DocumentCode :
3719159
Title :
Characterizing performance and fairness of big data transfer protocols on long-haul networks
Author :
Se-young Yu;Nevil Brownlee;Aniket Mahanti
Author_Institution :
Department of Computer Science, University of Auckland, New Zealand
fYear :
2015
Firstpage :
213
Lastpage :
216
Abstract :
This paper presents a characterization study of big data transfer protocols on a long-haul network. We analyzed the performance and fairness of three well-known open-source protocols, namely, GridFTP, FDT, and UDT. Using a real-world 10 Gb/s network link between New Zealand and Sweden, we studied data transfer rates (in terms of goodput) and fairness (in terms of impact on round trip time) of the protocols. We performed extensive experiments using single and multiple data flows to comprehend how these protocols behave in real-world situations. We found that GridFTP has the fastest data transfer rates when using a single flow. UDT suffered from poor performance due to implementation issues. A small buffer size limited FDT´s performance, however, this drawback can be overcome by using multiple flows in lieu of fairness.
Keywords :
"Protocols","Big data","Data transfer","Throughput","Sockets","Open source software","Measurement uncertainty"
Publisher :
ieee
Conference_Titel :
Local Computer Networks (LCN), 2015 IEEE 40th Conference on
Type :
conf
DOI :
10.1109/LCN.2015.7366309
Filename :
7366309
Link To Document :
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