Comparative performance analysis of high-speed transfer protocols for big data

Researchers working in diverse fields such as astronomy, experimental physics, genomics, and meteorology have to frequently deal with analyzing voluminous amounts of complex data. Such data is often referred to as big data. These researchers work in teams and have to transfer this data over long distances. Efficiently transferring big data over long distances requires the use of appropriate transfer protocols. Several TCP-based and UDP-based protocols have been proposed in the literature, however, a comparative analysis of such protocols is lacking in the literature. This paper presents a comparative performance analysis of four well-known high-speed data transfer protocols for long fat networks, namely, GridFTP, FDT, UDT, and Tsunami. We performed extensive experiments to measure the effectiveness of each protocol in terms of its throughput for various roundtrip times, and against increasing levels of congestion inducing TCP or UDP background traffic on a 10 Gb/s network. Our results show that without much tuning, TCP based protocols are able to achieve throughputs of more than 2 Gb/s. In presence of background traffic, UDP protocols perform better.