Efficient and Secure Transfer, Synchronization, and Sharing of Big Data

被引:57
作者
Chard, Kyle [1 ,2 ]
Tuecke, Steven [1 ,3 ]
Foster, Ian [1 ,2 ,4 ]
机构
[1] Univ Chicago, Computat Inst, Chicago, IL 60637 USA
[2] Argonne Natl Lab, Argonne, IL 60439 USA
[3] St Olaf Coll, Math & Comp Sci, Northfield, MN 55057 USA
[4] Arthur Holly Compton Distinguished Serv, Comp Sci, St Louis, MO 63130 USA
基金
美国国家卫生研究院; 美国国家科学基金会;
关键词
big data; data sharing; data transfer; Globus;
D O I
10.1109/MCC.2014.52
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Cloud computing provides a scalable computing platform through which large datasets can be stored and analyzed. However, because of the number of storage models used and rapidly increasing data sizes, it is often difficult to efficiently and securely access, transfer, synchronize, and share data. The authors describe the approaches taken by Globus to create standard data interfaces and common security models for performing these actions on large quantities of data. These approaches are general, allowing users to access different types of cloud storage with the same ease with which they access local storage. Through an existing network of more than 8,000 active storage endpoints and support for direct access to cloud storage, Globus has demonstrated both the effectiveness and scalability of the approaches presented. © 2014 IEEE.
引用
收藏
页码:46 / 55
页数:10
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