elasticat: a load rebalancing framework for cloud-based key-value stores
文献类型：会议论文
| 作者 | Qin Xiulei ; Wang Wei ; Zhang Wenbo ; Wei Jun ; Zhao Xin ; Huang Tao |
| 出版日期 | 2012 |
| 会议名称 | 2012 19th International Conference on High Performance Computing, HiPC 2012 |
| 会议日期 | December 18, 2012 - December 21, 2012 |
| 会议地点 | Pune, India |
| 关键词 | Computer science |
| 页码 | - |
| 中文摘要 | The problem of load rebalancing is an important issue for cloud-based key-value stores. However, the new virtualization environment and the store's stateful feature make this classical issue more challenging. In this paper, we build a new load rebalancing framework for cloud-based key-value stores, namely ElastiCat. It can be used for auto reconfiguring the store system with minimal costs and no disruption to the availability of the service. To evaluate and minimize the rebalancing costs, we firstly build two interference-aware prediction models to predict the data migration time and performance impact for each action using statistical machine learning and then create a cost model to strike a right balance between them. A cost-aware rebalancing algorithm is designed to utilize the cost model and balance rate to create a rebalancing plan and guide the choice of possible rebalancing actions. To maintain the availability of storage service, we propose a lightweight piggy-back based data access protocol. Finally, we demonstrate the effectiveness of the framework as well as the cost model using YCSB. © 2012 IEEE. |
| 英文摘要 | The problem of load rebalancing is an important issue for cloud-based key-value stores. However, the new virtualization environment and the store's stateful feature make this classical issue more challenging. In this paper, we build a new load rebalancing framework for cloud-based key-value stores, namely ElastiCat. It can be used for auto reconfiguring the store system with minimal costs and no disruption to the availability of the service. To evaluate and minimize the rebalancing costs, we firstly build two interference-aware prediction models to predict the data migration time and performance impact for each action using statistical machine learning and then create a cost model to strike a right balance between them. A cost-aware rebalancing algorithm is designed to utilize the cost model and balance rate to create a rebalancing plan and guide the choice of possible rebalancing actions. To maintain the availability of storage service, we propose a lightweight piggy-back based data access protocol. Finally, we demonstrate the effectiveness of the framework as well as the cost model using YCSB. © 2012 IEEE. |
| 收录类别 | EI |
| 会议主办者 | IEEE Comput. Soc. Tech. Comm. Parallel Process. (TCPP); ACM; CSIR; IISER; IISc |
| 会议录 | 2012 19th International Conference on High Performance Computing, HiPC 2012
 |
| 语种 | 英语 |
| ISBN号 | 9781467323703 |
| 源URL | [http://ir.iscas.ac.cn/handle/311060/15980]  |
| 专题 | 软件研究所_软件所图书馆_会议论文 |
| 推荐引用方式 GB/T 7714 | Qin Xiulei,Wang Wei,Zhang Wenbo,et al. elasticat: a load rebalancing framework for cloud-based key-value stores[C]. 见:2012 19th International Conference on High Performance Computing, HiPC 2012. Pune, India. December 18, 2012 - December 21, 2012. |
入库方式： OAI收割
来源：软件研究所
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