An Experimental Evaluation of Datacenter Workloads On Low-Power Embedded Micro Servers
Summary: Sensor-class micro servers (Intel Edison) evaluated for datacenter workloads with careful workload tuning for fair comparison to brawny clusters. Reports up to 3.5x work-done-per-joule on web services and MapReduce; linear web throughput scaling and reasonable MapReduce scalability despite coordination overhead. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Yiran Zhao
- 2. Shen Li
- 3. Shaohan Hu
- 4. Hongwei Wang
- 5. Shuochao Yao
- 6. Huajie Shao
- 7. Tarek Abdelzaher
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| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 927 | Data Processing on FPGAs | 2009 | VLDB | 0.0001321383 |
| 3,054 | Energy Management for MapReduce Clusters | 2010 | VLDB | 7.8742908e-05 |
| 3,456 | JouleSort: A Balanced Energy-Efficiency Benchmark | 2007 | SIGMOD | 7.4730938e-05 |
| 5,844 | Towards Energy-Efficient Database Cluster Design | 2012 | VLDB | 6.1296144e-05 |
| 6,039 | A Performance Study of Big Data on Small Nodes | 2015 | VLDB | 6.0592432e-05 |
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