Federation in Cloud Data Management: Challenges and Opportunities

被引：13

作者：

Chen, Gang ^{[1
]}

Jagadish, H. V. ^{[2
]}

Jiang, Dawei ^{[3
]}

Maier, David ^{[4
]}

Ooi, Beng Chin ^{[3
]}

Tan, Kian-Lee ^{[3
]}

Tan, Wang-Chiew ^{[5
]}

机构：

[1] Zhejiang Univ, Coll Comp Sci, Hangzhou 310027, Zhejiang, Peoples R China

[2] Univ Michigan, Dept Elect Engn & Comp Sci, Ann Arbor, MI 48109 USA

[3] Natl Univ Singapore, Sch Comp, Singapore 117417, Singapore

[4] Portland State Univ, Dept Comp Sci, Portland, OR 97201 USA

[5] Univ Calif Santa Cruz, Dept Comp Sci, Santa Cruz, CA 95064 USA

来源：

IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING | 2014年 / 26卷 / 07期

基金：

新加坡国家研究基金会;

关键词：

Cloud computing; database systems; database applications;

D O I：

10.1109/TKDE.2014.2326659

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Companies are increasingly moving their data processing to the cloud, for reasons of cost, scalability, and convenience, among others. However, hosting multiple applications and storage systems on the same cloud introduces resource sharing and heterogeneous data processing challenges due to the variety of resource usage patterns employed, the variety of data types stored, and the variety of query interfaces presented by those systems. Furthermore, real clouds are never perfectly symmetric-there often are differences between individual processors in their capabilities and connectivity. In this paper, we introduce a federation framework to manage such heterogeneous clouds. We then use this framework to discuss several challenges and their potential solutions.

引用

页码：1670 / 1678

页数：9

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