An Energy-Saving Algorithm in Networked Embedded System Based on Critical Tasks Served First Strategy

Bing Xue, Z. Zhao, Lu Wang, Xiaoli Zhu
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引用次数: 0

Abstract

Lots of collaborative applications that contain a number of dependent tasks run in networked embedded system, such as wireless sensor network, Cyber-Physical-System and so on. For the reasons that deadlines of some collaborative applications are usually not so hard and lifetime of whole system depends on energy dissipation, it is meaningful to figure out a good strategy for balancing delay with system energy dissipation. Considering this issue, our research focuses on trying to minimize total system energy dissipation for extending lifetime of whole system, on the premise that delay of finish time is acceptable. In this paper, we point out which tasks are critical among independent tasks from the perspective of energy-saving and propose BESF (Biggest Energy Span First) algorithm that first allocates the task with biggest energy span. Actually, BESF algorithm references BEATA algorithm, however, BESF could not only further decrease energy-consumption of whole system comparing with existing related algorithms, like BEATA, GEATA, but also still ensure that the finish time is tolerable. Experimental results show that in most situations, BESF algorithm is able to save more energy comparing with existing algorithms.
基于关键任务优先策略的网络化嵌入式系统节能算法
在无线传感器网络、信息物理系统等网络化嵌入式系统中,运行着大量包含大量依赖任务的协同应用。由于某些协同应用的最后期限通常不太严格,而整个系统的寿命取决于能量消耗,因此找出一种好的延迟与系统能量消耗的平衡策略是有意义的。考虑到这一问题,我们的研究重点是在可接受完工时间延迟的前提下,尽量减少系统总能耗,以延长整个系统的寿命。本文从节能的角度指出了独立任务中哪些任务是关键任务,提出了优先分配最大能量跨度任务的BESF(最大能量跨度优先)算法。实际上,BESF算法参考了BEATA算法,但与现有的BEATA、GEATA等相关算法相比,BESF不仅可以进一步降低整个系统的能耗,而且仍然可以保证完成时间在可容忍范围内。实验结果表明,在大多数情况下,与现有算法相比,BESF算法能够节省更多的能量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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