@inproceedings{232b24a22f8a4286bd64a5216f786455,
title = "Scibox: Online sharing of scientific data via the cloud",
abstract = "Collaborative science demands global sharing of scientific data. But it cannot leverage universally accessible cloud-based infrastructures like Drop Box, as those offer limited interfaces and inadequate levels of access bandwidth. We present the Scibox cloud facility for online sharing scientific data. It uses standard cloud storage solutions, but offers a usage model in which high end codes can write/read data to/from the cloud via the APIs they already use for their I/O actions. With Scibox, data upload/download volumes are controlled via Data Reduction-functions stated by end users and applied at the data source, before data is moved, with further gains in efficiency obtained by combining DR-functions to move exactly what is needed by current data consumers. We evaluate Scibox with science applications and their representative data analytics - the GTS fusion and the combustion image processing - demonstrating the potential for ubiquitous data access with substantial reductions in network traffic.",
keywords = "Cloud Storage, Data Sharing, Scientific Data",
author = "Jian Huang and Xuechen Zhang and Greg Eisenhauer and Karsten Schwan and Matthew Wolf and Stephane Ethier and Scott Klasky",
year = "2014",
doi = "10.1109/IPDPS.2014.26",
language = "English",
isbn = "9780769552071",
series = "Proceedings of the International Parallel and Distributed Processing Symposium, IPDPS",
publisher = "IEEE Computer Society",
pages = "145--154",
booktitle = "Proceedings - IEEE 28th International Parallel and Distributed Processing Symposium, IPDPS 2014",
note = "28th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2014 ; Conference date: 19-05-2014 Through 23-05-2014",
}