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Subject: Computer Science
Title:
towards a cost-aware data migration approach for key-value stores
Author: Qin Xiulei ; Zhang Wenbo ; Wang Wei ; Wei Jun ; Zhao Xin ; Huang Tao
Source: Proceedings - 2012 IEEE International Conference on Cluster Computing, CLUSTER 2012
Conference Name: IEEE International Conference on Cluster Computing
Conference Date: SEP 24-28, 2012
Issued Date: 2012
Conference Place: Beijing, PEOPLES R CHINA
Keyword: data migration ; key-value store ; rebalancing ; cost
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.
Sponsorship: IEEE, IEEE Comp Soc, IEEE Tech Comm Scalable Comp (TCSC), Sugon, Intel, Inspur, VMware, Mellanox, PARATERA, BLSC, LoongStore, Nvidia
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.
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.
Language: 英语
Content Type: 会议论文
URI: http://ir.iscas.ac.cn/handle/311060/15802
Appears in Collections:软件所图书馆_会议论文

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Recommended Citation:
Qin Xiulei,Zhang Wenbo,Wang Wei,et al. towards a cost-aware data migration approach for key-value stores[C]. 见:IEEE International Conference on Cluster Computing. Beijing, PEOPLES R CHINA. SEP 24-28, 2012.
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