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This article extends the study of online algorithms for energy-efficient deadline scheduling to the overloaded setting. Specifically, we consider a processor that can vary its speed between 0 and a maximum speed T to minimize its energy usage (the rate is believed to be a cubic function of the speed). As the speed is upper bounded, the processor may be overloaded with jobs and no scheduling algorithms can guarantee to meet the deadlines of all jobs.Anoptimal schedule is expected to maximize the throughput, and furthermore, its energy usage should be the smallest among all schedules that achieve the maximum throughput. In designing a scheduling algorithm, one has to face the dilemma of selecting more jobs and being conservative in energy usage. If we ignore energy usage, the best possible online algorithm is 4-competitive on throughput [Koren and Shasha 1995]. On the other hand, existing work on energy-efficient scheduling focuses on a setting where the processor speed is unbounded and the concern is on minimizing the energy to complete all jobs; O(1)-competitive online algorithms with respect to energy usage have been known [Yao et al. 1995; Bansal et al. 2007a; Li et al. 2006]. This article presents the first online algorithm for the more realistic setting where processor speed is bounded and the system may be overloaded; the algorithm is O(1)-competitive on both throughput and energy usage. If the maximum speed of the online scheduler is relaxed slightly to (1 + ε)T for some ε > 0, we can improve the competitive ratio on throughput to arbitrarily close to one, while maintaining O(1)-competitiveness on energy usage.
机译:本文将针对节能期限调度的在线算法的研究扩展到超载设置。具体来说,我们考虑一个处理器,它可以在0到最大速度T之间改变其速度,以最大程度地减少其能源消耗(速率被认为是速度的三次函数)。由于速度的上限,处理器可能会超负荷工作,并且没有调度算法可以保证满足所有作业的最后期限。最佳调度有望最大程度地提高吞吐量,此外,其能源消耗应在所有调度中最小实现最大的吞吐量。在设计调度算法时,必须面对选择更多工作并在能源使用方面保持保守的困境。如果我们忽略能源使用,那么最好的在线算法是在吞吐量上具有4竞争性[Koren and Shasha 1995]。另一方面,有关节能调度的现有工作集中在处理器速度不受限制的环境中,而关注点是使完成所有工作所需的能量降至最低。关于能源使用的O(1)竞争性在线算法是已知的[Yao等。 1995; Bansal等。 2007a; Li等。 2006]。本文介绍了第一种在线算法,用于更实际的设置,在这种情况下,处理器速度受到限制,系统可能会过载。该算法在吞吐量和能耗方面都具有O(1)竞争性。如果在线调度程序的最大速度在ε> 0时稍微放宽到(1 +ε)T,我们可以将吞吐量竞争比提高到任意接近1,同时保持能耗的O(1)竞争性。

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