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Obtaining optimal data transfer performance is of utmost importance totoday's data-intensive distributed applications and wide-area data replicationservices. Doing so necessitates effectively utilizing available networkbandwidth and resources, yet in practice transfers seldom reach the levels ofutilization they potentially could. Tuning protocol parameters such aspipelining, parallelism, and concurrency can significantly increase utilizationand performance, however determining the best settings for these parameters isa difficult problem, as network conditions can vary greatly between sites andover time. Nevertheless, it is an important problem, since poor tuning cancause either under- or over-utilization of network resources and thus degradetransfer performance. In this paper, we present three algorithms forapplication-level tuning of different protocol parameters for maximizingtransfer throughput in wide-area networks. Our algorithms dynamically tune thenumber of parallel data streams per file (for large file optimization), thelevel of control channel pipelining (for small file optimization), and thenumber of concurrent file transfers to increase I/O throughput (a techniqueuseful for all types of files). The proposed heuristic algorithms improve thetransfer throughput up to 10x compared to the baseline and 7x compared to thestate of the art solutions.

A Heuristic Approach to Protocol Tuning for High Performance Data Transfers