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| towards a cost-aware data migration approach for key-value stores | |
| Qin Xiulei; Zhang Wenbo; Wang Wei; Wei Jun; Zhao Xin; Huang Tao | |
| 2012 | |
| Conference Name | IEEE International Conference on Cluster Computing |
| Source | Proceedings - 2012 IEEE International Conference on Cluster Computing, CLUSTER 2012 |
| Pages | 551-556 |
| Conference Date | SEP 24-28, 2012 |
| Conference Place | Beijing, PEOPLES R CHINA |
| Indexed Type | ISTP ; EI |
| ISSN | 1552-5244 |
| Department | Qin Xiulei; Zhang Wenbo; Wang Wei; Wei Jun; Zhao Xin; Huang Tao Chinese Acad Sci Inst Software Beijing Peoples R China. |
| English Abstract | Live data migration is an important technique for key-value stores. However, due to the stateful feature, new virtualization technology, stringent low latency requirements and unexpected workload changes, key-value stores deployed in cloud environment have to face new challenges for data migration: effects of VM interference, and the need to trade off between the two ingredients of migration cost, say migration time and performance impact. To address these challenges, we focus on the data migration problem in a load rebalancing scenario and build a new framework that aims to rebalance load while minimizing migration costs. We build two interference-aware prediction models to predict the migration time and performance impact for each action using statistical machine learning and then create a cost model to strike a right balance between the two ingredients of cost. A cost-aware migration algorithm is designed to utilize the cost model and balance rate to guide the choice of possible migration actions. We demonstrate the effectiveness of the data migration approach as well as the cost model and two prediction models using YCSB.; Live data migration is an important technique for key-value stores. However, due to the stateful feature, new virtualization technology, stringent low latency requirements and unexpected workload changes, key-value stores deployed in cloud environment have to face new challenges for data migration: effects of VM interference, and the need to trade off between the two ingredients of migration cost, say migration time and performance impact. To address these challenges, we focus on the data migration problem in a load rebalancing scenario and build a new framework that aims to rebalance load while minimizing migration costs. We build two interference-aware prediction models to predict the migration time and performance impact for each action using statistical machine learning and then create a cost model to strike a right balance between the two ingredients of cost. A cost-aware migration algorithm is designed to utilize the cost model and balance rate to guide the choice of possible migration actions. We demonstrate the effectiveness of the data migration approach as well as the cost model and two prediction models using YCSB. |
| Keyword | Data Migration Key-value Store Rebalancing Cost |
| Sponsorship | IEEE, IEEE Comp Soc, IEEE Tech Comm Scalable Comp (TCSC), Sugon, Intel, Inspur, VMware, Mellanox, PARATERA, BLSC, LoongStore, Nvidia |
| Subject | Computer Science |
| Language | 英语 |
| Content Type | 会议论文 |
| URI | http://ir.iscas.ac.cn/handle/311060/15802 |
| Collection | 中国科学院软件研究所 |
| Recommended Citation GB/T 7714 | Qin Xiulei,Zhang Wenbo,Wang Wei,et al. towards a cost-aware data migration approach for key-value stores[C],2012:551-556. |
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