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Near optimal battery-aware energy management

机译:接近最佳的电池感知能源管理

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The paper addresses the problem of battery lifetime maximization for a job sequence executing on a processor with discrete voltage/frequency states under a deadline constraint. We consider a nonlinear electrochemical discharging model of the battery, and present a pseudo-polynomial time optimal algorithm and a fully polynomial time approximation algorithm as solutions. This is the first work that proposes both optimal and approximation algorithms for battery aware energy management based on voltage/frequency scaling techniques. Our experimental results show that the approximation algorithms widely outperform an existing technique. Further, for a number of realistic and synthetic benchmarks, the qualities of the solutions produced by our approximation techniques are much better than the required quality bounds imposed by the designer.
机译:本文针对在截止期限约束下在具有离散电压/频率状态的处理器上执行的工作序列,解决了电池寿命最大化的问题。我们考虑了电池的非线性电化学放电模型,并提出了拟多项式时间最优算法和完全多项式时间逼近算法作为解决方案。这是第一项提出基于电压/频率缩放技术的电池感知能量管理的最佳算法和近似算法的工作。我们的实验结果表明,近似算法的性能大大优于现有技术。此外,对于许多现实的和综合的基准,通过我们的近似技术生成的解决方案的质量远胜于设计人员规定的质量界限。

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