towards a cost-aware data migration approach for key-value stores

ISCAS OpenIR

	towards a cost-aware data migration approach for key-value stores
	Qin Xiulei; Zhang Wenbo; Wang Wei; Wei Jun; Zhao Xin; Huang Tao
	2012
会议名称	IEEE International Conference on Cluster Computing
会议录名称	Proceedings - 2012 IEEE International Conference on Cluster Computing, CLUSTER 2012
页码	551-556
会议日期	SEP 24-28, 2012
会议地点	Beijing, PEOPLES R CHINA
收录类别	ISTP ; EI
ISSN	1552-5244
部门归属	Qin Xiulei; Zhang Wenbo; Wang Wei; Wei Jun; Zhao Xin; Huang Tao Chinese Acad Sci Inst Software Beijing Peoples R China.
摘要	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.
关键词	Data Migration Key-value Store Rebalancing Cost
主办者	IEEE, IEEE Comp Soc, IEEE Tech Comm Scalable Comp (TCSC), Sugon, Intel, Inspur, VMware, Mellanox, PARATERA, BLSC, LoongStore, Nvidia
学科领域	Computer Science
语种	英语
内容类型	会议论文
URI标识	http://ir.iscas.ac.cn/handle/311060/15802
专题	中国科学院软件研究所
推荐引用方式 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.