An Energy-Efficient Stream Join for the Internet of Things

Adrian Michalke, P. M. Grulich, Clemens Lutz, Steffen Zeuch, V. Markl
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引用次数: 7

Abstract

The Internet of Things (IoT) combines large data centers with (mobile, networked) edge devices that are constrained both in compute power and energy budget. Modern edge devices contribute to query processing by leveraging accelerated processing units with multicore CPUs or GPUs. Therefore, data processing in the IoT presents the challenges of 1) minimizing the energy consumed while sustaining a given query throughput, and 2) processing increasingly complex queries within a given energy budget. In this paper, we investigate how modern edge devices can reduce the energy requirements of stream joins as a common data processing operation. We explore three dimensions to save energy: workload characteristics, computational efficiency, and heterogeneous hardware. Based on our findings, we propose the ecoJoin that 1) reduces energy consumption by 81% at a given join throughput, and 2) enables scaling the throughput by two orders-of-magnitude within a given energy budget.
面向物联网的节能流连接
物联网(IoT)将大型数据中心与(移动的、联网的)边缘设备相结合,这些设备在计算能力和能源预算方面都受到限制。现代边缘设备通过利用多核cpu或gpu的加速处理单元来促进查询处理。因此,物联网中的数据处理面临着以下挑战:1)在保持给定查询吞吐量的同时最大限度地减少能耗;2)在给定的能源预算内处理日益复杂的查询。在本文中,我们研究了现代边缘设备如何减少作为常见数据处理操作的流连接的能量需求。我们探讨了节约能源的三个方面:工作负载特征、计算效率和异构硬件。根据我们的研究结果,我们提出了ecoJoin, 1)在给定的连接吞吐量下减少81%的能耗,2)在给定的能量预算内将吞吐量扩展两个数量级。
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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