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Title:An Experimental Evaluation of Datacenter Workloads On Low-Power Embedded Micro Servers
Author(s):Zhao, Yiran; Li, Shen; Hu, Shaohan; Wang, Hongwei; Yao, Shuochao; Shao, Huajie; Abdelzaher, Tarek F.
Subject(s):Intel Edison
datacenter workload
web service
Abstract:This paper presents a comprehensive evaluation of an ultra-low power cluster, built upon the Intel Edison based micro servers. The improved performance and high energy efficiency of micro servers have driven both academia and industry to explore the possibility of replacing conventional brawny servers with a larger swarm of embedded micro servers. Existing attempts mostly focus on mobile-class micro servers, whose capacities are similar to mobile phones. We, on the other hand, target on sensor-class micro servers, which are originally intended for uses in wearable technologies, sensor networks, and Internet-of-Things. Although sensor-class micro servers have much less capacity, they are touted for minimal power consumption (< 1 Watt), which opens new possibilities of achieving higher energy efficiency in datacenter workloads. Our systematic evaluation of the Edison cluster and comparisons to conventional brawny clusters involve careful workload choosing and laborious parameter tuning, which ensures maximum server utilization and thus fair comparisons. Results show that the Edison cluster achieves up to 3.5× improvement on work-done-per-joule for web service applications and data-intensive MapReduce jobs. In terms of scalability, the Edison cluster scales linearly on the throughput of web service workloads, and also shows satisfactory scalability for MapReduce workloads despite coordination overhead.
Issue Date:2016-09-04
Publisher:VLDB Endowment
Citation Info:Zhao, Yiran, Shen Li, Shaohan Hu, Hongwei Wang, Shuochao Yao, Huajie Shao, and Tarek Abdelzaher. "An experimental evaluation of datacenter workloads on low-power embedded micro servers." Proceedings of the VLDB Endowment 9, no. 9 (2016): 696-707.
Series/Report:Proceedings of the VLDB Endowment 9, no. 9 (2016): 696-707.
Genre:Conference Paper / Presentation
Sponsor:This research was supported in part by NSF grant 13-20209.
Rights Information:Copyright 2016 VLDB Endowment 2150-8097/16/05. The license includes right to (a) publish and distribute the Work under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) License ( and (b) obtain a Digital Object Identifier (“DOI”) for the Work.
Date Available in IDEALS:2016-10-24

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