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Performance-aware task scheduling for energy harvesting nonvolatile processors considering power switching overhead

机译：考虑功率开关开销的，用于能量收集非易失性处理器的性能感知任务调度

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摘要

Nonvolatile processors have manifested strong vitality in battery-less energy harvesting sensor nodes due to their characteristics of zero standby power, resilience to power failures and fast read/write operations. However, I/O and sensing operations cannot store their system states after power off, hence they are sensitive to power failures and high power switching overhead is induced during power oscillation, which significantly degrades the system performance. In this paper, we propose a novel performance-aware task scheduling technique considering power switching overhead for energy harvesting nonvolatile processors. We first give the analysis of the power switching overhead on energy harvesting sensor nodes. Then, the scheduling problem is formulated by MILP (Mixed Integer Linear Programming). Furthermore, a task splitting strategy is adopted to improve the performance and an heuristic scheduling algorithm is proposed to reduce the problem complexity. Experimental results show that the proposed scheduling approach can improve the performance by 14% on average compared to the state-of-the-art scheduling strategy. With the employment of the task splitting approach, the execution time can be further reduced by 10.6%.
机译：非易失性处理器由于其零待机功率，对电源故障的恢复能力以及快速的读/写操作的特性，在无电池能量收集传感器节点中表现出强大的生命力。但是，I / O和传感操作在断电后无法存储其系统状态，因此它们对电源故障很敏感，并且在电源振荡期间会产生高功率开关开销，这会严重降低系统性能。在本文中，我们提出了一种新的性能感知任务调度技术，该技术考虑了用于能量收集非易失性处理器的功率切换开销。我们首先分析能量收集传感器节点上的功率开关开销。然后，通过MILP（混合整数线性规划）来制定调度问题。此外，采用了任务分割策略来提高性能，并提出了启发式调度算法来降低问题的复杂性。实验结果表明，与最新的调度策略相比，所提出的调度方法平均可将性能提高14％。通过使用任务拆分方法，执行时间可以进一步减少10.6％。

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