Abstract
The interest among a geographically distributed user base to mine massive collections of scientific data propels the need for efficient data dissemination solutions. An optimal data distribution scheme will find the delicate and often application-specific balance among conflicting success metrics such as minimizing transfer times, minimizing the impact on the network, and uniformly distributing load among participants. We use simulations to explore the performance of classes of data-distribution techniques, some of which successfully deployed in large peer-to-peer communities, in the context of today’s data-centric scientific collaborations. Based on these simulations we derive several recommendations for data distribution in real-world science collaborations.
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Al-Kiswany, S., Ripeanu, M., Iamnitchi, A., Vazhkudai, S. (2007). Are P2P Data-Dissemination Techniques Viable in Today’s Data-Intensive Scientific Collaborations?. In: Kermarrec, AM., Bougé, L., Priol, T. (eds) Euro-Par 2007 Parallel Processing. Euro-Par 2007. Lecture Notes in Computer Science, vol 4641. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74466-5_44
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DOI: https://doi.org/10.1007/978-3-540-74466-5_44
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74465-8
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