Name
Title | ||
|---|---|---|
Heat-based dynamic data caching: A load balancing strategy for energy-efficient parallel storage systems with buffer disks |
Abstract | ||
|---|---|---|
Performance improvement and energy conservation are two conflicting objectives in large scale parallel storage systems. In this paper, we propose a novel solution to achieve the twin objectives of maximizing performance and minimizing energy consumption of parallel storage systems. Specifically, a buffer-disk based architecture (BUD for short) is designed to conserve energy. A heat-based dynamic data caching strategy is developed to improve performance. The BUD architecture strives to allocate as many requests as possible to buffer disks, thereby keeping a large number of idle data disks in low-power states. This can provide significant opportunities for energy conservation while making buffer disks a potential performance bottleneck. The heat-based data caching strategy aims to achieve good load balancing in buffer disks and alleviate overall performance degradation caused by unbalanced workload. Our experimental results have shown that the proposed BUD framework and dynamic data caching strategy are able to conserve energy by 84.4% for small reads and 78.8% for large reads with slightly degraded response time. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/MSST.2011.5937238 | MSST |
Keywords | Field | DocType |
bud architecture,dynamic data,heat-based data,cache storage,heat-based dynamic data caching,energy-efficient parallel storage systems,potential performance bottleneck,buffer-disk based architecture,energy conservation,energy-efficient parallel storage system,performance improvement,resource allocation,load balancing strategy,energy consumption,overall performance degradation,buffer disk,heat-based dynamic data,idle data disk,load balance,energy efficient,storage system,algorithm design,algorithm design and analysis,heating,heuristic algorithm | Load management,Bottleneck,Energy conservation,Load balancing (computing),Efficient energy use,Computer science,Dynamic data,Energy consumption,Performance improvement,Distributed computing | Conference |
ISSN | ISBN | Citations |
2160-195X E-ISBN : 978-1-4577-0428-4 | 978-1-4577-0428-4 | 2 |
PageRank | References | Authors |
0.40 | 13 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ziliang Zong | 1 | 646 | 40.20 |
| Xiao Qin | 2 | 1836 | 125.69 |
| Xiaojun Ruan | 3 | 390 | 25.87 |
| Mais Nijim | 4 | 144 | 14.08 |