实时系统嵌入式应用的低功耗数据结构设计

Linhua Jiang, Chao Peng, Haibin Cai, Yixiang Chen, Xiaodong Chen
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引用次数: 2

摘要

在广泛使用的实时和嵌入式系统中,内存占用、能源等资源是非常有限的。我们试图找到解决方案——在数据结构设计的背景下——内存效率高,内存使用功耗低。我们分析了特定嵌入式应用程序的各种现有和创造性的新数据结构实现。低内存成本、低数据访问和低功耗是我们在数据结构探索过程中的主要标准。2D和3D Pareto曲线用于表示不同数据结构实现的权衡点。因此,可以在应用程序的实时约束下发现相对最优的数据结构。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Low Power Consumption Data Structure Design for Embedded Applications in Real-Time Systems
In the widely used real-time and embedded systems, resources such as memory footprint, energy, are very limited. We try to find solutions -- in the context of data structure design- that are memory efficient and low power consumption in memory usage. We analyze various existing and creative new data structure implementations of a specific embedded application. Low memory cost, data accesses and power consumption are our main criteria during our data structure explorations. 2D and 3D Pareto curves are used to present the trade-off points of different data structure implementations. Thus, the relative optimal data structures can be discovered within the real-time constraints of the application.
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