Abstract
Transferring large volumes of information from one location to potentially many others that are geographically distributed and across varying networks is still prevalent in modern scientific data systems. This is despite the movement to push computation to the data and to reduce data movement needed to compute answers to challenging scientific problems, to disseminate information to the scientific community, and to acquire data for curation and enrichment. Because of this, it is imperative that decisions made regarding data movement systems and architectures be backed by both analytical rigor, and also by empirical evidence and measurement. The purpose of this study is to expand on the work performed by our research team over the last decade and to take a fresh look at the evaluation of multiple topical data transfer technologies in use cases derived from data-intensive scientific systems and applications in the areas of Earth science. We report on the evaluation of a set of data movement technologies against a set of empirically derived comparison dimensions. Based on this evaluation, we make recommendations towards the selection of appropriate data movement technologies in scientific applications and scenarios.
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