Collaborative framework for high-performance p2p-based data transfer in scientific computing
With the advances in network bandwidth, computational power, memory capabilities, and storage technologies, computational science has been evolving over the past few years towards data intensive computing. In contrast to this evolvement, TCP -- Transmission Control Protocol remains to be the most commonly used protocol for data-transfer, despite it being unsuitable for moving large volumes of data sets across the networks, particularly for wide area networks (WANs). This is due to the default TCP settings on most hosts that are configured to deliver reasonable data-transfer performance -instead of optimal performance- both on Ethernet local area networks (LANs) and on WANs. Therefore, in order to circumvent the performance drawbacks over wide area high-speed networks originating from a window-based congestion control mechanism of TCP and its default settings, proposals of different solutions have arisen over the years. However, most of these solutions are based on a client/server paradigm, and therefore are focused on improving the performance of data transmission between sender and receiver. When there are multiple receivers interested in the same data sets -a situation that is very common in scientific computing- this approach fails to ameliorate the performance of bulk data-transfer between the receivers
Thesis, Dissertation, English, 2009
Dissertation Abstracts International
Indiana University, [Bloomington, Ind.], 2009