On-Demand Capacity Provisioning in Storage Clusters Through Workload Pattern Modeling
文献类型：期刊论文
| 作者 | Hu, Cheng2; Deng, Yuhui1,2; Yang, Laurence T.3 |
| 刊名 | IEEE ACCESS
 |
| 出版日期 | 2017 |
| 卷号 | 5页码:24830-24841 |
| 关键词 | IoT energy efficient energy saving storage cluster capacity demand estimation capacity provisioning QoS SLA |
| ISSN号 | 2169-3536 |
| DOI | 10.1109/ACCESS.2017.2767703 |
| 英文摘要 | Internet of Things (IoT), which is the inter-networking of a wide variety of physical devices, is widely used in our daily life. The exponential increase in the number of diverse devices has resulted in a significant increase in the volume, variety, velocity, and veracity of data (i.e., big data). These data present a large requirement on modern storage systems both for capacity and scale, and energy cost has become a critical problem. For storage clusters, much research effort has been invested in alleviating this problem by providing suitable resource capacity (i.e., on-demand providing). However, it is challenging to match the offered resource capacity with the real system workloads, thus resulting in a violation of service level agreement. By considering a storage cluster as a queueing system, this paper proposes a QoS-oriented capacity provisioning mechanism. Based on workload features, the mechanism models the pattern of current workloads as a suitable queueing model. In accordance with the model, our mechanism can well forecast the actual resource capacity demand without violating the service level agreement, and then offer the required resource capacity in terms of the real workloads. Experimental results demonstrate that the proposed mechanism significantly reduces the energy consumption of a typical storage cluster, while meeting the QoS requirements. It also significantly outperforms two classic and two state-of-the-art capacity provisioning mechanisms. |
| 资助项目 | NSFC[61572232] ; NSFC[61272073] ; Science and Technology Planning Project of Guangzhou[201604016100] ; Science and Technology Planning Project of Nansha[2016CX007] ; Key Laboratory of Computer System and Architecture, Institute of Computing Technology, Chinese Academy of Sciences[CARCH201401] |
| WOS研究方向 | Computer Science ; Engineering ; Telecommunications |
| 语种 | 英语 |
| WOS记录号 | WOS:000417742800073 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 源URL | [http://119.78.100.204/handle/2XEOYT63/5511]  |
| 专题 | 中国科学院计算技术研究所期刊论文_英文 |
| 通讯作者 | Deng, Yuhui |
| 作者单位 | 1.Chinese Acad Sci, Inst Comp, State Key Lab Comp Architecture, Beijing 100190, Peoples R China 2.Jinan Univ, Dept Comp Sci, Guangzhou 510632, Guangdong, Peoples R China 3.St Francis Xavier Univ, Dept Comp Sci, Antigonish, NS B2G 2W5, Canada |
| 推荐引用方式 GB/T 7714 | Hu, Cheng,Deng, Yuhui,Yang, Laurence T.. On-Demand Capacity Provisioning in Storage Clusters Through Workload Pattern Modeling[J]. IEEE ACCESS,2017,5:24830-24841. |
| APA | Hu, Cheng,Deng, Yuhui,&Yang, Laurence T..(2017).On-Demand Capacity Provisioning in Storage Clusters Through Workload Pattern Modeling.IEEE ACCESS,5,24830-24841. |
| MLA | Hu, Cheng,et al."On-Demand Capacity Provisioning in Storage Clusters Through Workload Pattern Modeling".IEEE ACCESS 5(2017):24830-24841. |
入库方式： OAI收割
来源：计算技术研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。