DocumentCode :
653996
Title :
Constructing a Social Content Delivery Network for eScience
Author :
Kugler, Kai ; Chard, Kyle ; Caton, Simon ; Rana, Omer ; Katz, Daniel S.
Author_Institution :
Karlsruhe Service Res. Inst., Karlsruhe Inst. of Technol., Karlsruhe, Germany
fYear :
2013
fDate :
22-25 Oct. 2013
Firstpage :
350
Lastpage :
356
Abstract :
Increases in the size of research data and the move towards citizen science, in which everyday users contribute data and analyses, have resulted in a research data deluge. Researchers must now carefully determine how to store, transfer and analyze "Big Data" in collaborative environments. This task is even more complicated when considering budget and locality constraints on data storage and access. In this paper we investigate the potential to construct a Social Content Delivery Network (S-CDN) based upon the social networks that exist between researchers. The S-CDN model builds upon the incentives of collaborative researchers within a given scientific community to address their data challenges collaboratively and in proven trusted settings. In this paper we present a prototype implementation of a S-CDN and investigate the performance of the data transfer mechanisms (using Glob us Online) and the potential cost advantages of this approach.
Keywords :
Big Data; data analysis; social networking (online); Big Data analysis; S-CDN model; collaborative environments; data storage; data transfer mechanisms; e-science; scientific community; social content delivery network; Collaboration; Communities; Databases; Facebook; Resource management; Servers; big data; content delivery network; social cloud; social computing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
eScience (eScience), 2013 IEEE 9th International Conference on
Conference_Location :
Beijing
Type :
conf
DOI :
10.1109/eScience.2013.52
Filename :
6683927
Link To Document :
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