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
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"
Conference_Titel :
Local Computer Networks (LCN), 2015 IEEE 40th Conference on
DOI :
10.1109/LCN.2015.7366309