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Title:
elasticat: a load rebalancing framework for cloud-based key-value stores
Author: Qin Xiulei ; Wang Wei ; Zhang Wenbo ; Wei Jun ; Zhao Xin ; Huang Tao
Source: 2012 19th International Conference on High Performance Computing, HiPC 2012
Conference Name: 2012 19th International Conference on High Performance Computing, HiPC 2012
Conference Date: December 18, 2012 - December 21, 2012
Issued Date: 2012
Conference Place: Pune, India
Keyword: Computer science
Indexed Type: EI
ISBN: 9781467323703
Department: (1) Institute of Software Chinese Academy of Sciences Beijing China; (2) State Key Laboratory of Computer Science Beijing China; (3) Graduate University of Chinese Academy of Sciences Beijing China
Sponsorship: IEEE Comput. Soc. Tech. Comm. Parallel Process. (TCPP); ACM; CSIR; IISER; IISc
Abstract: 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.
English Abstract: 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.
Language: 英语
Content Type: 会议论文
URI: http://ir.iscas.ac.cn/handle/311060/15980
Appears in Collections:软件所图书馆_会议论文

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Recommended Citation:
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.
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