Reducing service cost based on the skewness of data popularity for Cloud Storage Systems

被引：1
|
作者：
Huang, Zhen [1 ]
Peng, Yuxing [1 ]
Lin, Yisong [2 ]
机构：
[1] Natl Univ Def & Technol, Natl Lab Parallel & Distributed Proc, Changsha, Hunan, Peoples R China
[2] GLD, Beijing, Peoples R China
来源：
2013 IEEE SEVENTH INTERNATIONAL SYMPOSIUM ON SERVICE-ORIENTED SYSTEM ENGINEERING (SOSE 2013) | 2013年
基金：
美国国家科学基金会; 国家高技术研究发展计划(863计划);
关键词：
cloud storage; data popularity; skewness; availability; graph;
D O I：
10.1109/SOSE.2013.52
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
Reducing service cost has been a popular topic in recent studies on cloud storage systems. One of the basic techniques is to power down parts of service nodes. However, it will reduce the availability of data objects, which is the overriding concern of users. So we mathematically formulate the problem to close maximum service nodes under the constrain of a given high availability. According to our analysis, the problem is NP complete. In practical systems, few data objects get most accesses from while large number of objects get few. So we propose a parallelized greedy algorithm to power down service nodes based on the skewness of data popularity.
引用
收藏
页码：373 / 378
页数：6
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